JOSCM - Journal of Operations and Supply Chain Management - n. 02 | Jul/Dec 2015

Is there a Link between Supply Chain Strategies
and Firm Performance? Evidence from Large-Scale
Manufacturing Firms in Kenya
Richard Bitange Nyaoga
Egerton University
rnyaoga@yahoo.com
Peterson Obara Magutu
University of Nairobi
magutumop@yahoo.com
Josiah Aduda
University of Nairobi
jaduda@uonbi.ac.ke
ABSTRACT: The purpose of this study was to establish the relationship between supply chain strate-
gies and performance of large-scale manufacturing firms in Kenya by addressing three primary gaps in
the literature. The research gaps include the research findings and results on the relationship between
supply chain strategies and firm performance that have been contradicting and no attempt to clear the
contradictions; biased and unbalanced analysis of the different measures of firm performance, and
failure to use weighted scores to measure firm performance. Resource-Based View guided this study.
A sample of one hundred and thirty-eight (138) firms was drawn using proportionate sampling from
a population of six hundred and twenty-seven (627) large-scale manufacturing firms in Kenya. The
response rate was seventy-five (75) percent. The correlation analysis and regression analysis models
were used to test the hypotheses. The study findings indicate that Supply chain strategies are useful
predictors of the firm’s performance as supply chain strategies explain 76.7 % of the changes in the
firm’s performance.
Keywords: Supply chain management, Supply chain strategies, Firm performance
Volume 8• Number 2 • July - December 2015 http://dx.doi/10.12660/joscmv8n2p01-22
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Richard Bitange Nyaoga, R. B., Magutu, P. O., Aduda, J.: Is there a Link between Supply Chain Strategies and Firm Performance? ...
ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 8 Number 2 p 01 – 222
1. INTRODUCTION
The concept of supply chain management (SCM) has
been the subject of numerous studies in operational
management, purchasing, logistics, and marketing.
There are a number of constructs like supply chain
strategy and technology that can be used in these di-
verse research domains as there is lack of empirical
evidence in SCM practice (Halley & Beaulieu, 2009;
Hult, Ketchen, Cavusgil, & Calantone, 2006; Ketch-
en & Giunipero, 2004). Owing to lack of consensus
on definition and differing views on the concept of
SCM, this study was guided by Mentzer et al. (2001).
Mentzer et al. (2001) definition that is broad enough
and captures the issues of strategy and firm perfor-
mance. They define supply chain management as:
“…the systemic, strategic coordination of the
traditional business functions and the tactics
across these business functions within a partic-
ular company and across businesses within the
supply chain, for the purposes of improving the
long-term performance of the individual com-
panies and the supply chain as a whole (Men-
tzer et al., 2001, p. 18)”.
The Resource Based View (RBV) and Transactional
theories have played a very crucial role when con-
ducting research on the strategic perspectives of
operations and supply chain management (Burgess,
Singh, & Koroglu, 2006). The resource-based view
theory has been greatly used in SCM studies in the
last twenty years. This theory has to a great extent
shaped mastery of operational decisions in the con-
text of SCM (Halley & Beaulieu, 2009; Patterson,
Grimm, & Corsi, 2003).
Under the economic pillar of Kenya Vision, 2030,
manufacturing is one the five sectors that has been
identified to support economic development. In line
with the aspirations of Vision 2030, it is expected
to be a dominant and aggressive sector to support
the national growth, create employment, earn the
country foreign exchange and facilitate foreign in-
vestment (GoK, 2007). Many large-scale manufac-
turing subsector companies in Kenya particularly
multinational manufacturing firms have migrated
their operations to other countries. These firms have
relocated, shut down or downsized their opera-
tions because they consider Kenya as one of the least
yielding countries worldwide. This is due to poor
infrastructure, high tariffs and taxes. The local firms
have not been able to fill the manufacturing gaps left
by the multinationals as the government has done
very little to develop this struggling subsector lead-
ing to low international competitiveness (Okoth,
2012; PwCIL, 2010).
Hines (2009) define what the supply chain strategies
are, how they work and why firms invest in them as
follows:
“Supply chain strategies require a total systems
view of the linkages in the chain that work to-
gether efficiently to create customer satisfaction
at the end point of delivery to the consumer.As a
consequence, costs must be lowered throughout
the chain by driving out unnecessary costs and
focusing attention on adding value. Through-
put efficiency must be increased, bottlenecks
removed and performance measurement must
focus on total systems efficiency and equitable
reward distribution to those in the supply chain
adding value. The supply chain system must be
responsive to customer requirements.”
In essence, research indicates that there are six-
teen supply chain strategies in use today. These
include: synergistic; project logistics; Nano-chain;
information networks; market dominance; value
chain; extended; efficient; cash-to-cash cycle; inno-
vation; speed to market; risk-hedging; micro-chain;
tie down; none existent; and demand supply chain
strategies. There are some benefits, challenges, and
relative complexity for each of these sixteen supply
chain strategies. This has led to the categorization of
the sixteen supply chain strategies into a dichotomy
of Long-range and Mid-range supply chain strate-
gies (Gattorna, 2006; Gadde, & Hakansson, 2001).
The sixteen-supply chain strategy dichotomy was
central in this study about firm performance. This
study considered both the direct effect of these long-
range and mid-range supply chain strategies on the
performance of large-scale manufacturing firms in
Kenya.
Performance management is crucial and a para-
mount practice to the success of any business. Be-
ing a wide-ranging topic, one can focus on target/
goal setting, measurement, feedback or reward. The
biggest challenge facing firm performance mea-
surement is most scholars limit themselves to their
areas of specialization; few academics across these
functional boundaries to make reference to the re-
search of other experts outside their functional areas
(Neely, Bourne, & Kennerley, 2000). This study mea-
sured performance using indicators cutting across
all functional areas in relation to firm performance.

Organizations in today’s business environment have
a big challenge on how to remain competitive in the
marketplace through firm performance especially the
organization-wide performance (Collins, Worthing-
ton, Reyes, & Romero, 2010). Agha, Alrubaiee, & Jam-
hour (2011), argued that to remain competitive and
achieve competitive advantages, managers should in-
crease organizational performance by managing the
dimensions of core competence i.e. a shared vision;
cooperation and empowerment. Some authors like
Keegan, Eiler, & Charles (1989) and Kaplan & Norton
(1992) have suggested appropriate firm performance
measurement frameworks to the management com-
munity. They include the performance measurement
matrix and the Balanced Scorecard (BSC). The perfor-
mance measurement matrix as advanced by Keegan
et al. (1989) ranks activities in matrix form, but it does
not assign weights. The BSC is a tool that gives a bal-
anced view of how an organization is performing by
cascading firm performance perspectives down from
the strategic to operational level of business at four
levels of: customer service; financial stewardship; in-
ternal business processes; and service delivery inno-
vations (Gunasekaran, Patel, & Tirtiroglu, 2001). The
BSC has simplified the measurement of firm perfor-
mance, especially for supply chains where all units
share the metrics in the organization and supply
chain partners (Kaplan & Norton, 1992). According
to Bolo (2011) the concept of firm performance and
its measurement has not been extended beyond the
firm’s inbound operations. This limited visibility of
measures tends to exclude SC performance measures.
This study explored the balanced approach for firm
performance with four perspectives within the con-
text of large-scale manufacturing firms in Kenya.
1.1. Research Problem and Research Focus
According to Cooper & Ellram (1993), SCM is an
integrative philosophy to manage the total flow of
goods from the supplier to the ultimate user. Varma,
Wadhwa, & Deshmukh (2006) considers this defini-
tion of SCM as a management philosophy that tries
to bring about integration among various functions.
Cousins, Lawson, & Squire (2006), definition is com-
prehensive and critical, they describe the concept
as consisting of the flow of raw materials, finished
goods, finances and information while aiming to
achieve high customer expectations through prop-
er planning on demand forecasts, sales generation,
and efficient distribution. The flow should be well
coordinated in the form of a network starting with
suppliers then to manufacturers, next to distributors
and finally customers. But this definition does not
include the elements of uncertainty which require
some element of strategic focus. According to Kama-
ruddin & Udin (2009) there is a high degree of un-
certainty and difficulty in managing supply chains,
especially where there are multiple relationships
and interactions between elements of the firm’s ex-
isting network.
According to PwCIL (2010) and Okoth (2012), Ke-
nya’s large-scale manufacturing subsector has a
challenging history in terms of performance and
unstructured strategy. This study sought to test con-
textually the relationship between SC strategies and
performance of large-scale manufacturing firms in
Kenya. As observed by Burgess et al. (2006) most of
the researches done on SCM is on very few indus-
tries covering the consumer goods retailing, com-
puter assembling and automobile manufacturing.
This study overcame this by covering twelve subsec-
tors of the large-scale manufacturing firms in Kenya.
An expanded approach of sixteen-supply chain
strategies dichotomy is in use today, and the future
shall see firms competing using their supply chains
strategies (Gadde & Hakansson, 2001). Very few
studies have attempted to address such an expand-
ed approach to sixteen SC strategies in establishing
the relationship between supply chain strategy and
firm performance (Gattorna, 2006; Russell & Hoag,
2004). The sixteen-supply chain strategy dichotomy
provides an extended approach whose relationship
with firm performances are the subject of this study.
Most studies have therefore used a limited number
of measures that are not objective enough to establish
a link with the concepts studied. Mainly, they have
not used the Balanced Scorecard to determine firm
performance something the current study sought
to use. This was therefore guided by the following
research question: What is the relationship between
SC strategies and firm performance? The main ob-
jective of this study was to establish the relationship
between supply chain strategies and performance of
large-scale manufacturing firms in Kenya.
1.2. Empirical studies
Teeratansirikool, Siengthai, Badir, & Charoenngam
(2013) argued that all competitive strategies posi-
tively and significantly enhance firm performance.
Khan & Pillania (2008), argued that supplier evalu-
ation, strategic supplier partnership, sourcing flex-
ibility and trust in supply chain members have a

significant effect on supply agility and firm’s per-
formance. Qrunfleh & Tarafdar (2014) posits that in
small firms, efficient Supply Chain integration plays
a more critical function for sustainable performance
improvement, while, in large firms, the close inter-
relationship between the level of SCM practices and
competition capability have more significant effect
on performance improvement.
Li, Ragu-Nathan, Ragu-Nathan, & Subba Rao (2006)
intheirstudytheyconceptualizedonﬁvedimensions
of SCM practices (customer relationship, quality of
information sharing, strategic supplier partnership,
level of information sharing, and postponement)
and tested the relationships between competitive
advantage, SCM practices, and organizational per-
formance. Their results indicate that higher levels of
SCM practices can lead to improved competitive ad-
vantage and enhanced firm performance.
Ou, Liu, Hung, & Yen (2010) found out that external
customer‐firm‐supplier relation management posi-
tively influence firm internal contextual factors that
in turn have positive effects on firm performance.
Their finding indicates that successful implemen-
tation of SCM practices directly improves opera-
tional performance, and also indirectly enhances
customer satisfaction and financial performance of
the organization.
Golicic & Smith (2013) concluded that the relation-
ship between environmental supply chain practices
and operational-based, market-based and account-
ing-based forms of firm performance are positive and
significant, giving support for the argument that sus-
tainable supply chain management leads to increased
firm performance. Zolait, Ibrahim, Chandran, Pan-
diyan, & Sundram (2010) in their study argued that
information flow, financial flow, and physical flow
were statistically significant to firm performance. Lee,
Kim, & Choi (2012) argued that there are a significant
indirect relationship between Green Supply Chain
Management (GSCM) practice implementation and
firm performance through mediating variables of op-
erational efficiency and relational efficiency.
1.3. Conceptual Model and Hypothesis
The conceptual model in figure 1 below is in sup-
port for the arguments raised from literature review
that the SC strategies that consist of Mid-range SC
strategies and Long-range SC strategies have a re-
lationship with firm performance outcome of large-
scale manufacturing firms in Kenya. Figure 1 below
is emphasizing the interconnection between the SC
strategies and firm performance in one comprehen-
sive framework intended to assist the researcher in
developing a clear understanding of the linkages be-
tween the two variables.
Figure 1: Conceptual Model
below is emphasizing the interconnection between the SC strategies and firm performance in one
comprehensive framework intended to assist the researcher in developing a clear understanding of the
linkages between the two variables.
Figure 1: Conceptual Model
H1
H1a
H1b
Source: Author, 2014
Based on the study objective, this study examined the supply chain strategies that consist of Mid-range
SC strategies and Long-range SC strategies and their relationship with firm performance. Hence, the
following hypotheses were tested:
H1: Supply chain strategies are positively related to firm performance
Mid-Range Supply
Chain Strategies
Long-Range Supply
Chain Strategies
Supply Chain Strategies
Firm Performance
i. Finance & Stewardship
ii. Customer Services
iii. Internal Business Operations
iv. Employee & Organizational
Innovation
(Dependent Variable)
Independent Variables
Source: Author, 2014

Based on the study objective, this study examined
the supply chain strategies that consist of Mid-range
SC strategies and Long-range SC strategies and their
relationship with firm performance. Hence, the fol-
lowing hypotheses were tested:
H1: Supply chain strategies are positively related to firm
performance
Given that the sixteen-supply chain strategy dichot-
omy (Mid-range SC strategies and Long-range SC
strategies) was used as independent variables about
firm performance, the following two sub-hypothe-
ses were derived from the hypothesis two.
H1a: Mid-range SC strategies are positively related to
firm performance
H1b: Long-range SC strategies are positively related to
firm performance
2. METHODOLOGY
2.1. General Background of Research
The positivistic philosophy was preferred to guide
this study since it combines static and a priori ap-
proaches. The positivistic paradigm often requires
a test of a model using questionnaires constructed
without input from the respondents as it was the
case for this study. Moreover, this research com-
prised of predefined (a priori) relationships that
required primarily theory testing as all the hypoth-
eses are stated with predictive rigor for acceptance
aimed at making positivistic conclusions.
2.2. Research Design
This study adopted a cross-sectional survey and
descriptive design. The design was appropriate
because it is useful in establishing the nature of ex-
isting situation and current conditions and also in
analyzing such situations and conditions. Johnson,
Scholes, & Whittington (2007) did a similar study
in USA and used the same methodology and vari-
ables. Fawcett, Ogden, Magnan, & Cooper (2006)
used strategy implementation as the independent
variable and performance as the dependent variable
using a triangulation methodology consisting of lit-
erature review, survey, and case studies. Given this
approach, a cross-sectional survey method was used
to obtain the empirical data to determine the link-
ages between variables.
2.3. Population of the Study
The target population was all large-scale manufac-
turing firms in Kenya. The unit of analysis was the
large scale manufacturing firm. In Kenya, according
to the KAM directory (2010/2011) large scale enter-
prises have more than 100 workers, medium enter-
prises have from 51 to 100 workers, small enterprises
have from 11 to 50 workers, and micro-enterprises
are those with 10 or fewer workers. There are 2,000
manufacturing companies in Kenya, from which the
target population is 627 large-scale manufacturing
firms. Although the categorizations of manufactur-
ing firms according to size has been based on the
number of employees, the type and level of tech-
nology used, size of capital investment and capac-
ity utilization can be used to justify the choice of
large-scale manufacturing firms. The main reason
for this choice is that these firms are likely to exhibit
an elaborate SCM philosophy, exhibit high activity
levels, have enough resource to be employed in sup-
ply chain strategy implementation, make use of sup-
ply chain strategies and SCT in SCM. The number of
employees is a good indicator of size because being
profit making; employees can be taken as a proxy for
supply chain performance, profits, technology utili-
zation and firm performance. Large-scale manufac-
turing firms that make more than two-thirds of the
industrial coverage is considered as the strength of
this research since prior studies had ignored sector-
specific supply chain variables on firm performance.
2.4. Sample of Research
The appropriate sample size for a population-based
survey was determined largely by three factors
(Kate, 2006): (i) the estimated percentage prevalence
of the population of interest – 10% (ii) the desired
level of confidence and (iii) the acceptable margin
of error.
The sample size required can be calculated accord-
ing to the following Kate (2006) formula
been based on the number of employees, the type and level of technol
investment and capacity utilization can be used to justify the choice of
firms. The main reason for this choice is that these firms are likely to e
philosophy, exhibit high activity levels, have enough resource to be employe
implementation, make use of supply chain strategies and SCT in SCM. The
good indicator of size because being profit making; employees can be tak
chain performance, profits, technology utilization and firm performance. L
firms that make more than two-thirds of the industrial coverage is conside
research since prior studies had ignored sector-specific supply chain variable
2.4. Sample of Research
The appropriate sample size for a population-based survey was determine
(Kate, 2006): (i) the estimated percentage prevalence of the population o
desired level of confidence and (iii) the acceptable margin of error.
The sample size required can be calculated according to the following Kate (
n =
t² x p(1-p)
m²
Where:
n = required a sample size, t = confidence level at 95% (standard value
percentage prevalence of the population of interest – 10%, m = margin of e
of 0.05)
Therefore, the sample size (n) for this study can be computed as follows:
Where:
n = required a sample size, t = confidence level at
95% (standard value of 1.96), p = estimated percent-
age prevalence of the population of interest – 10%, m
= margin of error at 5% (standard value of 0.05)

Therefore, the sample size (n) for this study can be
computed as follows:
10
e size, t = confidence level at 95% (standard value of 1.96), p = estimated
of the population of interest – 10%, m = margin of error at 5% (standard value
ize (n) for this study can be computed as follows:
n =
1.96² x .1(1-.1)
.05²
n =
3.8416 x .09
.0025
n =
.3457
.0025
n =
138.30 ~ 138
One hundred and thirty-eight (138) large scale manufacturing firms were sampled and contac
participate in the study. Then the large-scale manufacturing firms (sample) were stratified into t
key sectors/strata as shown in table 1based on the KAM directory of 2010/2011.
Table 1: Sampling Strata
Large-Scale Manufacturing Sectors/Strata Strata Popn
N
Proportionate Sampling
Pn=N/Total Popn *Sample
Building, Construction, and Mining 15 3
Food, Beverages, and Tobacco 154 33
Chemical and Allied 71 16
Energy, Electrical and Electronics 43 10
Plastics and Rubber 66 14
Textile and Apparels 68 15
Timber, Wood Products, and Furniture 26 6
Pharmaceutical and Medical Equipment 32 7
Metal and Allied 62 14
Leather Products and Footwear 8 2
Motor Vehicle Assembly and Accessories 22 5
Paper and Paperboard 60 13
Total 627 138
Source: Researcher, (2014)
Proportionate sampling was done to pick the required number of respondents from the twelve
strata. This gave every firm an opportunity to participate in the study.
2.5. Instrument and Procedures
Data for this study was collected from both primary and secondary sources that are meant to rein
each other (Stiles, 2003). Primary data entailed responses on all the study variables: supply
strategies and firm performance. Secondary data, particularly five-year historical data on
performance data was sourced from company annual reports, pamphlets, office manuals circ
policy papers, corporate /business plans as well as survey reports from Kenya Associatio
Manufacturers and Kenya Central Bureau of Statistics for the years 2006 - 2010. This is becau
normal planning cycle at the strategic level is five years.
The questionnaire and data forms were the principal tools for collecting primary data and seco
data respectively. One respondent, either the Operations Manager or Supply Chain Manage
Manager or procurement manager from each firm, was selected to participate in the study. Wils
One hundred and thirty-eight (138) large scale man-
ufacturing firms were sampled and contacted to
participate in the study. Then the large-scale manu-
facturing firms (sample) were stratified into twelve
key sectors/strata as shown in table 1based on the
KAM directory of 2010/2011.
n =
.3457
.0025
n =
138.30 ~ 138
One hundred and thirty-eight (138) large scale manufacturing firms were sampled and contacted to
participate in the study. Then the large-scale manufacturing firms (sample) were stratified into twelve
key sectors/strata as shown in table 1based on the KAM directory of 2010/2011.
Large-Scale Manufacturing Sectors/Strata Strata Popn
N
Proportionate Sampling
Pn=N/Total Popn *Sample
Building, Construction, and Mining 15 3
Food, Beverages, and Tobacco 154 33
Chemical and Allied 71 16
Energy, Electrical and Electronics 43 10
Plastics and Rubber 66 14
Textile and Apparels 68 15
Timber, Wood Products, and Furniture 26 6
Pharmaceutical and Medical Equipment 32 7
Metal and Allied 62 14
Leather Products and Footwear 8 2
Motor Vehicle Assembly and Accessories 22 5
Paper and Paperboard 60 13
Total 627 138
Proportionate sampling was done to pick the required number of respondents from the twelve (12)
strata. This gave every firm an opportunity to participate in the study.
Data for this study was collected from both primary and secondary sources that are meant to reinforce
each other (Stiles, 2003). Primary data entailed responses on all the study variables: supply chain
strategies and firm performance. Secondary data, particularly five-year historical data on firm
performance data was sourced from company annual reports, pamphlets, office manuals circulars,
policy papers, corporate /business plans as well as survey reports from Kenya Association of
Manufacturers and Kenya Central Bureau of Statistics for the years 2006 - 2010. This is because the
normal planning cycle at the strategic level is five years.
The questionnaire and data forms were the principal tools for collecting primary data and secondary
data respectively. One respondent, either the Operations Manager or Supply Chain Management
Manager or procurement manager from each firm, was selected to participate in the study. Wilson &
Proportionate sampling was done to pick the re-
quired number of respondents from the twelve (12)
strata. This gave every firm an opportunity to par-
ticipate in the study.
Data for this study was collected from both primary
and secondary sources that are meant to reinforce
each other (Stiles, 2003). Primary data entailed re-
sponses on all the study variables: supply chain
strategies and firm performance. Secondary data,
particularly five-year historical data on firm per-
formance data was sourced from company annual
reports, pamphlets, office manuals circulars, policy
papers, corporate /business plans as well as survey
reports from Kenya Association of Manufacturers
and Kenya Central Bureau of Statistics for the years
2006 - 2010. This is because the normal planning cy-
cle at the strategic level is five years.
The questionnaire and data forms were the principal
tools for collecting primary data and secondary data
respectively. One respondent, either the Operations
Manager or Supply Chain Management Manager or
procurement manager from each firm, was selected
to participate in the study. Wilson & Lilien (1992)
showed that single informants are most appropriate
in non-new task decisions. Based on this, the criteri-
on for choice of a respondent in each firm is that one
should be experienced or knowledgeable about the
supply chain management, operations management
decisions and activities of the firm at the time of the
survey. The researcher administered the question-
naires personally in order to enhance the response
rate and quality of data collected as supported by
Bhagwat & Sharma (2007) using the official request.
2.6. Data Analysis
The positivistic approach that advocates for hy-

potheses testing using quantitative techniques to
research guided data analysis (Stiles, 2003).Thus, in-
formation required for testing the study hypotheses
was generated using quantitative data analytical
techniques. Consequently, data analysis followed
Umma (2006) four step process for data analysis:
“getting data ready for analysis; getting a feel for the
data; testing the goodness for the data; and testing
the hypotheses”.
The researcher used descriptive statistics for Likert
scale variables in the questionnaire. The measures of
dispersion were used in order to explore the under-
lying features in the data on large scale manufactur-
ing firms in Nairobi, Kenya. Descriptive statistics
covered all response variables as well as the demo-
graphic characteristics of respondents. Descriptive
statistics provides the basic features of the data col-
lected on the variables and provide the impetus for
conducting further analyzes on the data (Ezirim &
Nwokah, 2009; Mugenda & Mugenda, 2003).
A correlation analysis was done to establish the rela-
tionships among the study variables. The correlation
analysis was computed to describe the relationships
that exist among key variables of the study and/or use
the known correlation to determine the outcome from
one variable to another. A multiple linear regression
model was adopted to study the linear relationships
among the various study variables. A multiple linear
regression analysis is a multivariate statistical tech-
nique used to estimate the model parameters and
determine the effect of individual independent vari-
ables (IVs) on the dependent variable (DV).
Firm performance
(Y) = b0+ b1X1 + b2X2 + b3X3 + b4X4 …+ bpXp + ei (1)
Where;
Y is the dependent variable (Firm Performance) and
is a linear function of X1, X2, X3, X4…Xi plus ei .
Y Firm Performance Index (FPI) was computed as an
average of the five year’s Annual Firm Performance
Composite.
b0 is the regression constant or intercept, b1-p are
the regression coefficients or change induced in Y
by each X, ei is a random variable, error term that
accounts for the variability in Y that cannot be ex-
plained by the linear effect of the i predictor vari-
ables and X1-p are independent variables (Long-
range and Mid-range supply chain strategies)
3. RESEARCH RESULTS AND FINDINGS
One of the methodological weaknesses of previous
studies were small sample sizes and low response
rate. This study’s response rate of 75% is high com-
pared to previous studies whose average response
rate was 65 percent or less. Kidombo (2007) who
had studied large private manufacturing firms in
Kenya had 64% response rate; Kirchoff (2011) had
a very low response rate of 28 percent. According
to Tomaskovic-devey et al. (2007) any response rate
of about 15.4% is considered as yielding a relatively
high response rate considering the demands on the
time of top-level executives. All subsectors of the
large scale manufacturing sector were well repre-
sented in this study, avoiding any chances of bias or
misrepresentation.
The majority of the firms (68%) have successfully
managed their supply chains while 16% see their
supply chains as very successful and somewhat
successful. This is an indication that the supply
chain department exists in most large-scale man-
ufacturing firms (84) and probably managed by
specialists who understood what the items in the
questionnaire were testing and the appropriate re-
sponse that was required. This implies that only
those firms that have managed their supply chains
have sound strategies that are in place to guide the
operations of the firm.
3.1. Firm Performance Index
Weighted scores were applied on the collected data
to determine the firm performance index on aver-
age for all the firms that participated in this study as
shown in Table 2 below.

Table 2: Firm Average Performance Index
DOMAIN
ACHIEVEMENTS Weighted Performance (WP i) … (4)
2006
2007
2008
2009
2010
2006
2007
2008
2009
2010
A. Financial & Stewardship
Pre-tax Profits
Kshs
. (m) 10
108.
6
132.
1
137.
2
131.
8
158.
0
10.8
6
13.2
1
13.725
49
13.1
8
15.80
718
Debt –Equity Ratio % 5 38.3 42.1 48.0 47.2 50.5 1.91 2.10 2.40 2.36 2.525
Return on Investment % 5 41.7 45.9 51.1 53.7 57.5 2.08 2.29 2.55 2.68 2.87
Development Index % 5 44.7 49.5 55.4 60.1 66.0 2.23 2.47 2.77 3.00 3.30
Payback on investments Time 5 8.7 8.2 7.3 6.4 6.9 0.43 0.41 0.36 0.32 0.34
Weights – Sub Total 30
242.
2
27
7.9
29
9.8
29
9.5
33
9.2
17.
54
20.
50
21.81
7
21.
56
24.8
6
B. Customers Perspective
Customer satisfaction % 10 61.3 65.7 70.8 75.8 79.7 6.13 6.57 7.08 7.58 7.97
Customer price margin % 6 39.8 41.8 43.4 45.5 46.5 2.39 2.50 2.60 2.73 2.79
Resolution of customer
complaints % 4 60.0 64.7 69.5 73.4 79.2 2.40 2.59 2.78 2.93 3.17
16
1
17
2
18
3
19
4
20
5
10.
9
11.
7 12.5
13.
3 13.9
C. Internal Business Operations
AverageFPI----6
Cost efficiency % 10 55.9 59.8 64.3 68.5 73.3 5.59 5.98 6.43 6.85 7.33
Automation % 8 50.9 56.2 61.7 66.3 72.7 4.07 4.50 4.93 5.30 5.82
Warranty quality % 6 55.9 59.6 63.8 68.3 73.3 3.35 3.58 3.83 4.10 4.39
Safety Measures % 2 59.1 63.9 68.9 72.0 78.9 1.18 1.27 1.37 1.44 1.57
Research & Development % 4 51.5 56.3 61.0 65.1 71.9 2.06 2.25 2.449 2.60 2.87
Work Environment % 2 56.3 60.4 64.9 68.5 73.6 1.12 1.20 1.29 1.37 1.47
Capacity Utilization % 4 58.2 62.3 67.9 72.3 77.9 2.33 2.49 2.71 2.89 3.11
ISO Certification
(9001:2008) % 4 44.3 47.6 55.7 59.9 65.5 1.77 1.90 2.22 2.39 2.62
43
2
46
6
50
8
54
3
58
7
21.
5
23.
2 25.3
27.
0 29.2
D. Employee and Organization Innovation
Employee satisfaction % 5 59.4 64.2 68.1 71.8 75.8 2.97 3.21 3.409 3.59 3.79
Employee Retention % 2 75.6 79.8 81.9 85.7 87.3
1.51
2
1.59
6 1.638
1.71
4 1.746
Employee productivity % 2 60.5 65.0 69.4 72.0 75.5 1.21 1.30 1.38 1.44 1.51
Competency Development % 1 56.6 61.4 65.5 69.6 73.4 0.56 0.61 0.65 0.69 0.73
25
2
27
0
28
5
29
9
31
2 6.3 6.7 7.1 7.4 7.8
TOTAL/Performance
Index 100 Annual Firm Performance......5
56.
2
62.
1 66.6
69.
2 75.8
66.
0
Source: Research Data, 2014
From the results in Table 2 above on firm performance, there is specific improvement on the four
dimensions of firm performance of financial & stewardship, customers’ perspective, internal business
operations including those of employee and organization innovation. This is an indication that the
firms have improved performance that is balanced touching on all aspects of the firm about its internal
and external customers who make up its supply chain. All the four domains were equally affected in
From the results in Table 2 above on firm perfor-
mance, there is specific improvement on the four
dimensions of firm performance of financial & stew-
ardship, customers’ perspective, internal business
operations including those of employee and orga-
nization innovation. This is an indication that the
firms have improved performance that is balanced
touching on all aspects of the firm about its inter-
nal and external customers who make up its supply
chain. All the four domains were equally affected
in 2008/2009 period that might be as a result of the
post-election violence in Kenya. Each of the four di-
mensions of the firm’s performance is a relative sec-
tor to the total sub weights. For example, in 2006 the
firms scored 6.3 out of the possible score of 10% in
the employee and organization innovation (x/10).
The above computations were done for each firm to
determine their annual firm performance and firm
performance index that was used as the dependent
variables (Y) in the next section of correlation analy-
sis and subsequently on test of hypotheses.

3.2. The Correlation between Supply Chain Strategies
and Firm Performance
Spearman’s rank order correlation analyzes the re-
lationships between supply chain strategies (Mid-
range and long-range) and firm performance as pre-
sented in Table 3 below. From the results in Table
3, there is a strong, and positive relationships are
observed between long-range supply chain strate-
gies (r = 0. 690, p< 0.01) and firm performance. These
two long-range supply chain strategies are demand
supply chain strategy and innovation supply chain
strategy. Indeed, innovations and demand are spe-
cific the firms’ operations and products respectively.
Table 3: Correlation between Supply Chain Strategies and Firm Performance
16
Spearman’s rank order correlation analyzes the relationships between supply chain strategies (Mid-
range and long-range) and firm performance as presented in Table 3 below. From the results in Table
3, there is a strong, and positive relationships are observed between long-range supply chain strategies
(r = 0. 690, p< 0.01) and firm performance. These two long-range supply chain strategies are demand
supply chain strategy and innovation supply chain strategy. Indeed, innovations and demand are
specific the firms’ operations and products respectively.
Table 3: Correlation between Supply Chain Strategies and Firm Performance
Supply Chain Strategy Variables Spearman’s rho
Coefficients
Long-range SC Strategy Innovation SC strategy. 0. 690(**)
Mid-range SC Strategy No need for SC strategy 0.591(*)
Long-range SC Strategy Demand SC strategy. 0.545(*)
** Correlation is significant at p< 0.01 level (2-tailed).
* Correlation is significant at p< 0.05 level (2-tailed).
Also from the results in Table 3 above, the Mid-range supply chain strategy have a weak but
significant relationship (r = 0.591, p<0.05) with firm performance. This is characterized by a
nonexistent supply chain strategy in the firm which can lead to total supply chain failure and customer
dissatisfaction.
The results of supply chain strategy and firm performance show that it is long-range planning that can
support firm competitiveness as evidenced by the effect of long-range supply chain strategies on both
supply chain performance and firm performance. The Mid-range strategies are used by most firms as
** Correlation is significant at p< 0.01 level (2-tailed).
* Correlation is significant at p< 0.05 level (2-tailed).
Also from the results in Table 3 above, the Mid-range
supply chain strategy have a weak but significant re-
lationship (r = 0.591, p<0.05) with firm performance.
This is characterized by a nonexistent supply chain
strategy in the firm which can lead to total supply
chain failure and customer dissatisfaction.
The results of supply chain strategy and firm perfor-
mance show that it is long-range planning that can
support firm competitiveness as evidenced by the
effect of long-range supply chain strategies on both
supply chain performance and firm performance.
The Mid-range strategies are used by most firms
as experimental strategies as they craft long-range
strategies. The only surprising result is that none of
the long-range supply chain is supporting both sup-
ply chain performance and firm performance, mean-
ing that firms can implement several supply chain
strategies to support various objectives at the supply
chain level and corporate level.
3.3. Hypothesis Testing
This study aimed at establishing the relationship
between SC strategies and firm performance among
large-scale manufacturing firms in Kenya. The lit-
erature review and theoretical reasoning led to the
reasoning that both Mid-range and Long-range sup-
ply chain strategies are associated with firm perfor-
mance. The four Mid-range supply chain strategies
are operational and will affect firm midterm perfor-
mance. The long-range supply chain strategies are
most representative of how companies articulate
their models for competing now and in the future.
Hence, the following hypotheses were tested:
H: Supply Chain Strategies are positively related to Firm
Performance
The supply chain strategies items were measured on
a scale of 1 to 5 where “5” was to a great extent and
“1” to a very small extent. It consisted of statements
that sought to measure the extent to which the firms
have used the supply chain strategies. Supply chain
performance index computed from the achievement
on certain items for five years. The Spearman’s cor-
relation showed significant relationship between
long-range (r = 0. 690, p< 0.01) and mid-range (r =
0.591, p< 0.05) supply chain strategies individually
with firm performance. Further analysis using mul-
tiple regression analysis is presented in Table 4 be-
low and Annex I.

Table 4: Regression Results for Supply Chain Strategies and Firm Performance
18
Model Summary: Objective 2 (Data Analysis Model #i)
Method: Stepwise (Criteria: Probability-of-F-to-enter≤.050,
Probability-of-F-to-remove ≥ .100). ANOVA(f)
Stepwise
Model R R2
Adjusted R2
Std. Error of the
Estimate
Mean
Square F Sig.
1 .545(a) .297 .291 10.19816 4490.500 43.177 .000(a)
2 .674(b) .455 .444 9.02904 3432.442 42.104 .000(b)
3 .720(c) .519 .505 8.52191 2612.157 35.969 .000(c)
4 .757(d) .574 .556 8.06489 2164.888 33.284 .000(d)
5 .793(e) .629 .611 7.55540 1900.903 33.300 .000(e)
6 .818(f) .669 .649 7.17663 1683.812 32.693 .000(f)
7 .837(g) .701 .679 6.85599 1512.331 32.174 .000(g)
8 .848(h) .720 .696 6.67527 1358.204 30.481 .000(h)
9 .860(i) .739 .714 6.47731 1239.438 29.542 .000(i)
10 .868(j) .754 .727 6.32309 1138.048 28.464 .000(j)
11 .876(k) .768 .740 6.17524 1053.680 27.631 .000(k)
12 .891(l) .794 .767 5.84211 999.409 29.282 .000(l)
a, b, c, d, e, f, g, h, i, j, k, l Predictors: (Constant), Supply chain strategies
m Dependent Variable: Firm Performance
From the regression results in Table 4 above, twelve models have been generated using a stepwise
approach where the probability-of-F-to-enter was ≤.050 while the probability-of-F-to-remove was ≥
.100. The stepwise multiple regression model number 12 or L is the most significant model since it has
the inclusion of most supply chain strategies while the results are significant at the set confidence
interval of 95%. Also from the model Table 4, it is observed that as one moves from stepwise model 1
to 12, the standard error of the estimated models decrease from 10.19816 to 5.84211 as so does the F
values from 43.177 to 28.282. The adjusted R2
improves from 0.291 to 0.767. Although all the twelve
models are significant, stepwise model number twelve is a good predictor of the relationship between
supply chain strategies and firm performance.
The stepwise regression model number 12 shows a strong significant relationship between supply
chain strategies and firm performance, implying that the supply chain strategies explain 76.7 % of the
a, b, c, d, e, f, g, h, i, j, k, l Predictors: (Constant), Supply chain strategies
m Dependent Variable: Firm Performance
From the regression results in Table 4 above, twelve
models have been generated using a stepwise ap-
proach where the probability-of-F-to-enter was ≤.050
while the probability-of-F-to-remove was ≥ .100. The
stepwise multiple regression model number 12 or L
is the most significant model since it has the inclusion
of most supply chain strategies while the results are
significant at the set confidence interval of 95%. Also
fromthemodelTable4,itisobservedthatasonemoves
from stepwise model 1 to 12, the standard error of the
estimated models decrease from 10.19816 to 5.84211 as
so does the F values from 43.177 to 28.282. The adjust-
ed R2 improves from 0.291 to 0.767. Although all the
twelve models are significant, stepwise model number
twelve is a good predictor of the relationship between
supply chain strategies and firm performance.
The stepwise regression model number 12 shows a
strong significant relationship between supply chain
strategies and firm performance, implying that the
supply chain strategies explain 76.7 % of the chang-
es in the firm’s performance. The coefficients of this
predictive model aimed at addressing the concerns
of objective two as modeled in model number eight
of the data analysis are given as in Annex I.
From the specific beta coefficients for the measures
of supply chain strategies in Annex, I indicate that
both long range and Mid-range the supply strategies
make some contribution to the firm’s performance.
All the long range supply chain strategies that af-
fect supply chain performance also affect firm per-
formance. They include the long range risk-hedging
supply chain strategy (beta = -0.348); Speed to mar-
ket supply chain strategy (beta = -0.304) and cash-
to-cash cycle supply chain strategy (beta = -0.240).
The supply chain strategies that have an impact on
firm performance and not the firm’s supply chain
performance outcome include: efficient supply
chain strategies where the firm continuously plans
its supply chain network to limit exposure to cost
fluctuations(beta = 0.729); project logistics supply
chain strategies that allows the firm to cost effective-
ly receives and delivers products as the sources of
supply and customer change (beta = 0.435); innova-
tion supply chain strategy focused on variable pro-
ductivity to meet speculative purchasing and sales
promotion (beta = 0.403); Demand supply chain
strategy responsive and flexible to customer needs
to enable the firm feed customers in ways that are
efficient for them (beta = 0.343); Synergistic supply

chain strategy where the firm creates additional re-
lationship with supply chain members at the point
where their operation interact (beta = 0.261). These
are among the long range supply chain strategies
that build around projects, innovation, demand
forecasting and synergy that are key to the firm’s
positive performance. The two Mid-range strate-
gies that have a positive impact on the firm’s perfor-
mance include: Third-party supply chain strategy
where the firm evaluates opportunities to outsource
areas that are not their core competencies in the sup-
ply chain (beta = 0.310) and the supply chain strat-
egy where numerous internal and external activities
are co-ordinated to conform to the overall business
strategy (beta = -0.235). The supply chain strategy
on conformance has a negative effect on the firm’s
performance as it denies the firm some level of flex-
ibility for the firm to adjust to the changes in its en-
vironment of operation. It only the investment on
long-range supply chain strategies that can lead to
improved firm performance levels.
As shown in Table 4 above and Annex I, when Mid-
range and long-range supply chain strategies are in-
cluded in the same model, they have a strong posi-
tive effect on firm performance with a correlation
coefficient of R = 0.891(l) and adjusted R2 = 0.767,
F = 29.282; Sig. = .000(l). This implies that 76.7% of
the variance in the firm’s performance is explained
by the combined variables of Mid-range and long-
range supply chain strategies. The relationships be-
tween supply chain strategies and firm performance
are positive. Given that the calculated F = 29.282,
while the F Critical = 1.7611; at α = 5% (95% C.I),
numerator degrees of freedom - V1 = 16 (17-1) and
denominator degrees of freedom -V2 = 87 (103-16).
Then F ≥ F Critical at α = 5%. This is a clear indica-
tion that supply chain strategy is a significant pre-
dictor of the firm’s performance. The relationships
explained by the combined variables of Mid-range
and long-range supply chain strategies on the firm’s
performance are positive and statistically signifi-
cant. Hence, H is accepted.
The second objective had two sub-hypotheses to
be tested. Other than the combined effect of supply
chain strategies, it was anticipated that Mid-range
supply chain strategies are likely to have important
implications on firm performance. Hence, the fol-
lowing sub-hypothesis was tested:
H1a: Mid-range SC Strategies are positively related to
Firm Performance
The results of Spearman’s correlation showed a cor-
relation coefficient of r = 0.591, p< 0.05. The multiple
regression analysis is presented in Table 5a&b below.
Table 5a: Regression Model Summary Results for Mid-Range
Supply Chain Strategies and Firm Performance
Model No. 8a
R R Square Std. Error of the Estimate F Sig.
.545(a) .297 11.24111 2.218 .102(a)
a Predictors: (Constant), Mid-range Supply chain strategies
b Dependent Variable: Firm Performance
Table 5b: Regression Results for Mid-Range Supply Chain Strategies and Firm Performance
Mid-range Supply
chain strategies
Nano-Chain
supply chain
strategy
Tie down the firm
supply chain
strategy
Third-party
SC strategy
No need for
supply chain
strategy
Standardized
Coefficients (Beta)
.477 .211 -.124 -.175
The beta values for the four Mid-range supply chain strategies show greater individual contributions.
From the summary of standardized beta coefficients in Table 5b above, the two Mid-range supply
chain strategies that have a positive effect (positive beta value) on the firm’s performance outcome
include: mid-range supply chain strategies that allows the firm's assets and operations to react to
Model No. 8a
.545(a) .297 11.24111 2.218 .102(a)
Mid-range Supply
chain strategies
Nano-Chain
supply chain
strategy
Tie down the firm
supply chain
strategy
Third-party
SC strategy
No need for
supply chain
strategy
Standardized
Coefficients (Beta)
.477 .211 -.124 -.175
The beta values for the four Mid-range supply chain strategies show greater individual contributions.
From the summary of standardized beta coefficients in Table 5b above, the two Mid-range supply

The beta values for the four Mid-range supply chain
strategies show greater individual contributions.
From the summary of standardized beta coefficients
in Table 5b above, the two Mid-range supply chain
strategies that have a positive effect (positive beta
value) on the firm’s performance outcome include:
mid-range supply chain strategies that allows the
firm’s assets and operations to react to emerging
customers trends at each node of the supply chain
(Nano-Chain supply chain strategy); and mid-range
supply chain strategies where numerous internal
and external activities are coordinated to conform
to the overall business strategy (Tie down the firm
supply chain strategy). The two riskiest Mid-range
supply chain strategies for the firm’s performance
are those mid-range supply chain strategies where
the firm evaluates opportunities to outsource areas
that are not their core competencies in the supply
chain (Third-party SC strategy); and mid-range sup-
ply chain strategies where the firm does not have or
pursue a formal supply chain strategy (No need for
supply chain strategy).
The analysis in Table 5a and 5b above show that the
Mid-range supply chain strategies have a positive
relationship with firm performance with a correla-
tion coefficient of R = .545(a) and R2 = 0.297. This
implies that 30% of the variance in firm performance
is explained by the Mid-range supply chain strate-
gies. Given that α = 5%, the F value of 2.218 is not
significant (sign. = 0.102) hence Mid-range supply
chain strategies are not good predictors of the firm’s
performance. Hence, Ha is Accepted.
Hb: Long-range SC Strategies are positively related to
Firm Performance
The results of Spearman’s correlation showed a cor-
relation coefficient of r = 0. 690, p< 0.01. The multiple
regression analysis is presented in Table 6 below.
Table 6: Regression Model Summary Results for Long-Range
Supply Chain Strategies and Firm Performance
strategies. Given that α = 5%, the F value of 2.218 is not significant (sign. = 0.102) hence Mid-range
supply chain strategies are not good predictors of the firm’s performance. Hence, Ha is Accepted.
Hb: Long-range SC Strategies are positively related to Firm Performance
The results of Spearman’s correlation showed a correlation coefficient of r = 0. 690, p< 0.01. The
multiple regression analysis is presented in Table 6 below.
Table 6: Regression Model Summary Results for Long-Range Supply Chain Strategies and Firm
Performance
Model No. 8b
.858(a) .735 8.76469 3.011 .030(a)
a Predictors: (Constant), Long-Range Supply chain strategies
Based on the beta values for the twelve long-range supply chain strategies that show greater individual
contributions to the firm’s performance, the strategies that have a positive effect (positive beta value)
on firm’s performance include: long-range supply chain strategies where the firm continuously plans
its supply chain network to limit exposure to cost fluctuations (Efficient Supply Chain strategy, Beta =
.610); long-range supply chain strategies focused on variable productivity to meet speculative
purchasing and sales promotion (Innovation supply chain strategy, Beta =.421) long-range supply
chain strategies responsive and flexible to customer needs to enable the firm Feed Customers in ways
that are efficient for them (Demand supply chain strategy, Beta =.368); long-range supply chain
strategies that allows the firm to cost effectively receives and delivers products as the sources of
supply and customer change (Project logistics supply chain strategy, Beta =.240); long-range supply
chain strategies where the firm creates additional relationship with supply chain members at the point
where their operation interact (Synergistic SC strategy, Beta =.183); and lastly long-range supply chain
a Predictors: (Constant), Long-Range Supply chain strategies
Based on the beta values for the twelve long-range
supply chain strategies that show greater individual
contributions to the firm’s performance, the strate-
gies that have a positive effect (positive beta value)
on firm’s performance include: long-range supply
chain strategies where the firm continuously plans
its supply chain network to limit exposure to cost
fluctuations (Efficient Supply Chain strategy, Beta =
.610); long-range supply chain strategies focused on
variable productivity to meet speculative purchas-
ing and sales promotion (Innovation supply chain
strategy, Beta =.421) long-range supply chain strat-
egies responsive and flexible to customer needs to
enable the firm Feed Customers in ways that are
efficient for them (Demand supply chain strategy,
Beta =.368); long-range supply chain strategies that
allows the firm to cost effectively receives and deliv-
ers products as the sources of supply and customer
change (Project logistics supply chain strategy, Beta
=.240); long-range supply chain strategies where
the firm creates additional relationship with supply
chain members at the point where their operation
interact (Synergistic SC strategy, Beta =.183); and
lastly long-range supply chain strategies that allows
the firm and supply chain members to adopt to dif-
ferent products of different segment of the market
(Speed to market supply chain strategy, Beta = -.094).
The most risky long-range supply chain strategies
for the firm’s performance are those long-range sup-
ply chain strategies aimed at speeding and retain-
ing cash flow for the firm (Cash-to-cash cycle supply
chain strategy, Beta = -.161); long-range supply chain
strategies directed to minimizing risks like produc-
tion capacity, quality, floods and earthquakes in the
process of procurement, production and distribu-

tion (Risk-hedging Supply Chain strategy, Beta =
-.189); long-range supply chain strategies that pro-
vides balance of flexibility and cost efficiency in the
supply chain while meeting the requirements of the
marketplace requirements (Value chain strategy,
Beta = -.211); long-range supply chain strategies that
increases the firm’s ability to mass-maximize and
build close relations with customers when design-
ing new and modifying existing products (Market
dominance and backlog supply chain strategy, Beta
= -.301); and long-range supply chain strategies that
are reactive to procurement, production and distri-
bution in dynamic environments to answer to cus-
tomer needs (Micro-chain supply chain strategy,
Beta = -.404).
The analysis in Table 6 above show that the long-
range supply chain strategies have a strong positive
effect on firm performance with a correlation coef-
ficient of R = 0. 858 (a) and R2 = 0. 735. This implies
that 74% of the variance in firm performance is part-
ly explained by the long-range supply chain strate-
gies. Both Mid-range and long-range supply chain
strategies explain 76% of the variance in firm per-
formance, meaning it is the long-range supply chain
strategies that contribute most to the firm’s perfor-
mance. Given that α = 5%, the F value of 3.011 is sig-
nificant (sign. = 0.030) the long-range supply chain
strategies are good predictors of the firm’s perfor-
mance. Hence, Hb is Accepted.
4. DISCUSSION OF THE FINDINGS
Scholarly research should contribute to and extend
the current literature by filling in existing gaps for
both researchers and managers (Kirchoff, 2011;
Varadarajan, 2003). This section discusses the find-
ings guided by the primary research objectives and
hypotheses. This study aimed at establishing the re-
lationship between SC strategies and performance
of large-scale manufacturing firms in Kenya. Two
sub-hypotheses were derived from this objective.
The hypotheses tested the relation between Mid-
range and long-range supply chain strategies with
firm performance.
Most previous conceptual and qualitative research
has focused on the strategy content with general
guidelines, but the influence of these strategies on
the relationship between supply chain strategies
and firm performance has neither been thoroughly
underpinned with theory nor analyzed through em-
pirical research (Chopra & Meindl, 2007). The results
supported the hypothesized relationships except in
the case of Mid-range supply chain strategies that
don’t have much support for firm performance. This
empirical evidence is, therefore, a major contribu-
tion the specific supply chain strategies (not content)
and their relationship firm performance.
Although, most previous studies have examined the
concept of supply chain strategy and firm perfor-
mance, there are very few of them on supply chain
strategy and even fewer studies about the relation-
ship between supply chain strategy and firm perfor-
mance (Gudnason & Riis, 1984). This study has in-
deed taken this opportunity to confirm that there is a
positive and significant relationship between supply
chain strategies and firm performance. This clears
the contradiction by Menor, Kristal, & Rosenzweig
(2007) that the investment in supply chain strategy
is associated with increased costs, and it does not
translate to improved firm performance.
Mid-range SC strategies are not good predictors of
firm performance. Particularly, the supply chain
strategies that focus on conformance have a nega-
tive effect on the firm’s performance as they deny
the firm some level of flexibility to adjust to the
changes in its environment of operation. It is only
the investment on long-range SC strategies that can
lead to improved firm performance levels. The riski-
est long-range SC strategies for the firm’s perfor-
mance are those long-range supply chain strategies
aimed at speeding and retaining cash flow for the
firm. This relationship between SC strategies and
firm performance is based on data collected over a
period of five years. The use of secondary data espe-
cially for firm performance metrics is a big strength
in explaining the causal relationships. This provided
an opportunity to peruse the firm manuals and fi-
nancial reports to crosscheck the achievements in
firm performance. This was to fill the gaps identi-
fied by Sánchez & Pérez (2005) which indicated that
most studies in firm performance have used cross-
sectional data, which are limited in order to explain
causal relationships; with failure to use any second-
ary data to crosscheck firm performance. The study
findings agree with the conclusions that supply
chain practices have a significant effect on firm per-
formance (Golicic & Smith, 2013; Khan & Pillania,
2008; Lee et al., 2012; Li et al., 2006)
This study used a balanced scorecard to measure
firm performance. This affirms that the best way to
measure the implementation of any strategy and
yield valid results is through the use of the Balanced

Scorecard. This findings are supported by Kaplan
& Norton (1992) conclusion that a Balanced Score-
card supports management to improve the financial
performance of the enterprise where failure trans-
lates the improved operational performance into im-
proved financial performance that send executives
back to the drawing board to rethink the company’s
strategy or its implementation plans.
5. CONCLUSIONS
There is a strong and significant relationship be-
tween supply chain strategy and the firm’s perfor-
mance where Supply chain strategies explain 76.7 %
of the changes in the firm’s performance.
5.1. Contributions to Knowledge
By empirically testing the extent to which supply
chain strategies are associated to firm and supply
chain performance, the present study adds to aca-
demic knowledge in several ways by proving em-
pirical evidence pointing towards the significant use
of supply chain strategies that will lead to different
levels of achievement in firm performance. The in-
clusion of the construct supply chain strategy in this
study contributes to both the operations manage-
ment and SCM literature as both the operationaliza-
tion and empirical testing of supply chain strategy
has only been investigated in the strategic manage-
ment and marketing literature. This study of supply
chain strategy within operations management was
motivated by premise presented by Boyer & Pagell
(2000) and Chan & Qi (2003) that there is need for
empirical research that will give an extension of the
operations strategy perspective towards the more
recent supply chain thinking.
Certain strategies are developed and implemented
by firms due to stakeholder pressure, regulatory de-
mands, social legitimacy, and the perceived direct
economic benefits. However, the economic benefits
and motivation for implementing SC strategies have
rarely been tested empirically (Thun & Müller, 2010;
Zhu, Sarkis, & Lai, 2008). The findings in this study
represent the first empirical study that has found a
significant relationship between SC strategies and
firm performance improvements. This indicates that
firms use SC strategies to improve their financial
stewardships, service delivery, operations and cus-
tomer dynamics that are multiple dimensions relat-
ed to firm performance. This study also widens the
avenue for further research on the moderating role
of SCT on the relationship between SC strategies and
firm performance. Scholars can use the results to
extend performance metrics, study comparisons of
different sample sets, and look at longitudinal data
for break-even points on the number of SC strategies
and technologies implementation.
The findings from this empirical study provide
evidence that the RBV of the firm is an important
theory in the study of the relationship between SC
strategies to firm performance. This extends the
conceptual and empirical research in areas related
to SC strategy by suggesting that firms with enough
capabilities and resources may be more likely to
implement SC strategies and realize improvement
in firm performance, compared to the competition.
Based on the conclusions by Puri (2013) and that
most empirical research on the relationship between
supply chain practices and firm performance is lim-
ited in number and often with conflicting findings,
this current study had set out to conclusively and
empirically investigate the role of technology in the
relationship between SC strategies and firm perfor-
mance. This empirical study has contributed to a
greater understanding of the relationship between
SC strategies and firm performance to the current
knowledge in this area.
5.2. Future Research Directions
The limitations in the previous section can be ad-
dressed but beyond that, there are a number of in-
teresting and exciting future research possibilities
based on the findings from this study. While the
objective of this study was achieved, the future re-
search in an effort to enhance the conclusions of this
study’s findings by focusing on other variables like
risk management strategies as a moderator on the
relationship between SC strategies and firm perfor-
mance. This study focused on supply chain strate-
gies that could cut across procurement, value cre-
ation and distribution. Future studies can narrow
their focus to procurement strategies, value creation
strategies, and distribution strategies by comparing
their impact on firm performance.
The data collected for firm performance was quan-
titative in nature. This was in response to Awino’s
(2011) suggestion that in order to provide a rich
research database for future research, future study
may explore alternative performance measurement
indicators of the quantitative nature, such as finan-
cial measures, accounting measures, balance score-

cards, linkages to financial statements amongst oth-
ers. These secondary data was not easy to get. The
firms indicated that it was classified information
while other indicated that was confidential, hence
giving the researcher tough conditions in its use.
6. REFERENCES
Agha, S., Alrubaiee, L., & Jamhour, M. (2011). Effect of Core
Competence on Competitive Advantage and Organizational
Performance. International Journal of Business and Manage-
ment, 7(1), 192–204. http://doi.org/10.5539/ijbm.v7n1p192
Bhagwat, R., & Sharma, M. K. (2007). Performance measurement
of supply chain management: A balanced scorecard ap-
proach. Computers and Industrial Engineering, 53(1), 43–62.
http://doi.org/10.1016/j.cie.2007.04.001
Bolo, A. Z. (2011). An empirical investigation of selected strategy
variables on firms performance :A study of supply chain man-
agement in large private manufacturing firms in Kenya. Busi-
ness Administration and Management, 3(October), 228–236.
Boyer, K. K., & Pagell, M. (2000). Measurement issues in empiri-
cal research: Improving measures of operations strategy and
advanced manufacturing technology. Journal of Operations
Management, 18(3), 361–374. http://doi.org/10.1016/S0272-
6963(99)00029-7
Burgess, K., Singh, P. J., & Koroglu, R. (2006). Supply chain
management: a structured literature review and implica-
tions for future research. International Journal of Opera-
tions & Production Management, 26(7), 703–729. http://doi.
org/10.1108/01443570610672202
Chan, F. T. S., & Qi, H. J. (2003). An innovative performance
measurement method for supply chain management. Supply
Chain Management: An International Journal, 8(3), 209–223.
http://doi.org/10.1108/13598540310484618
Chopra, S., & Meindl, P. (2007). Supply Chain Management: Strat-
egy, Planning and Operation, (3rd ed.). Pearson Prentice Hall.
Collins, J. D., Worthington, W. J., Reyes, P. M., & Romero, M.
(2010). Knowledge management, supply chain technolo-
gies, and firm performance. Management Research Review,
33(10), 947–960. http://doi.org/10.1108/01409171011083969
Cooper, M. C., & Ellram, L. M. (1993). Characteristics of Sup-
ply Chain Management and the Implications for Pur-
chasing and Logistics Strategy. The International Jour-
nal of Logistics Management, 4(2), 13–24. http://doi.
org/10.1108/09574099310804957
Cousins, P. D., Lawson, B., & Squire, B. (2006). Supply chain
management: theory and practice – the emergence of an
academic discipline? International Journal of Operations
& Production Management, 26(7), 697–702. http://doi.
org/10.1108/01443570610672194
Ezirim, A. C. ., & Nwokah, N. G. . (2009). Firms entrepreneurial
orientation and export marketing performance in the Nige-
rian non-oil sector. European Journal of Scientific Research,
35(3), 318–336.
Fawcett, S. E., Ogden, J. a., Magnan, G. M., & Cooper, M. B.
(2006). Organizational commitment and governance for
supply chain success. International Journal of Physical Dis-
tribution & Logistics Management, 36(1), 22–35. http://doi.
org/10.1108/09600030610642913
Gattorna, J. (2006). Living supply chains: how to mobilize the
enterprise around delivering what your customers want. Fi-
nancial Times Series (1st ed.). Prentice Hall. http://doi.org/0-
273-70614-4
GoK. (2007). Kenya Vision 2030: A Globally Competitive and
Prosperous Kenya. Government of Kenya, National Econom-
ic and Social Council (NESC). Nairobi, Kenya.
Golicic, S. L., & Smith, C. D. (2013). A Meta-Analysis of Environ-
mentally Sustainable Supply Chain Management Practices
and Firm Performance. Journal of Supply Chain Manage-
ment, 49(2), 78–95.
Gudnason, C., & Riis, J. (1984). Manufacturing strategy. Omega
(Vol. 12). http://doi.org/10.1016/0305-0483(84)90057-4
Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance
measures and metrics in a supply chain environment. Inter-
national Journal of Operations & Production Management,
21(1/2), 71–87. http://doi.org/10.1108/01443570110358468
Halley, A., & Beaulieu, M. (2009). Mastery of operational compe-
tencies in the context of supply chain management. Supply
Chain Management: An International Journal, 14(1), 49–63.
Hines, T. (2009). Supply chain strategies: customer driven
and customer focussed (2nd ed.). Routledge. http://doi.
org/10.4324/9780203631669
Hult, G. T. M., Ketchen, D. J., Cavusgil, S. T., & Calantone, R. J.
(2006). Knowledge as a strategic resource in supply chains.
Journal of Operations Management, 24(5), 458–475. http://
doi.org/10.1016/j.jom.2005.11.009
Johnson, G., Scholes, K., & Whittington, R. (2007). Explor-
ing Corporate Strategy. (8th ed.). Prentice Hall. http://doi.
org/10.1016/0142-694X(85)90029-8
Kamaruddin, N. K., & Udin, Z. M. (2009). Supply chain technol-
ogy adoption in Malaysian automotive suppliers. Journal
of Manufacturing Technology Management, 20(3), 385–403.
Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard -
measure that drive performance. Harvard Business Review,
70(1), 71–79.
Kate Cowles. (2006). Statistical Methods and Computing: Sample
size for confidence intervals with known t Intervals. IOWA.
Keegan, D. P., Eiler, R. G., & Charles, R. J. (1989). Are your per-
formance measures obsolete? Management Accounting,
Ketchen, D. J., & Giunipero, L. C. (2004). The intersection of
strategic management and supply chain management. In-
dustrial Marketing Management, 33(1), 51–56. http://doi.
org/10.1016/j.indmarman.2003.08.010

Khan, A., & Pillania, R. (2008). Strategic sourcing for supply
chain agility and firms’ performance: A study of Indian man-
ufacturing sector. Management Decision, 46(10), 1508–1530.
Kidombo, H. (2007). Human Resource Strategic Orientation, Or-
ganizational Commitment and Firm Performance in Large
Private Manufacturing Firms in Kenya. University of Nairobi.
Kirchoff, J. F. (2011). A Resource-Based Perspective on Green
Supply Chain Management and Firm Performance. Univer-
sity of Tennessee.
Lars-Erik Gadde, Hakan Hakansson, G. P. (2001). Supply Network
Strategies (2nd ed.). West Sussex, UK: John Wiley & Sons.
Lee, S. M., Kim, S. T., & Choi, D. (2012). Green supply chain man-
agement and organizational performance. Industrial Man-
agement & Data Systems, 112(8), 1148–1180. http://doi.org/
DOI 10.1108/02635571211264609
Li, S., Ragu-Nathan, B., Ragu-Nathan, T. S., & Subba Rao, S.
(2006). The impact of supply chain management prac-
tices on competitive advantage and organizational perfor-
mance. Omega, 34(2), 107–124. http://doi.org/10.1016/j.ome-
ga.2004.08.002
Menor, L. J., Kristal, M. M., & Rosenzweig, E. D. (2007). Exam-
ining the Influence of Operational Intellectual Capital on
Capabilities and Performance. Manufacturing & Service Op-
erations Management, 9(4), 559–578. http://doi.org/10.1287/
msom.1060.0131
Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W.,
Smith, C. D., & Zacharia, Z. G. (2001). Defining Supply Chain
Management. Journal of Business Logistics, 22(2), 1–25.
http://doi.org/10.1002/j.2158-1592.2001.tb00001.x
Neely, A., Bourne, M., & Kennerley, M. (2000). Performance
measurement system design: developing and testing a pro-
cess-based approach. International Journal of Operations
& Production Management, 20(10), 1119–1145. http://doi.
org/10.1108/01443570010343708
Neuman, W. L. (2009). Social Research Methods: Qualitative and
Quantitative Approaches (7th ed.). Pearson.
Okoth, J. (2012, February 17). Are multinationals leaving Kenya?
The Financial Post: Bruce House, Standard Street. Nairobi.
Ou, C. S., Liu, F. C., Hung, Y. C., & Yen, D. C. (2010). A structural
model of supply chain management on firm performance. In-
ternational Journal of Operations & Production Management,
Patterson, K. a., Grimm, C. M., & Corsi, T. M. (2003). Adopting
new technologies for supply chain management. Transpor-
tation Research, E 39, 95–121. http://doi.org/10.1016/S1366-
5545(02)00041-8
Puri, G. (2013). Factors affecting the Adoption of B2B E-com-
merce – An Empirical Study, 6(1), 13–22.
PwCIL. (2010). Industrial Manufacturing: A brief overview of the
industrial manufacturing sector in Kenya. Nairobi, Kenya.
Qrunfleh, S., & Tarafdar, M. (2014). Supply chain information sys-
tems strategy: Impacts on supply chain performance and firm
performance. International Journal of Production Economics,
147(PART B), 340–350. http://doi.org/10.1016/j.ijpe.2012.09.018
Russell, D. M., & Hoag, A. M. (2004). People and information
technology in the supply chain: Social and organizational in-
fluences on adoption. International Journal of Physical Dis-
tribution & Logistics Management, 34(2), 102–122. http://doi.
org/10.1108/09600030410526914
Sánchez, A. M., & Pérez, M. P. (2005). Supply chain flexibility and
firm performance: A conceptual model and empirical study
in the automotive industry. International Journal of Opera-
tions & Production Management, 25(7), 681–700. http://doi.
org/10.1108/01443570510605090
Stiles, J. (2003). A philosophical justification for a realist ap-
proach to strategic alliance research. Qualitative Market
Research: An International Journal, 6(4), 263–271. http://doi.
org/10.1108/13522750310495346
Teeratansirikool, L., Siengthai, S., Badir, Y., & Charoenngam,
C. (2013). Competitive strategies and firm performance: the
mediating role of performance measurement. International
Journal of Productivity and Performance Management, 62(2),
168–184. http://doi.org/10.1108/17410401311295722
Thun, J.-H., & Müller, A. (2010). An Empirical Analysis of Green
Supply Chain Management in the German Automotive In-
dustry. Business Strategy and the Environment, 19(2), 119–
132. http://doi.org/10.1002/bse
Tomaskovic-devey, D., Leiter, J., Thompson, S., Quarterly, A. S.,
Sep, N., & Tomaskovic-, D. (2007). Organizational Survey
Nonresponse Organizational Survey Nonresponse Devey ,
Shealy Thompson. Science, 39(3), 439–457.
Umma, S. (2006). Research methods for business (4th ed.). Wiley
India Pvt.
Varadarajan, P. R. (2003). Musings on Relevance and Rigor of
scholarly research in marketing. Journal of the Academy of
Marketing Science, 31(4), 368–376.
Varma, S., Wadhwa, S., & Deshmukh, S. G. (2006). Implement-
ing supply chain management in a firm: issues and remedies.
Asia Pacific Journal of Marketing and Logistics, 18(3), 223–
243. http://doi.org/10.1108/13555850610675670
Wilson, E. J., & Lilien, G. L. (1992). Using single informants to
study group choice: An examination of research practice
in organizational buying. Marketing Letters, 3(3), 297–305.
http://doi.org/10.1007/BF00994137
Zhu, Q., Sarkis, J., & Lai, K. (2008). Green supply chain man-
agement implications for “closing the loop.” Transportation
Research Part E: Logistics and Transportation Review, 44(1),
1–18. http://doi.org/10.1016/j.tre.2006.06.003
Zolait, A. H., Ibrahim, A. R., Chandran, V. G. R., Pandiyan, V.,
& Sundram, K. (2010). Supply chain integration: an empiri-
cal study on manufacturing industry in Malaysia. Journal of
Systems and Information Technology, 12(3), 210–221. http://
doi.org/10.4018/jtd.2010070103

Annex I: Regression Coefficients (a) for Supply Chain Strategies and Firm Performance
Model
Indicators:
Objective i (Data
Analysis Model
#i)
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B
Std.
Error
Beta
Model # 1
(Constant) 29.97 4.746 6.315 .000
A SC strategy focused on variable productivity
to meet speculative purchasing and sales
promotion: LR Innovation SC strategy
7.70 1.171 .545 6.571 .000
Model # 2 (Constant)
-58.61 16.941
-
3.459
.001
A SC strategy focused on variable productivity to
meet speculative purchasing and sales promotion:
LR Innovation SC strategy
7.77 1.037 .551 7.491 .000
SC a strategy responsive and flexible to
customer needs to enable the firm Feed
Customers in ways that are efficient for them: LR
Demand SC strategy.
17.93 3.323 .397 5.397 .000
-24.41 18.522
-
1.318
.191
9.58 1.096 .679 8.734 .000
A SC a strategy responsive and flexible to
Demand SC strategy.
16.52 3.160 .365 5.227 .000
A SC strategy that is reactive to procurement,
production and distribution in dynamic
environments to answer to customer needs: LR
Micro-chain SC strategy
-7.15 1.956 -.286 -3.658 .000
-32.42 17.673
-
1.835
.070
promotion: LR Innovation supply chain strategy
7.01 1.264 .497 5.543 .000
Demand SC strategy.
17.44 3.002 .386 5.809 .000
-8.24 1.876 -.330 -4.395 .000
A strategy that allows the firm to cost
effectively receives and delivers products as the
sources of supply and customer change: LR
Project logistics SC strategy
5.02 1.410 .312 3.557 .001
Model # 5 (Constant) 11.64 20.132 .578 .564
A supply chain strategy focused on variable
productivity to meet speculative purchasing and
sales promotion: LR Innovation SC strategy
7.19 1.185 .510 6.070 .000
SC strategy responsive and flexible to customer
needs to enable the firm Feed Customers in ways
15.69 2.849 .347 5.507 .000

34
Model
Indicators:
Objective i (Data
Analysis Model
#i)
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B
Std.
Error
Beta
that are efficient for them: LR Demand SC
strategy.
-9.64 1.795 -.386 -5.373 .000
6.51 1.377 .405 4.727 .000
A SC strategy aimed at speeding and retaining
cash flow for the firm: LR Cash-to-cash cycle SC
strategy
-7.36 1.913 -.257 -3.847 .000
Model # 6 (Constant) 22.55 19.389 1.163 .248
7.18 1.126 .509 6.374 .000
Demand SC strategy.
14.34 2.734 .317 5.245 .000
-8.45 1.740 -.338 -4.853 .000
7.81 1.362 .486 5.732 .000
strategy
-7.13 1.818 -.249 -3.921 .000
A strategy that increases the firm's ability to
mass-maximize and build close relations with
customers when designing new and modifying
existing products: LR Market dominance and
backlog SC strategy
-3.95 1.159 -.232 -3.408 .001
Model # 7 (Constant) 28.09 18.603 1.510 .134
6.99 1.077 .496 6.497 .000
Supply chain a strategy responsive and flexible
to customer needs to enable the firm Feed
Demand SC strategy.
12.752 2.659 .282 4.796 .000
-9.31 1.684 -.373 -5.529 .000

Model
Indicators:
Objective i (Data
Analysis Model
#i)
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B
Std.
Error
Beta
7.42 1.307 .462 5.679 .000
strategy
-7.276 1.737 -.254 -4.188 .000
backlog SC strategy
-4.63 1.127 -.271 -4.103 .000
A strategy where the firm evaluates
opportunities to outsource areas that are not their
core competencies in the supply chain: MR
Third-party SC strategy
3.19 .997 .199 3.207 .002
Model # 8 (Constant) 26.26 18.127 1.449 .151
6.81 1.051 .483 6.480 .000
Demand SC strategy.
13.39 2.601 .296 5.147 .000
-9.64 1.645 -.386 -5.861 .000
Project logistics supply chain strategy
6.09 1.378 .379 4.420 .000
strategy
-7.06 1.694 -.247 -4.170 .000
backlog SC strategy
-5.73 1.183 -.336 -4.845 .000
3.012 .973 .188 3.102 .003
A strategy where the firm continuously plans its
supply chain network to limit exposure to cost
fluctuations: LR Efficient SC strategy
2.56 1.023 .200 2.504 .014
Model # 9 (Constant) 26.41 17.590 1.502 .137
7.19 1.030 .510 6.982 .000

36
Model
Indicators:
Objective i (Data
Analysis Model
#i)
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B
Std.
Error
Beta
Demand SC strategy.
14.26 2.546 .315 5.600 .000
A supply chain strategy that is reactive to
procurement, production and distribution in
dynamic environments to answer to customer
needs: LR Micro-chain supply chain strategy
-9.89 1.599 -.396 -6.185 .000
7.76 1.480 .483 5.241 .000
strategy
-8.65 1.752 -.303 -4.940 .000
backlog SC strategy
-6.50 1.185 -.381 -5.486 .000
core competencies in the SC: MR Third-party SC
strategy
4.51 1.103 .281 4.094 .000
SC network to limit exposure to cost fluctuations:
LR Efficient SC strategy
3.83 1.104 .299 3.471 .001
A SC strategy that allows the firm and supply
chain members to adopt to different products of
different segment of the market: LR Speed to
market SC strategy.
-2.89 1.101 -.258 -2.626 .010
Model # 10 (Constant) 38.23 17.878 2.139 .035
6.45 1.054 .457 6.116 .000
strategy.
13.97 2.488 .309 5.616 .000
-10.32 1.572 -.413 -6.567 .000
8.56 1.484 .533 5.769 .000

38
Model
Indicators:
Objective i (Data
Analysis Model
#i)
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B
Std.
Error
Beta
SC network to limit exposure to cost fluctuations:
LR Efficient SC strategy
4.82 1.095 .376 4.400 .000
A SC strategy that allows the firm and SC
members to adopt to different products of
market SC strategy.
-3.39 1.061 -.303 -3.195 .002
A SC strategy where numerous internal and
external activities are co-ordinated to conform to
the overall business strategy: MR Tie down the
firm SC strategy
-3.64 1.351 -.162 -2.690 .008
A strategy where the firm creates additional
relationship with SC members at the point where
their operation interact: LR Synergistic SC
strategy
2.22 .945 .161 2.347 .021
Model # 12 (Constant) 55.14 17.918 3.078 .003
5.69 1.009 .403 5.633 .000
strategy.
15.53 2.367 .343 6.561 .000
-13.02 1.597 -.521 -8.155 .000
6.99 1.452 .435 4.817 .000
strategy
-6.87 1.669 -.240 -4.119 .000
backlog SC strategy
-7.321 1.179 -.429 -6.207 .000
4.989 1.007 .310 4.951 .000
supply chain network to limit exposure to cost
fluctuations: LR Efficient SC strategy
9.35 1.678 .729 5.572 .000
A SC strategy that allows the firm and supply -3.41 1.004 -.304 -3.393 .001

Model
Indicators:
Objective i (Data
Analysis Model
#i)
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B
Std.
Error
Beta
chain members to adopt to different products of
market SC strategy.
A SC strategy where numerous internal and
external activities are co-ordinated to conform to
the overall business strategy: MR Tie down the
firm SC strategy
-5.26 1.363 -.235 -3.857 .000
A strategy where the firm creates additional
relationship with SC members at the point where
their operation interact: LR Synergistic SC
strategy
3.601 .980 .261 3.673 .000
A SC strategy directed to minimizing risks like
production capacity, quality, floods and
earthquakes in the process of procurement,
production and distribution: LR Risk-hedging SC
strategy
-6.42 1.868 -.348 -3.434 .001
a Dependent Variable: Firm Performance
Method: Stepwise (Criteria: Probability-of-F-to-enter≤.050, Probability-of-F-to-remove≥ .100).
Auhtor’s Biography:
Richard Nyaoga is a Lecturer in the Faculty of Commerce Department of Accounting, Finance and
Management Science of Egerton University-Kenya. Richard has a wide experience in teaching spanning over
seven years. Richard has widely published in various peer reviewed journals. Richard has an Undergraduate and
Masters Degrees from The University of Nairobi Kenya and a PhD in Management Science.
Peterson Magutu is a Lecturer in The University of Nairobi. He has taught, published and consulted widely on
Management Science related areas. Dr. Magutu has An Undergraduate, Master and PhD both from the
University of Nairobi. Magutu's research interests lie in developing and testing basic models used in operations
management and management science especially in supply chain management.
Josiah Aduda is currently the Associate Professor and Dean of the school of business University of Nairobi.
Dr. Aduda has wide experience in teaching and publishing in areas of Management. He has undergraduate &
Masters from University of Nairobi and a PhD from Univeristy of Dar es Salaam- Tanzania.
Auhtor’s Biography:
Richard Nyaoga is a Lecturer in the Faculty of Commerce Department of Accounting, Finance and Manage-
ment Science of Egerton University-Kenya. Richard has a wide experience in teaching spanning over seven
years. Richard has widely published in various peer reviewed journals. Richard has an Undergraduate and
Masters Degrees from The University of Nairobi Kenya and a PhD in Management Science.
Peterson Magutu is a Lecturer in The University of Nairobi. He has taught, published and consulted widely
on Management Science related areas. Dr. Magutu has An Undergraduate, Master and PhD both from the
University of Nairobi. Magutu’s research interests lie in developing and testing basic models used in opera-
tions management and management science especially in supply chain management.
Josiah Aduda is currently the Associate Professor and Dean of the school of business University of Nairobi.
Dr. Aduda has wide experience in teaching and publishing in areas of Management. He has undergraduate
& Masters from University of Nairobi and a PhD from Univeristy of Dar es Salaam- Tanzania.

The Development of Logistics Services in the United
States
Yeongling H. Yang
San Diego State University
hyang@mail.sdsu.edu
ABSTRACT: This research studies third party logistics (3PL) providers in the United States to inves-
tigate how the industry has strategically developed its service offerings in response to the customers’
growing needs in managing global supply chains. Logistics management has significant impacts on
various aspects of supply chains such as response time, total supply chain cost, sourcing risk, customer
service, security, etc. The results show that 3PL services vary based on industry served, region served,
and asset ownership structure. Over the years logistics services providers have served more industry
sectors, became asset light, and provided broader services. Two of the five service categories, technol-
ogy services and special services, have been evolved and expanded rapidly. The development has
strengthened the capabilities of the logistics service providers and sustained the growth of the industry.
23

H. Yang, Y.: The Development of Logistics Services in the United States
1. INTRODUCTION
As companies expand into the global marketplace,
logistics becomes critical in support of their global
supply chains. In order to remain competitive in
today’s changing business environment, more and
more companies focus on core competencies. In-
stead of developing in-house capabilities in the
various logistics disciplines such as transportation
planning, warehouse management, and information
technology, companies are opting to outsource to
third party logistics providers. Third-party logistics
(3PL) is the use of contracted firm(s) to supply servic-
es in the planning, implementation and controlling
of the flow and storage of raw materials, in-process
inventory, finished goods, and related information
throughout the supply chain. Third party logistics
providers may handle all or part of the distribution
of merchandise along the supply chain to the con-
sumer. Hence the firms are able to concentrate on
their own core business, while the 3PLs concentrate
on inflows and outflows of the global supply chain
activities.
Third party logistics was identified as a separate in-
dustry and service in the late 1980s, and started to
gain market share in the U.S. only since early 1990s
(Ashenbaum, et al., 2005). Since then, the third par-
ty logistics industry has grown rapidly from about
US$6 billion in 1991 to US$146.4 billion in 2013. In
the United States, the logistics cost was 8.5% of the
GDP in 2013, and the average 3PL user paid approx-
imately 10.5% of the company’s logistics operating
budget to 3PL providers. In contrast, the logistics
cost was 18% of the GDP in China and the average
3PL user outsourced only 7% of the company’s lo-
gistics budget on 3PL services in 2013 (Armstrong &
Associates, 2015).
3PL relationships are more complex than tradition-
al logistics supplier relationships, which are often
transaction based and focus on single function (Sim-
chi-Levi, et al., 2003, p. 149). As 3PLs become more
vital to a company’s operations, these arrangements
require active participation by both parties. In con-
tracting out the logistics operations, the third party
provider is now an important partner which has sig-
nificant impacts on the company’s quality, service,
and dependability. Boyson et al. (1999) showed that
the outsourcing of logistics functions had proven to
be effective in helping firms to achieve competitive
advantages, improve their customer service levels
and reduce their overall logistics costs. Berglund et
al. (1999) found that 3PLs can add value by creat-
ing operational efficiencies and by sharing resources
across customers. This paper investigates the strate-
gic development of 3PL services in the United States
in the last decade and studies the role of 3PLs in
managing today’s global supply chains.
2. LITERATURE REVIEW
In earlier years, companies chose 3PL providers
mainly by cost. However Millegan (2000) noted that
more meaningful relationships had been emerging
since late 1990s. Bhatnagar et al. (1999) found that
other than cost, customer service and flexibility/
customization were the most important factors for
selecting logistic outsourcing. For example, ship-
pers are choosing their providers based on their
emphasis on value, innovation and performance
in an increasingly global context. This trend pres-
ents a challenge for the logistics service providers.
Millegan’s study (2000) indicated that customer
demands for performance and sophistication had
been accelerating. The 3PL providers need to keep
pace in service scope.
Lieb and Bentz’s (2005) surveyed the use of 3PLs ser-
vices by large American manufacturing firms. They
found that eighty percent of sixty Fortune 500 manu-
facturers indicated that they had used 3PL services
in 2004. Major companies outsource logistics servic-
es to 3PLs are from demand sensitive, fast-moving
industries such as consumer product goods, elec-
tronics, food and beverage, and automotive com-
panies. However companies from more specialised
industries, such as furniture, cosmetics, and renew-
able energy, are beginning to outsource logistics ser-
vices (O’Reilly, 2011).
Various strategies are utilized by 3PL providers.
Other than serving the needs of individual custom-
er, some 3PLs take multiple customers within a par-
ticularly focused industry sector, yielding greater
efficiencies and cost savings. Some 3PLs spend great
resources to develop competitive specific channels
and then use the channel throughout their customer
base. Industry-specific 3PLs often use the same sup-
ply chain design and channels for clients that are
competitors (Burnson, 1999). As more diverse in-
dustries use 3PLs and outsource more logistic func-
tions, the scope of services provided by 3PLs shall
be broadened.
Another strategy for 3PLs is to consolidate or form
alliances with other 3PLs. As mentioned earlier,
most of these 3PLs offer a variety of services from

transportation management, contract carrier, ware-
house management, and information technology,
but no one company dominates the market share in
all of these areas. Consolidation or multiple partner
alliances are sometimes the only way to provide the
range of diverse geographic services demanded by
customers (Cook, 1998). Current trend in consolida-
tion and strategic alliances comes from the pressure
of 3PL users to extend global capabilities and pro-
vide one-stop-shopping. Cost efficiency can be im-
proved as the benefit of scale economy. This trend
changes the ownership structure of the 3PL indus-
try. Some examples of consolidation include UPS’s
acquisition of Fritz, which allowed freight forward-
ing to be added to the expertise of the transporta-
tion and warehousing giant. Fritz was also a signifi-
cant ocean non-vessel operating common carrier as
well as a charter agent. Thus UPS was able to move
beyond the small parcel dimension of global trade.
Exel, a warehousing and freight-forwarding leader,
acquired Mark VII so that it could add domestic sur-
face transportation management to its offered ser-
vices. In addition to partnerships with other service
providers, 3PL providers also enhance and expand
partnerships with their users.
Furthermore, as globalization escalates, the 3PL pro-
viders seek international partners for overseas cov-
erage. Some 3PL providers target a specialized niche
market to differentiate them and then form alliances
with other players. HUB Group is a good example
of this strategy. Hub Group has decided to focus on
intermodal transportation due to its strong relation-
ship with the nation’s railroad services in the United
States. When a niche player has a customer that is
looking for a more comprehensive service, they may
partner up with another niche player that comple-
ments their own service. HUB Group partnered up
with TMM Logistics in Mexico in order to be able
to increase their presence in Mexico. TMM Logistics
is the dominant logistic provider in Mexico. With
this strategic partnership Hub, a niche 3PL player,
is able to provide cross-border transportation (Busi-
ness Wire, 2002).
Most of the extant literature focuses on the perspec-
tives from the customers/users of 3PLs services. For
examples, Murphy and Poist (1998) examined third-
party logistics usage among a group of small to large
manufacturers and non-manufacturers. Vaidyana-
than (2005) proposed a conceptual framework using
IT as the focus to evaluate the core functionalities
of 3PL providers for the users. Moberg and Speh
(2004) surveyed the warehouse customers to com-
pare the selection criteria of a regional warehouse
and a national warehouse. Some literature studies
3PLs within a specific country context. For example,
Lieb and Bentz (2004, 2005) and Langley et al. (2004)
repeatedly surveyed the use of 3PL services among
large American manufacturers over the years. Sep-
arate studies by Piplani et al. (2004) and Wilding
and Juriado (2004) investigated customers’ percep-
tions of 3PLs in Singapore and Europe, respectively.
Knemeyer and Murphy (2005) studied the users of
3PL services to investigate whether certain 3PL re-
lationship outcomes are influenced by relationship
characteristics or customer attributes. Their findings
suggest that one relationship characteristic, com-
munication with the provider, showed statistically
significant influences on all outcomes. Anderson,
et al. (2011) surveyed over three hundred manag-
ers responsible for purchasing logistics services and
found three distinct decision models. They conclud-
ed that the drivers of 3PL selection vary greatly be-
tween customer groups.
Murphy and Poist (2000) compared the perspectives
of 3PL providers and 3PL users on most commonly
provided/used services. They found some overlaps
and mismatches between the 3PL services offered
and used. There are overlaps on five of the ten most
commonly provided/used services: EDI capabil-
ity, freight consolidation, warehousing, consulting,
and freight bill payment. The customers tend to be
interested in operational services such as customs
clearance, pick and delivery, freight charge audit-
ing, intermodal service, and order picking and pack-
ing. However, their sample size was rather small
and the comparisons are not from paired samples.
Yeung, et al. (2006) investigated the relationship of
strategic choices on a composite measure of finan-
cial performance for 3PL providers in Hong Kong.
They found that the combined strategy of cost and
differentiation performing best and pure cost strat-
egy performing the worst.
Little research is conducted from the perspective
of the 3PL service provider. Hertz and Alfredsson
(2003) followed the strategic development of four
different types of logistics firms into 3PLs. They
found that the existing network of these firms’ cus-
tomers, customers’ customers and partners seemed
to have played an important role for the develop-
ment into a 3PL and also in the continued devel-
opment. Larson and Gammelgaad (2001) studied
Danish logistics providers and found them to be

more niche firms, focusing on the domestic market
and limited sets of customers by industry. Lieb and
Kendrick (2003) provided some macro level insights
into the third-party logistics industry; but their results
were based on a survey of a small sample of twenty
CEOs of the largest 3PL companies in the U.S. Min
and Joo (2006) studied six largest 3PLs in the United
States for their operational efficiency. Zhou, et al.
(2008) conducted a similar study with top ten largest
Chinese 3PL providers and identified some sources
of inefficiency.
3. RESEARCH QUESTIONS AND HYPOTHESES
This research explores service offerings from 3PL
providers in the United States in the last decade to
investigate how 3PL service scope has been strategi-
cally developed in response to the customers’ grow-
ing needs in global supply chain management. The
goal is to provide a longitudinal investigation on the
strategic development in this industry. Based on ex-
tant literature reviewed, the following hypotheses
are proposed.
H1: 3PLs service scope gets broader over time.
H2: 3PLs serve more industry sectors over time.
H3: 3PLs get more global over time.
H4: Asset ownership structure of 3PLs changes over
time.
H5: Service offerings vary among the asset owner-
ship structure of 3PLs.
H6: Service offerings vary between global and North
America focused 3PLs.
4. METHODOLOGY
This study uses secondary data published by In-
bound Logistics on their annual survey of American
3PLs, published in its July issue every year. Unlike
Lieb and Bentz’s survey (2004, 2005), which focuses
only on the largest American manufactures’ per-
spectives on 3PLs, this dataset consists of a mix of
large, public companies and small, niche provid-
ers from 3PL industry, reflecting a broad range of
capabilities. Inbound Logistics, established in 1981,
is the leading trade magazine for logistics and sup-
ply chain managers in various industries. Each year,
Inbound Logistics invites companies to submit data
using an online questionnaire with an extensive list
of questions (Inbound Logistics Top 100 3PL Pro-
viders Questionnaire). Then the top one hundred
companies are selected from a pool of over 250 com-
panies through survey inputs, phone interviews,
and online research. The selected companies offer
various operational capabilities and experiences in
logistics services. Their database includes informa-
tion such as regions served, industry sectors served,
asset ownership, possible services in five categories,
and membership of three certificates-- ISO, Smart-
Way, and C-TPAT. Services listed on this database
were much broader in scope and in industry cover-
age comparing to the ones listed on Lieb and Bentz’s
(2005) survey that contained only 26 services for six-
ty large manufacturing companies. Table 1 shows all
five 3PL service categories and their specific servic-
es. All data in the Inbound Logistics database from
five points in time—2002, 2004, 2007, 2010, and 2013
are analysed to test the hypotheses. Sample size is
100 per year. Since the number of services varies
somewhat from year to year, some raw counts are
converted to percentages in data analysis.
Table 1: Major 3PL services categories
Category Service Types
Logistics Services
Inbound Logistics, Integrated Logistics, Warehousing, Lead Logistic Provider, Inven-
tory Management, JIT, Process Re-Engineering, Vendor Management, Payment Audit
Processing, Product Life Cycle Management, Global Trade Services
Transportation Services
Small Package, Air Cargo, LTL, TL, Intermodal, Ocean, Rail, Bulk, Dedicated Con-
tract Carriage, Fleet Acquisition, Equipment/ Drivers, Final Mile
Warehousing Services
Pick/Pack Sub-Assembly, Cross docking, DC Management, Location Services, Ven-
dor Managed Inventory, Fulfilment

Special Services
Direct to Store, Direct to Home, Import/Export/Customs, Reverse Logistics, Marketing
Customer Service, Logistics/Transportation Consulting, Global Expansion (sourcing/
selling), Security Analysis, Contingency/Crisis Planning, Labor Management
Technology/ Web Ser-
vices
EDI, Satellite/Wireless Communication, Enterprise Web Enablement, Product Visibil-
ity, Customer Relationship Management
Source: Inbound Logistics, various issues 2002-2013
Radar diagrams are drawn to show the levels of the
five service categories over years. ANOVA tests are
conducted to analyse service scope (H1) and industry
breadth (H2) over years as well as the asset ownership
impact on service offerings (H5). Chi-square tests are
conducted to show changes on region served (H3) and
asset ownership over years (H4). Lastly independent t
test is used to see if 3PLs with a global focus opposed
to a North America focus offer different services (H6).
5. ANALYSIS AND RESULTS
There are five strategic service categories provided
by 3PLs—logistics, transportation, warehousing,
special services, technology and internet-based ser-
vices. Each category contains four to thirteen spe-
cific services. Figure 1 shows the average percent-
ages of services in each category provided each year.
Over the years, broader scope of 3PL services are
offered. For logistics services, the most commonly
offered services are inbound logistics and integrated
logistics, and the least offered services are global
trade service and payment audit process. For trans-
portation services, TL, LTL, and intermodal are of-
fered by almost all 3PLs and the last-mile delivery
service is gaining ground in recent years. For ware-
housing services, over 80% of the companies offer
cross docking and pick/pack subassembly and more
companies offer vendor managed inventory and lo-
cation services in recent years.
Figure 1: Services Provided by 3PLs
0,00
20,00
40,00
60,00
80,00
Logistics Services
Transportation
Servicces
Warehousing
Services
Special Services
Tech/Web Services
Figure 1: Services Provided by 3PLs
2002
2004
2007
2010
2013

Two categories—special services and technology
services clearly show expansions over time. Figure 2
and Figure 3 depict the average percentages of spe-
cific service offered in each category, respectively.
Reverse logistics was offered by 78% of the com-
panies in 2002 and 85% of the companies in 2013.
Deliver directly to store service was offered by 69%
in 2002 and 83% in 2013. The special service cate-
gory keeps expanding. New services such as global
sourcing and market expansion, security analysis,
contingency & crisis planning, and logistics labor
management were added to the list in 2007. On the
technology service category, EDI link has been of-
fered by almost all 3PLs since 2002. All other tech-
nology related services have shown significant
growth. For examples, enterprise web enablement
service was increased from 52% of the companies
in 2002 to 92% of the companies in 2010; customer
relationship management was increased from 24%
of the companies in 2002 to 67% of the companies in
2013, while product visibility service was increased
from 39% in 2002 to 92% in 2013.
Figure 2: Value-added Services Provided by 3PLs
0
20
40
60
80
100
Direct to Store
Direct to Home
Import/Export/Customs
Reverse Logistics
Marketing Customer Service
Logistics/Transportaion
Consulting
Global Exapnsion
(Sourcing/Selling)
Security Analysis
Contigency/Crisis Planning
Labor Management
Figure 2: Value-added Services Provided by 3PLs
2002
2004
2007
2010
2013
Figure 3: Tech/Web Services by 3PLS
0
20
40
60
80
100
EDI
Satellite/Wireless Communication
Enterprise SystemsProduct Visibility
Customer Relationship Mgmt
Figure 3: Tech/Web Services by 3PLS
2002
2004
2007
2010
2013

ANOVA analysis (Table 2) on the aggregated num-
bers of all service categories shows significant
growth at p=.000 level. Hence Hypothesis 1 is not
rejected. Further analyses on each service category
find that transportation service, special services, and
technology based service show significant growth
over the years, with p values of .025, .002, and .000,
respectively. The technology related services show
double digit growth in most of the years. Although
not at the significant level, logistics services are also
growing at a steady rate. The service categories that
have even more future growth potentials are in the
transportation service and special service areas.
Four industry sectors—manufacturing, retail/e-tail,
distributor, and services—are reported in the sur-
vey. Most 3PLs serve more than one industry sector.
Table 3 shows that 3PLs are serving more industries
over time. ANOVA analysis reveals that all growth
comes from the retail sector, distribution sector, and
service sector, with p values of .006, .040, and .004,
respectively. Hence hypothesis 2 is not rejected.
Table 2: ANOVA test on service category by year
Service Category 2002 2004 2007 2010 2013 F Statistic Sig.
All services 63.54 74.02 73.11 74.36 71.25 7.086 .000
Logistics services 71.81 73.55 75.56 76.46 77.10 1.062 .375
Transportation services 62.53 70.34 70.98 69.44 71.17 2.810 .025
Warehouse services 69.53 76.43 76.43 77.10 76.43 1.059 .376
Special services 55.72 69.70 60.49 64.14 62.50 4.434 .002
Tech/Web services 53.54 74.34 82.42 87.27 73.20 56.728 .000
Number presents the average percentage of companies providing services in each category
Table 3: ANOVA test on industry served by year
Industry served 2002 2004 2007 2010 2013 F Statistic Sig.
Manufacturing 98 97 98 99 99 .393 .813
Retail/e-retail 77 87 92 91 91 3.640 .006
Distributor 83 89 92 96 88 2.526 .040
Service 53 71 69 78 67 3.907 .004
Number represents count
As the supply chains getting global, one would ex-
pect the 3PLs will also expand their services to glob-
al regions. Table 4 shows an increase of globally fo-
cused 3PLs over the years. However Chi-square test
does not show the increase was at a significant level
(p value=0.359). Hence Hypothesis 3 is rejected. As-
set ownership varies among the 3PL companies.
Table 4 shows significant changes (p value=0.003)
on asset ownership of 3PLs over the years. Hence
Hypothesis 4 is not rejected. Pure asset-owned 3PLs
were going down from twenty three companies in
2002 to only eight companies in 2013. The number
of 3PLs that leverage both asset and non-asset capa-
bilities grows from thirty-two companies in 2002 to
fifty-two companies in 2013.

Table 4: Chi-square tests on region and asset ownership by year
Region 2002 2004 2007 2010 2013
Chi-
Square
Sig.
North America 42 51 46 40 38
4.364 0.359
Global 58 49 54 60 62
Asset Ownership 2002 2004 2007 2010 2013
Chi-
Square
Sig.
Non-Asset 44 44 49 50 40
23.021 0.003Asset 23 20 13 6 8
Both 32 36 38 44 52
Number represents count
In general asset-based providers offer dedicated
services, primarily through owned or leased as-
sets. Non-asset-based providers offer administrative
management services, and tend to subcontract for
the necessary logistics assets which are not available
in-house. ANOVA tests (Table 5) are conducted on
all data and find significant difference (p=.000) in
the overall service levels among the three types of
asset ownership. Non-asset based 3PLs offer an av-
erage of 69.42% of all service surveyed. Asset based
3PLs offer an average of 66.08% of all services and
the both non-asset and asset based 3PLs offer an av-
erage of 75.70% of all services. Hence Hypothesis 5
is accepted. In fact 3PLs that leverage on both non-
asset and asset based capabilities provide more ser-
vices in all service categories, the averages ranging
from 68.02% in special services to 81.89% in ware-
house services. This result is consistent with Stank
and Maltz’s study (1996), but it is different from
Murphy and Poist’s study (1998). Murphy and Poist
(1998) concluded that there were no differences in
the number of services offered by either asset-based
or non-asset-based providers. However, their study
compared customers’ reported usage of services
from asset-based and non-asset-based providers,
not the actual services offered by 3PLs.
Table 5: Service category means and ANOVA tests by asset ownership
Service Category
Non-As-
set based
Asset
based
Both non-asset
and asset based
F Statistic Sig.
All services 69.42 66.08 75.70 10.240 .000
Logistics services 73.87 64.41 78.19 10.034 .000
Transportation services 67.95 58.81 72.15 7.242 .001
Warehouse services 66.49 83.06 81.89 18.475 .000
Special services 59.27 57.71 68.02 5.306 .005
Tech/Web services 71.81 71.61 78.53 6.467 .002
Number represents the average percentage of companies of each asset ownership type in providing each service category

Table 6 indicates that the service levels differ be-
tween the global players and North America region-
al players significantly (p=.000). Hence Hypothesis 6
is accepted. Global 3PL companies provide signifi-
cantly broader level of services in all categories ex-
cept the technology category, the averages ranging
from 66.93% in special services to 79.63% in logistics
services.
Table 6: Service category means and independent t tests by Region Served
Service Category North America Global t Value Sig.
All services 66.61 74.81 -5.422 .000
Logistics services 68.13 79.63 -6.143 .000
Transportation services 61.91 73.94 -6.136 .000
Warehouse services 74.94 75.31 -.134 .894
Special services 56.37 66.93 -4.844 .000
Tech/Web services 74.47 73.78 .311 .756
Number represents the average percentage of companies of each region focus in providing each service category
6. MANAGERIAL IMPLICATIONS
As business goes global, the supply chain networks
and logistics complexity increases. Outsourcing
logistics functions offers the opportunity for sup-
ply chain participants to concentrate on their core
capabilities. The growth of the third-party logistics
industry makes both the formation and dismantling
of supply chain arrangements easier.
This study shows 3PLs have served more industry
sectors over the years. Third-party logistics have
been commonly utilized in the manufacturing sec-
tor. As logistics outsourcing becomes a viable strat-
egy, industry sectors such as retail and e-retail, dis-
tribution and wholesale, and service sector have
also adopted the best practices, which expand 3PL
service markets. The fastest growing market for
3PLs comes from the service sector and retail/e-re-
tail sector. In 2002, 53% of 3PLs served in the ser-
vice sector and the percentage was increased to 78%
in 2010. Retail/e-retail sectors also had significant
growth of 14% from 2002 to 2013. Some 3PLs focus
on e-retailers and offer warehousing, shipping, and
order-management services to support the business-
to-customer (B2C) e-business model. As of 2013,
the number of industry served per 3PL providers
ranged from one to sixteen, with an average of ten
verticals. Armstrong & Associates (2009) reported
seventy-seven percent Fortune 500 companies used
3PLs for logistics and supply chain functions and
many of them used more than one 3PLs provider.
For examples, General Motors, Procter & Gamble,
Wal-Mart, PepsiCo, and Ford Motor each used 30
or more 3PLs (Armstrong & Associates, 2009). Simi-
larly O’Reilly (2011) reported seventy-seven percent
of more than 5000 3PLs users working with multiple
3PLs partners.
Asset based companies are typically larger firms.
They usually enjoy economies of scale, own ware-
house or transportation assets, have broader indus-
try knowledge, and have a larger customer base.
However non-asset based firms are more flexible
and more able to tailor services with specialized in-
dustry expertise. This study finds fewer pure asset
based 3PLs companies over the years. Asset-based
companies have tapped into the non-asset based ca-
pabilities to serve their customers. As the customers
demand more service offerings from 3PLs, the ex-
panded service scope satisfies customer’s desire for
“one-stop” shopping. The transportation and logis-
tics market in the United States is highly fragment-
ed. Strategic merger and acquisition has become a
strategy as consolidation provides a significant op-
portunity to build up capabilities and expand mar-
kets. Publicly traded logistics companies and private
equity firms are seen as the most aggressive buyers,
going after smaller private companies or specific
niche areas that are highly valuable to profit and
revenue (Reuters, 2011). For example, Thoma Bravo
LLC, a leading private equity investment firm, ac-
quired UPS Logistics Technologies, a business unit
of UPS, in 2010. The newly independent company
has been renamed Roadnet Technologies, Inc. with

the goal to provide world-class transportation man-
agement applications (PEHub, 2010).
In response to the specific needs of each industry
and customer, there is a proliferation of 3PLs servic-
es. This study shows that service scope gets broader
over time in this industry. The results, in general,
continue the trend projected by Persson and Virum
(2001) and Lieb and Bentz (2003). Not only 3PL com-
panies offer more services in all categories, the rank
orders of the five service categories change also. In
2002 the rank order from the most offered services to
the least offered services was logistics, warehousing,
transportation, special services, and technology ser-
vices. In 2010 the rank order was changed to tech-
nology services, warehousing, logistics, transporta-
tion, and special services.
Van Hoek’s (2000) found that traditional third-party
logistics services such as warehousing and logistics
have become commoditized. To differentiate in the
3PLs market, logistics and supply chain related tech-
nologies have help created niche expertise. This is
interesting because in Lieb’s 2003 user survey, users
of 3PLs generally did not see 3PL providers as lead-
ing edge suppliers of information technology. Lieb
and Bentz (2004) indicated that 3PLs must decide
upon appropriate strategies for strengthening their
technology capabilities to convince potential users.
This research shows that 3PLs have made consis-
tently and significantly improvement in technology
and web service offerings in the last decade. In 2002
only 53 percent of 3PLs companies offered technol-
ogy services and the percentage was increased to
73.2% in 2013. Technology services related to prod-
uct visibility, customer relationship management,
and enterprise web enablement have shown rapid
growth. Via technologies, the buyer, seller, and
shipping partners can monitor the status of a ship-
ment in real time from start to finish. For example,
FedEx and UPS have modified their services quickly
to accommodate their e-commerce customers for
package delivery (Armstrong, 2004). Looking for-
ward, Figure 3 shows wireless communication and
customer relationship management are the two ar-
eas with more room for future growth.
Traditionally, turnover rate was high in 3PL market.
Mottley (1998) showed that more than one-third
of users had cancelled at least one 3PL contract.
However, a later survey by Lieb and Bentz (2004)
showed seventy-two percent of the users identified
in their survey had used 3PL services for more than
five years, which is the highest percentage ever re-
ported in this category in their surveys. This finding
indicates that the relationships between customers
and some 3PLs are stabilized over time and may be
changing from adversary to partnership. However,
using a proprietary database Armstrong & Associ-
ates (2009) studied 3,936 3PLs customer relation-
ships from 2005 through 2008. It is found that only
18.5% of the relationships were considered strategic
and the remaining 81.5% were classified as tactical
relationships. To become a true strategic partner to
its logistic outsourcer, these high value-added spe-
cial services could create competitive advantages.
One way to gain reputation as 3PL leaders is through
certifications. Table 7 shows three certificates to im-
prove 3PLs’ credentials. ISO is a highly regarded in-
ternational standard for an established quality sys-
tem in a company. ISO was first published in 1987
by International Organization for Standardization.
As shown in Table 7, ISO is most adopted by 3PLs
companies serving global region and service sector.
Asset-based 3PLs companies do not embrace this
quality certificate. In 2004, US EPA launched Smart-
WaySM — an innovative brand that represents en-
vironmentally cleaner, more fuel efficient transpor-
tation options. SmartWay brand identifies products
and services that reduce transportation-related emis-
sions. SmartWay partners are committed to sustain-
ability through promoting greater energy efficiency
and air quality within the freight transport sector
(EPS web site). Recently many companies have de-
veloped sustainable supply chain initiatives. 3PLs
with SmartWay certificate may become a strategic
partner to such initiatives. C-TPAT (Customs-Trade
Partnership against Terrorism) is a new certificate
from the first worldwide supply chain security ini-
tiative in 2007. The voluntary government-business
initiative is to build cooperative relationships that
strengthen and improve overall international supply
chain and U.S. border security (C-TPAT web site).
C-TPAT is adopted more by global players and non-
asset based 3PLs companies. Supply chain security
is a growing concern in global business. More 3PLs
are expected to provide special services in this area.

Table 7: Certificate adoption by industry, region, and asset ownership structure
Industry served ISO Smart Way C-TPAT
Manufacturing 57.58% 65.66% 59.6%
Retail/e-retail 57.14% 68.13% 61.5%
Distributor 55.68% 63.64% 60.4%
Service 65.67% 76.12% 62.8%
Region served ISO Smart Way C-TPAT
Domestic 50% 46.74% 45%
Global 62.90% 79.03% 70%
Asset Ownership ISO Smart Way C-TPAT
Non-Asset 55.00% 62.50% 62%
Asset 37.50% 62.50% 50%
Both 63.46% 69.23% 59.1%
Number represents the percentage of 3PLs adopted the certificate. ISO and Smart Way numbers are from 2013 survey and C-
TPAT numbers are from 2010 survey.
7. CONCLUSION AND FUTURE RESEARCH
Logistics management has significant impacts on
various aspects of supply chains such as response
time, total supply chain cost, sourcing risk, custom-
er service, security, sustainability, etc. A 3PL study
by three professional organizations and Georgia
Institute of Technology affirms that logistics is
one of the keys to company’s success, and many
firms give credits to logistics service providers for
helping them achieve critical service, cost, and cus-
tomer satisfaction goals (Lagley et al., 2004). This
study proposed seven hypotheses based on extant
literature to examine the strategic development of
the 3PLs industry in the United Sates. Using sec-
ondary data gathered from 3PLs in the last decade,
comprehensive analyses are conducted to provide
a longitudinal view.
This study shows that 3PLs services vary based on
industry verticals served, regions served, and asset
ownership structure. Over last decade 3PLs have
served more industry sectors, became asset light,
and provided broader services. 3PL companies offer
five service categorires—transportation, logistics,
warehousing, technology, and value-added special
services. The first three categories are traditional
services. The last two service categories have been
evolved and expanded rapidly in the last decade,
and the new capabilities have strengthened the stra-
tegic position of this industry.
The limitation of this study comes from the sec-
ondary data utilized. The dichotomy nature of the
data makes it hard to assess the quality and impact
of 3PLs services. Moreover, the data represent the
provider’s view. For future studies, it will be useful
to obtain paired data to get outsourcers’ inputs. Ob-
taining financial and assessment data will provide
more insights to the development of 3PLs industry.
In addition, new issues in global supply chains such
as supply chain risks, sustainability, and security
have imposed enormous challenges. It will be in-
teresting to conduct a detailed study on the role of
3PLs and its strategies to make profound impacts in
these areas.
8. REFERENCES
Anderson, E., Coltman, T., Devinney, T. and Keating, B. (2011),
“What Drives the Choice of a Third-Party Logistics Provid-
er?” Journal of Supply Chain Management, Vol. 47 No. 2.
Armstrong&Associates(2015),Global3PLMarketSizeEstimates,
available at: http://www.3plogistics.com/3PLmarketGlobal.
htm (accessed 6 Sept 2015).
Armstrong & Associates (2009) Guides & Market Research Re-
ports, available at: http://www.3plogistics.com/PR_3PL_
Customers-2009.htm, (accessed 9 April 2012).
Ashenbaum, B., Maltz, A. and Rabinovich, E. (2005), “Stud-
ies of Trends in Third-Party Logistics Usage: What Can
We Conclude?” Transportation Journal, Vol. 44 No. 3, pp.
39-50.

Berglund, M., van Laarhoven, P., Sharman, G. and Wendel, S.
(1999), “Third Party Logistics: Is There a Future?” Interna-
tional Journal of Logistics Management, Vol. 10 No. 1, pp. 59-70.
Bhatnagar, R., Sohal, A. S. and Millen, R. (1999), “Third Party Lo-
gistics Service: A Singapore Perspective”, International Jour-
nal of Physical Distribution and Logistics Management, Vol. 29
No. 9, pp. 569-587.
Boyson, S., Corsi, T., Dresner, M. and Rabinovich, E. (1999),
“Managing Effective Third Party Logistics Partnerships:
What Does It Take?” Journal of Business Logistics, Vol. 20 No.
1, pp. 73-100.
Business Wire (2002), “Hub Group and TMM Logistics Announce
Operating Partnership to Streamline Cross-Border Ship-
ping”, 29 October.
Burnson, P. (1999), “Getting Logistics in Order”, World Trade,
Vol. 12 No. 8, pp. 50-52.
Cooke, J. A. (2000), “3PLs: Riding the Wave”, Logistics Manage-
ment and Distribution Report, Vol. 39 No. 7, pp. 69.
C-TAPT, available at http://www.cbp.gov/xp/cgov/trade/cargo_
security/ctpat/ (accessed on April 3, 2012)
EPA SmartWay, available at http://www.epa.gov/smartway/in-
dex.htm (accessed on April 3, 2012.)
Hertz, S. and Alfredsson, M. (2003), “Strategic development of
third party logistics providers”, Industrial Marketing Manage-
ment, Vol. 32 No. 20, pp. 139.
Inbound Logistics (2002-2013), “Top 100 American 3PLs”, various
Issues in July, Thomas Publishing Company.
Inbound Logistics Top 100 3PL Providers Questionnaire, available
at http://www.inboundlogistics.com/cms/3pl-questionnaire/
(accessed on November 21, 2105.)
Knemeyer, A. M. and Murphy, P. R. (2005), “Exploring the Po-
tential Impact of Relationship Characteristics and Customer
Attributes on the Outcomes of Third-Party Logistics Ar-
rangements”, Transportation Journal, Vol. 44 No. 1, pp. 5-19.
Lagley, C. J. jr., Allen, G. R. and Dale, T. A. (2004), “Third-Party
Logistics: Results and Findings of the 2004 Ninth Annual
Survey”, in Georgia Institute of Technology, Cap Gemini U.S.,
and Federal Express Corporation.
Larson, P. D. and Gammelgaad, B. (2002), “Logistics in Denmark:
A Survey of the Industry”, International Journal of Logistics:
Research and Applications, Vol. 4 No. 2, pp. 191-206.
Lieb, R. C. and Bentz, B. A. (2005), “The Use of Third-Party Lo-
gistics Services by Large American Manufacturers: The 2004
Survey”, Transportation Journal, Vol. 44 No. 2, pp. 5-15.
Lieb, R. C. and Bentz, B. A. (2004), “The Use of Third-Party Lo-
gistics Services by Large American Manufacturers: The 2004
Survey”, Transportation Journal, Vol. 43 No. 3, pp. 24-34.
Lieb, R. C. and Kendrick, S. (2003), “The Year 2002 Survey: CEO
Perspectives on the Current Status and Future Prospects
of the Third-Party Logistics Industry in the United States”,
Transportation Journal, Vol. 42 No. 3, pp. 5-17.
Millegan, B. (2000), “Third-Party Logistics Providers Told To
‘Get to the Net”, Purchasing, Vol. 129 No. 8, pp. 91.
Min, H. and Joo, S. (2006), “Benchmarking the Operational Ef-
ficiency of Third Party Logistics Providers using Data Envel-
opment Analysis”, Supply Chain Management, An Internation-
al Journal, Vol. 11 No. 3, pp. 572-587.
Moberg, C. R. and Speh, T. W. (2004), “Third-Party Warehousing
Selection: A Comparison of National and Regional Firms”,
Mid - American Journal of Business, Vol. 19 No. 2.
Mottley, R. (1998), “Good News, Bad News for 3rd
Parties”, Amer-
ican Shipper, Vol. 40 No. 12, pp. 38-40.
Murphy, P. and Poist, R. (2000), “Third-Party Logistics: Some
User Versus Producer Perspectives”, Journal of Business Logis-
tics, Vol. 21 No. 1, pp. 121-133.
Murphy, P. R. and Poist, R. F. (1998), “Third-party logistics us-
age: An assessment of propositions based on previous re-
search”, Transportation Journal, Vol. 37 No. 4, pp. 26-36.
O’Reilly, J. (2011), “3PL Perspectives 2011”, Inbound Logistics,
July, pp. 71-86.
PEHub (2010) Thoma Bravo Closed Buy of UPS’s Logistics Tech-
nologies Unit, available at http://www.pehub.com/91805/
thoma-bravo-closes-buy-of-upss-logistic-technologies-unit/
(Accessed on April 12, 2012)
Persson, G. and Virum, H. (2001), “Growth Strategies for Logis-
tics Service Providers: A Case Study”, International Journal of
Logistics Management, Vol. 12 No. 1, pp. 53-64.
Rajesh, P., Pokharel, S. and Tan, A. (2004), “Perspectives on the
Use of Information Technology at Third Party Logistics Ser-
vice Providers in Singapore”, Asia Pacific Journal of Marketing
and Logistics, Vol. 16 No. 1, pp. 27-43.
Reuters (2011), US Logistics M&A Expected to Pick Up, available
at http://www.pehub.com/101438/reuters-us-logistics-ma-
expected-to-pick-up/ (accessed on April 12, 2012)
Simchi-Levi, D., Kaminsky, P. and Simchi-Levi, E. (2003), De-
signing and Managing the Supply Chain, second edition, Irwin
McGraw-Hill, Boston, MA.
Stank, T.P. and Maltz, A.B. (1996), “Some Propositions on Third-
Party Choice: Domestic vs. International Logistics Providers”,
Journal of Marketing Theory and Practice, pp. 45-54.
Sowinski, L. L. (2000), “Is There a Perfect Logistics Software Prod-
uct on the Market?” World Trade, Vol. 13 No. 2, pp. 32-36.
Vaidyanathan, G. (2005), “A Framework for Evaluating Third-
Party Logistics”, Communications of the ACM, Vol. 48 No. 1,
pp. 89-95.
Van Laarhoven, P., Berglund, M. and Peters, M. (2000), “Third-
Party Logistics in Europe - Five Years Later”, International
Journal of Physical Distribution & Logistics Management, Vol.
30 No. 3, pp. 425-442.
Wilding, R. and Rein, J. (2004), “Customer perceptions on logis-
tics outsourcing in the European consumer goods industry”,
International Journal of Physical Distribution & Logistics Man-
agement, Vol. 34 No. 7/8, pp. 628.

Wilson, R. (2004), “15th
Annual State of Logistics Report: Global-
ization”, available at: http://www.nescon.org/cgi-bin/2004/
index2.pl?r_wilson_presentation, (accessed 9 April 2012).
Yeung, J. Y., Selen, W., Sum, C. and Huo, B. (2006), “Linking Fi-
nancial Performance to Strategic Orientation and Operations
Priorities—An Empirical Study of Third-Party Logistics Pro-
viders”, International Journal of Physical Distribution & Logis-
tics Management, Vol. 34 No. 3, pp. 210-230.
Zhou, G., Min, H., Xu, C. and Cao, Z. (2008), “Evaluating the
Comparative Efficiency of Chinese Third-Party Logistics
Providers using Data Envelopment Analysis”, International
Journal of Physical Distribution & Logistics management, Vol. 38
No. 4, pp. 262-279.
Author’s Biography:
Yeongling H. Yang, Ph.D., is a Professor of the Management Information Systems Department at San Diego
State University in USA.

Characterization of cross-functional integration level:
A multi case study in Agribusiness Organizations
Ana Cristina Ferreira
Federal University of Uberlândia
ana-cristina18@hotmail.com
Franciele Olivo Bertan
folivo2@yahoo.com.br
Marcio Lopes Pimenta
pimenta.mp@gmail.com
ABSTRACT: A point that has generated discussion in the literature is the level of integration required
for the coordination of activities between areas. However, there is a lack of theoretical definitions and field
studies that explain this phenomenon in depth. Thus, this study aims to characterize the level of cross-
integration, the factors that generate it and the impacts on organizational performance. For this, interviews
with managers of Operations, R&D and Marketing/Commercial areas, from two multinational companies
based in Minas Gerais were performed. The results indicate that the level of integration can be analyzed as
a combination of three factors: 1) absence of overlapping of perceptions about integration factors over the
processes, balance between formality and informality, and absence of manifest conflicts of interest. This
is a setting that provides a deeper definition than those obtained in the studied literature, which basically
present integration mechanisms, without detailing how these should be applied in order to generate higher
levels of integration.
Keywords: Cross-functional integration; Integration level; Operations; R&D; Marketing.
36

Ferreira, A. C., Bertan, F. O., Pimenta, M. L.: Characterization of cross-functional integration level: A multi case study in Agribusiness Organizations
1. INTRODUCTION
The integration management can help to ensure that
there is harmony between organizational functions,
so that they can work together (Lawrence & Lorsch,
1967). This is an important factor, as it can improve
the sense of interdependence and organizational
results (Stank, Daugherty & Ellinger, 1999). There
are studies on this issue that address the correlation
between generating mechanisms of functional inte-
gration and results (Stank et al. 1999; Ellinger, 2000;
Daugherty, Mattioda & Grawe, 2009). This perspec-
tive represents the mainstream in the studied litera-
ture, in which, some authors identify important tools
to conduct the cross-functional integration (Kahn
& Mentzer, 1996; Kahn, 1996; Gimenez & Ventura,
2005; Jütnner, Christopher & Baker, 2007).
An element that has generated discussion in the
literature is the level of integration, which corre-
sponds to the intensity in which the areas relate to-
wards the coordination of their activities (Pimenta,
2011). There is, however, a lack of theoretical defi-
nitions and field studies explaining, in depth, how
this phenomenon operates. Authors such as Kahn
(1996) and Gimenez and Ventura (2005) mention the
importance of achieving higher levels of integration,
since this element denotes strong correlation with
the improvement of functional and organizational
results. Pagell (2004) elaborates a little further in
the practical sense, explaining that the definition of
the level of integration is relative, because different
managers in different contexts can interpret it in dif-
ferent ways. Thus, characterization should be based
on semantic definition of evidence, which is often
subjective.
Santos and D’Antone (2014), after conducting a re-
view of literature, argued that it is necessary to ver-
ify if integration can have a degree of measurement,
and if high levels of integration are necessary and
advisable. The authors also propose new topics for
further research, revealing, among them, the lack of
studies dealing with the level of integration.
Pimenta (2011) identifies characteristics of three in-
tegration levels (high, medium and low) in the con-
text of Marketing and Logistics. According to him,
high levels of integration are characterized by the
balance between formal and informal mechanisms
of integration within the points of contact between
areas. Basnet (2013) developed a scale for assess-
ing the level of cross-functional integration, and his
work is one of the first to measure this element quan-
titatively. However, the study mentioned features
integration levels according to the mere presence or
absence of mechanisms of integration, not correlat-
ing other elements such as: as points of contact and
formality and informality of integration.
We believe that a qualitative study can help to im-
prove the understanding about the level of cross-
functional integration in order to identify a set of
factors beyond the mere presence of integration
mechanisms. In this sense, this study aims to char-
acterize different levels of cross-functional integra-
tion according to its peculiarities in terms of inte-
gration factors (mechanisms), practical perceptions,
formality / informality and conflicts between inter-
nal functions. Regarding these features, Santos and
D’Antone (2014) found no papers dealing with the
issues considered here, mainly about differences in
the perception between people of the same company
in relation to integration factors.
The following section presents a theoretical review
about cross-functional integration and level of inte-
gration.
2. CROSS-FUNCTIONAL INTEGRATION
The increasing complexity of the competitive envi-
ronment has required quick decision making and
increasing harmony between demand and supply.
The management of cross-functional integration can
contribute to reach these needs (Silva, Lombardi &
Pimenta, 2013). Integration can be defined as “the
quality of the state of collaboration that exists among
departments that are required to achieve unity of ef-
fort by the demands of the environment” (Lawrence
& Lorsch, 1967, p.11). Thus, it contributes to improve
internal cooperation and the competitiveness of the
organization (Baofen, 2013).
Pagell (2004) refers to integration as a process in
which functions, such as production, purchasing
and logistics, work cooperatively to reach accept-
able results for the organization. Stank et al. (1999)
highlight that integration can bring many benefits
such as reduced production cycles, successful new
product strategies, better understanding of consum-
er values and also improved service levels.
Kahn and Mentzer (1996) state that cross-functional
integration is practiced by processes of interaction
and collaboration, consisting, respectively, in both
formal and informal processes that lead to depart-
ments acting together towards a cohesive organiza-

tion. To Baofen (2013) as antecedents of integration,
it is necessary to exist good relationship, trust and
commitment in relationships. Jin, Luo & Eksioglu
(2013) established that awareness of the competitive
potential that integration can provide is not enough
to mobilize resources and mitigate resistance to col-
laboration, and it takes commitment, which is the
key element.
The literature on integration presents analyses of
various elements such as: integration factors (Daugh-
erty et al 2009); contact points (Mentzer et al., 2008);
formality and informality (Kahn & Mentzer, 1996;
Ellinger, Keller & Hansen, 2006); integrating effects
(Stanket al. 1999; Gimenez, 2006; Jutnner et al. 2007)
and level of integration (Basnet, 2013). Kidron et al.
(2013), claim that informal and formal mechanisms
may increase the level of integration, especially the
informal ones. There is also a sub-theme in this issue
that discusses about antecedents and consequences
of the level of integration (Basnet, 2013). This sub-
theme will be specifically addressed below.
2.1 Integration Level
The level of cross-functional integration is the in-
tensity of the involvement of functions with each
other, based on the interaction frequency and on the
ability to perform activities that require cooperation
(Pimenta, 2011). Stank et al. (1999) noted that orga-
nizations with high level of integration, through co-
operation, achieve higher performance than the less
integrated organizations.
Kahn and Mentzer (1996) argue that not all situations
require high levels of integration. For these authors,
working with critical products and processes, in tur-
bulent environments, requires high levels of internal
integration, which in turn will result in higher ad-
ministrative costs for such an achievement. On the
other hand, when the market is stable and the ac-
tivity does not demand major efforts from different
departments, there may be a low integration level,
since a high intensity of integration in this situation
could compromise the efficiency of tasks.
Formal integration factors, like mutual evaluation
and incentive mechanisms, can increase the level of
integration between functions (Kahn, 1996; Gimenez
& Ventura, 2005; Jütnner et al 2007). Griffin and
Hauser (1996) highlight that the difference between
the ideal level, which is the necessary integration,
and the real one, forms the integration gap. If the
difference between the need of integration desired
by the organization and effective is large, the joint
performance can be compromised because the level
of integration achieved is not enough to respond to
external demands. If the gap is small, it means that
there was the desired integration by the organiza-
tion, and this can positively affect performance.
Pagell (2004) states that the definition of the level of
integration is relative, based on the semantic defini-
tion of evidences, which are often subjective. Pimen-
ta and Silva (2012) corroborate this statement and
add that, to each organization, a high or low level of
integration may have different meanings, even for
different people from the same organization. Thus,
Pimenta (2011) states that it is important to research
about what high, low or medium integration means
in the perception of managers. As several different
responses may arise, these can be analyzed by con-
tent and grouped according to the perception of the
agents who work in the integrated functions.
According to Pimenta and Silva (2012), there are dif-
ferent ways of analyzing the level of integration: the
amount of integration factors used, the frequency of
contact, the perception of the agents about the ease
to conduct joint processes and decisions.
To Bellmunt and Torres (2013), most part of the lit-
erature covers the theme of internal integration from
external integration. Thus, internal and external fac-
tors of influence should be considered to measure
the integration level. For internal integration, the
concept most widely accepted is two-dimensional,
which considers the interaction (formal aspects) and
collaboration (informal aspects). According to Gup-
ta et al. (1986) and Clark and Fujimoto (1991), these
two dimensions form a concept where low levels of
integration imply low levels of interaction and col-
laboration, and vice versa. On the other hand, the
one-dimensional concept considers that there is an
internal integration component (interaction or co-
operation, for example). By studying the integration
between Marketing and Logistics, Pimenta (2011)
presents a classification of three levels of integra-
tion and their respective characteristics, as shown in
Table 1.

Table 1: Features of different levels of integration
Integration Level Characteristics
High Presence of integration factors formally applied
Trust, team spirit, and informal elements
There are management actions to generate integration
Medium* Great willingness to help other functions to resolve conflicts informally
Little senior management effort
Low Lack of integration factors **
Unwillingness of people to integrate
Insulation between employees and short-term contact
* There may be great efforts of senior management and unwillingness of people.
** There may be integration factors, but not in a balanced way between formal and informal.
Source: Adapted from Pimenta (2011).
Among the various definitions presented in Table
1, “conflicts” is an element that can interfere in the
level of integration, depending on its type and inten-
sity. Authors such as Pondy (1989) and Simons and
Peterson (2000) argue that conflicts can disrupt the
processes and decisions due to the lack of integration
factors.
Pondy (1989) clarifies that organizational conflicts
were seen in the past as aberrations that interrupted
the normal course of processes, breaking the effi-
ciency of the work flow. In a broader perspective,
this author suggests that even the worst conflicts can
be avoided with the use of management tools, such
as: appropriate organizational structure, training to
generate mutual understanding of perceptions and
goals, or even to separate members with relation-
ship problems.
Simons and Peterson (2000) identify two types of
conflicts: 1) task conflicts (related to the content of
managerial decisions due to different standpoints
about the process); 2) relationship conflicts: (emo-
tional conflicts due to the perception of personal in-
compatibility). For these authors, the existence of re-
lationship conflict generates poor quality decisions.
According to these authors, trust between team
members is essential to avoid relationship conflicts
and provide higher quality decisions.
The next section deals with the description of the
methodological procedures performed in in the
preparation of this paper.
3. METHODS
This study is considered qualitative and descriptive.
A strategy of multiple case studies was conducted,
in order to provide a higher representation than a
single case study. According to Yin (2005), after ob-
taining the characteristics of the object of analysis,
the researcher must try to replicate of the results in
the analysis of other cases, identifying convergences
or differences that will contribute to solving the pro-
posed problem.
Two multinational companies, that develop and
produce seeds, were studied. These organizations
have processing units of seeds and experimental
fields in Minas Gerais State, Brazil. As noted in the
interviews, the context of these companies indicates
a strong need for cross-functional integration for 1)
the development of new cultivars; 2) the improve-
ment of genetics and aspects of plant science; 3) the
market positioning. Therefore, it was decided to
study new product development processes, because
they denote high necessity of cross-functional inte-
gration in these companies.
3.1 Data collection
Ten in depth interviews were conducted. The in-
terview guide was based on concepts from the lit-
erature, divided into three categories: 1) integration
factors (Daugherty et al., 2009; Kidron et al., 2013);
2) perception of the level of integration (Kahn &
Mentzer, 1996; Pimenta, 2011; Bellmunt and Tor-
res, 2013;Basnet, 2013); 3) impacts of the integra-

tion level on performance (Stank et al. 1999; Pagell,
2004;Gimenez, 2006; Jutnner et al.2007;Baofen, 2013).
The questions were developed considering the new
product development (NPD) processes, and there-
fore, the 10 interviewees belong to areas directly
involved with the NPD process: Operations, R&D,
Sales / Marketing. Table 2 shows the characteristics
of the respondents.
Table 2: Characteristics of respondents
Company Interviewed code Function
1 TO 1 R&D
1 A2 Production
1 A3 R&D
1 A4 R&D
1 A5 Commercial
2 B1 R&D
2 B2 Production
2 B3 R&D
2 B4 Commercial
2 B5 Commercial
All participants were interviewed in their work-
place. The interviews lasted around an hour and
were recorded with the consent of the participants,
allowing subsequent transcription to better under-
stand the interviews.
3.2 Data analysis
The transcriptions were submitted to the technique
of content analysis. Based on the guidelines of Bar-
din (1979), the following steps were adopted:
»» Pre-analysis of the transcripts: quick read, prior
identification;
»» In depth analysis;
»» Coding: the particular significance of each ele-
ment is highlighted in frames;
»» Categorization: codes are grouped into categories
defined in the literature or observed in the con-
text of the subject matter
Through these procedures, four categories of anal-
ysis related to the level of functional integration
were found:
1. Integration factors: mechanisms that generate
integration, related to the culture, interpersonal
disposal, or formal managerial actions (Pimenta,
2011; Pimenta and Silva, 2012);
2. Perceptions of overlapping: This element was not
present in the interview guide. It consists of the
main theoretical contribution of this paper and
emerged from the interviews and content analysis.
Overlapping occurs when an employee perceives
the existence of an integration factor, but another
(or many others) employee involved in the same
process does not perceive it. In such cases, the per-
ception of integration is not homogeneous.
3. Formality / informality: The way the integration
factors are operationalized, i.e., formal or infor-
mal processes ( Ruekert and Walker, 1987; Kahn,
1996; Kahn and Mentzer, 1998).
4. Conflicts: to reduce/eliminate: conflicts between
the areas of Production, Marketing and Logistics
(Ballou, 2006; Ellegaard and Koch, 2014); conflicts
of interests and conflicts of performance between
the internal functions and organization; func-
tional strategies not well defined or not clarified;
lack of group vision and misaligned objectives
(Pondy, 1989; Moses and Ahlström, 2008; Paiva,
2010); and promote trust as a way to reduce con-
flicts (Simons and Peterson, 2000)
These categories and their respective relationships
with the level of integration are defined in the fol-
lowing topic.
4. RESULTS
The four categories identified in the content analy-
sis, reinforced by quotations from the interviewees
are explained in this topic. After the individual defi-
nition of each one, a set of characteristics of different
levels of cross-functional integration in presented.
4.1 Integration Factors
Table 3 shows the analysis of the integration factors,
i.e. mechanisms that generate integration. It also
shows how these factors are operationalized in the
perception of the respondents. Twenty-one integra-
tion factors were perceived in different hierarchical
levels and different phases of the studied processes.
In addition, the type of application of the integration
factors was identified according to their formality or
informality.

Table 3: Description of the integration factors and presence of formality and informality
Integration Factors Type of Application
Company 1
Type of Application
Company 2
Company 1 Company 2
Adequate communi-
cation structure
Formal Formal There is an excess in
the use of communi-
cation tools.
There is a well-de-
fined structure.
Consideration of
informal groups
Formal Informal Managers recognize
the need to work in
an integrated manner,
and encourage this
practice.
Managers recognize
the voluntary willing-
ness to work in an in-
tegrated manner.
Cross-functional
meetings
Formal Formal There are too many
meetings.
There are formal
meetings.
Cross-functional
teams
Formal Formal and informal Meetings are held
periodically with the
specific group, for
alignment between
areas.
There are support
teams for the process
to happen. There are
also informal adjust-
ments.
Cross-functional
training
Formal Formal There is training for
related areas. These
sometimes occur as
meetings for the de-
velopment of new
products.
There is training
about the content of
the areas and about
relationship.
Goals aligned with
strategy
Formal Formal Individual goals
and departments are
aligned to the objec-
tive of the company.
The employees are
encouraged to think
of the whole com-
pany, towards a com-
mon goal.
Group spirit - Informal There is a climate of
cooperation, facilitat-
ing conflict resolu-
tion.
Informal communi-
cation
- Informal The communication
related to all process-
es is formalized.
People are always
available for informal
communication.
Information Sharing Formal Informal There is information
sharing by equipment
and software.
People are not shy
about sharing infor-
mation.
Information techno-
logy
Formal Formal and informal The company pro-
vides modern com-
munication mecha-
nisms, but its use,
however, is not sat-
isfactory, which be-
comes a barrier.
There are ample
mechanisms of in-
formation, but some-
times they hamper
integration. Willing-
ness to share helps
integrate.
Integration by hie-
rarchy
Formal - There are formal
meetings and rules to
be followed; besides,
some functions de-
pend on marketing to
perform their duties.
The functions have
independent manag-
ers.

Job rotation Formal Formal Job rotation provides
necessary skills to in-
tegrate areas.
There is job rotation,
it is central to the
company’s develop-
ment.
Joint planning Formal Formal Formal processes,
involving different
functions in different
stages of product de-
velopment.
Planning together
provides efficiency
in the activities to be
performed.
Longevity of rela-
tionships
Formal and Informal Formal and informal Managers acknowl-
edge that a low turn-
over of employees
helps to integrate
functions. But there
are no initiatives to
reduce turnover.
The company has
older employees,
who create trust and
integration between
people.
Mutual reward /
evaluation systems
Formal Formal There are differences
in rewards but this
does not generate dis-
comfort among the
areas.
The performance
evaluation and re-
ward systems and
commission do not
generate discomfort.
There is transparency.
Mutual understand-
ing
Formal Informal There is a good
mechanism for in-
formation, but some-
times when there is a
change of policy it is
not well notified to all
functions.
It happens mainly in
managerial levels.
Somewhat lacking in
operational levels.
Non-conflicting goals Formal Formal There are conflicting
goals and it generates
duplicate tasks.
There are common
goals, based on the fi-
nal customer, but the
perspectives are con-
flicting.
Physical proximity Formal and informal Informal Physical proximity is
related to the com-
pany’s infrastructure
and encourages in-
formal communica-
tion, which facilitates
discussion and under-
standing of the activi-
ties.
Physical proximity is
related to the com-
pany’s infrastructure
that facilitates in-
tegration and com-
munication between
areas.
Recognition of Inter-
dependence
Formal Informal There is planning be-
tween these teams,
respecting the knowl-
edge of other areas.
There is recognition
of interdependence,
which facilitates co-
operation.
Top management
support
Formal Formal Top management
supports the integra-
tion process.
Top management is
integrated with all
areas, all of which ac-
count for the risks.

Trust Formal and informal Formal and informal There is trust, but
some people act in-
appropriately. When
this happens, meet-
ings to resolve the
conflict are conduct-
ed.
There is trust, but
some people act in-
appropriately. When
this happens, meet-
ings to resolve the
conflict are conduct-
ed.
Willingness to resol-
ve conflicts
Formal Informal There are meetings to
get in touch with oth-
er departments and
discuss solutions to
resolve the conflict.
There is something
structured to resolve
conflicts, but people
end up solving them
by themselves.
Among the factors above, we can highlight the plan-
ning together as fundamental to the smooth running
of activities in both companies, since these factors
end up encouraging other informal mechanisms.
This planning often happens in the form of cross-
functional meetings.
There is a meeting to evaluate the product pro-
motion and the new molecule requests. Too
many meetings, this Company lives for meet-
ings (A4). The impact of the planning is direct,
you can optimize time, resources and get maxi-
mum efficiency in the activity that you are do-
ing (B3). There are systematic meetings with
set agendas (B4).
In both companies, goals are aligned with the strat-
egy. “We can criticize or not the goals that the com-
pany has, but since the goals are outlined, they call
people to trace the individual goals in accordance
with the company’s goal “(A3). For Company 2, the
alignment of objectives helps to eliminate conflicts
of interest. “It is explained to each employee, from
when he or she starts to work here, so the company
induces them to think not as an individual, but as a
whole company”(B3). The meetings are also oppor-
tunities to reduce misunderstandings.
In the annual conventions, there is opportu-
nity to better know each other and to under-
stand the objectives of each other (A3). People
understand the interdependence. Most part of
the teams respects the knowledge of other area
(A4); The cooperative work between the teams
is very strong, because they acknowledge inter-
dependence “(B3).
Based on these descriptions, one can see that, to a
greater or lesser extent, the two companies have
positive aspects with respect to how integration fac-
tors are applied. However, within a same company,
respondents showed antagonistic perceptions with
regard to the occurrence of these factors. These dis-
tortions may signal a drop in the level of integration.
The next topic deals with this issue.
4.2 Overlapping of perceptions on the integration factors
There are perceptions of overlaps with regard to
the existence of integration factors. For example,
while an interviewee from a given company has rec-
ognized a factor, another one who has a different,
opposite view, cannot recognize it. Table 4 presents
all factors that have overlaps in the two companies
studied. For this analysis, it was found that when
a respondent perceives an integration factor with-
in the company (Present), and the other does not
(Missing), there is an overlap of perception (marked
in gray). When all respondents indicate that certain
factor is present or missing within the company, it
means that there is no overlap of perception.

Table 4: Grouped perception showing overlap between presence and absence of integration factors
Company 1 Company 2
Factors Present Missing Present Missing
Adequate communication structure X X X
Consideration of informal groups X X X
Cross-functional meetings X X X
Cross-functional teams X X X
Cross-functional training X X X X
Goals aligned with strategy X X X
Group spirit X X X X
Informal communication X X X X
Information sharing X X X X
Information technology X X X X
Integration by hierarchy X X X X
Job rotation X X X X
Joint Planning X X
Longevity of relationships X X X X
Mutual evaluation/ rewards systems X X X
Mutual understanding X X X
Non-conflicting goals X X X X
Physical proximity X X X X
Recognition of Interdependence X X X
Top management support X X X
Trust X X X X
Willingness to resolve conflicts X X X X
It is necessary to highlight that the factor “Joint Plan-
ning” did not present overlapping perceptions in
any of the companies. All respondents claimed that
this factor is present within companies. To Com-
pany 1, the consideration to informal groups, is an-
other factor present. In Company 2, the respondents
highlighted eight factors: Hierarchical dependence
between functions; Top management support; Ad-
equate communication structure; Cross-functional
teams; Mutual evaluation/ rewards system; Cross-
functional meetings; Mutual understanding; Goals
aligned with strategy.
To Company 1, three of the respondents said that
the company values the longevity of relationships,
contrary to respondent A4’s reply, which states that
Today we have a large number of rotating peo-
ple within the company. So we have a certain
age gap, where we have the older people, aver-
age people we do not see much, and the younger
staff. This newer staff has a very high turnover,
so we’re losing some of this expertise of infor-
mation exchange (A4).
The same happens with Company 2, where inter-
viewee B4 said that the organization “has a very old
staff, but we have a point where the company is ex-
tremely dynamic, to move people to seek diversity,
but the well-defined processes can guide us”(B2).
This overlap also happens when you ask about the
top management support for integration processes.
For interviewee A5 “We have done a great job to
integrate various events to provide mutual under-
standing.” However, for interviewee A3, “there is a
real difficulty to integrate the team’s base and the
leadership does not cooperate with it”.

When asked about the existence of cross-functional
teams, three of the respondents from Company 1
claim that it exists. However, interviewee A3 said
that “the concept is very well implemented, but in
practice there is a difficulty in demanded resourc-
es and investment in time “(A3); “In the past there
were temporary teams, that now are specific groups”
(A4); “It existed in the past, not now” (A5).
Overlapping perceptions are even more visible
when questioned on cross-functional meetings. In-
terviewee A3 said that “there are too many meet-
ings, it is a negative thing, they are excessive”; while
participant A5 reports that “it is not common, but it
exists in the company”.
Another divergence noted was about the system of
evaluations/ rewards. Interviewee A2 stated that
“people from an area do not aim to harm the per-
formance of other areas” but he said that there are
differences of reward policies among areas. This
point of difference is also highlighted by other re-
spondents. However, it also indicates that there are
discomforts with this issue.
The major discomfort is not the competition be-
tween the areas, but the difference between the
awards. The commercial area has a prize almost
six times greater than the R&D area or a mar-
keting area (A4). Discomfort, and some actually
have privileges (A3). There is a certain jealousy
of the commercial part ... Then the other depart-
ments see us organizing parties, traveling... So,
our award, in general, our remuneration, is far
superior to other departments (A5).
Considering the willingness to resolve conflicts in
Company 1, four respondents said that teams work
together. However, it is important to note the re-
sponse of interviewee A3, in which he states that:
If I’m not from that area and choose to respond,
and is not successful, I can be reprimanded for
it. So, most of the people are shy to provide help
at some points (A3).
In Company 2, interviewed B4, stated that “we have
business teams, who make it very easy for problem
and conflict solving”. As for the B3:
This integration exists, but when there is any
more difficult problem it is directed to lead
managers. However, it occurs, but only in cases
where the problem is broader (B3).
Interviewee A4 said that information sharing “fre-
quently occurs in the meetings.” However, inter-
viewees A2 and A3 informed that there is a lack of
time to perform it, “the scarce time limits people, but
people are willing to share, sometimes with some
barriers” (A2). “The level of activities that each per-
son manages within a private company is high. You
are pressed for a result, you are very busy, so the
time you have for parallel problems is scarce” (A3).
The overlap also happens in Company 2, where
respondent B4 says he has “open access”, i.e. has
no problems in sharing information. However, B3
states that “there are certain sectors within the com-
pany who work with absolute secrecy. It will only
be diffused when you are very sure about the impact
that such information will bring to the company’s
own image “(B3).
With regard to the knowledge that an area has about
another, interviewee A1 states that it occurs through
communication. However, A4 states: “often we have
new people in the area, that do not know what is the
real function of the area is. Thus, there are conflicts
in which an area does the same thing as another.
Then you need to have an adjustment here”. The
lack of mutual understanding within a given area
also seems to generate difficulties in the alignment
of the goals with the organization:
The company demands what we should do, but
conflicts between functions often emerge. The
person does not understand his/ her function,
and ends up doing duplicate work, doing the
same that other teams are doing (A4). Some-
times there is a lack of clarity in the description
of each function to avoid these conflicts (A2).
Taking into account the training conducted within
Company 2, interviewee B3 said that this “is highly
valued and encouraged.” However, B2 reports:
We have, for example, leadership training,
which has several modules. People from various
fields gather for a yearly meeting of company
managers. Strategies are explained, sales plans,
however, we don’t have a specific training for
Product Development, or integration (B2).
When asked if physical proximity encourages infor-
mal communication, Interviewee B3 stated that: “it
happens primarily in newly built offices, where the
entire space was designed to facilitate integration”.
However, for B2, Company 2 “has several research
centers and production plants throughout Brazil, I

would say that this geographic distance inhibits in-
tegration”.
About the influence of hierarchy on integration in
Company 2, B3 states: “this happens because hi-
erarchical relationships are very clear and highly
respected”. In spite of this, B1 does not agree with
that, “because the company is very horizontal and
stimulates us to overcome barriers. There are few
barriers, we do not see much value in it” (B1).
About Group spirit within Company 2, three inter-
viewees stated that it exists and is well stimulated.
However, B2 opposes this view: “if all goes well, ok,
however, if there is a crisis situation with regard to the
area, then it simply disappears (Group spirit)” (B2).
Company 1 has more overlaps than Company 2.
This irregular perception of respondents shows that
cross-functional integration does not occur uniform-
ly over the processes or between different hierarchi-
cal levels. Table 5 shows the hierarchical levels and
stages of the studied processes. It was also high-
lights the perception about formality and informal-
ity, as well as the integration factor that corresponds
to these states.
Table 5: Differences of perception of integration at different hierarchical levels at different stages of
product development
Occurrence of integration in the phases of product development
Early stage Intermediate phase Final phase
Hierarchicallevels
Manage-
ment
A1 - formal (cross-functional
meetings, planning)
Formal establishing infor-
mal (exchange of experience)
B2 - formal establishing
informal (Top management
support);
Formal (hierarchical depen-
dency between functions)
A5 - formal (information sharing)
B4 - informal (Group spirit)
Formal establishing informal
(information sharing)
Operational
Level
A2 - formal (functional meet-
ings)
A3 - formal (lack of confi-
dence, objectives sharing)
A4 - formal (cross-functional
meetings)
B1 - formal establishing in-
formal (meetings creating
ties through forums for dis-
cussion)
B3 - formal (cross-functional
teams)
B5- informal (Group spirit)
Formal establishing informal
(information sharing)
It is important to note that, according to the hierar-
chical position of the interviewee and phase in Prod-
uct Development, perceptions of integration and
occurrence of integration factors may differ. There
may be integration factors in a hierarchical level and
not in others. Or, these factors exist in a part of the
process, and in others, no.
This is clear within Table 5, in which the functions of
the interviewees A4, A3 and A2 are at the operation-
al level. These three people presented a large vol-
ume of missing integration factors. This group also
complained about the excess of formality, especially
in cross-functional meetings. As for Company 2, the
highlight comes from Interviewee B2, who present-
ed more missing factors, and signs for the majority
of formal processes. In addition, B2 is at the manage-
ment level, which differs from Company 1, in which
the interviewees that perceive lack of factors are at
operating levels.
Thus, it can be considered that, a high level of cross-
functional integration is related to a homogeneous
existence of integration factors in all levels and at all
stages of the process.
4.3 formality and informality
For Kidron et al. (2013) informal and formal mecha-
nisms may increase the level of integration, especial-
ly the informal atmosphere. But a balance between
the two is necessary. The analysis of field data re-
vealed a complaint by respondents from Company
1 on the excessive formality, as seen in the following
excerpts:
No, we have nothing informal within the com-
pany. All is well formalized. Emails, commu-
nications, everything is registered, nothing is
informal. Because you can be here today, to-
morrow you’re in another area, and someone

else comes and takes what was your decision
and leaves. Then informality does not exist in
the company (A5). I do not see very informal
communication, but formal communication be-
tween the teams (A4). We have ground rules,
there are several formal meetings or created
environments to induce interaction between ar-
eas, i.e. the hierarchy operates asking us to have
formal moments for it (A3).
Interviewee A3 stated: “there is a bureaucratic is-
sue, it requires various departments interacting to
solve bureaucracies and to generate confidence be-
tween areas. I would say a lot of formality is nec-
essary within the processes to tie confidence” (A3).
The same respondent states that “it is easy to share
information, informally. Because we have communi-
cator (a instant messenger tool) inside the company,
where no formality is required for the exchange of
information “(A3).
Considering this issue of informal communication
and the mechanisms of information technology, par-
ticipant A4 states that “often the person ends up not
having a personal conversation, they prefer sending
an email than to call or stop in the hall to talk. In my
view, this IT issue ends up generating more formal
communication than informal” (A4).
In an opposite view from Company 1, Company 2
presents more informality in their processes:
The company has a lot of informality, it has no
problems in this kind of relationship. It is not
bureaucratic, we can talk, talk, no problem (B2).
Certainly, the company encourages it enough
(B1). However, depending on the information
we are seeking, communication is formal (B4).
There is formal integration, but informal inte-
gration also exists and it is constant, there is
a big incentive for people from different areas
to seek information of what is happening in the
other areas (B3).
Thus, when there are formal processes, that stimu-
lates informal collaborative behavior, the interaction
between departments and even between people. It
happens in a more harmonious way, generating a
high level of integration.
4.4 Conflicts
Although the two surveyed companies promote ac-
tions to manage relations between areas efficiently,
some conflicts may arise and affect negatively both
the cross-functional integration and the progress of
new product development processes. In Company
1, conflicts can occur for lack of planning, or when
“planning is not considered in the field phases.
It also happens when communication is not clear
about updates of the project’s progress” (A1). Con-
flicts can happen in the transition from one stage of
NPD to another, because “some issue that occurs in
the earlier stages can impact the next phase” (A2).
According to interviewee A5, this creates conflicts
between the functions that are part of NDP.
This type of conflict in NPD processes may also gen-
erate mistrust between the areas:
If I work in the third phase and receive a prod-
uct from the second phase that has quality prob-
lems or delay, it does not reach expectations,
and then you do not really believe anymore in
what the area delivers, there is a distrust” (A3).
The respondent used the term distrust to refer to this
problem, when an area does not deliver its part as it
should, resulting in conflicts between them. The lack
of trust is an element related to relationship conflicts
and may generate management decisions of poor
quality, as cited by Simons and Peterson (2000).
Interviewee A4 mentioned another conflict high-
lighted within Company 1:
Is the conflict of interest, they push the prob-
lems to the other department. So, a conflict of
interest arises between areas. One area gains
more responsibility than the other. It also hap-
pens because the areas don’t know the responsi-
bilities of each other, so, an earlier problem may
affect the next phase of NPD. (A4),
In Company 2, the main problems are related to the
lack of alignment between functional goals and mar-
ket positioning of products.
Self-centeredness, they think that their goals
are more important than the other functions
(B1). There is conflict of interest in positioning
of some products in the market, because today
the company works with a number of different
products within the agricultural line (B3).
A likely explanation for these conflicts of interest
may be the system of evaluation and rewards that
the company adopts. Interviewee B2, with this re-
gard, said: “I think that indicators inhibit coop-

eration, sometimes it conflicts somewhat with our
greater goal, which is customer service” (B2).
Considering the above, it becomes clear that con-
flicts can be useful elements to improve the relation-
ship and collaboration between people. But when
they turn to manifest conflicts, based on personal
interest, they can lead to unilateral decisions. Rela-
tionship conflicts, as quoted by Simons and Peter-
son (2000), may also culminate in the same situation.
These types of conflicts are perceived as being diffi-
cult to solve and may reduce the level of integration.
Moreover, as cited by Pondy (1989), conflicts can be
a source of enhancement, and thus contribute to the
increased integration level. However, they must be
managed through integration factors, such as train-
ing to generate mutual understanding of percep-
tions and goals, or even separating members with
relationship problems.
4.5 Characterization of the level of integration
The level of cross-functional integration can be an-
alyzed as a combination of three factors: homoge-
neous perception of integration factors throughout
the stages of the process (as opposed to overlap-
ping), balance between formality and informality,
lack of manifest conflicts of interest, as described in
the topics above.
With regard to the homogeneous perception of in-
tegration factors, Company 1 displays the highest
level of overlap. Considering the formality and in-
formality, again, this Company presents excessive
formality, as highlighted by the interviewees. The
lack of balance between formal and informal inte-
gration factors indicates that the level of integration
should not be high.
For Company 2, one of the most important elements
to characterize its integration level is the existence
of informality, encouraged by formal factors like
cross-functional teams and top management sup-
port. In this company, the cross-functional teams are
considered very important for the smooth running
of the NPD, mainly because it facilitates the sharing
of information between the areas, and reduces the
incidence of manifest conflict of interest.
Based on field data, Company 2 has more consis-
tency of its activities related to integration than
Company 1, because it aligns formal and informal
aspects that are critical for integration. The percep-
tion of integration factors is also more homogeneous
in Company 2 than Company 1. In addition, respon-
dents from Company 2 identify fewer situations of
manifest conflicts of interest related to functional
relationships than Company 1. Such evidences in-
dicate that the level of integration in Company 2 is
higher than in Company 1.
Based on the conclusions reached at the end of each
subtopic of the results, we propose a definition of
different levels of cross-functional integration and
their respective characteristics, as shown in Table 6.
Table 6: Characteristics of functional integration levels
Integration functional level Characteristics
High Integration factors are perceived homogeneously by the different functions involved in the
implementation of processes, throughout their initial, intermediate and final stages;
Integration factors are perceived homogeneously at different hierarchical levels: strategic,
managerial and operational, when the processes depend on decisions made at different lev-
els; Existence of formal and informal integration factors that can generate collaboration
without excessive bureaucracy and rigid structures;
Absence of manifest conflicts of interest that are often difficult to solve through mutual
cooperation between the integrated functions. The existence of team spirit and mutual un-
derstanding between the functions contributes to the solution of conflicts, strengthening the
relationships. The functions are more concerned with organizational results and therefore
are willing to sacrifice functional privileges.

Medium There is some overlap about the perception of absence/presence of integration factors along
different stages of the process, but that is not enough to hinder cooperation toward the com-
mon goals;
There is some overlap about the perception of absence/presence of integration factors at dif-
ferent hierarchical levels, but that is not enough to hinder cooperation toward the common
goals;
Integration is achieved primarily by formal factors. There are more formal than informal
factors - or - Integration is achieved primarily by informal factors. There are more informal
than formal factors. There is not a balance between formality and informality. There are no
formal factors that stimulate the existence of informal collaborative behaviors.
There are conflicts of interest, difficult to solve, which are sometimes resolved through mu-
tual cooperation between the integrated functions, or hierarchical order impositions.
Low The integration factors may exist at some stages of the process, but are missing at others;
There is too much formality in the application of integration factors, generating excessive
bureaucracy and waste of time in meetings and standardized tasks - or - there is over-reli-
ance on informalities to achieve integration, in which case the management does not define
formal integration factors such as: meetings, planning together and cross-functional teams;
Existence of manifest conflicts of interest that are often difficult to solve through coopera-
tion between the functions. Group spirit and mutual understanding are not perceived be-
tween the functions, creating an environment in which each function is more concerned with
functional results than with the result of the organization as a whole.
5. FINAL CONSIDERATIONS
This study proposes a set of characteristics to define
different levels of cross-functional integration based
on: homogeneous perception about integration fac-
tors throughout the stages of the process, balance
between formality and informality, absence of mani-
fest conflicts of interest. The case studies helped to
identify different situations involving each of these
three elements in order to define the characteristics
of the three different integration levels: high, medi-
um and low, as detailed in Table 6.
About the theoretical contribution, one relevant point
of this study was to verify the existence of overlapping
perceptions about integration factors, i.e., different
respondents had opposing opinions on the existence
or not of the same factor. When there is overlapping,
integration is not perceived homogeneously among
people in the same process, and that fact may indicate
low level of integration. Another element related to
low levels of integration is the presence of manifest
conflicts. In the companies studied, the main integra-
tion problems are related to conflicts of interest and
difficulty to understand its real function.
From a practical point of view, managers should
observe activities in which a high level of integra-
tion can generate improvements in processes and
outcomes. Firstly, they should manage the relation-
ships between the integrated functions based on the
presence of integration factors over all the phases of
the process in analysis. Secondly, managers should
observe the existence of balance between formal and
informal integration factors. Formal factors may
stimulate the existence of spontaneous cooperative
behaviors. Thirdly, managers should pay attention
to the motives that generate manifest conflicts of
interest, once they can reduce the integration level
due to their particular point of view in prejudice of
the whole company’s perspective. Finally, excessive
application of formal factors can create a barrier to
integration. Interviewees from the two surveyed
companies explained that Information Technology
in excess makes it difficult to integrate, since it ex-
cessively formalizes processes and cuts people from
informal communications.
Due to the method of case study, this research has
limitations of coverage, since its conclusions cannot
be generalized. Future studies may suggest the con-
struction of a scale for assessing the level of integra-
tion, based on each of the three defined levels and
their respective characteristics. Thus, these stud-
ies may test correlations among the elements here
suggested in order to identify levels of integration
in different stages of several processes that require
cooperation among internal functions. Especially
when these processes involve decisions of different
hierarchical levels for its implementation.

6. REFERENCES
Ballou, R. H. (2006). Gerenciamento da Cadeia de Suprimentos-:
Logística Empresarial. Bookman.
Baofeng, H. (2013). Relationship management and supply chain inte-
gration: Literature review and research directions.
Bardin, L. (1979). Análise de conteúdo. Lisboa: Edições 70.
Basnet, C. (2013). The measurement of internal supply chain
integration. Management Research Review. Vol. 36 No. 2, pp.
153-172.
Bellmunt, T. V. & Torres, P. R. (2013). Integration: attitudes, pat-
terns and practices. Supply Chain Management: An Interna-
tional Journal 18/3, 308–323.
Clark, K. & Fujimoto, T. (1991). Product Development Performance-
Strategy, Organization, and Management in the World Auto
Industry. Boston: Havard Bussiness Scool Press.
Daugherty, P. J., Chen, H., Mattioda, D. D., & Grawe, S. J. (2009).
Marketing/logistics relationships: influence on capabilities
and performance.Journal of Business Logistics, 30(1), 1-18.
Ellegaard, C., & Koch, C. (2014). A model of functional integra-
tion and conflict: The case of purchasing-production in a
construction company.International Journal of Operations &
Production Management, 34(3), 325-346.
Ellinger, A. E. (2000). Improving Marketing/Logistics cross-func-
tional collaboration in the supply chain. Industrial Marketing
Management, v. 29, n. 1, p. 85-96.
Ellinger, A. E.; Keller, S. B. & Hansen, J. D. (2006). Bridging The
Divide Between Logistics And Marketing: Facilitating Col-
laborative Behavior. Journal of Business Logistics, v. 27, n. 2,
p. 1-28.
Gimenez, C. (2006). Logistics integration processes in the food
industry. International Journal of Physical Distribution & Logis-
tics Management, v. 36, n. 3, p. 231-249.
Gimenez, C. & Ventura, E. (2005). Logistics-production, logistics-
marketing and external integration: Their impact on perfor-
mance. International Journal of Operations & Production Man-
agement, v. 25, n. 1, p. 20-38.
Griffin, A. & Hauser, J. R. (1995). The International Center for Re-
search on the Management of Technology Integrating R & D and
Marketing: A Review and Analysis of the Literature. Cam-
bridge, MA.
Gupta, A. K; Raj, S. P. & Wilemon, D. (1986). A model for Study-
ing R&D-Marketing Interface in the Product Innovation Pro-
cess. Journal of Marketing. v. 50; p. 7-17.
Jin, M.; Luo, Y. & Eksioglu, S. D. (2013). Integration of production
sequencing and outbound logistics in the automotive indus-
try. Int. J. Production Economics, v. 113, p. 766-774.
Jüttner, U.; Christopher, M. & Backer, S. (2007). Demand chain
management-integrating marketing and supply chain man-
agement. Industrial Marketing Management, v. 36, n. 3, p.
377-392.
Kahn, K. B. (1996). Interdepartmental integration: a definition
with implications for product development performance.
Journal of Product Innovation Management, v. 13, p. 137-151.
Kahn, K. B. & Mentzer, J. T. (1996). Logistics and interdepartmen-
tal integration. International Journal of Physical Distribution &
Logistics Management, v. 26, n. 8, p. 6-14.
Kidron, A. (2013). Internal integration within human resource
management subsystems. Journal of Managerial Psychology.
Vol. 28 No. 6, pp. 699-719.
Lawrence, P. R. & Lorsch, J. W. (1967). Organization and environ-
ment: managing differentiation and integration. 7. ed. Bos-
ton: Harvard University, p. 279.
Mentzer, J. T.; Stank, T. P. & Esper, T. L. (2008). Supply Chain
Management And Its Relationship To Logistics , Marketing
, Production , And Operations Management. Journal of Busi-
ness Logistics, v. 29, n. 1, p. 31-46.
Moses, A., & Åhlström, P. (2008). Problems in cross-functional
sourcing decision processes. Journal of Purchasing and Supply
Management, 14(2), 87-99.
Onoyama, S. S.; et al. (2008). Integração intra e interorganizacio-
nal no desenvolvimento de produtos: estudo de caso no setor
de laticínios. Revista Gestão Industrial, v.4, n.1, p. 68-87.
Pagell, M. (2004). Understanding the Factors that Enable and In-
hibit the Integration of Operations, Purchasing and Logistics.
Journal of Operations Management, 22, 459-487.
Paiva, E. L. (2010). Manufacturing and marketing integration
from a cumulative capabilities perspective. International jour-
nal of production economics, 126(2), 379-386.
Pimenta, M. L. (2011). Caracterização da dinâmica de integração in-
terfuncional: um estudo multicaso em Marketing e Logística.
[s.l.] Universidade Federal de São Carlos.
Pimenta, M. L & Silva, A. L. da. (2012). Desafios da integração
interfuncional: o papel da formalidade e da informalidade.
Anais... XXXVI Encontro Anpad.
Pimenta, M. L. & Silva, A. L. da. (2012). Dimensões Da Inte-
gração Interfuncional: Proposta De Uma Estrutura De
Análise. Anais... XXXII Encontro Nacional De Engenharia De
Produção, Bento Gonçalves, RS.
Pondy, L. R. (1989). Reflections on organizational conflict. Journal
of Organizational Change Management, 2(2), 94-98.
Ruekert, R. W., & Walker Jr, O. C. (1987). Marketing’s interaction
with other functional units: a conceptual framework and em-
pirical evidence. The Journal of Marketing, 1-19.
Santos, J. B., & D’Antone, S. (2014). Reinventing the wheel? A
critical view of demand-chain management. Industrial Mar-
keting Management, 43(6), 1012-1025.
Silva, A. L. Da; Lombardi, G. H. V. & Pimenta, M. L. (2013).
Alinhamento interfuncional: um estudo exploratório sobre
os pontos de contato entre marketing, logística e produção.
Gestão & Produção, São Carlos, v. 20, n. 4, p. 863-881.

Simons, T. L., & Peterson, R. S. (2000). Task conflict and relation-
ship conflict in top management teams: the pivotal role of
intragroup trust. Journal of applied psychology, 85(1), 102.
Stank, T. P.; Daugherty, P. J. & Ellinger, A. E. (1999). Marketing/
Logistics Integration and Firm Performance. The International
Journal of Logistics Management, v. 10, n. 1, p. 11-24.
Yin, R. K. (2005). Estudo de caso: planejamento e métodos. Porto
Alegre: Bookman.
ANA CRISTINA FERREIRA: Bachelor’s in Administration from Federal University of Viçosa, Campus of
Rio Paranaíba (2013). Master’s student in Administration from Federal University of Uberlândia.
FRANCIELE OLIVO BERTAN: is barchelor in Agronomy (2006) and Master (2008) in Science and Seed Tech-
nology at the Federal University of Pelotas. Doctorate in agronomy (2014) , the area of specialty in Production
and Seed Technology For the Federal University of Uberlândia.
MARCIO LOPES PIMENTA: Bachelor’s in Administração de Empresas from UEMG - Fundação Educacio-
nal de Patos de Minas (1999), master’s in Administration from Universidade Federal de Uberlândia (2008)
and doctorate in Production Engineering from Universidade Federal de São Carlos (2011). He is currently full
professor at Universidade Federal de Uberlândia.

Engineering Design Methodology for Green-Field
Supply Chain Architectures
Taxonomic Scheme
Petar Radanliev
Anglia Ruskin University, Lord Ashcroft International Business School
petar.radanliev@anglia.ac.uk
ABSTRACT: Supply chain engineering requires a design that possesses the flexibility of a complex
adaptive system, consisting of interlinking architecture, with external dimensions and system germane
internal elements. The aim of this paper is to critically analyse the key supply chain concepts and ap-
proaches, to assess the fit between the research literature and the practical issues of supply chain archi-
tecture, design and engineering. The objective is to develop a methodology for strategy engineering,
which could be used by practitioners when integrating supply chain architecture and design. Taxo-
nomic scheme is applied to consider criteria for strategy architecture, hierarchical strategy integration
design, strategy engineering, and integration of supply chain as a conceptual system. The results from
this paper derived with the findings that the relationship between supply chain architecture, design
and engineering is weak, and challenges remain in the process of adapting and aligning operations.
This paper derived with a novel approach for addressing these obstacles, through a conceptual frame-
work diagram and a new methodology, based on the taxonomic scheme. The novelty that derives from
this paper is an engineering design methodology for integrating supply chain architecture and design,
with criteria that enable decomposing and building a green-field (new and non-existent) supply chain
as a system. The taxonomic scheme revealed a number of tools and mechanism, which enabled the
development of a new methodology for engineering integrated architecture and design. The review
derived with improvements to current and existing theories for analysing interdependencies within
and between their individual contexts. This issue is addressed with a hierarchical method for network
design, applied for building and combining the integration criteria. The resulting methodology is field
tested through a case study with the slate mining industry in North Wales.
Keywords: Supply chain architecture, supply chain design, green-field supply chain conceptual engineering.
52

Radanliev, P.: Engineering Design Methodology for Green-Field Supply Chain Architectures - Taxonomic Scheme
1. INTRODUCTION
The progress of integrating supply chain principles
is weak, specifically towards ‘adapting’ (Saad et
al., 2002) and ‘aligning’ (Sakka et al., 2011). Supply
chain decisions are commonly based on individual
company profitability goals (Leng and Chen, 2012),
undermining that supply chain is a single entity sys-
tem (Mintzberg et al., 1998, Schnetzler et al., 2007,
Narasimhan et al., 2008, Ivanov, 2009, Perez-Franco
et al., 2010). In addition, the supply chain strategy in
practice is frequently not related to the competitive
strategy (Mckone et al. 2009). This findings create
the rationale for further investigation on how supply
chain strategies are engineered, and the overarching
architectures that enable integration of operations.
Supply chain engineering has been defined as a com-
plex adaptive system (Bozarth et al., 2009, Pathak et
al., 2007), consisting of interlinking architecture and
design, with external dimensions and system ger-
mane internal elements (Melnyk et al., 2013). Supply
chain strategic engineering represents an effective
method for implementing strategic integration (He
and Lai, 2012). However, further research is required
to include the relationship of change in culture and
structure to integration (Nikulin, et al. 2013).
Supply chain strategy engineering as a green-field
concept of non-existent until formulated supply chain,
should embrace collaborative commerce and synchro-
nisation of information flow (Frohlich and Westbrook,
2001, Vickery et al., 2003, Al-Mudimigh et al., 2004,
Manthou et al., 2004, Kim, 2006).
The area of research for this paper is the field of
supply chain engineering that include the external
architecture and internal design, in a green-field
engineering (new and non-existent supply chain).
To evaluate the present approaches in supply chain
practice, the paper begins with a review of existing
supply chain models, which cover the relevant as-
pects of green-field supply chain integration. The
research areas reviewed are: supply chain engineer-
ing, supply chain architecture, supply chain design,
and supply chain integration.
There is a vast number of developed or proposed
supply chain models focused on one or more supply
chain areas. The objective of this paper is to group
the factors in recognisable taxonomic scheme, and
to derive with a new set of principles for green-field
supply chain strategy engineering of the supply
chain architecture and design.
1.1 Research Objectives
The research problems investigated are related to
engineering the integration of supply chain architec-
ture and design. The research objectives are:
1. To derive with a set of principles for a green-field
supply chain architecture with multiple supply
chain participants.
2. To derive with set of principles for green-field
supply chain integration design.
3. To systematically integrate the supply chain en-
gineering principles, based on the architecture
and design criteria, for individual activities to-
wards pre-defined green-field integration areas.
To relate the criteria to the methodology, the taxo-
nomic scheme is presented in a hierarchical concept
map and concept diagram methods are applied. The
objectives of the paper are oriented around external
and salient dimensions, which directly affect the
supply chain architecture, and design, and the sup-
ply chain engineering consist of external and inter-
nal elements, forces and factors.
1.2 Structure of the paper
This paper is structured in the following order: first-
ly the research aim and objectives are defined, along
with the rationale for the study; secondly, the lit-
erature review outlines the most prominent models
and methods in this field; thirdly: the reasoning be-
hind key tenants of the methodology are discussed
in detail, with specific observations from existing
literature on this topic; fourthly, the methodology
that derived from this study is presented, followed
by the principles key, containing the key tenets and
abbreviations. The fourth step also relates the key
tenets to existing literature and elaborates on the
benefits from the methodology to practitioners and
academics; and finally, the emerging principles are
analysed to clarify how the key tenets are applied
to the new methodology for engineering green-field
supply chain architecture and design. To clarify how
the methodology can be interpreted and applied, the
methodology is field-tested through case study on
the Slate Mining Industry in North Wales.
2. LITERATURE REVIEW
The literature review reveals the most prominent lit-
erature and outlines the tools and mechanisms that

enabled this paper to derive with the principles for
engineering green-field supply chain integration.
The objective of the literature review is to analyse
the key tenets that enable the architecture for in-
ter-relating the design of supply chain operations.
Recent literature addressed the aspect of reformulat-
ing existing supply chains when problems emerge
(Nikulin, et al. 2013, Melnyk et al., 2013, Perez-Franco
2010). However, those studies ignored the vast list of
measurements in existing literature (Van der Vaart
and van Donk, 2008) and the diverse external dimen-
sions and the elements, factors and forces that are
present in different environments (Radanliev, 2015a).
Nikulin, et al. (2013), Melnyk et al., (2013), and
Perez-Franco (2010) addressed the aspect of re-engi-
neering, while Van der Vaart and van Donk, (2008)
defined the re-engineering strategic patterns. Nev-
ertheless, the topic of formulating a supply chain
strategy as a green-field concept, remains elusive
and most of the closely related frameworks (Radan-
liev, 2015b, Schnetzler et al., 2007, Hafeez, et al. 1996,
and Pettigrew, 1977) have never advanced into full
working methodologies, defining the engineering in
a step by step supply chain engineering design.
There is much confusion in existing supply chain
literature on terminologies defining re-engineering
and engineering (Radanliev, 2015c). Terms such as
supply chain engineering, design or architecture
are commonly used in supply chain re-engineering
studies, effectively referring to re-designing. The
research in this paper distances from the aspect of
re-engineering and is focused on the engineering of
non-existent supply chains in a green-field context.
Therefore, the term green-field is a clarification con-
cept referring to non-existent supply chains, in other
words, the field is green, and there is nothing there.
3. RESEARCH METHODOLOGY
The research methodology applied in this paper
was taxonomy of approaches from literature re-
view. The selected papers have been related to sup-
ply chain strategy, distancing from supply chain
management. Recent literature clearly separated
between the topics of supply chain management
and supply chain strategy (Perez-Franco et al., 2010,
Schnetzler et al., 2007, Martínez-Olvera and Shunk,
2006). Supply chain management has been defined
as the process of transforming materials into a fin-
ished product, presenting a long term objective
where validation should expand over a long period
of time (Saad et al., 2002, Mentzer et al., 2001). The
supply chain strategy was considered as an inves-
tigation into how the supply chain should operate
efficiently to compete, by evaluating costs, benefits
and trade-offs in the supply chain operational com-
ponents (Perez-Franco et al., 2010, Schnetzler et al.,
2007, Martínez-Olvera and Shunk, 2006).
In exception of a few cases, the papers have been
selected with a research time horizon over the last
10 years (2005-2015), covering literature published
on the topic of supply chain strategy engineering. A
limited number of most prominent papers from ear-
lier literature have also been reviewed, because of
their specific contribution to the topic of green-field
supply chain strategy engineering.
By distancing from the area of supply chain manage-
ment, the number of relevant papers was reduced
dramatically. This focused the review of literature
specific to the engineering aspect of a supply chain
strategy, and building a methodology for green-field
supply chain strategy engineering.
Over seventy papers have been reviewed, covering
empirical techniques (case/field study, survey, ar-
chival research, action research, conceptual models)
or modelling techniques (optimisation, simulation,
algorithms, systems). What united all the papers
reviewed is their singular focus on supply chain
strategy, was identified as a topic far less covered in
existing literature than supply chain management.
Multiple methods have been used to search for ap-
propriate literature, to provide transparency, and to
reduce risk of missing out on important literature.
The databases used include the Web of Science and
the Business Source Complete. In addition, Google
Scholar was used to ensure the literature selected
provides a wide coverage of the topic. The initial re-
sults produced more results than a single study can
handle. The process of selecting the most pertinent
literature involved applying selection criteria. The
selection criteria are based on deriving with key-
words and scanning first the titles for those word.
Secondly, the selected literature was further reduced
by scanning the abstract to ensure direct relevance to
the topic.
The complexity of the subject, the multiple environ-
ments, dimensions, elements and concepts, required
a research that does not set any limits to categorising
the conceptual, analytical or empirical nature of the
existing approaches. Many of the approaches identi-

fied in literature are focused on resolving singular
supply chain problems, and are not relating to other
aspects of supply chain engineering. This presented
the rational for applying a taxonomic scheme to in-
vestigate, interrelate and group the attitudes, prac-
tices and patterns, present in existing literature on
the topics of supply chain: engineering, integration,
architecture and design. The taxonomic scheme en-
abled categorising concepts into different clusters.
The categorisation enabled the process of recognis-
ing, differentiating and understanding different atti-
tudes, practices and patterns for engineering supply
chain strategy, and interrelating them in accordance
to positive relationships between different concepts.
But in general, many of the studies have hardly built
on previous work. The taxonomic scheme enabled
combing and pairing factors and elements from dif-
ferent papers, because they were based on the same
aspect of research, and discussed the same con-
structs and items in terms of supply chain strategy
engineering. As a result of the taxonomic scheme,
the analysis derived with the most prominent atti-
tudes, patterns, and practices for supply chain engi-
neering, and the interactions, or interrelationships
between these factors.
The synthesised knowledge is then applied for
building a methodology integrating the approaches
in existing literature on supply chain strategy engi-
neering.
The papers have been analysed around a taxonomy
of characteristics, to map and evaluate green-field
supply chain strategy engineering. The different
approaches have been categorised in hierarchical
methodology.
The case study method was applied to field-test the
resulting methodology on formulating a green-field
supply chain strategy for the Slate Mining Industry
in North Wales.
4. TAXONOMIC SCHEME
4.1 Green-field strategic integration
The process of merging distinct green-field opera-
tional areas into the supply chain area, creates an
urgency to integrate the information and physical
flow into relationships that link these areas and fos-
ters ‘trust and commitment’ (TC) with supply chain
partners (Bozarth et al., 2009). Pathak et al. (2007)
designed a set of principles based on TC, however,
the principles would benefit from being tested with
case study, in a similar way that other frameworks
are field-tested (Perez-Franco et al., 2010, Narasim-
han et al., 2008, Martínez-Olvera, 2008, Martínez-
Olvera and Shunk, 2006). In addition, these frame-
works would benefit from criteria to evaluate and
measure performance of integrating supply chain
participants into a ‘networked organisation’ (NO)
(Sukati et al., 2012). Where performance depends on
‘identification of best candidates’ (IBC) (Lee and Bil-
lington, 1992), and requires measurement system for
‘interdependence and organisational compatibility’
(IOC) in supply chain design (Beamon, 1998).
4.2 Characterising green-field integration
‘Supply chain strategy integration’ (SCI) is described
as a ‘single entity system’ or a ‘confederation’ (Men-
tzer, 2001) and a ‘networked organisation’ (Ivanov,
2009). The ‘single entity system’ should be focused
on ‘capturing the essence and forecasting the effect’
of supply chain integration and performance (CEFE)
(Mentzer, 2001), through combining resources and
capabilities (Narasimhan et al., 2008). In addition, to
‘characterise greenfield supply chain strategy and
integration’ (CGSI) the functional activities should
be investigated to identify actual instead of desired
strategy outcomes (Cigolini et al., 2004).
Strategic integration represents an effective method
for implementing strategic choices and further re-
search is required to include the ‘architecture imple-
mentation’ (FI) in integration (He and Lai, 2012).
To address this, an algorithm has been described
for selecting best supply chain integration strategy
through separation in ‘space, time, parts and con-
ditions’ (STPC) for scenarios when problems occur
(Nikulin et al. 2013). The soundness and the logic be-
hind Nikulin et al. (2013) approach could be applied
as a tool to build upon a framework for supply chain
strategy architecture. Such framework should em-
brace collaborative commerce and synchronisation
of supply chain information flow, promoting flex-
ibility and effectiveness (Frohlich and Westbrook,
2001, Vickery et al., 2003, Al-Mudimigh et al., 2004,
Manthou et al., 2004, Kim, 2006).
4.3 Categorising green-field integration activities
Supply chain competences lead to diverse perfor-
mance advantages in various business environments
(Closs and Mollenkopf, 2004), but the same practices
and patterns cannot be applicable in every industry

context to achieve superior performance (Nikulin et
al., 2013, Van der Vaart and van Donk, 2008, Vickery
et al., 2003). Factors that improve supply chain inte-
gration and performance have been categorised into
attitudes, practices and patterns (Van der Vaart and
van Donk, 2008). The relationship between these
clusters remains elusive and the number of ‘archi-
tecture elements’ (FE) and ‘architecture concepts’
(FCo), should be validated through further research.
Formulating supply chain strategies in the context of
‘green-field architecture’ (GF) with a singular focus
on integration and performance (Frohlich and West-
brook, 2001), presents limitations (Childerhouse and
Towill, 2011, Perez-Franco et al., 2010, Rosenzweig
et al., 2003), because various supply chain aspects
should be considered in the design and architecture
stage, and supply chain integration activities have a
unique set of benefits (Swink et al., 2007).
A holistic framework for supply chain design (Mel-
nyk et al. 2013) concluded that supply chain de-
sign must consider the ‘external dimension’ (ExD).
The study recommended a process for uncovering
the various pieces that orchestrate the overall sup-
ply chain architecture and design, through inves-
tigating the ‘underlying factors’ (UF) and ‘salient
dimensions’(SaD), such as ‘external elements’ (EE),
‘factors’ (EFa), and ‘forces’ (EFo) (Melnyk et al. 2013).
4.4 Green-field supply chain decomposition design
Supply chain design is a dynamic process and in-
terdependencies should be analysed ‘within’ and
‘between’ in individual context (Dubois et al., 2004).
One approach for building and combining the cri-
teria is a hierarchical method for network design
(Dotoli et al., 2005). This approach can be strength-
ened by building upon the principles from ‘Analyti-
cal Target Cascading’ in context of decomposing a
complete supply chain hierarchical tree (Qu et al.,
2010), similarly to ‘decomposing supply chain into
hierarchical tree’ (DSCHT) (Schnetzler et al. 2007).
The DSCHT combined with the techniques from
the customer–product–process–resource (CPPR)
(Martínez-Olvera and Shunk, 2006) and ‘analytical
target cascading’ (ATC), provide the background for
designing a new engineering method that would in-
clude the process of getting from the ‘present to (the)
required’ stage (PR).
The design process could apply a ‘conceptual ap-
proach for supply chain inter-organisational inte-
gration’ (CSCIOI) (Perez-Franco et al., 2010). Alter-
natively, conceptual system can be verified with
system dynamics and mathematical modelling (Iva-
nov, 2009), however, mathematical modelling could
hardly calculate with precision the perceptions of
the individual decision maker perceptions.
Engineering systems literature integrated a system
dynamics principles to decompose supply chain
and tested the approach though dynamic analysis
(Hafeez et al., 1996). The engineering system ap-
proach could be applied as a visualisation tool for
presenting and interlinking multiple supply chain
areas with external business dimensions (Lertpatta-
rapong, 2002), but such approach could hardly com-
prehend the supply chain complexities and multiple
variables in ‘integration as a method for integrating
strategic choices’ (IMSC), leading to the conclusion
that conceptual architectures and supply chain de-
composition design are stronger visualisation tools.
Nevertheless, engineering design techniques such
as the Pugh Controlled Convergence (Pugh, 1990),
the Enhanced Quality Function Deployment (Claus-
ing, 1992), the Design Structure Matrix (Eppinger et
al., 1994) the Engineering System Matrix (Bartolo-
mei et al., 2007), and the ‘techniques tool matrix’
(Cigolini et al., 2004), can be applied in combination
with ‘cascading strategy’ (Narasimhan et al., 2008),
to case study, to build the supply chain strategy en-
gineering architecture and design as a conceptual
system (Perez-Franco et al., 2010). Such an approach
can be combined with supply chain decomposition
(Schnetzler et al., 2007) to address the ‘architecture
criteria’ (FCr) problem.
4.5 Green-field conceptual engineering
‘Conceptual model’ approach (CM) has been applied
for strategy architecture to evaluate decision makers
strategic goals (Perez-Franco et al., 2010, Narasim-
han et al., 2008, Cigolini et al., 2004). Therefore, ‘a
conceptual system for supply chain decomposition’
(CSSCD), could integrate operational level employ-
ees to identify relationship between the vision and
goals and for explaining the relationship between
concepts (Platts et al., 1996, Menda and Dilts, 1997).
4.6 Ontological semantic alignment for green-field design
Alternatively, an ‘ontological approach can be applied
for semantic alignment’ (OASA) where knowledge
elicitation, containing, mapping and merging should
represent the foundations for adapting or aligning

supply chain principles (Sakka et al., 2011). The process
should conceptualise strategy as a system of choices,
patterns or decisions to address the phenomenon of
‘strategy absence’ (SA) in strategy architecture (Ink-
pen and Choudhury, 1995). The process should start
by reaching a consensus on the ‘preliminary salient di-
mensions’ (PSaD) and strategic objectives (Platts et al.,
1996, Menda and Dilts, 1997). The process can be fur-
ther clarified by applying ‘architecture criteria’ (FC),
such as: procedure, process and participation, which
require communication mechanisms to enable con-
cept understanding (Inkpen and Choudhury, 1995).
The concept understanding should apply design ‘in-
tegration criteria’ (EC) through systematic innovation
(Sheu and Lee, 2011), as a method for distilling inno-
vation to strategy. However, strategy absence must
be addressed through the architecture criteria prior
to applying the integration criteria, because system-
atic innovation brings strategy dynamics through the
‘process chain and virtual eChain’ (PC-VC) feedback
mechanisms, whereas strategy absence effectively dis-
ables the feedback mechanisms and reduces the ‘sup-
ply chain agility’ (SCA).
The feedback mechanisms enable the process of: (1) an-
ticipating the demand for a product, market standards
and influencers, product variety and life cycle (Fisher,
1997); (2) investigating the internal and external factors
(Narasimhan et al., 2008); (3) determine the supplier or
customer focus and level of integration (Frohlich and
Westbrook, 2001); and (4) enable building trust and
commitment, or interdependence and organisational
compatibility (Mentzer, 2001). These feedback mecha-
nisms enable building upon the supply chain architec-
ture criteria and until present, the architecture criteria
has not been combined with the ‘integration criteria’
(EC): visibility (Inkpen and Choudhury, 1995, Fish-
er, 1997), acceptance (Saad et al., 2002), participation
(Menda and Dilts, 1997, Zhou and Chen, 2001, Qureshi
et al., 2009), communication (Tracey et al., 1999), for-
mality (Andrews et al., 2009), adaptability (Sakka
et al., 2011, Saad et al., 2002), integration (Bozarth et
al., 2009), effectiveness (Fisher, 1997) flexibility (Kim,
2006) and responsiveness (Fisher, 1997). Building upon
and combining the criteria would represent a novel
contribution from synthesising existing knowledge for
deriving new findings.
4.7 Green-field supply chain engineering in uncertain en-
vironments
Recent literature are the indications that supply
chain engineering and competitive strategy are com-
monly not linked to the ‘corporate strategy’ (CS)
(Mckone et al., 2009). Adding to these concerns are
the findings that challenges still remain in the pro-
cesses for ‘adapting and aligning’ (AA) supply chain
engineering (Saad et al., 2002) and operations (Sakka
et al., 2011). The strategy architecture represents a
process of ‘capabilities integration’ (CE) and accept-
ing the reality and acting upon that reality in a given
business environment (Miller and Friesen, 1978).
The supply chain engineering topic remains incon-
clusive and there are remaining ‘barriers to change
and approaches to overcome’ (BCAO) (Mckone et
al., 2009, Saad et al., 2002, Sakka et al., 2011).
In a similar context, various algorithms have been
applied to several supply chain problems, however,
in some environments the ‘participants aims and ob-
jectives’ (PAO) problem is larger than the test data
and optimal solutions cannot be found in reason-
able time frame (Lee et al., 2010) leading to ‘strategy
absence’ (SA). Metaheuristic algorithms could in the
future provide a solution for identifying optimal
logistic solution for supply chain strategy design
(Griffis et al., 2012). Such a method would be use-
ful for addressing the logistics as a specific problem
in strategy architecture. However, metaheuristics
would hardly anticipate aspects such as the in-
dividual decisions of decision makers in the vast
numbered dimensions in multiple business envi-
ronments. In this context, the conceptual system ap-
proach has been proven effective for ‘supply chain
strategy articulation’ (SCSA) and optimal solution
detection (Perez-Franco et al., 2010).
4.8 Supply chain efficiency of green-field architectures
The process of determining the underlying factors
of salient dimensions in supply chain engineering,
should be focused on preserving core-activities and
outsource non-core activities (Gilley and Rasheed,
2000). For example, in the ‘transport and logistics
strategy’ (TLS) third party logistic partnerships en-
able cost reduction combined with improvement
in service and operational efficiency (Sheffi, 1990),
bringing into focus the ‘transportation and logistics
integration strategic elements’ (TLISE). In this con-
text, further investigation of a potential ‘fit’ between
companies outsourcing intensities and vertical stra-
tegic integration could strengthen existing under-
standing of the ‘outsourcing through abstention’
(OTA) problem (Gilley and Rasheed, 2000). Since
greater collective operational activities need to be
advanced through supply chain alliances, then the

strategic problem of ‘integration as a method for in-
tegrating strategic choices’ (IMSC) grows into one
of a degree (Frohlich and Westbrook, 2001), how-
ever, the right level of ‘fit, intensity and integration’
(FOI) should be identified to optimise performance
(Jayaram and Tan, 2010).
4.9 Engineering the performance of green-field architectures
Existing frameworks such as Kaplan and Norton
(1996), which was expanded by Brewer and Speh
(2000), are applicable to specific supply chain catego-
ries ‘supply chain performance measures and inte-
gration’ (SCPME). These frameworks are not applied
to evaluate strategy architecture that can be defined
as ‘green-field performance measures’ (GPM), where
measuring performance in effect refers to forecasting
performance. The most advanced performance mea-
surement system identified is the SCOR model (SCC,
2001) because the model is applied to industry and
has evolved through feedback from industry. How-
ever, in an uncertain market demand and continuous
new product development, flexibility and feasibility
should also be included in the performance measures
(Perez-Franco et al., 2010).
4.10 Engineering the environmental dimensions for
green-field architectures
Supply chain engineering must anticipate ‘product
and product family’ (PF) in the design process, while
supply chain architecture must be designed in ac-
cordance to the ‘best product operating cost’ (BPOC)
(Liu and Hipel, 2012, Lo and Power, 2010, Lamothe
et al., 2006). The supply chain design must anticipate
‘design for environment’, and ‘design for disassem-
bly’ (DE-DD) (Clendenin, 1997). Supply chain strat-
egy architecture should be focused on: (1) optimising
the company strategy and service elements through
‘postponement strategy and market demand’ (PS-
MD) (Korpela et al., 2001b); (2) the relationship be-
tween buyer and supplier in the ‘strategy dimen-
sions’ (StD) (Van der Vaart and van Donk, 2008, Closs
and Mollenkopf, 2004); (3) the supply chain functions
must be based on the ‘business environment’ (BE); (5)
the supply chain integration strategy must be based
on the ‘market and distribution planning’ (MDP)
strategies (Narasimhan and Kim, 2002).
5. FORMULATING THE METHODOLOGY
The taxonomic scheme applied, is aimed at address-
ing various problems emerging in formulating a
green-field supply chain strategy. These are critically
appraised above, with specific observations against
each approach, to identify limitations and areas ap-
plicable to designing a methodology for green-field
supply chain strategy engineering. The taxonomy of
literature resulted in identifying, categorising and
cataloguing the main themes (Table 1) necessary for
generating a new methodology.
The methodology is transcribed into a concept dia-
gram (Figure 1), before the findings from the tax-
onomy of literature are summarised into building
blocks, and drawn into diagram of problems relat-
ed to practical aspects of supply chain engineering
(Figure 2). The concept diagram and the building
blocks are related to the identified gaps in existing
literature.
The process of categorising, cataloguing and relat-
ing the key tenets from existing literature enabled
the development of a new methodology (Figure
2 and Figure 3). The approach is compliant with
Eisenhardt (1989), Glaser and Strauss (1967) and Yin
(2009) guidance on theory building. The method-
ology contains different aspects, which interrelate
to define and interpret the process of engineering a
green-field supply chain integration strategy. Differ-
ent aspects of the taxonomy are interrelated to de-
fine the methodology. Interrelated aspects are inter-
preted in the following building blocks.
In the supply chain engineering methodology, the
architecture of a green-field project integration strat-
egy is interpreted as: articulation of the external
dimensions, elements, forces and factors out of the
control of the business and supply chain strategy.
The critical analysis of the factors and problems de-
rived with emerging categories of external dimen-
sions, elements, forces and factors.
The methodology interrelates the architecture,
through evaluating salient dimensions in relation
to the external elements, forces and factors. In the
process of interrelating these aspects, different prob-
lems emerge from the salient dimensions in relation
to the external elements, forces and factors. The tax-
onomy of approaches determined the importance
of dimensions, elements, forces and factors in rela-
tion to key tenets for green-field strategy integration
(Table 1).
The priority of the supply chain engineering meth-
odology is placed on designing a method for system-
atic prioritising of activities towards green-field inte-

gration areas. The design aspect is defined through
applying the key tenets (Table 1), to designing hier-
archical concept map (Figure 1), for identifying and
organising individual operational activities towards
integrated supply chain strategy engineering.
The second aspect of the methodology is the design-
ing of evaluation criteria for the integrated supply
chain strategy. The priority of this aspect of the de-
sign was, to investigate how conflict of interests can
be identified and eliminated. This was addressed
though designing a diagram interrelating the con-
cepts that emerged from the taxonomy of approach-
es (Figure 2). The objective of the diagram was to
enable supply chain participants to visualise indi-
vidual business objectives and gaps in interrelating
the supply chain strategy. The diagram should be
interpreted in individual context of the supply chain
scenario in accordance to the concepts defined in the
taxonomy (Table 1). The design of conceptual dia-
gram related to the specific supply chain scenarios,
enables visualising individual activities and gaps in
integration of supply chain operations, specific to in-
dividual supply chain activities.
Table 1: Taxonomy of key tenets for engineering a green-field supply chain integration strategy
Taxonomic Scheme
StD: Strategy Dimensions
BE: Business environment
ExD: External dimension
SaD: Salient dimension
GF: Greenfield supply chain
Architecture
SA: Strategy absence
CS: Corporate strategy
SCSA: Supply chain strategy
articulation
PAO: Participants aims and
objectives
FE: Architecture Elements
FCr: Architecture criteria
NO: Networked organisation
TC: Trust and commitment
IOC: Interdependence and
organisational compatibility
IBC: Identification of best
candidates
CSCIOI: Conceptual supply
chain inter-organisational
integration
FCo: Architecture Concepts
CE: Capabilities integration
EE: External element
EFa: External factor
EFo: External force
UF: Underlying factor
FI: Architecture
Implementation
AA: Adapting and aligning
OASA: ontological approach for
semantic alignment
DSCHT: Decomposing
supply chain into
hierarchical three
PR: process of getting
from the present to the
required stage
CSSCD: Conceptual
system for supply chain
decomposition
CF: Framework approach
PSaD: Preliminary salient
dimensions
PF: product and product family
BPOC: best product operating
cost
DE-DD: design for environment
and design for disassembly
PS-MD: postponement strategy
and market demand
MDP: market and distribution
planning
TLS: Transport and
logistics strategy
TLISE: transportation and
logistics integration strategic
elements
SCA: supply chain agility
SCPME: Supply chain
performance measures and
integration
GPM: Greenfield supply
chain performance measures
SCI: Supply chain integration
OTA: Outsourcing through
abstention
FOI: fit, intensity and integration
CEFE: Capture the essence
and forecast the effect of
supply chain integration and
performance
CGSI: Characterise Greenfield
supply chain supply chain
strategy and integration
BCAO: Barriers to
change and approaches to
overcome
IMSC: integration as a
method for integrating
strategic choices
STPC: Separation in
space, time, parts and
conditions
PC-VC: Process chain and
virtual eChain
Principles emerging from the Taxonomic Scheme
The process of building methodology (Figure 2) is
relying on a number of key tenets (Table 1) present-
ed as supply chain engineering principles:
»» First principle: in supply chain architecture, to under-
stand the companies’ real strategies the architecture
must be interacting with the design (activities) (Su-
kati et al., 2012, Perez-Franco et al., 2010, Bozarth et al.,
2009,Cigolinietal.,2004,Porter,1996,Andrews,1982).
»» Second principle: to understand how supply
chains are designed, ‘tacit knowledge’ should be
considered as instrumental in distinguishing be-
tween the engineering the strategy and the design
of the activities (Sukati et al., 2012, Perez-Franco
et al., 2010).
»» Third principle: supply chain can be engineered
as a conceptual system, where the architecture is
based on a conceptual design (Melnyk et al. 2013,
Perez-Franco et al., 2010, Bozarth et al., 2009).
»» Fourth principle: the supply chain activities are
sufficient for conceptualising the architecture, de-
sign and engineering (Melnyk et al. 2013, Perez-

Franco et al., 2010, Bozarth et al., 2009, Cigolini
et al., 2004).
»» Fifth principle: supply chain engineering contains
architecture and design, where the engineering is
the central idea of the external architecture and
internal design (Perez-Franco et al., 2010), but the
design is representative of the integrated objec-
tives and the design determines the architecture
(Melnyk et al. 2013, Narasimhan et al., 2008, Men-
tzer, 2001).
»» Sixth principle: the supply chain engineering re-
lies on the integrated design and the design is the
based on the external architecture, but while the
architecture is influenced, it is not determined by
the integrated design (Nikulin et al. 2013, Sukati
et al., 2012, Inkpen and Choudhury, 1995). The
design represent a set of ideas incorporated in the
engineering that; supplement, assist and enable
the architecture (Melnyk et al. 2013, Perez-Franco
et al., 2010, Martínez-Olvera, 2008, Schnetzler et
al., 2007, Martínez-Olvera and Shunk, 2006).
The next step in interpreting and applying the taxo-
nomic scheme (Table 1), was to design a conceptual
framework diagram identifying the gaps in litera-
ture on engineering a green-field integration strat-
egy (Figure 1). The conceptual framework
Defining the conceptual framework diagram
and the methodology
The conceptual framework diagram (Figure 1) rep-
resents the supply chain architecture and integra-
tion design, and is based on supply chain activities
identified in existing literature and presented in a
taxonomic scheme (Table 1). The architecture and
design relates the activities to the predetermined
supply chain integration areas from the taxonomic
scheme (Table 1). These are evaluated with combin-
ing the evaluation criteria from existing literature
(Table 1) and interrelated to the conceptual frame-
work (Figure 2).
Figure 1 represents the architecture and design, and
the gaps that are identified in literature. Those gaps
represent problems that could create negative effects
on green-field supply chain engineering. Thus, they
need to be addressed in a systematic process when
engineering the green-field supply chain strategy.
Figure 2 represents that systematic process for sup-
ply chain engineering, and should be interpreted as
the process for interrelating the attitudes, practices
and patterns present in existing literature. The full
list of attitudes, patters, and practices is outlined in
the taxonomic scheme (Table 1).
An important conclusion based on the taxonomic
scheme (Table 1) is that there is little consensus on
how to engineer green-field supply chain strategy in-
tegration, or on how to measure the effects of supply
chain architecture on integration and performance. In
Figure 1, we take this concern as a starting point to
create a conceptual framework diagram from existing
research studies on the topic of supply chain architec-
ture and design. In the Figure 2, the findings derived
from the taxonomic scheme (Table 1) are applied as a
discussion focused on the interrelationships between
the various supply chain strategic factors, on the rela-
tionship between supply chain architecture and de-
sign, and on the attitudes, practices and patterns that
have an impact on supply chain engineering.
Examining the relationship between supply chain
architecture and design, without concrete set of eval-
uation criteria of the interrelationships between the
different supply chain engineering factors, seems in-
conclusive. Given the complex interactions between
attitudes, patterns and practices, outlined in Table 1,
it seems necessary to take into account these interac-
tions when investigating the process of engineering
supply chain architecture and design.
For example, one would anticipate an interaction be-
tween architecture (e.g. external elements, factors and
forces) and practices (e.g. corporate strategy). Similarly,
we would expect there to be a relationship between cor-
porate strategy and the integrated business strategy.

Figure 1: Conceptual framework for engineering a
green-field supply chain integration
External
Dimensions
Business
Environment
Salient
Dimensions
External
Factors
External
Elements
External
Forces
GAP1
GAP2
GAP3
GAP4
Business
Strategy
Integrated
Business
Strategy
Green-Field Architecture
Integrated
Supply Chain
Strategy
Operational
Activities
GAP5
Corporate
Strategy
Supply Chain
Strategy
GAP6
GAP7
GAP8
GAP9
GAP10
Integration Design
Business Dimension Supply Chain Dimension
GAP11
In line with the finding from the taxonomic scheme
(Table 1), it seems logical, especially from a concep-
tual point of view, to focus on systematically engi-
neering the holistic supply chain, by focusing on the
interrelationship between supply chain architecture
and integration design in individual context. Many
authors instead focus on individual problems in in-
dividual context. It is not sufficient to have a solu-
tion to one problem and to ignore other supply chain
problems. The objective of methodology (Figure 2)
is to systematically address multiple problems in the
same time.
Figure 2: Methodology for engineering a green-
field supply chain integration strategy
ExD
BE
SaD
EFaEE EFo
GAP1:
GF
BCAO
GAP2:STPC
GAP3:PF-BPOC-DE-DD-PS-MD-MDP
GAP4:GPM
BS
IBS
Green-Field Architecture
ISCS
OA
GAP5:
CGSI
CS SCS
GAP6: CEFE-CF
GAP7:
PAO
OTA
GAP8: SCSA
GAP9: TLS-TLISE
GAP10:
SA
IMSC
DSCHT
CSSCD
Integration Design
D1 D2
GAP11:
StD
FCr
NO
TC
IOC
IBC
CSCIOI
PC-VC-FOI-PR-UF-OASA-AA
The methodology (Figure 2) measures the interrela-
tionships within a single relationship and then to re-
late the supply chain engineering of the architecture
and design. The advantage of relating individual in-
terrelationships is that it is relatively easy to acquire
reliable, evaluation criteria for single interrelation-
ship. By doing that, it becomes clearer about what is
exactly being engineered (Figure 2) and interrelated
to the multiple relationships (Table 1).
To ensure validity of these findings, the methodol-
ogy is field tested with a case study of the Mining
Industry. Before field testing the methodology, a set

of six principles are defined. The set of principles en-
able academics and practitioners to interrelate dif-
ferent aspects of the methodology and to help them
in interpreting Table 1, Figure 1 and Figure 2.
Field testing the new methodology with a case
study
The case study was performed on the Slate Mining
Industry in North Wales (Figure 3), to formulate a
green-field supply chain strategy, integrating the
complete supply chain. The case study included a
Slate Mining Quarry, Civil Engineering Compa-
ny, Logistics Company, Rail Terminal Company,
Wholesalers (Virtual Quarries) and Retailers (Gar-
dening and Building Materials Shops). The final
result of the engineering is expressed in Figure 3,
detailing how different aspect are interrelated in
practice and interpreting the practical contributions
from the methodology.
The supply chain engineering in the case study was
performed by applying the methodology and as-
sembling the Pugh controlled convergence (PuCC)
conceptual design (Pugh, 1990), in combination with
the mechanisms for capturing, evaluating and refor-
mulating a supply chain strategy (Perez-Franco et
al. 2010). These methods are applied in combination
with: the supply chain design decomposition pyra-
midal arrangements (Schnetzler et al., 2007) and the
engineering system dynamics for supply chain de-
sign (Hafeez et al., 1996).
Figure 3: Application of the methodology on the Slate Mining Industry in North Wales.
Practical Application of the Methodology for Engineering a Green-Field Supply Chain Architecture
work for Conceptual Engineering of a Green-Field Supply Chain Architecture,
nal of Operations and Supply Chain Management, Volume X Number X pp. X
2) measures the
gle relationship and
n engineering of the
advantage of relating
that it is relatively
aluation criteria for
ing that, it becomes
y being engineered
d to the multiple
hese findings, the
h a case study of the
field testing the
inciples are defined.
ble academics and
ferent aspects of the
in interpreting Table
dology with a case
on the Slate Mining
re 3), to formulate a
egy, integrating the
ase study included a
ngineering Company,
Terminal Company,
ies) and Retailers
aterials Shops). The
The attention of many researchers outlined in this
Practical Application of the Methodology for
Engineering a Green-Field Supply Chain
Architecture
BE
ExD
SaD
CS
SCSA
Architecture
CE
Design
Material Flow
Information Flow
Supplier Manufacturer
Inbound
Logistics
Distribution
Centre
Retailers
Find
Customer
Outbound Logistics
Wholesalers
Reversed Logistics
SA
OASA
AA
DSCHT
CSSCD
PR
CF
Research framework
EFa
EFo
PSaDSrD
PAO
FCr
NO
TC
IOC
IBC
CSCI
OI
GF
FCoFE
BPOC
PF
DE-DD
MDP
PS-MD
TLS
SCA
TLISE
GPM
FOI
OTA
FISCPME
SCI
CGSI
CEFE
BCAO
IMSC
STPC
PC-VC
EE
UF
Figure 3: Application of the methodology on the
Slate Mining Industry in North Wales.

6. DISCUSSION AND IMPLICATIONS
The attention of many researchers outlined in this pa-
per, has often focused on a single area of supply chain
strategy. They have generally neglected research on
the whole performance of the supply chain strategy
engineering, which includes the architecture and
design aspects. Considering these gaps, this paper
established a methodology, which used the concept
of strategic decision making levels and supply chain
integration processes, as the approach to the study
of the holistic supply chain strategy engineering. In
the theory generation stages, the methodology was
designed towards green-field strategy engineering
for integrating multiple participants. The concept of
green-field integration sets this apart from existing
methods, which are designed to re-formulate existing
strategies of individual companies.
The implications of this study are focused on the
strategic operational activities, and on avoiding pre-
scriptive and descriptive approaches, and addressed
the operationalisation aspects of supply chain engi-
neering. While validating the methodology with a
case study, the methodology guided the develop-
ment of integrated strategy, and addressed multiple
supply chain complexities, which represented test-
ing the theory in a real life phenomenon with mul-
tiple variables.
7. CONCLUSION
The paper revealed a new methodology for en-
gineering, architecting, and designing integrated
green-field supply chain. The methodology derived
with the conclusion that green-field supply chain
architecture, design and engineering represents a
dynamic process, and should be analysed in indi-
vidual contexts. The critical summary of literature
reviewed resulted in identifying the main themes in
a summary map (Table 1), necessary for generating
a new methodology (Figure 1). The main themes are
categorised in key tenants (Table 1). The key ten-
ants are catalogued for addressing several problems
present in engineering the architecture and design
of green-field supply chains. These are critically ap-
praised, with specific observations, to identify and
catalogue the key tenants that function as principles
for building the methodology.
The hierarchical method for network design was ap-
plied for building and combining the architecture, de-
sign and engineering criteria. This approach was sup-
ported with principles from DSCHT, and combined
with the techniques from ATC. The new principles
contribute to knowledge with: (1) architecting the
supply chain elements from multiple supply chain
participants; (2) designing the participants’ main
aims and objectives, and (3) engineering the process
of getting from the present to the required stage. The
supply chain principles are also aimed at anticipating
operational capabilities through internal competen-
cies and by considering inter-organisational integra-
tion in combination with operations re-engineering.
The concept verification applied architecture and in-
tegration criteria as a method for strategy engineer-
ing. The new methodology enables building upon
the supply chain engineering criteria that until pres-
ent, has not been built upon and combined with the
process engineering design criteria: visibility, accep-
tance, participation, communication, adaptability,
integration, effectiveness, flexibility, and respon-
siveness. Combining the criteria represents a holis-
tic approach for supply chain architecture and result
in deriving new understandings of green-field sup-
ply chain engineering that can be applied by supply
chain practitioners.
7.1 Limitations and future research
The methodology contributes to and enriches the
existing literature and provides background for fur-
ther academic research in this subject. However, this
methodology was verified with a single case study
on the mining industry, and while it is anticipated
that the proposed methodology is suitable for oth-
er sectors, the findings would need to be delimited
through further testing and research.
Further research is required into the topic of address-
ing strategy absence. In scenarios of high strategy ab-
sence the engineering and evaluation criteria of this
methodology would be difficult to implement. In
that respect, the main challenge for future research is
in extracting supply chain strategy tacit knowledge
and converting it into explicit. There is a strong pref-
erence in practice towards desired over feasible ob-
jectives. This issue becomes one of a degree in an in-
tegration, because of avoidance of criticism, conflict,
disagreement, and controversy. Future research stud-
ies should be aware that these challenges.
8. References
Abdur Razzaque, M., and Chen Sheng, C. (1998). Outsourcing of
logistics functions: a literature survey. International Journal of
Physical Distribution and Logistics Management, 28(2), pp.89–107.

Al-Mudimigh, A. S., Zairi, M., and Ahmed, A. M. M. (2004). Ex-
tending the concept of supply chain: The effective management of
value chains. International Journal of Production Economics,
87(3), pp.309–320.
Andrews, K. R. 1982. The Concept of Corporate Strategy. In C.R.
Christensen, K. R. Andrews, J. L. Bower, R. G. Hamermesh
And M. E. Porter (Eds.), Business Policy: Text And Cases, Ir-
win, Homewood, Il.
Andrews, R. B., George A. Law, J. W., Richard, M., (2009). Strat-
egy Formulation, Strategy Content and Performance: An
Empirical Analysis. Public Management Review, 11, pp.1-22.
Beamon, B.M., 1998. Supply Chain Design and Analysis: Models
and Methods. International Journal of Production Econom-
ics, 55(3), pp. 281–294
Bogataj, M., and Bogataj, L. (2001). Supply chain coordination
in spatial games. International Journal of Production Economics,
71(1-3), pp.277–285.
Bozarth, C.C., Warsinga, D.P., Flynnb, B.B., Flynn, E.J., 2009. The
impact of supply chain complexity on manufacturing plant per-
formance. Journal of Operations Management, 27(1), pp.78–93.
Brewer, P. C., and Speh, T. W. (2000). Using the balanced score-
card to measure supply chain performance. Journal of Busi-
ness Logistics, 21(1), 75–94.
Childerhouse, P., and Towill, D. R. (2011). Arcs of supply chain
integration. International Journal of Production Research, 49(24),
pp.7441–7468.
Cigolini, R., Cozzi, M., and Perona, M. (2004). A new framework
for supply chain management. International Journal of Opera-
tions and Production Management, 24(1), pp.7–41.
Clausing, D. (1992). Enhanced quality function deployment
(EQFD). [Cambridge, Mass.] : Massachusetts Institute of Tech-
nology, MIT Center for Advanced Engineering Study, MIT Press.
Clendenin, J. A. (1997). Closing the Supply Chain Loop: Reengi-
neering the Returns Channel Process. The International Jour-
nal of Logistics Management, 8(1), pp. 75–86.
Closs, D. J., and Mollenkopf, D. A. (2004). A global supply chain
framework. Industrial Marketing Management, 33(1), pp.37–44.
Dotoli, M. Fanti, M. P., Melonia., and Zhoub, M.C., 2007. A
multi-level approach for network design of integrated sup-
ply chains. Interna-tional Journal of Production Research. 43
(20), pp 4267-4287
Dubois, A., Hulthén, K., and Pedersen, A.C. (2004). Supply
chains and interdependence: a theoretical analysis. Journal of
Purchasing and Supply Management, 10(1), pp.3–9.
Eisenhardt, K. M. (1989). Building Theories From Case Study Re-
search. Academy Of Management Review, 14(4), pp. 532-550.
Eppinger, S. D., Whitney, D. E., Smith, R. P., and Gebala, D. A.
(1994). A model-based method for organizing tasks in product
development. Research in Engineering Design, 6(1), pp.1–13.
Frohlich, M. and Westbrook, R., 2001. Arcs of Integration: An In-
ternational Study of Supply Chain Strategies. Journal of Opera-
tions Management. 19 (2001), pp. 185–200.
Gilley, K. M., and Rasheed, A. (2000). Making More by Doing
Less: An Analysis of Outsourcing and its Effects on Firm Per-
formance. Journal of Management, 26(4), pp.763–790.
Glaser, B. S., and Stauss, A.L. (1967). The Discovery of Grounded
Theory, London, Weidenfeld & Nicolson.
Griffis, S. E., Bell, J. E., and Closs, D. J. (2012). Metaheuristics in
Logistics and Supply Chain Management. Journal of Business
Logistics, 33(2), pp.90–106.
Hafeez, K., Griffiths, M., Griffiths, J., and Naim, M. M. (1996).
Systems design of a two-echelon steel industry supply
chain. International Journal of Production Economics, 45(1-3),
pp.121–130.
He, Y., and Lai, K. K. (2012). Supply chain integration and service
oriented transformation: Evidence from Chinese equipment
manufacturers. International Journal of Production Economics,
135(2), pp.791–799.
Hipel, K. W. (2012). A Hierarchical Decision Model to Select
Quality Control Strategies for a Complex Product. IEEE
Transactions on Systems, Man, and Cybernetics - Part A: Systems
and Humans, 42(4), pp.814–826.
Inkpen, A., and Choudhury, N. (1995). The seeking of strategy
where it is not: Towards a theory of strategy absence. Strate-
gic Management Journal, 16(4), pp.313–323.
Ivanov, D. (2010). An adaptive framework for aligning (re)plan-
ning decisions on supply chain strategy, design, tactics, and
operations. International Journal of Production Research, 48(13),
pp.3999–4017.
Jayaram, J. and Tan, K.C., 2010. Supply Chain Integration with
Third-Party Logistics Providers. International Journal of Pro-
duction Economics, 125 (2), pp. 262–271.
Kaplan, R. and Norton, D., 1996. Using the balanced scorecard as
a strategic management system. Harvard Business Review,
74 (1), pp. 75-85
Kim, D. (2006). Process chain: A new paradigm of collaborative
commerce and synchronized supply chain. Business Hori-
zons, 49(5), pp.359–367.
Korpela, J., Lehmusvaara, A., and Tuominen, M. (2001). An ana-
lytic approach to supply chain development. International
Journal of Production Economics, 71(1-3), pp.145–155.
Korpela, J., Lehmusvaara, A., Tuominen, M., Lamothe, J., Hadj-
Hamou, K., Aldanondo, M., Siferd, S. P. (2001). Customer
service based design of the supply chain. International Journal
of Production Economics, 69(2), pp.193–204.
Lamothe, J., Hadj-Hamou, K., and Aldanondo, M. (2006). An op-
timization model for selecting a product family and design-
ing its supply chain. European Journal of Operational Research,
169(3), pp.1030–1047.
Lee, H. and Billington, C., (1992). Managing supply chain inven-
tory: pitfalls and opportunities. Sloan management review,
33(3), pp.64–73.
Lertpattarapong, C. (2002). Applying System Dynamics Ap-
proach to the supply chain management problem, MSc The-
sis, Massachusetts Institute of Technology, MIT Press.

Lee, H., Padmanabhan, V. and Whang, S., (1997). The bullwhip
effect in supply chains1. Sloan management review, 38(3),
pp.93–102.
Lo, S. M., and Power, D. (2010). An empirical investigation of
the relationship between product nature and supply chain
strategy. Supply Chain Management: An International Journal,
15(2), pp.139–153.
Manthou, V., Vlachopoulou, M., and Folinas, D. (2004). Virtual
e-Chain (VeC) model for supply chain collaboration. Interna-
tional Journal of Production Economics, 87(3), pp. 241–250.
Martínez-Olvera, C. (2008). Methodology for realignment of sup-
ply-chain structural elements. International Journal of Produc-
tion Economics, 114(2), pp.714–722.
Martínez-Olvera, C., and Shunk, D. (2006). Comprehensive
framework for the development of a supply chain strategy.
International Journal of Production Research, 44(21), pp.4511–
4528.
Mckone-Sweet, K., and Lee, Y.T. (2009). Development and Anal-
ysis of a Supply Chain Strategy Taxonomy. Journal of Supply
Chain Management, 45(3), pp.3–24.
Melnyk, S. A., Narasimhan, R., and DeCampos, H. A. (2013).
Supply chain design: issues, challenges, frameworks and
solutions. International Journal of Production Research, 52(7),
pp.1887–1896.
Menda, R. and Dilts, D., (1997). The manufacturing strategy for-
mulation process: linking multifunctional viewpoints. Jour-
nal of Operations Management, 15(4), pp.223–241.
Mentzer, J.T., DeWitt, W., Keebler, J.S., Min. S., Nix, N.W., Smith,
C.D., Zacharia, Z.G. (2001). Defining Supply Chain Manage-
ment. Journal of Business Logistics, 22(2), pp.1–25.
Miller, D. and Friesen, P.H., 1978. Archetypes of Strategy Formu-
lation. Management Science, 24(9), pp.921–933.
Narasimhan, R., Kim, S.-W. and Tan, K.-C., 2008. An Empirical
Investi-gation of Supply Chain Strategy Typologies and Re-
lationships to Performance. International Journal of Production
Research, 46(18), pp.5231 – 5259.
Nikulin, C., Graziosi, S., Cascini, G., Araneda, A., and Minutolo,
M. (2013). An Algorithm for Supply Chain Integration based
on OTSM-TRIZ. Procedia - Social and Behavioral Sciences, 75,
pp.383–396.
Pathak, S. D., Day, J. M., Nair, A., Sawaya, W. J., and Kristal, M.
M. (2007). Complexity and adaptivity in supply networks:
building supply network theory using a complex adaptive
systems perspective. Decision Sciences, 38(4), pp.547–580.
Perez – Franco, R. J, Sheffi, Y. Silbey, S., Frey, D., Singh, M., Leve-
son, N. 2010. A methodology to capture, evaluate and refor-
mulate a firm’s supply chain strategy as a conceptual system.
PhD Thesis, MIT Press
Platts, K., Mills, J. and Neely, A., (1996). Evaluating manufacturing
strategy formulation processess. International Journal of Pro-
duction Economics: Proceedings of the 8th International Work-
ing Seminar on Production Economics, 46-47, pp. 233–240
Porter, M. (1996). What is Strategy? Harvard Business Review, 61-78.
Pugh, S. (1990). Total Design: Integrated Methods for Successful
Product Engineering, Addison-Wesley Wokingham, UK.
Radanliev, P., (2015a) ‘Green-field Architecture for Sustainable
Supply Chain Strategy Formulation’, International Journal of
Supply Chain Management, 4(2), pp.62-67.
Radanliev, P., (2015b) ‘Supply Chain Systems Architecture and
Engineering Design: Green-field Supply Chain Integration’
Operations and Supply Chain Management: An International
Journal, 9(1), pp. 22-30.
Radanliev, P., (2015c) ‘Architectures for Green-Field Supply
Chain Integration: Supply Chain Integration Design’, Journal
of Supply Chain and Operations Management, 13(2), pp.56-78.
Qu, T., Huang, G. Q., Cung, V.-D., and Mangione, F. (2010). Opti-
mal configuration of assembly supply chains using analytical
target cascading. International Journal of Production Research,
48(23), pp.6883–6907.
Qureshi, M. N., Kumar, P., and Kumar, D., 2009. Selection of
Transportation Company: An Analytic Network Process Ap-
proach. Icfai Journal of Supply Chain Management, 6(2), pp.26-38.
Rao, P., and Holt, D. (2005). Do green supply chains lead to com-
petitiveness and economic performance? International Journal
of Operations and Production Management, 25(9), pp.898–916.
Rosenzweig, E. D., Roth, A. V, and Dean, J. W. (2003). The in-
fluence of an integration strategy on competitive capabilities
and business performance: An exploratory study of consum-
er products manufacturers. Journal of Operations Management,
21(4), pp.437–456.
Saad, M., Jones, M., and James, P. (2002). A review of the prog-
ress towards the adoption of supply chain management
(SCM) relationships in construction. European Journal of Pur-
chasing and Supply Management, 8(3), pp.173–183.
Sakka, O., Millet, P.-A., and Botta-Genoulaz, V. (2011). An on-
tological approach for strategic alignment: a supply chain
operations reference case study. International Journal of Com-
puter Integrated Manufacturing, 24(11), pp.1022–1037.
Scc. (2001). Supply-Chain Operations Reference-Model. Pitts-
burgh: Supply Chain Council, Inc., Retrieved From The
World Wide Web: Http://Www.Supply-Chain.Org.
Schnetzler, M. J., Sennheiser, A., and Schönsleben, P. (2007). A
decomposition-based approach for the development of a
supply chain strategy. International Journal of Production Eco-
nomics, 105(1), pp. 21–42.
Shah, J., and Singh, N. (2001). Benchmarking Internal Supply
Chain Performance: Development of a Framework. The Jour-
nal of Supply Chain Management, 37(1), pp.37–47.
Sheffi, Y., (1990). Third party logistics: present and future pros-
pects. Journal of Business Logistics, 11(2), pp.27–39.
Sheu, D. D., and Lee, H.-K. (2011). A proposed process for sys-
tematic innovation. International Journal of Production Re-
search, 49(3), pp.847–868.
Soni, G., and Kodali, R. (2010). Internal benchmarking for assess-
ment of supply chain performance. Benchmarking: An Interna-
tional Journal, 17(1), pp.44–76.

Sukati, I., Hamid, A. B., Baharun, R., and Yusoff, R. M. (2012).
The Study of Supply Chain Management Strategy and Prac-
tices on Supply Chain Performance. Procedia - Social and Be-
havioral Sciences, 40, pp.225–233.
Swink, M., Narasimhan, R., and Wang, C. (2007). Managing
beyond the factory walls: Effects of four types of strategic
integration on manufacturing plant performance. Journal of
Operations Management, 25(1), pp.148–164.
Tracey, M., Vonderembse, M. A., and Lim, J.S. (1999). Manufac-
turing technology and strategy formulation: keys to enhanc-
ing competitiveness and improving performance. Journal of
Operations Management, 17(4), pp.411–428.
Van der Vaart, T., and van Donk, D. P. (2008). A critical review of
survey-based research in supply chain integration. Interna-
tional Journal of Production Economics, 111(1), pp.42–55.
Van Donk, D. P., and van der Vaart, T. (2005). A case of shared
resources, uncertainty and supply chain integration in the
process industry. International Journal of Production Econom-
ics, 96(1), pp.97–108.
Vickery, S. K., Jayaram, J., Droge, C., and Calantone, R. (2003).
The effects of an integrative supply chain strategy on cus-
tomer service and financial performance: an analysis of di-
rect versus indirect relationships. Journal of Operations Man-
agement, 21(5), pp.523–539.
Yin, R. K. 2009. Case study research: Design and methods, Sage
Publications, Inc.
Zhou, S., and Chen, R. (2001). A decision model for selecting par-
ticipants in supply chain. Journal of Shanghai University (Eng-
lish Edition), 5(4), pp.341–344.
Zsidisin, G. A., and Siferd, S. P. (2001). Environmental purchas-
ing: a framework for theory development. European Journal of
Purchasing and Supply Management, 7(1), pp.61–73.
Petar Radanliev is a Postdoctoral Research Fellow at Anglia Ruskin University in Cambridge. Dr Radanliev
holds a Ph.D. in Technology from the University of South Wales, MSc (Econ) and BA (Hons) from University
of Wales, Aberystwyth.

A Stochastic Two-Echelon Supply Chain Model for the
Petrol Station Replenishment Problem
Kizito Paul Mubiru
Kyambogo University
kizito.mubiru@yahoo.com
ABSTRACT: In this paper, a new mathematical model is developed to optimize replenishment poli-
cies and inventory costs of a two-echelon supply chain system of kerosene product under demand
uncertainty. The system consists of a fuel depot at the upper echelon and four petrol stations at the
lower echelon. The petrol stations face stochastic stationary demand where inventory replenishment
periods are uniformly fixed over the echelons. Adopting a Markov decision process approach, the
states of a Markov chain represent possible states of demand for the inventory item. The replenish-
ment cost, holding cost and shortage costs are combined with demand and inventory positions in order
to generate the inventory cost matrix over the echelons. The matrix represents the long run measure
of performance for the decision problem. The objective is to determine in each echelon of the planning
horizon an optimal replenishment policy so that the long run inventory costs are minimized for a given
state of demand. Using weekly equal intervals, the decisions of when to replenish additional units are
made using dynamic programming over a finite period planning horizon. A numerical example dem-
onstrates the existence of an optimal state-dependent replenishment policy and inventory costs over
the echelons.
Keywords: Petrol station, supply chain, replenishment, stochastic, two-echelon
67

Mubiru, K. P.: A Stochastic Two-Echelon Supply Chain Model for the Petrol Station Replenishment Problem
1. INTRODUCTION
The goal of a supply chain network is to procure raw
materials, transform them into intermediate goods
and then final products. Finally, delivery of prod-
ucts to customers is required through a distribution
system that includes an echelon inventory system.
The system spans procurement, manufacturing and
distribution with inventory management as one key
element. To cope with current turbulent market
demands, there is still need to adopt coordinated
inventory control across supply chain facilities by
establishing optimal replenishment policies in a
stochastic demand environment. In practice, large
industries continually strive to optimize replenish-
ment policies of products in multi-echelon inventory
systems. This is a considerable challenge when the
demand for manufactured items follows a stochastic
trend. One major challenge is usually encountered:
determining the most desirable period during which
to replenish additional units of the item in question
given a periodic review production-inventory sys-
tem when demand is uncertain.
In this paper, a two-echelon inventory system is
considered whose goal is to optimize replenishment
policies and the inventory costs associated with
kerosene product. At the beginning of each period,
a major decision has to be made, namely whether to
replenish additional units of fuel or not to replenish
and keep fuel at prevailing inventory position in or-
der to sustain demand at a given echelon. The paper
is organized as follows. After reviewing the relevant
literature §2, a mathematical model is described in
§3 where consideration is given to the process of es-
timating the model parameters. The model is solved
in §4 and applied to a special case study in §5.Some
final remarks lastly follow in §6.
2. LITERATURE REVIEWS
Rodney and Roman (2004) examined the optimal
policies study in the context of a capacitated two-
echelon inventory system. This model includes
installations with production capacity limits, and
demonstrates that a modified base stock policy is
optimal in a two-stage system when there is a small-
er capacity at the downstream facility. This is shown
by decomposing the dynamic programming value
function into value functions dependent upon indi-
vidual echelon stock variables. The optimal struc-
ture holds for both stationary and non stationary
customer demand.
Axsater S (2005) formulated a simple decision rule
for decentralized two-echelon inventory control. A
two-echelon distribution inventory system with a
central warehouse and a number of retailers is con-
sidered. The retailers face stochastic demand and
the system is controlled by continuous review in-
stallation stock policies with given batch quantities.
A back order cost is provided to the warehouse and
the warehouse chooses the reorder point so that the
sum of the expected holding and backorder costs
are minimized. Given the resulting warehouse pol-
icy, the retailers similarly optimize their costs with
respect to the reorder points. The study provides a
simple technique for determining the backorder cost
to be used by the warehouse.
Cornillier F,Boctor F,Laporte G and Renand J(2008)
developed an exact algorithm for the petrol station
replenishment problem. The algorithm decomposes
the problem into a truck loading and routing prob-
lem. The authors determine quantities to deliver
within a given interval of allocating products to
tank truck compartments and of designing deliv-
ery routes to stations. In related work by Cornillier
F,Boctor F,Laporte G and Renand J(2009) , a heuris-
tic for the multi-period petrol station replenishment
problem was developed. In this article, the objective
is to maximize the total profit equal to the revenue
minus the sum of routing costs and of regular and
overtime costs. Procedures are provided for the
route construction, truck loading and route packing
enabling anticipation or the postponement of deliv-
eries. The solution procedure to the problem was
extended by Cornillier F,Boctor F,Laporte G and
and Renand J(2009). The authors analyzed the petrol
station replenishment problem with time windows.
In this article, the aim is to optimize the delivery of
several petroleum products to a set of petrol stations
using limited heterogeneous fleet of trucks by as-
signing products to truck compartments, delivery
routes and schedules.
In related work by Haji R (2011), a two-echelon in-
ventory system is considered consisting of one cen-
tral warehouse and a number of non-identical re-
tailers. The warehouse uses a one-for-one policy to
replenish its inventory, but the retailers apply a new
policy that is each retailer orders one unit to central
warehouse in a predetermined time interval; thus
retailer orders are deterministic not random.
Abhijeet S and Saroj K (2011) considered a vendor
managed Two-Echelon inventory system for an inte-
grated production procurement case. Joint econom-

ic lot size models are presented for the two supply
situations, namely staggered supply and uniform
supply. Cases are employed that describe the inven-
tory situation of a single vendor supplying an item
to a manufacturer that is further processed before it
is supplied to the end user. Using illustrative exam-
ples, the comparative advantages of a uniform sub
batch supply over a staggered alternative are inves-
tigated and uniform supply models are found to be
comparatively more beneficial and robust than the
staggered sub batch supply.
2.1 The Stochastic Two-Echelon Supply chain Model ver-
sus Petrol Station Replenishment Models
The literature cited provides profound insights by
authors that are crucial in analyzing two-echelon in-
ventory systems. Existing models that address the
petrol station replenishment problem are similarly
presented. Based on the existing models by scholars,
a new stochastic dynamic programming approach is
sought in order to relate state-transitions with cus-
tomers, demand and inventory positions of the item
over the echelons. This is done with a view of opti-
mizing replenishment policies and inventory costs
of the supply chain in a multi-stage decision setting.
As noted by Cornillier F,Boctor F,Larporte G and
Renand J(2008,2009,2009),the three models address
the petrol station replenishment problem from the
transportation and logistics perspective. The source
(depot) is not vividly known and the overall goal is
to minimize transportation costs of petroleum prod-
ucts. Randomness of demand is not a salient issue
or not discussed at all. However, demand uncertain-
ty has a direct bearing in answering the inventory
question of “when to deliver or replenish” at mini-
mum inventory costs.
On a comparative note, the stochastic Two-Echelon
supply chain Model incorporates demand uncertainty
indeterminingoptimalreplenishmentdecisionswhere
“shortage” or “no shortage” conditions are catered for
when calculating total inventory costs over the eche-
lons. The Model can assist inventory managers of pe-
troleum products in answering the question of “when
to replenish” at minimum costs under demand uncer-
tainty. Petrol stations within a supply chain framework
that share a common fuel depot can consider adopting
the stochastic Two-Echelon supply chain model. As
cost minimization strategy, the model provides a prac-
tical solution to replenishment decisions of petroleum
products under demand uncertainty.
3. MODEL FORMULATION
3.1 Notation and assumptions
i,j = States of demand
F = Favorable state
U = Unfavorable state
h = Inventory echelon
n,N = Stages
Z = Replenishment policy
NZ
= Customer matrix
NZ
ij
= Number of customers
DZ
= Demand matrix
DZ
ij
= Quantity demanded
QZ
= Demand transition matrix
QZ
ij
= Demand transition probability
CZ
= Inventory cost matrix
CZ
ij
= Inventory costs
eZ
i
= Expected inventory costs
aZ
i
= Accumulated inventory costs
cr
= Unit replenishment costs
ch
= Unit holding costs
cs
= Unit shortage costs
i,j ε {F,U} h ε {1,2} Z ε {0,1} n=1,2,…………………….N
We consider a two-echelon inventory system con-
sisting of a fuel depot storing kerosene fuel for a
designated number of petrol stations at echelon
1.At echelon 2; customers demand kerosene at pet-
rol stations. The demand during each time period
over a fixed planning horizon for a given echelon
(h) is classified as either favorable (denoted by state
F) or unfavorable (denoted by state U) and the de-
mand of any such period is assumed to depend on
the demand of the preceding period. The transi-
tion probabilities over the planning horizon from
one demand state to another may be described by
means of a Markov chain. Suppose one is interested
in determining an optimal course of action, namely

to replenish additional units of kerosene (a decision
denoted by Z=1) or not to replenish additional units
of kerosene (a decision denoted by Z=0) during each
time period over the planning horizon, where Z is a
binary decision variable. Optimality is defined such
that the minimum inventory costs are accumulated
at the end of N consecutive time periods spanning
the planning horizon under consideration. In this
paper, a two-echelon (h =2) and two-period (N=2)
planning horizon is considered.
3.2 Finite - period dynamic programming problem for-
mulation
Recalling that the demand can either be in state F or
in state U, the problem of finding an optimal replen-
ishment policy may be expressed as a finite period
dynamic programming model.
Let gn
(i , h) denote the optimal expected inventory costs
accumulated during the periods n,n+1,…...,N given that
the state of the system at the beginning of period n is iє{
F, U }.The recursive equation relating gn
and gn+1
is
(1)
iє{F , U } , h={1,2} , n= 1,2,…………………….N
together with the final conditions
gN+1
(F , h ) = gN+1
(U , h ) = 0
This recursive relationship may be justified by noting that the cumulative inventory costs CZ
ij
(h)+ gN+1
(j) re-
sulting from reaching state j є{F, U} at the start of period n+1 from state i є{ F, U } at the start of period n occurs
with probability QZ
ij
(h).
Clearly, eZ
(h) = [QZ
ij
(h)] [ RZ
(h) ]T
, Z є{0,1} , h є{1,2} (2)
where ‘T’ denoted matrix transposition, and hence the dynamic programming recursive equations
(3)
(4)
result where (4) represents the Markov chain stable state.
3.2.1 Computing QZ
(h) and CZ
(h)
The demand transition probability from state iє{ F, U } to state j є{ F, U },given replenishment policy Z є{ 0,1
} may be taken as the number of customers observed over echelon h with demand initially in state i and later
with demand changing to state j, divided by the sum of customers over all states. That is,
iє{F , U }, Z є{0,1} , h= {1, 2} (5)
When demand outweighs on-hand inventory, the inventory cost matrix CZ
(h) may be computed by means of
the relation

Therefore,
(6)
for all i,jє{ F, U }, h є{1,2} and Zє{0,1}.
The justification for expression (6) is that DZ
ij
(h) –
IZ
ij
(h) units must be replenished to meet excess de-
mand. Otherwise replenishment is cancelled when
demand is less than or equal to on-hand inventory.
The following conditions must, however hold:
Z=1 when cr
> 0 and Z=0 when cr
= 0
cs
> 0 when shortages are allowed and cs
= 0 when
shortages are not allowed.
4. OPTIMIZATION
The optimal replenishment policy and profits are
found in this section for each period over echelon h
separately.
4.1 Optimization during period 1
When demand is favorable (ie. in state F), the opti-
mal replenishment policy during period 1 is
The associated inventory costs are then
Similarly, when demand is unfavorable (ie. in state U
), the optimal replenishment policy during period 1 is
In this case, the associated inventory costs are
4.2 Optimization during period 2
Using (2),(3) and recalling that aZ
i
(h)denotes the
already accumulated inventory costs at the end of
period 1 as a result of decisions made during that
period, it follows that
Therefore when demand is favorable (ie.in state F),the
optimal replenishment policy during period 2 is
while the associated inventory costs are
Similarly, when the demand is unfavorable (ie. in
state U), the optimal replenishment policy during
period 2 is

In this case the associated inventory costs are
5. CASE STUDY
In order to demonstrate use of the model in §2-3, real
case applications from Total(U)Ltd, a fuel company
for kerosene product and four Total petrol stations
in Uganda are presented in this section. The fuel
depot supplies kerosene at petrol stations (echelon
1), while end customers come to petrol stations for
kerosene (echelon 2).The demand for kerosene fluc-
tuates every week at both echelons. The fuel depot
and petrol stations want to avoid excess inventory
when demand is Unfavorable (state U) or running
out of stock when demand is Favorable (state F) and
hence seek decision support in terms of an optimal
replenishment policy and the associated inventory
cost of kerosene in a two-week planning period. The
network topology of a two-echelon inventory sys-
tem for kerosene is illustrated in Figure 1 below:
Figure 1: A two-echelon supply chain for kerosene product
hence seek decision support in terms of an optimal replenishment policy and the associated
inventory cost of kerosene in a two-week planning period. The network topology of a two-
echelon inventory system for kerosene is illustrated in Figure 1 below:
FUEL DEPOT PETROL STATIONS CUSTOMERS
(1)
Station 1
customers
(2)
Total (U) Ltd
Depot Station 2
customers
(3)
Station 3
Customers
(4)
Station 4
Customers
Echelon 1 Echelon 2
(h=1) (h=2)
Figure 1: A two-echelon supply chain for kerosene product
5.1 Data collection
Samples of customers demand and inventory levels were taken for kerosene product (in
thousand litres) at echelons 1 and 2 over the state-transitions and the respective replenishment
policies for twelve weeks as shown in Table 1.
5.1 Data collection
Samples of customers demand and inventory levels were taken for kerosene product (in thousand litres)
at echelons 1 and 2 over the state-transitions and the respective replenishment policies for twelve weeks as
shown in Table 1.

Table 1: Customers, demand and replenishment policies
given state-transitions, and echelons over twelve weeks
STATE
TRANSITION
(i,j)
ECHELON
(h)
REPLENISHMENT
POLICY
(Z)
CUSTOMERS
NZ
ij
(h)
DEMAND
DZ
ij
(h)
INVENTORY
IZ
ij
(h)
FF
FU
UF
UU
1
1
1
1
1
1
1
1
91
71
64
13
156
15
107
11
95
93
93
94
FF
FU
UF
UU
1
1
1
1
0
0
0
0
82
30
55
25
123
78
78
15
43.5
45
46.5
45.5
FF
FU
UF
UU
2
2
2
2
1
1
1
1
45
59
59
13
93
60
59
11
145
40
35.5
79.5
FF
FU
UF
UU
2
2
2
2
0
0
0
0
54
40
45
11
72
77
75
11
81
78.5
79.5
78.5
In either case, the unit replenishment cost (cr
) is $1.50, the unit holding cost per week (ch
) is $0.50 and the unit
shortage cost per week (cs
) is $0.75
5.2 Computation of Model Parameters
Using (5) and (6), the state transition matrices and inventory costs (in million UGX) at each respective echelon
for week1 are

for the case when additional units were replenished (Z=1) during week 1, while these matrices are given by


for the case when additional units were not replenished (Z=0) during week 1.
When additional units were replenished (Z = 1), the matrices Q1
(1), C1
(1) , Q1
(2) and C1
(2) yield the inven-
tory costs(in million UGX)
However, when additional units were not replenished (Z=0), the matrices Q0
(1), C0
(1) , Q0
(2) and C0
(2) yield
the inventory costs(in million UGX)
When additional units were replenished (Z=1), the accumulated inventory costs at the end of week 2 are cal-
culated as follows:
Echelon 1:
Echelon 2:
When additional units were not replenished (Z=0), the accumulated inventory costs at the end of week 2 are
calculated as follows:
Echelon 1:

Echelon 2:
5.3 The Optimal Replenishment Policy
Week1: Echelon 1
Since 111.32 < 184.25, it follows that Z=1 is an optimal re-
plenishmentpolicyforweek1withassociatedinventory
costs of $111.32 for the case of favorable demand. Since
39.01 < 64.32, it follows that Z=1 is an optimal replenish-
ment policy for week 1 with associated inventory costs
of $39.01 for the case when demand is unfavorable.
Week1: Echelon 2
Since 2.90 < 42.45, it follows that Z=0 is an optimal
replenishment policy for week 1 with associated in-
ventory costs of $2.90 when demand is favorable.
replenishment policy for week 1 with associated in-
ventory costs of $8.44 when demand is unfavorable.
Week 2: Echelon 1
replenishment policy for week 2 with associated ac-
cumulated inventory costs of $190.95 when demand
is favorable. Since 138.12 < 203.18, it follows that Z=1
is an optimal replenishment policy for week 2 with
associated accumulated inventory costs of $138.12
when demand is unfavorable.
Week 2: Echelon 2
Since 112.94 < 125.35, it follows that Z=1 is an op-
timal replenishment policy for week 2 with associ-
ated accumulated inventory costs of $112.94 for the
case of favorable demand. Since 157.40 < 164.16, it
follows that Z=1 is an optimal replenishment policy
for week 2 with associated accumulated inventory
costs of $157.40 for the case of unfavorable demand.
6. CONCLUSION
A two-echelon supply chain model with stochastic
demand was presented in this paper. The model
determines an optimal replenishment policy and
inventory costs of kerosene product under demand
uncertainty. The decision of whether or not to re-
plenish additional units is modeled as a multi-period
decision problem using dynamic programming over
a finite planning horizon. Results from the model in-
dicate optimal replenishment policies and inventory
costs over the echelons for the given problem. As a
cost minimization strategy in echelon-based inven-
tory systems, computational efforts of using Mar-
kov decision process approach provide promising
results for the petrol station replenishment problem.
However, further extensions of research are sought
in order to analyze replenishment policies that mini-
mize inventory costs under non stationary demand
conditions over the echelons. In the same spirit, the
model developed raises a number of salient issues
to consider: Lead time of kerosene during the re-
plenishment cycle and customer response to abrupt
changes in price of the product. Finally, special in-
terest is thought in further extending our model by
considering replenishment policies for minimum
inventory costs in the context of Continuous Time
Markov Chains (CTMC).
7. REFERENCES
Rodney P & Roman K, 2004, ”Optimal Policies for a capacitated Two-
Echelon Inventory system”, Operations Research, 152(5), 739-747.
Axsater S, 2005, A simple decision rule for decentralized two-
echelon inventory control, International Journal of Production
Economics, 93-94(1), 53-59.
Cornillier F,Boctor F,Laporte G & Renand J,2008,”An Exact Algo-
rithm for the Petrol station Replenishment Problem”, Journal
of Operations Research Society,vol.59,No.5,pp.607-615.

Cornillier F,Boctor F,Laporte G & Renand J,2009,”The Petrol sta-
tion Replenishment Problem with Time Windows”, Comput-
ers and Operations Research, vol.56,No.3,pp.919-935.
Cornillier F,Boctor F,Laporte G & Renand J,2009,”A Heuristic for
the multi-period Petrol station Replenishment Problem”, Eu-
ropean Journal of Operations Research, vol.19,No.2,pp.295-305.
Haji R & Tayebi H,2011,”Applying a new ordering policy in a
two-echelon inventory system with Poisson demand rate re-
tailers and transportation cost”, International Journal of Busi-
ness Performance and Supply chain Modeling,20-27.
Abhijeet S & Saroj K, 2011, A Vendor-managed Two-Echelon
Inventory system for an integrated procurement case”, Asia
Pacific Journal of Operations Research, 28(2), 301-322.
Kizito Paul Mubiru:An Industrial Engineer by profession. Graduated with a Bachelors in Industrial Engineer-
ing at University of San Antonio,Texas(USA) and later pursued a Masters in Business Administration(MBA).
Currently a full time Lecturer at Kyambogo University and a PhD candidate of Operations Research at Mak-
erere University,Uganda.

Key Organisational Factors For Building Supply Chain
Resilience: A Multiple Case Study Of Buyers And
Suppliers
Carla Roberta Pereira
PUC-Campinas
pereiracrz@gmail.com
Andrea Lago da Silva
UFSCar
deialago@hotmail.com
ABSTRACT: Achieving resiliency along the supply chain requires internal and external effort from
all members of the chain. The purpose of this paper to identify key organisational factors for building
resiliency in the supply chain, and to understand how these factors can influence the development or
enhancement of supply chain resilience. To do so, a multiple case study was performed on different
supply chains to validate organisational factors identified in the literature. As a result, ten organisa-
tional factors (six internal and four external) were highlighted and propositions were developed after a
cross-case discussion to affirm the influence of them in building or enhancing supply chain resilience.
Keywords: Supply Chain Resilience, Organisational Factors, Case Study.
77
DEP/UFSCar
deialago@ufscar.br

Pereira, C. R., Silva, A. L.: Key Organisational Factors For Building Supply Chain Resilience: A Multiple Case Study Of Buyers And Suppliers
1.INTRODUCTION
Recognising the increasing number of events that
have been hampering thousands of supply net-
works, recent studies have emphasized the great
importance of identifying sources of risk that might
threaten business, in order to create effective ac-
tions to mitigate them. Extensive examples are
easily found in the literature along with historical
cases of tsunamis, epidemics, and terrorist attacks.
The World Economic Forum (2015) has published
a report about the most likely and severe risks that
might occur globally, and it is clear how risks from
different categories (economic, environmental, geo-
political, societal and technological) are connected
and may influence each other. Consequently, they
are very likely to cause supply disruptions, which
potentially end up having great impacts for small
to large businesses throughout the complex global
network. Furthermore, this report highlights politi-
cal and environmental instability as a high societal
risk, and Brazil has been highlighted in it due to the
many protests against corruption, and urban issues
due to climate change.
The percentage of global companies reporting a
loss of income due to a supply chain disruption in-
creased from 28% in 2011 to 42% in 2013 (Sáenz and
Revilla, 2014). In this context of increasing numbers
of natural and man-made disasters, businesses from
every sector have vividly demonstrated the recent
need for changes to traditional strategies, especially
companies that depend on timely delivery of mate-
rials. The concept of supply chain resilience brings
forward the idea of developing effective actions in
preparing, responding and recovering from any dis-
ruptive event by means of resource management
(Ponomarov and Holcomb, 2009). Creating resilient
actions along the supply chain to respond to the
most recent likely risks and disasters is therefore a
way to assure competitive advantage and survival.
In this regard, scholars have seen this topic as a great
opportunity to be explored and thus helping prac-
titioners with business continuity and competitive
advantage (Sáenz and Revilla, 2014; Pereira et al.,
2014; Ambulkar et al., 2015). Although several
researchers (e.g. Sheffi, 2001; Christopher and Peck,
2004; Brandon-Jones et al., 2014; Fiksel et al., 2015)
have explored ways to better cope with unexpected
events and the consequent unplanned outages, scant
attention has been paid to investigating the main in-
ternal and external organisational factors for building
resiliency in the supply chain. The purpose of this pa-
per is twofold: to identify key organisational factors
to building resilience in supply chains, and to under-
stand how these factors can influence the develop-
ment or enhancement of supply chain resilience.
This paper is structured as follows. Section 2 re-
views the literature on supply chain resilience, and
the internal and external organisational factors iden-
tified that help to create supply chain resilience. Sec-
tion 3 reveals the research methodology, followed
by section 4 which discuss details from each case
regarding internal and external organisational fac-
tors. Section 5 presents the framework for building
resiliency, and develops propositions for each of the
organisational factors after the cross-case analysis.
Finally, section 6 draws the final conclusions and
points out further research opportunities.
2.LITERATURE REVIEW
2.1 Supply Chain Resilience
The term ‘resilience’ was not well-known in busi-
ness in the past and, to some extent, its meaning
nowadays is still limited to a minority of research-
ers within the supply chain management field.
From Latin origem (resilire), resilience means to
leap back or to rebound. Thus, this concept can be
explained as “the ability of an entity or a system to
‘recover form and position elastically’ following a
disturbance or disruption of some kind” (Simmie
and Martin, 2010, p.28). Ergo, the concept of resil-
ience has also been applied to different subjects
such as ecology, psychology, economy, social, and
organisational approaches to demonstrate the ca-
pacity of any system to return to the equilibrium
state after a temporary disturbance. Because of this
overarching view, resilience has become a multi-
dimensional and multidisciplinary phenomenon
in the last forty years (Ponomarov and Holcomb,
2009; Pereira et al., 2014).
In accordance with this, Figure 1 illustrates the defi-
nitions of the resilience concept in different research
areas, with noted similarities. Today there are many
definitions of supply chain resilience proposed by
different authors in the operational management
area. Hohenstein et al. (2015) listed 46 definitions
from 2003 to 2013. Nevertheless, it is noteworthy
that the general idea is consistent. Thus, the defini-
tion of supply chain resilience followed in this study
is the capability of supply chains to prepare for un-
expected events so as to be able to respond to and
recover from them in a way to restore operations to

the previous performance level, or even to a new
and higher level.
Admitting that almost every supply chain faces
supply disruptions of varying severity and types
(Wieland, 2013; Golgeci and Ponomarov, 2013,
Treiblmainer, 2014), Christopher and Peck (2004)
classified those disruptions into: internal, external
and environmental. Being prepared for any future
disruptive event enables companies to create effi-
cient and effective responses, and therefore are less
vulnerable to disturbances (Ponomarov and Hol-
comb, 2009; Pettit et al., 2010; Azevedo et al, 2013b;
Scholten et al., 2014). For this reason, resilience is
recognised as a responsive capability for firm per-
formance as well as a key factor of a firm’s survival
(Golgeci and Ponomarov, 2013).
Figure 1. Definitions of resilience in different areas
Source: created by the author
2.2 Internal and external organisational factors that chal-
lenge the building of supply chain resilience
In a general way, it is known that every buyer seeks
to ensure that all orders are placed with the right
amount, at the right time, at the right place and for
the right quality, while suppliers are responsible for
fulfilling that buyer’s requirements. However, sat-
isfying all of these “rights” has never been an easy
task for supply managers. Lately, these objectives
have been a challenge for those that wish to enhance
the value of the products/service as well as satisfy-
ing customers.
The challenge is therefore to help organisations to
develop efficient capabilities through their own re-
sources to cope with rapid-onset events. Based on
that, agility in threat detection and response, col-
laboration and information sharing among supply
chain members, besides assertive decision making
to overcome different kinds of disruptions are cru-
cial to enabling to companies continue their busi-

ness without significant impacts (Pereira et al., 2014;
Sholten et al., 2014; Ambulkar et al., 2015; Van der
Vegt et al., 2015). How to better prepare for an ef-
ficient response and recovery from such unforeseen
disruptions is considered an important capability,
which is called here as resilience.
To achieve supply chain resilience through the ac-
tions of buyers and suppliers, internal and external
organisational factors were identified in the litera-
ture as ways of building this capability. Table 1 ex-
poses the internal and external organisational fac-
tors and the corresponding references.
Recognising that the knowledge built up by manag-
ers and employees from their experiences through-
out the years makes them more prepared and com-
petitive in general, the backup of any information
from a company’s development should be an impor-
tant dataset to be kept safe. In this regard, develop-
ing and updating this kind of database can help pro-
fessionals to manage and monitor risk from previous
experiences and hence be more capable of mitigating
future risks and creating resilience. All information
recorded (knowledge acquired and backup) by the
company can be used to train employees, conduct
effective post-disruption analysis, understand the
total cost of supply chain management (Blackhurst
et al., 2011), and closely monitor the contingencies
from various risk resources (Jüttner and Maklan,
2011). Therefore “the capacity to learn from past dis-
ruptions to develop better preparedness for future
events is a principal property of resilience” (Pono-
marov and Holcomb, 2009, p.137).
Table 1. Internal and external organisational factors
It is asserted by Christopher and Peck (2004) that
safety stock or a “slack” in the inventory can also
be a fundamental way to create supply chain re-
silience. If any unexpected incident happens, the
company can easily overcome that situation by
holding inventory (Zsidisin and Wagner, 2010),
especially of critical items. Although redundancy
may be considered a good strategy to create re-
sponsiveness, it is important to remind that it only
affords the company with extra time to think about
next actions (Zsidisin et al., 2000).
The way products are designed and assembled may
be a strategic manner to cope with unpredictability
by increasing flexibility and responsiveness of the
processes. The success of Dell after the earthquake

in Taiwan is a good example of product flexibility.
As product designs and supply chain processes are
demand-based, Dell was able to change the configu-
ration of their computers and keep the manufactur-
ing and sales without huge losses (Sheffi and Rice,
2005; Tang, 2006b). Consequently, the more complex
the products’ configuration becomes, the more dif-
ficult is the recovery from any supply chain disrup-
tion (Blackhurst et al., 2011).
Technology is considered a powerful tool to share
and spread information nowadays. Tachizawa and
Gimenez (2010) affirm that the adoption of technol-
ogy tools, such as EDI (Electronic Data Interchange),
can help to integrate organisational processes. In
this sense, having tools to facilitate communication
is a good way to improve responsiveness in times
of disruption. Sheffi and Rice (2005) report the case
of UPS after the shutdown of the United Parcel Ser-
vice of America’s air hub due to a severe blizzard
in Louisville (January, 1996). After the UPS recov-
ery, which was successful because of its flexible
processes, UPS developed its own weather service
in order to avoid future disruptions. In fact, it is
reported by the same authors that this software can
work much better than National Weather Service in
forecast accuracy.
Colicchia et al. (2010) assert that a better under-
standing of the risk sources for specific supply chain
settings can enable the design of a more resilient
supply chain. Additionally, Zsidisin et al. (2005)
describe four processes to prevent discontinuities:
risk identification (enumerating the causes/sources
of potential supply chain disruptions); risk assess-
ment (evaluation of the probability of occurrence
and the impact an event will have on the business);
risk treatment (strategies development for reducing
their probability and/or mitigating their impact on
the business); and risk monitoring (looking at devel-
opments in the supply chain that may increase or
decrease risks on an on-going basis). Therefore, by
managing risk and their effects on business, compa-
nies become a more prepared function to manage,
and hence deal with, disruptive situations.
Decisions regarding supplier base, supplier rela-
tionship and development, and criteria for supplier
are essential to develop valuable sourcing strate-
gies. Thus, determining the supplier base (sole or
multiple for each item) is one of the key elements
of supplier management (Christopher et al., 2011;
Azevedo et al., 2013b) , and it is therefore one of the
key ways to build resilience. How to relate to sole,
dual or multiple suppliers is also a prominent deci-
sion. Christopher et al. (2011) assert that in terms
of single supplier, a close relationship is advised,
while for a number of different suppliers, a less
close relationship is appropriate in order to spread
risks. Not only Christopher et al. (2011) but also,
Svahn and Westerlund (2009) and Zsidisin and
Wagner (2010) discuss and claim the same point.
Furthermore, enhancing the relationship between
buyers and suppliers may increase collaboration,
alignment and visibility. Regarding supplier selec-
tion, many criteria are to be considered: supplier
locations (e.g. Sheffi, 2001; Christopher et al., 2011);
processes, practices and culture (Sheffi, 2001); com-
mon platforms for products (Zsidisin et al., 2000;
Stecke and Kumar, 2009); capacity constraints
(Christopher et al., 2011); financial stability (Zsi-
disin et al., 2000); and effectiveness of the supplier’s
management team (Zsidisin and Wagner, 2010).
Moreover, developing members of the supply
chain to be as responsive as possible in times of dis-
turbance is a valuable factor to overcome resilience.
If the company helps the suppliers to develop their
processes, they become aligned and more respon-
sive to changes (Zsidisin et al., 2000). Furthermore,
it can help to improve information sharing, integra-
tion and also flexibility (Yi et al., 2011).
Although the design of the supply chain can be
the result of companies’ choices regarding strate-
gic sourcing, there are also cases in which redesign
will be needed to mitigate risk and create a more re-
sponsive supply chain. In this context, Tang (2006a)
shows that Liz Claiborne moved all its textile supply
chains to China, which caused a reduction from 10-
50 weeks to fewer than 60 days in the lead time of
the company’s products. Therefore, how to design
the supply chain is also highlighted here as an im-
portant factor, considering that rearrangements of it
may enable an easily recovery.
Having more than one option for delivery is a wise
strategy to help companies avoid large and small
problems regarding flow disruptions. These options
can be divided into transportation modes or routes
(Tang, 2006a). The Brazilian post office (Correios)
has recently used this strategy to deal with protests
against the government that blocked hundreds of
roads, which hampered Correios’ service. However,
Correios had the advantage of working with other
modes of transportation, such as by plane. Hence,
it was able to overcome the situation by delivering
urgent loads on time by plane (ILOS, 2013).

3. RESEARCH METHODOLOGY
This research started with an extensive literature
review to identify the organisational factors listed
in Table 1. After that, empirical data was gathered
through a multiple case study in order to validate
the factors found in the literature. To guide this
study, two research questions were addressed:
- What are the key organisational factors for building sup-
ply chain resilience?
- How do internal and external organisational factors
influence the development or enhancement of the supply
chain resiliency?
Among many qualitative techniques for collecting
the data, the case study approach was considered
an appropriate method that fitted these research re-
quirements by investigating the phenomenon in a
current real-life context without interfering on the
phenomenon (Yin, 2009). Following on from these
research questions, a case study protocol was devel-
oped through the specification of all details and re-
quirements.
Four focal companies (buyers) including two of their
key suppliers were selected to be part of this empiri-
cal study. The reason for choosing a multiple case
study is that it is considered less vulnerable than
using a single case study in which all efforts are in-
vested in only one “shot” (Stuart et al., 2002). The
companies were selected based on different criteria,
such as:
- size of the focal company: medium to large-size compa-
nies which are naturally more complex in terms of struc-
ture, processes and human capital (Massey and Dawes,
2001; Paiva, 2010);
- type of company: manufacturing companies to limit the
scope of the study, since interesting cases of resilient so-
lutions are related to this type of companies (e.g. Chris-
topher and Peck, 2004; Carvalho et al., 2012a; Brandon-
Jones et al., 2014);
- location: Brazilian companies were chosen due
to the lack of studies about supply chain resil-
iency in this particular country, and considering
the emergent need of this capability to local prac-
titioners;
- sectors: a variety of sectors (beverage, household
appliance, food, and agribusiness) provide a rich
view of extreme situations, and helps to clarify com-
mon issues among companies, as well as identify ex-
isting differences (Christopher et al., 2007);
After identifying companies that fit into these cri-
teria, contact was made by e-mail and telephone to
present the aim of the study, the methods of data
collection and contributions. In addition, a formal
letter was attached to the e-mail, providing all the
details of the research including the confidential-
ity of the data shared by them. Table 2 shows the
main information about companies included in
each case (one focal company and two suppliers
from each one).
Regarding data gathering, semi-structured inter-
views and secondary data (archival data provided
by suppliers and focal companies as well as infor-
mation from their websites) were conducted with in-
dividuals from the focal companies as well as from
their key suppliers. As a result, six to nine individu-
als from each of the four supply chains (buyers and
suppliers) were interviewed. Most of the interviews
were conducted by Skype due to the distance be-
tween one company and another. Deakin and Wake-
field (2013) argue that synchronous online inter-
viewing is a useful supplement or replacement for
face-to-face interviews.
In total, 30 individuals from buyers and suppliers
were interviewed. The interviews lasted around 45
minutes each, and were conducted between January
and May of 2014. All interviews were recorded and
transcribed for further analysis. Additional notes,
impressions and ideas that occurred during the data
collection were also recorded and added to the case
study database (Yin, 2009). Furthermore, to increase
the reliability of the data gathered, a follow up by
e-mail was made in case details were missed during
the analysis (Voss et al., 2008).

Table 2. General information of the cases
9
Table 2. General information of the cases
Case Companies
Annual Prod.
Volume
Interviewees Main characteristics of the companies in each case
BEV
BEV-FC:
carbonated / non
carbonated drinks
180 million
litters
Strategic Procurement Manager (Mproc1), Plant Manager
(Mplan1), Purchasing Manager (Mpurc1), Commodity
Manager (Mcom1), Production and Material Planning
Manager (Mpmp1)
BEV-FC (focal company) is one of the 40 Brazilian plants of the multinational
organisation, but it has thousands of other plants in over 200 countries. BEV-S1
and BEV-S2 are both large companies (suppliers). BEV-S1 supplies BEV-FC
weekly with one of the main input to produce several final products. Thus,
BEV-S1 is considered one of the largest companies in the plastic segment.
BEV-S2 is also a large company which has additional plants abroad.
Recognising them as two large suppliers, BEV-FC is not their main customer;
however they do provide critical items to BEV-FC, which means that any
problem with these suppliers might cause a supply disruption to BEV-FC.
BEV-S1:
Plastic packaging
110 tons Market Intelligence (Mmint1s1), Sales Manager (Msale1s1)
BEV-S2:
Plastic film
80 tons Sales Person (Psale1s2), SAC Manager (Msac1s2)
KAPPL
KAPPL-FC:
Household
appliance
Disclosure not
allowed
Inbound Logistics Manager (Minlog2), Production and
Planning Control Manager (Mppc2), Transport Manager
(Mtransp2), Purchasing Manager (Mpurc2)
KAPPL-FC (focal company) is a well-known multinational company, which has
been ranked as the world's second-largest appliance maker by units sold.
Currently, it has sold more than 5 million products from 8 strong brands in
around 150 countries, however the highest sales have been in US and Brazil. In
Brazil, it holds 5 plants in three different cities. Both suppliers in this case are
responsible for supplying the focal company with specific raw materials to
manufacturer three important products. KAPPL-S1 and KAPPL-S2 are both
small national companies, but important suppliers to KAPPL-FC.
KAPPL-S1:
Metallurgical
960 thousand
components
Head of the company (Hcomp2s1), Admin assistant
(Aasm2s1)
KAPPL-S2:
Wood structure
360 thousand
items
Sales Person (Psale2s2)
FOOD
FOOD-FC:
Food
1.4 million
tons
Metal Commodity Buyer (Bmet3), Coffee Commodity Buyer
(Bcof3), Logistics Buyer (Blog3), Nuts Commodity Buyer
(Bnut3)
FOOD-FC is a multinational organisation that operates in more than 86
countries, and holds 30 plants in Brazil with more than 220.000 employees. In
Brazil, it is responsible for 141 brands, and a gross sales of 16 billion reais. Both
suppliers work in the same agribusiness sector, and they are responsible for
supplying the focal company demand with a specific raw material in "nuts"
segment. The FOOD-S1 plays a strategic role by intermediating the second tier
supplier (FOOD-S2) and the focal company (FOOD-FC).
FOOD-S1: Juices &
concentrates
N/A Sales Manager (Msales3s1)
FOOD-S2:
Nuts
90 thousand
tons
Sales Manager (Msales3s2), Procurement Manager
(Mproc3s2)
AGRO
AGRO-FC:
Agribusiness
N/A
Procurement Manager (Mproc4), Commodity Manager
(Mcom4), Materials Analyst (Amat4)
AGRO-FC is a multinational company that operates in more than 90 countries,
and holds around 15 plants in Brazil with about 1800 employees along a
complex and diverse supply chain; it has suppliers with different profiles - from
chemical industry to independent producers and farmers. In Brazil, this focal
company works with two business divisions - seeds and crop protection. Both
suppliers (AGRO-S1 and AGRO-S2) are responsible for supplying the focal
company with a specific pigment. They are large companies and operate in the
chemical sector; because of that, they considered each other competitors.
AGRO-S1:
Pigments
Disclosure not
allowed
Supply Chain Manager (Mscm4s1), Sales Person (Psale4s1)
AGRO-S2:
Surfactants & special
chemicals
2 million tons Sales Manager (Msale4s2)
After all the interviews had been transcribed, the
data was analysed qualitatively by means of the
content analysis method (Bardin, 2008; Gibbs, 2009;
Voss, 2008). The aim of this technique is to help
the researcher extract useful information in order
to provide understanding of the phenomenon in
study and, consequently, to build knowledge (Bar-
din, 2008). To support this analysis, a qualitative
software named QDA Miner was used to codify the
interviews (data fragmenting and re-assembling),
which made it easier to interpret them by enabling
the visualisation of the outcomes in different ways.
4. WITHIN-CASE ANALYSIS
The main results from each case are shown in this sec-
tion, which details the unique characteristics of each
case regarding the constructs of the analysis. These
individual results will then be consolidated for the
cross-case assessment in the next section, which is the
basis for the development of the propositions.
4.1 Case 1
Following the construct of analysis presented in the
literature review (section 2), this case explores how
the focal company act to deal with each of the inter-
nal and external organisational factors. Regarding
knowledge acquired and backup, all interviewees
from the buyers, as well as from their suppliers,
have emphasized the great importance of knowl-
edge acquired to prepare the company to deal with
critical supply disruptions, especially when the
knowledge comes from lessons learned. Further-
more, in dealing with different types of disrup-
tions over the years, managers become capable of
better managing internal and external companies’
resources to re-establish the normal operating per-
formance. It was found that DRINK-S2 has a formal
way to register problems and solutions through
customer service registrations in DRINK-S2, while
DRINK-FC and DRINK-S1 do not have any way of
recording lessons learned.
Interviewees have also affirmed the importance of
holding additional inventory to mitigate the vari-
ability of the raw materials along the supply chain.
Although all interviewees have asserted the need
of a reliable safety stock, DRINK-FC seems to work
with low volume of stock, aiming to reduce cost.
This is technically and theoretically sound to some
extent; however, interviewees from both suppli-
ers have asserted that DRINK-FC requires a high-

er stock from its suppliers so that they are able to
promptly supply it in case of any emergency. This
can be observed even through Mpmp1’s statement:
“[...] We depend on them; so their stocks have to
handle the changes in demand in order to keep us
supplied. Otherwise we can’t do anything. This is
our limitation”. However, Mproc1 from the DRINK-
Corporation has stated that in times of high demand,
they do increase the internal stock volume (raw ma-
terial as final product). Furthermore, interviewees
from DRINK-S1 and DRINK-S2 have affirmed that
stock is therefore their main tool to deal with supply
disruptions, however the challenge is to solve the
problem of high stock when there may be changes in
product specification. “My customer might change
their product specification and this will impact on
my stock. Basically it’s wasted money” (Msac1s2).
Interviewees from DRINK-FC admitted to have a
sort of flexibility in product manufacturing by hav-
ing substitutable items. In fact, they affirmed that
substitutable products and communication are criti-
cal factors to be managed. “We try to work with sub-
stitutable products, whether it is final product or
raw material, or even communication. I think these
are critical factors” (Mpmp1). Regarding DRINK-
S1 and DRINK-S2, interviewees have reported that
they do not have such flexibility to customer’s prod-
uct due to their product’s standardization, but they
have a simple process to manufacture the raw mate-
rial required by DRINK-FC.
Regarding communication, it was emphasized not
only within the organisations, but also along the
suppliers (between DRINK-FC and DRINK-S1/
DRINK-S2). “The better the communication, the
faster the problem gets solved, both internally and
externally. Remember those barriers that I told you
about - I believe that a greater proximity can help
with them” (Msale1s1). The technological ways used
to improve communication were e-mail, Skype and
an internal system similar to the ERP (Enterprise
Resource Planning). On the other hand, DRINK-FC
has a system that integrates all information about
the consequences and results of a problem, and
then helps develop an action plan to cope with that
particular problem. To do so, it makes use of qual-
ity tools, such as PDCA and Ishikawa graph, and
involves internal business functions as well as the
corresponding suppliers. Regarding suppliers, only
Mmint1s1 from DRINK-S1 has confirmed the exis-
tence of a similar system to the DRINK-FC, however
he also states that it is not well used on a daily basis.
By observing the business environment and market
behaviour, managers usually apply their knowledge
to manage risks likely to happen. In this regard,
DRINK-FC as well as DRINK-S1 and DRINK-S2
showed to be aware of incidents that might happen
even though they continuously execute practices to
mitigate them. “Can incidents happen? Yes. Could
[a plant] catch fire? Yes. But this is the responsibil-
ity of this committee, to analyse and deal with these
incidents that may occur” (Mplan1). Additionally,
Mplan1 reported the existence of a corporation’s
group of incidents management that is located in the
headquarters of DRINK (in the United States). Thus,
when a very critical incident occurs, it is reported to
this group, which decides what kind of action is go-
ing to take place in order to diminish the economical
losses as well as the consequences for the company’s
image. Although both suppliers presented well-es-
tablished risk management practices, it is interesting
to highlight that they take all these risk mitigation
actions without having them as a formal procedure.
Looking at outside of the focal company (DRINK-
S1), there are some strategic sourcing factors that
have to be considered to create supply chain resil-
ience. Not surprisingly, the supply base is definitely
a key factor to DRINK-FC. However, DRINK-S1 and
DRINK-S2 are also aware of the benefits of not de-
pending on a single supplier. “In the past, we have
had problems like this, so today we don’t have any
kind of exclusivity with any suppliers. [...] I never
give a purchase order to just one supplier. I go even
further than two suppliers; today we work with 3
or 4 suppliers” (Mmint1s1). Therefore, they prefer
having more than one supplier for a critical item in
order to not risk any shortages in supply to their
customers (in this case, DRINK-FC). What is partic-
ularly interesting from DRINK-FC’s and also from
DRINK-S2’s perspective is the support from their
franchises in acting as suppliers when a disruption
happens. Although the company may depend on a
single supplier when there is no substitutable sup-
pliers in the market, they can normally exchange be-
tween franchises. The results from both sides of the
focal company have shown a good relationship be-
tween DRINK-FC and its suppliers DRINK-S1 and
DRINK-S. In this context, Mplan1 have asserted that
“[...] disruption is something we mitigate through
partnership”. Thus, DRINK-FC promotes coaching
and workshops to their suppliers as a way to get all
of them together and make the relationship stronger.
Interviewees from the focal company have empha-
sized that besides intensively sharing information,

they also share possible risks with suppliers and this
increases the level of collaboration and trust. For this
reason, they support each other in time of need.
In the case of taking strategic decisions to reconfig-
ure the supply chain in order to mitigate risk, the
focal company usually analyse the location of their
suppliers and franchises to order urgent materials
in case of shortages. If the closest supplier has a
problem, they have other suppliers that will likely
supply them. Regarding this issue, it is noteworthy
that due to DRINK-FC’s and DRINK-S2’s work with
franchises, they can use them to change routes in
case any operation fails. Additionally, both suppli-
ers in this case are responsible for delivering orders
to DRINK-FC, which are made by road, although
interviewees reported situations in which a plane
was used as a way to make the delivery faster, and
consequently mitigate the consequences of a failure
to supply.
4.2 Case 2
Following the same rationale of the case above, con-
structs of analysis presented in this case are here
discussed. Interviewees from APPL-FC as well as
APPL-S1 and APPL-S2 have strongly affirmed the
importance of knowledge acquired to better deal
with disruptions and, consequently, overcome
them. “Internal, external and any other knowledge
possible” (Mppc2). Considering that all interview-
ees in this case have worked in those companies for
more than 20 years, except for one interviewee from
APPL-S1 (4 years), the knowledge asset of the sup-
ply chain is valuable indeed. In this sense, they have
affirmed that experience is achieved through daily
work and information sharing with older employees
from the company. Despite this, no way to record
lessons learned was found in any of these three com-
panies - “No, we don’t have this. It’s more of a daily
routine” (Mtransp2).
APPL-FC does not hold much stock due to a just-in-
time system. In this case, they have to be constantly
in contact with suppliers to check if all the planned
deliveries are going to arrive on time. However, to
balance the demand as well as supply fluctuations,
APPL-FC holds a very small safety stock of raw ma-
terials within the company. On the other hand, inter-
viewees from APPL-S1 and APPL-S2 have asserted
that the redundancy of some items (a high volume
of safety stock) is their best strategy to manage dai-
ly changes in demand, and continuously monitor
APPL-FC requirements in case any trouble arrives
upstream of their supply chain. H o w e v e r ,
when the raw material is scarce in the market or
has a long lead time (imported items, for instance),
APPL-FC must hold additional stock. To hold stock
in suppliers’ plants, APPL-FC makes use of an ex-
ternal inventory by holding it in a warehouse that
is located near the plant. The responsibility for the
level of inventory in the warehouse is the suppliers’.
The focal company and its suppliers are connected
through electronic data interchange (EDI) in order
to operate the vendor-managed inventory (VMI)
strategy. In this context, APPL-FC seems to make
full use of EDI by using a specific system to connect
the focal company and its suppliers. Information is
shared in real time, hence suppliers are able to visu-
alise any changes made in the company’s inventory.
Therefore, it improves the visibility along the supply
chain as well as the response capacity if any unex-
pected event occurs.
Although interviewees have positively affirmed the
benefits of product flexibility for supply chain resil-
ience, APPL-FC seems to not make use of it. Most of
the interviewees and especially those from the sup-
pliers (APPL-S1 and APPL-S2) have stated that each
product has particular characteristics, and because
of that they need unique and specific components.
Nevertheless, interviewees from APPL-FC men-
tioned the possibility of changing a product’s con-
figuration in the absence of a specific item, but there
is always additional cost in changing components
to fit another product. Unlike APPL-FC, interview-
ees from APPL-S1 have confirmed their capability
to change their products if there is a need. In this
respect, Hcomp2s1 reported that if they lose a cus-
tomer for any reason, they are capable of changing
their processes in order to produce another item.
Interviewees from APPL-FC reported well-devel-
oped procedures to mitigate risk by identifying pos-
sible risks from the suppliers and hence managing
and reconfiguring internal and external resources to
moderate them. These resources can be related to in-
formation sharing through internal communication,
safety stock and location of inventories (internal or
external), for example. Thus, risk analysis and risk
management are constantly executed in daily activi-
ties. Even if there is no team or department dedi-
cated to this task, standard procedures are executed
in daily activities, such as the follow-up of items to
identify critical ones (based on inventory and clas-
sification of the ABC-level items), contingency plans

for critical items, and daily meetings to discuss the
current operation. Hence, interviewees have men-
tioned risk management as a way to prevent breaks
of the flow. Furthermore, Minlog2 reported a new
practice in which they record the problem, and ex-
plore it afterwards in order to find the cause. “In-
ternally, the company is forced to have contingency
plans. We have to think about mitigating. If this hap-
pens...what do you do? If that happens, what do you
do? We have to have a strategy. Otherwise, when
people talk about supply disruptions, we often talk
about hours, but risk means months, or even years”
(Minlog2).
Through the discussion about sourcing strategies,
interviewees from APPL-FC have shown many
ways to deal with suppliers so as to better cope with
unexpected events. In this regard, APPL-S1 and AP-
PL-S2 have confirmed the statements of APPL-FC
interviewees about avoiding single sourcing and im-
proving supplier relationships. Therefore, APPL-FC
seeks to closely work with few suppliers but never
depends on single sourcing. For this reason, these
companies always have an extra supplier approved
for each item.
“There was a time when APPL- FC existed as
a global company which followed the Swedish
train of thought that said: it is much better to
have few suppliers and consolidate volumes and
get a better cost. But we are in Brazil; it’s a bit
tricky to do that, and fortunately the company
realised that after a while. So now, for example,
you have to have at least three approved suppli-
ers - two of them for daily supplying and one as
a backup, a stand-by” (Mpurc2).
However, there are some occasions in which it hap-
pens, due to the lack of capable suppliers available
in the market. When this happens, APPL-FC seeks
to develop new suppliers. In this regard, the head
of the APPL-S1 has reported that APPL-FC helped
to develop APPL-S1 due to a critical problem they
had with an imported item. It turned out that hav-
ing a national supplier would help them reduce the
lead time, the level of stock, and consequently, have
a faster response due to closer location. In terms of
suppliers, APPL-FC did not show any preference
for large suppliers. In fact, it keeps many small sup-
pliers nearby, which helps them in terms of shorter
lead time. Thus, the supplier criteria is the competi-
tiveness of the supplier. It is through a close rela-
tionship between focal company and suppliers that
these companies practice strong communication,
share information, and become familiar with the
processes.
As with APPL-FC, both suppliers in this case make
use of strategies related to set up of the supply chain
configuration in order to prepare themselves to be
capable of responding and recovering from untime-
ly events. It is worth emphasizing that APPL-S1 and
APPL-S2 are both located near to APPL-FC, 90 Km
away. Additionally, the warehouse recently set up
by them is only 12 Km away from the focal compa-
ny. It therefore enables APPL-FC to have a quick re-
sponse supply, and it can sometimes reduce the total
cost when considering the transportation tax. Taking
into account the distance among suppliers and the
focal company (APPL-FC), road transportation is
used to collect and deliver raw materials at the first
tiers of the APPL-FC supply chain, and shipping for
imported items. Mpurc2 added to this by saying that
“such transportation is by ship. So perhaps the flex-
ibility to streamline is infrequent air freight”.
4.3 Case 3
As well as in the other cases, interviewees in this case
were very positive in affirming the importance of
managers’ experience and their knowledge to man-
age risk and to deal with disruptions. In this regard,
interviewees from the three companies in this case
have affirmed that the more knowledge acquired
in how to manage and control internal and external
resources, the more capable managers become with
coping with disruptions. Nevertheless knowledge
acquired is normally restricted to those who were
part of a critical situation, since none of the compa-
nies in this case has a way to register lessons learned
from a critical event in order to pass it on to new
employees.
Strategies to manage stock are a key point to miti-
gate the impact of a disruption in the first place. This
kind of decision sought to be part of COMES-FC, but
it was also reported by the suppliers (COMES-S1
and COMES-S2) as an important way to overcome
supply drawbacks in a short time. “So it’s clear that
a big inventory doesn’t make your crisis disappear.
It gives you more time, but depending on the size
of the crisis, just having stock doesn’t help you, you
know?” (Bnut3). On the other hand, inventory has
to be very well managed in this particular supply
chain, considering that COMES has a short shelf life.
Therefore, keeping high volumes of stock is a risk
to the company, in case the market does not per-

form to expectations - millions of dollars might be
lost in stocking products for a long period. In the
past, COMES-S2 used to hold a high volume of in-
ventory to deal with the off-season. Currently, this
practice has changed due to the short time in getting
products from Africa (only seven days). Neverthe-
less, this supplier still keeps 60 days stock of non-
processed raw material.
The development of new products was highlighted
by interviewees from COMES-S1 and COMES-FC as
an important factor to deal with extreme situations.
In doing so, those companies were able to mitigate
problems in supplying Production with specific raw
material. In terms of product flexibility, COMES-S2
cannot support this strategy due to the wide range of
the products’ particularities for different customers.
Regarding tools to improve buyer-supplier com-
munication, only Msales3s1 has reported the use
of technology to exchange information between
buyer and supplier. They confirm that COMES-S2
has an online system to place purchasing orders -
“But COMES-S2 has a system. Every purchase order
I make here, I add to the system and they can see
it in Fortaleza, you know” (Msales3). Nevertheless,
it is not a system that shares real time information
between companies. Moreover, interviewees from
COMES-FC have not reported any system that is
used to place orders to COMES-S1 or COMES-S2.
Otherwise, they do often contact by e-mail, Skype
and telephone. To identify possible risk and disrup-
tions, the only tool mentioned was the reports from
government institutions that provide the medium
term forecast about weather and crop development,
but they are not accurate and reliable enough for
companies to rely on them.
Identifying sources of risk and mitigating them is
an important action that competitive companies are
aware about, however, no formal procedure was
reported by the interviewees. Interviewees have af-
firmed that risk management is normally embedded
into daily activities, and there is no exclusive func-
tion or team to take care of this particular subject. In
this case, contingency plans are specially drawn for
items that are considered critical. In addition, they
assert that the contingency plan is a costly strategy;
however they are aware that it is safer for the busi-
ness than maintaining the low price strategy in ex-
treme risk occasions.
Strategic sourcing is definitely the most discussed
and emphasised factor by the interviewees, with
regards to being more resilient. All three compa-
nies showed that they are aware of the risk in de-
pending on a single supplier, especially when the
supplier is not a large company and is responsible
for a critical item for the final product. In this sense,
they have this strategy well developed, in terms of
holding at least three approved suppliers for any
critical items. They also assert that having a big
supplier base is not the solution to mitigate risk
and possible disruptions. There is a need to have
qualified suppliers to attend COMES-FC require-
ments, and COMES-FC qualifies them, analysing if
the suppliers have extra capacity and whether they
work with large suppliers. They affirm that it helps
to avoid problems related to the lack of supplier
capacity or poor financial health of the supplier.
If there is no supplier in the market for a specific
item, or if suppliers seem to be a risk for the buyer,
interviewees agreed that developing suppliers is
a safe way to keep the company operating in the
event of a supplier problem. For this reason Bmet3
alleges that “So, the challenge is external, but it’s
also internal. Externally we face a challenge to find
a supplier who fits. Internally, we also face a chal-
lenge to ensure that we have a second or third op-
tion developed”.
As important as having a good supply base is the
relationship between the focal company and its
suppliers. Interviewees from COMES-FC have af-
firmed that the continuous communication with
supplier is a key way to keep updated and to de-
velop a trustful and committed relationship. If
any risk is about to arise or something has just
happened, suppliers automatically contact the
buyer in order to discuss the problem, and come
up with good solutions for both parties. The
companies in this case clearly demonstrate the
importance of this relationship to develop resil-
ience through communication, commitment and
collaboration between internal and external parts
of the company.
In this case, companies use shipping for imported
items and road transport to make the majority of
the deliveries. Only one interviewee mentioned the
airplane mode to deliver an urgent parcel to other
country. However this mode of transportation is
very restrictive with regards to the type of product
that can be sent. For some of COMES-FC’s raw ma-
terial, for instance nuts, it would not be possible use
airplane for transportation.

4.4 Case 4
Increasing the knowledge of managers enables them
to become more capable of dealing with further
disruptions; even though these disruptions might
arise from different causes. All interviewees have
affirmed the importance of this issue for creating
resilience within the company, and consequently
along the supply chain. In spite of this positive af-
firmation, only CHEM-S1 records the problems and
the actions taken to overcome them. Thus, much in-
formation can be lost over time, and new members
might have not the opportunity to learn from oth-
ers’ experience. “Yeah, this is really important. Each
season is different, but a material may behave the
same for different seasons. So really, knowledge is a
facilitator” (Mcom4).
As well as emphasizing creating supply chain resil-
ience, redundancy of critical components is another
factor well-discussed and well-applied to compa-
nies’ activities for coping with supply risk. Internal
safety stock was shown to be a common business
strategy of these companies to avoid production
breaks and supply disruptions along the supply
chain, especially when the raw material comes from
a single source. Moreover, CHEM-FC makes use of
this factor to cover another possible factor - prod-
uct flexibility. Neither CHEM-FC nor CHEM-S1 or
CHEM-S2 have product flexibility due to the prod-
uct’s specification. It is possible, but is not welcomed
by the companies, as can be seen in one of the ex-
amples above. “let’s say that the most critical case is
the product that is single sourcing, highest volume.
If this product has any shortage, the gross profit that
I’m going to lose is high. [In this case] it’s just the
stock; Even if we make an agreement with the sup-
plier to keep stock as well, CHEM-FC also keeps a
safety stock” (Mproc4). Nevertheless, this agribusi-
ness supply chain has a unique element to deal with
for safety stock. Some raw materials/products have
a short shelf life; thus, there is a limitation regarding
the size of the internal safety stock. The higher the
stock, the lower the quality of the product over time.
Therefore, redundancy of critical components is just
a partial strategy to creating supply chain resilience.
CHEM-FC has extra time to implement other strate-
gies to cope with supply disruptions, knowing that
additional stock is kept externally - at their suppliers
- which are strategically located nearby.
Having technology that supports internal and exter-
nal information sharing appears to be a good tool
to keep members updated throughout the business,
and hence knowing as soon as possible about pos-
sible changes that may turn into disruptions. Thus,
technology to improve communication is another
factor mentioned by the interviewees in this case.
It has shown to be valuable for creating resilience,
by sharing information with important members
within the focal company (CHEM-FC) or along
the supply chain (CHEM-S1 and CHEM-S2 in this
case). However, no technology that shares real time
information was found between the focal company
and its supplier. Apart from telephone, e-mails and
Skype, interviewees from CHEM-FC and CHEM-S1
have mentioned SAP (System Application Products)
and Team Space as technologies. Nonetheless, ac-
cording to their statement both systems seem to be
internally-focused.
Interviewees from CHEM-FC mentioned the exis-
tence of a department responsible for identifying
and analysing risk that might affect different types
of commodities. Thus, information provided from
this department is rather important for manag-
ers to make decisions and guarantee preparedness
and response to rapid onset events that might come
from CHEM-S1, CHEM-S2 or any other suppliers.
Procurement interviewees from CHEM-FC were
shown to have well-developed risk management
practices in which they observe possible risks from
their suppliers, and hence manage and reconfigure
internal and external resources to avoid them. These
resources can be related to internal communication,
safety stock, location of the inventories (internal or
external), size and number of suppliers or even sup-
plier relationship. Furthermore, risk analysis and
management is executed as part of daily activities,
so that it is a common practice.
Interviewees from CHEM-FC reported the com-
plex situation of having more than one supplier ap-
proved for every component. The issue given was
the lack of substitutable suppliers in market, the
lack of product quality from other suppliers, the
long distance between buyer and supplier, or even
because the company could not approve any extra
suppliers due to excessive bureaucracy. In line with
this, the criteria applied to select and approve sup-
pliers in this case are related to the size of the sup-
pliers. Thus, CHEM-FC seeks to work with global
companies, so that it does not become vulnerable to
suppliers regarding their financial health or a lack of
commitment. Additionally, the location of the sup-
plier is relevant to reduce lead time. In this sense,
Mproc4 affirms “CHEM-FC has few contracts or

purchases from small suppliers. Most of the sup-
pliers are global. The reason is to mitigate risk”. In
terms of supplier development, as CHEM-FC pre-
fers working with global suppliers, it does not look
to develop new suppliers; however, for special cir-
cumstances the company is trying to develop new
ones so as not to depend on one critical supplier.
Although the interviewees have positively affirmed
the need of good supplier relationship, CHEM-FC
works closely with strategic suppliers only, and not
with all of them. “If I have a supplier that I define as
strategic, I will work in partnership with them. I’ll
talk to them about innovation projects, I will focus
all my efforts to improve the supplier, I will work
with them every month to see what the opportuni-
ties are, what volume I’ll need... this is a strategic
partnership”(Mproc4).
Supply chain configuration and transportation
modes were also considered relevant factors in this
case due to actions taken by members from CHEM-
FC as well as CHEM-S1 and CHEM-S2 to reconfig-
ure routes and/or to change modes in order to reach
the goal, and not fall into breaks. “Products can’t be
more than 300 Km from my processing plant. It’s a
perishable material, so as soon as I take it from the
field, I have to take it for processing” (Mcom4).
5. FRAMEWORK AND PROPOSITIONS
This section presents the general results of the cross-
case analysis. Figure 2 summarizes the main internal
and external organisational factors purposed to help
companies to enhance resiliency in the supply chain.
Considering all eight factors identified through the
literature review, two additional factors were iden-
tified through the empirical data: organisational
structure, and external inventory. Through the dis-
cussion of the results, propositions were developed
to reaffirm how the identified internal and external
organisational factors can help to enhance supply
chain resiliency.
Figure 2. Framework of the main internal and external organisational factors for supply chain resilience

Knowledge acquired and backup from lessons
learned from past critical events is a key factor for
increasing a manager’s experience in order to deal
with future disruptions. It is through knowledge
acquired that managers or employees from buy-
ers and suppliers improve their abilities to manage
available resources to prepare, respond and recover
their business from any critical breaks. In this sense,
Ponomarov and Holcomb (2009, p.137) affirmation
says that “the capacity to learn from past disruptions
to develop better preparedness for future events is
a principal property of resilience”. Furthermore, it
means that they are able to deal with a wide range of
disruptions through wisely managing and control-
ling other internal or external factors, and hence cre-
ating supply chain resilience. Although companies
from the four cases are embedded in different sup-
ply chains, this factor was strongly highlighted by
all of them as an important factor to improve their
abilities to cope with future untoward events.
One characteristic that differentiated this factor from
one case to another was the routine of recording
problem situations (backup). Only DRINK-S1 (Case
1) and CHEM-S1 (Case 4) record problems and the
subsequent actions taken to overcome them. This is
therefore a critical finding of this analysis considering
that Sheffi (2001, p.4) has stated that “companies can-
not afford to maintain redundant employees around
“just in case”; companies should ensure that their
knowledge is backed up”. Much information can be
lost over time, and new members might not have the
opportunity to learn from others’ experience. It can
undermine the resilient capability of companies along
their supply chain, reminding them that knowledge
management is part of the planning process to build
supply chain resilience, and constant information
exchange and learning from horizontal and vertical
supply chain partners to keep skill levels up is there-
fore essential in a company.
P1: The practice of recording and making a backup of the
lessons learned from past experiences increases supply
chain resilience through shared knowledge.
Internal inventory was also a predominant factor
found in the four cases. Although stock may be con-
sidered a good strategy to mitigate disruptive im-
pacts in the first place and create responsiveness
through redundancy, it only affords the company
extra time to find other effective actions to cope with
the consequences (Zsidisin et al., 2000). All compa-
nies within the cases are aware of the high cost of
maintaining inventory, especially APPL-FC which
works with the kanban system; however they all
hold a minimal safety stock of raw materials which is
done in a strategic manner. DRINK-FC, for instance,
holds additional stock in times of high demand,
whereas APPL-FC holds higher volume of stock
of imported items which demand long lead times.
As well as APPL-FC, COMES-S2 used to hold high
volumes of stock for imported items, however it has
since changed this due to importations from Africa
which now take only seven days to arrive at the Bra-
zilian coast. Despite this, COMES-S2 still holds 60
days of stock to cover any unpredictable events that
could stop it from serving it’s customers (COMES-
FC, for instance). Thus, it seems that all companies
hold different volumes of stock according to their
needs. In Cases 3 and 4, for example, companies do
hold high stock due to the short shelf life of their
products - The higher the stock, the lower the qual-
ity of the product over time.
P2: Product characteristics, customer requirements and
the company’s strategy must be carefully considered to
define the correct amount of internal inventory, in order
to build supply chain resilience.
Developing interchangeable or substitutable items,
which characterise product flexibility, is therefore
a powerful alternative to companies to mitigate a
possible lack of specific items due to a disaster in a
supplier’s plant, for example (Sheffi and Rice, 2005;
Tang, 2006b). Despite this action being considered
a great strategy for creating supply chain resilience,
only in Cases 1 (DRINK) and 3 (COMES) has this
strategy showed up. Furthermore, DRINK-FC only
has this ability for B and C-level items (goods with
medium or lowest consumption value). For this
reason, interviewees from DRINK-S1 and DRINK-
S2 have stated that they are unable to provide any
substitutable item to DRINK-FC considering the
uniqueness of its products. One of the APPL-FC
managers has affirmed that this lack of flexibility is a
limitation of the company; on the other hand, APPL-
S1 has shown to be flexible in this regard. Lastly, no
evidence of this factor was found in Case 4 (CHEM).
The more complex the products’ configuration be-
comes, the more difficult the recovery from any
supply chain disruption is (Blackhurst et al., 2011).
Moreover, depending on the type of product, prod-
uct flexibility may require changes in the design and
to the project, and it can be costly. This seems to be
the reason why APPL-FC does not use this strategy.
On the other hand, it may simplify manufacturing

processes and likely would increase the options of
available suppliers, as well as reduce the base of
suppliers. Although building supply chain resil-
ience through product flexibility might be a costly
factor at first glance, it may bring advantages that
would certainly absorb the initial investment.
P3: Product flexibility promotes supply chain resilience
through considerable investment, but can generate addi-
tional benefits to absorb this cost.
Technological ways to communicate are considered
fundamental for sharing and spreading information
from horizontal and vertical supply chain partners
(Christopher and Lee, 2004; Tachizawa and Gimenez,
2010). This communication can be very useful for
managing the increasing number of activities within
and outside the company, and thus know as soon as
possible about possible changes that could turn into
disruptions. Regarding this factor, only APPL-FC
has presented the Electronic Data Interchange (EDI)
to exchange information between buyer (APPL-FC)
and its suppliers (APPL-S1 and APPL-S2). Through
this system, information is shared in real time and
suppliers are able to visualise any changes made in
the company’s inventory (Tachizawa and Gimenez,
2010). Nevertheless, it is only achievable if there is
trust and collaboration among supply chain mem-
bers. Also, technology for early detection of disrup-
tions highlights technologies related to risk identi-
fication, actions and solutions development, and
supply chain rearrangements. No evidence of this
kind of technology was found in any of the cases as
it is presented in the literature (Sheffi, 2001; Sheffi
and Rice, 2003; Blackhurst et al., 2005; Tang, 2006b;
Carvalho et al., 2012b; Azevedo et al. 2013b); how-
ever this kind of tool was suggested as an improve-
ment for creating resilience by interviewees from
Case 4 (CHEM).
P4: Technological tools help to build supply chain resil-
ience by increasing visibility along buyers and suppliers.
According to Colicchia et al. (2010) “a better under-
standing of the risk sources for specific supply chain
settings can enable the design of a more resilient
supply chain”. Thus, recognising that resilience is a
result of some companies’ strategic actions and deci-
sions, which aims to prepare the supply chain to ef-
fectively respond and recover from disruption, risk
management is therefore an essential factor in this
study. Differences among cases were also found re-
lated to this factor, as they are embedded in different
supply chains. In Case 1, DRINK-FC makes use of
a strategic purchasing matrix (spending vs. product
complexity) to purchase items and they have a cor-
poration’s management group for incidents to report
serious cases. Regarding their suppliers (DRINK-S1
and DRINK-S2), it is observed that although they do
have risk mitigation actions, they do not acknowl-
edge them as formal procedures. Similarly, CHEM-
FC also has a department responsible for identifying
and analysing risks. Differently from Case 1 and 4,
Case 2 and 3 do not have any group or department
responsible for monitoring and identifying risks.
Golgeci and Ponomarov (2013) affirm that through
effective risk management and mitigation, it is pos-
sible to build supply chain resilience so that, supply
chain resilience reaches beyond the purposes of risk
management.
P5: The capacity for building supply chain resilience
through risk management may be increased through the
creation of a group responsible for exploring and identify-
ing internal, external and environmental risk.
Interviewees from all cases have pointed out the hi-
erarchical structure as a barrier to creating supply
chain resilience due to the rigid hierarchy and de-
lays or long processes to get internal approvals. It is
known that if the company has a very rigid organ-
isational structure where functions do not commu-
nicate with each other, it can limit the flow of infor-
mation and hence become a barrier to visibility and
resilience as well (Christopher and Peck, 2004). It’s
due to this that “the ability of different organisations
or internal business departments to work together
to develop a collective strategy often determines the
success or failure of managing a disaster and/ or sup-
ply chain disruption” (Scholten et al., 2014, p.219).
P6: Hierarchical structure is a barrier to creating supply
chain resilience.
Regarding strategic sourcing, supply base is defi-
nitely the most discussed and emphasised factor
in all cases. Dual sourcing or multiple sourcing for
each item (or at least for critical items) was highly
discussed as a way to avoid crashes, and conse-
quently becoming resilient (Sheffi, 2001; Sheffi and
Rice, 2005; Azevedo et al., 2013). Related to criteria
for supplier selection, DRINK-FC did not mention
anything about supplier selection as a way to cre-
ate resilience, however it is observed through data
that they choose large suppliers to provide A-level
items, and they observe capacity and location for

B and C-level items. As well as Case 1, COMES-FC
has reported capacity and supplier size. Therefore,
they all fit into the criteria found in the literature
(Blackhurst et al, 2005; Tang, 2006a; Carvalho et al.,
2012a), knowing that large companies are consid-
ered by them as companies with financial stability.
Aside from those, competitiveness was highlighted
by APPL-FC as a criteria for their supplier selection,
recognising that they also focus on capacity and lo-
cation, but that they do not prioritize size of the sup-
pliers. Supplier relationship was particularly noted
in Case 4, in which CHEM-FC works closely with
strategic suppliers only, and not with all of them. In
the rest of the cases, they do not specify any differ-
ence regarding supplier relationship; in fact, they
have strongly highlighted the close relationship
with them. In terms of supplier development, all fo-
cal companies seek to have large suppliers in order
to mitigate risk, however it was noticed that they all
have developed a supplier (at least once) after a se-
vere incident that they have faced. Overall, factors
related to the upstream of the supply chain are defi-
nitely strategic issues to be explored and analysed in
order to create supply chain resilience.
P7: Strategic sourcing related to the base of suppliers,
criteria for supplier selection, supplier relationship and
supplier development is a key factor to build supply chain
resilience.
External inventory is a factor that came out from the
empirical data analysis from Cases 2 and 4, since
buyers made use of external inventory to guarantee
their supply. To do so, they hold additional stock
(raw material) in warehouses or even in supplier’s
plants - both located nearby them. For this reason,
buyers always hold less stock than their suppliers
(as was noted in all cases). Lastly, interviewees from
Case 4 (CHEM) have stated that they hold invento-
ries as a way of compensating for the lack of product
flexibility. Therefore, as well as internal inventory, a
“slack” in external inventory is considered a funda-
mental way to deliver material on time (Carvalho et
al., 2012a) and consequently create supply chain re-
silience in the current unstable environment (Chris-
topher and Peck, 2004; Zsidisin and Wagner, 2010;
Scholten et al., 2014).
P8: Keeping external inventory located nearby the buy-
ers’ factories can enhance agility to respond to unexpected
disruptions and consequently increase supply chain re-
silience.
Strategies related to design of the supply chain can
definitely help develop alternatives in order to be re-
silient. Distance between buyers and suppliers was
well-highlighted in all cases as an important factor.
This is clearly seen in APPL-FC where the ware-
house was strategically located only 12km away
from the focal company, and other suppliers are also
located nearby. Companies from Case 4 (CHEM)
work with global suppliers, and although they do
not have proximity in their favour, they do analyse
the location of their suppliers in order to evaluate
risks of political or climate instability. Toyota Mo-
tors has had many troubles in holding all strategic
suppliers in the same area, because in the case of a
local disaster (such as a tsunami) it loses all of them
(Sheffi, 2005; Tang, 2006). In Case 1, for instance,
the location of the franchises from DRINK-FC and
DRINK-S2 are also strategic, and they make full use
of it to avoid great disruptions.
P9: The network configuration considering location of the
supply chain members is a factor that can promote supply
chain resilience.
Having at least more than one option for delivery in
terms of routes or modes will help companies to mit-
igate disruptions, as stated by Tang (2006b). Thus, if
any route was damaged due to a strike or problems
on the road, there are alternatives for maintaining
the normal operation of the company. Regarding
transportation modes, transportation by road was
predominantly mentioned by interviewees in all cas-
es, while shipping was reported for imported items,
and a plane is an alternative used only in severe
situations. APPL-FC and COMES-FC therefore have
this flexibility, except CHEM-FC, who can make use
of air transport but normally make their deliveries
by road only. Moreover, in Case 3 (COMES) there
is a restriction on airplane transportation due to the
type of product. Examples of the route strategy were
found in all cases, since buyers monitor the routes
and take action to deal with unforeseen situations.
P10: Decisions about transportation can certainly in-
crease supply chain resilience, through alternatives routes
and transportation modes.
6. CONCLUSION
The concept of supply chain resilience is currently ex-
celling compared to other approaches to supply chain
management as it enables an organisation to prepare

for, respond to, and successfully recover from disrup-
tions. For this reason, understanding the company’s
vulnerabilities and knowing how to effectively act to
mitigate them is fundamental to survive in today’s
complex and dynamic business environment. This
exploratory study sought to investigate what the key
internal and external organisational factors are for
building resiliency in the supply chain, and how these
factors influence the development or enhancement of
supply chain resilience. As a result, ten organisational
factors (six internal and four external) were highlight-
ed in the framework (Figure 2) and propositions were
developed to confirm how each of them influence the
building of, or enhancing of, supply chain resilience.
The findings of this study help to expand the un-
derstanding of supply chain resilience in how it can
be developed through observing the identified or-
ganisational factors, and taking actions from both
side of the supply chain, in order to face challenges
and impacts of the current global market. Addition-
ally, as supply chain resilience is a recent approach
to supply chain management, very few managers
have demonstrated knowledge of this concept. In
this regard, a new approach has been introduced to
the participants of this research by inciting them to
demonstrate how their current practices and strate-
gies efficiently cope with supply disruptions. Lastly,
the findings are not limited to the companies’ sectors
explored in this study. Managers from other sectors
can make use of the factors to build resilient capabil-
ity for dealing with critical situations and effectively
responding and recovering from them.
This study did not have the intention of exploring the
costs involved in creating resilience in companies,
however it has been made clear through the discus-
sion that the investment to achieve resilience may
be high, considering the importance of developing
actions related to inventory and product flexibility,
for example. Nevertheless, the cost to create resil-
ience cannot be viewed as a barrier to companies to
develop this capability. The great negative impacts
of disruptions for companies’ finance and image are
noticeable (Christopher and Holweg, 2011), and it is
widely known that the cost to recover a customer
is much higher than to keep them (Ballou, 2010).
Creating supply chain resilience will certainly gen-
erate benefits that will cover all expenditures, such
as increasing the available suppliers in the market
and reduce the base of suppliers through product
flexibility. In this regard, it would be interesting to
develop studies that analyse how the costs of re-
silience can be beneficial to companies survival, as
well as quality. Additionally, further research could
test and validate the propositions developed in this
study by expanding the research into each of the fac-
tors and identifying additional practices that could
help practitioners to build or enhance the supply
chain resiliency. Through a quantitative research in
different sectors (manufacturing or service) it would
be valuable not only to test these propositions, but
also to find new ones.
References
Ambulkar, S.; Blackhurst, J., and Grawe, S. (2015), “Firm’s resil-
ience to supply chain disruptions: scale develpment and em-
pirical examiniation”, Journal of Operations Management,
Vol.33, No.34, pp.111-122.
Azevedo, S, Govindan, K, Carvalho, H, and Cruz-Machado, V.
(2013), “Ecosilient Index to assess the greenness and resil-
ience of the upstream automotive supply chain”, Journal Of
Cleaner Production, Vol.56, pp.131-146.
Ballou, R.H. Gerenciamento da cadeia de suprimentos: plane-
jamento, organização e logística empresarial. Porto Alegre:
Bookmann, 2010.
Bardin, L. (2008), “Análise de conteúdo”, Lisboa: Edições 70.
(Original book published in 1977).
Blackhurst, J., Craighead, C. W., Elkins, D. and Handfield, R. B.
(2005), “An empirically derived agenda of critical research is-
sues for managing supply-chain disruptions”, International
Journal of Production Research, Vol.43, No.19, pp.4067-4081.
Blackhurst, J., Dunn, K. S. and Craighead, C. W. (2011), “An em-
pirically derived framework of global supply resiliency”,
Journal of Business Logistics, Vol.32, No.4, pp.374-391.
Brandon-Jones, E., Squire, B., Autry, C. W. and Petersen, K. J.,
(2014), “A contingent resource-based perspective of supply
chain resilience and robustness”, Journal of Supply Chain
Management, Vol.50, No. 3, pp. 55-73.
Carvalho, H., Azevedo, S.G. and Cruz-Machado, V. (2012a), “Ag-
ile and resilient approaches to supply chain management:
influence on performance and competitiveness”, Logistics
Research, Vol.4, No.1-2, pp.49-62.
Carvalho, H., Barroso, A. P., Machado, V. H., Azevedo, S. and
Cruz-Machado, V. (2012b), “Supply chain redesign for resil-
ience using simulation”, Computers & Industrial Engineer-
ing, Vol.62, No.1, pp.329-341.
Christopher, M. and Peck, H. (2004), “Building the resilient sup-
ply chain”, International Journal of Logistics Management,
Vol.15, No.2, pp.1-14.
Christopher, M., Jia, F., Khan, O., Mena, C., Palmer,A., Sandberg, E.
(2007), “Global Sourcing and Logistics - Logistics Policy project
number - LP 0507”, Report produced at the Centre for Logistics
and Supply Chain Management at Cranfield School of Manage-
ment on behalf of the Department for Transport (DfT), pp.1-141.

Christopher, M., Holweg, M., (2011), “Supply Chain 2.0: man-
aging supply chains in the era of turbulence”, International
Journal of Physical Distribution & Logistics Management,
Vol.41, No.1, pp.63-82.
Christopher, M., Mena, C., Khan, O. and Yurt, O. (2011), “Ap-
proaches to managing global sourcing risk”, Supply Chain
Management, Vol.16, No.2, pp.67-81.
Colicchia, C., Dallari, F. and Melacini, M. (2010), “Increasing sup-
ply chain resilience in a global sourcing context”, Production
Planning & Control, Vol.21, No.7, pp.680-694.
Deakin, H., and Wakefield, K. (2013), “Skype interviewing: re-
flections of two PhD researchers”, Qualitative Research,
Vol.0, No.0, pp.1-14.
Fiskel, J., Polyviou, M., Croxton, K.L., and Pettit, T.J. (2015),
“From risk to resilience: learning to deal with disruption”,
Risk Management, Vol.56, No.2, pp.79-86.
Gibbs, G. (2009), “Análise de dados qualitativos”, Porto Alegre:
Artmed.
Golgeci, I. and Ponomarov, S. Y., (2013), “Does firm innovative-
ness enable effective responses to supply chain disruptions?
An empirical study”, Supply Chain Management: An Inter-
national Journal, Vol.18, No.6, pp. 604– 617.
Hohenstein, N.; Feisel, E. and Hartmann, E. (2015), “Research on
the phenomenon of supply chain resilience: a systematic re-
view and paths for further investigation”, International Jour-
nal of Physical Distribution & Logistics Management, Vol.45
No.1/2, pp.90-117.
Instituto de Logística e Supply Chain - ILOS (2013), “Manifesta-
ção afeta logística e já para fábricas pelo país”, available at:
www.ilos.com.br/clipping/index.php?optioncom_content&t
askview&id7009&Itemid27(accessed 02 September 2013).
Jüttner, U. and Maklan, S. (2011), “Supply chain resilience in the
global financial crisis: an empirical study”, Supply Chain
Massey, G. and Dawes, P.L. (2001), “Integrating Marketing and
Sales: the frequency and effectiveness of methods ussed in
Australia and the United Kingdom”. In: ANZMAC Confer-
ence, 2001, Auckland, Proceedings.... Auckland, New Zea-
land,: ANZMAC, 2001.
Paiva, E.L. (2010), “Manufacturing and marketing integration
from a cumulative capabilities perspective” , International
Journal of Production Economics, Vol.126, No.2, pp.379-386.
Pereira, C.R.; Christopher, M., and Silva, A.L. (2014), “Achieving sup-
ply chain resilience: the role of procurement”, Supply Chain Man-
agement: an international journal, Vol.19, No.5-6, pp.626-642.
Pettit, T.J., Fiksel, J. and Croxton, K.L. (2010), “Ensuring supply
chain resilience: development of a conceptual framework”,
Journal of Business Logistics, Vol.31, No.1, pp.1-21.
Ponomarov, S.Y. and Holcomb, M.C. (2009), “Understanding the
concept of supply chain resilience”, International Journal of
Logistics Management, Vol.20, No.1, pp.124-143.
Sáenz, M. J. and Revilla, E., (2014), “Creating more resilient sup-
ply chains”, MIT Sloan Management Review, June, 2014.
Scholten, K., Scott, P. S. and Fynes, B., (2014), “Mitigation pro-
cesses – antecedents for building supply chain resilience”,
Supply Chain Management: An International Journal, Vol.19,
No.2, pp. 211– 228.
Sheffi, J. (2005), The resilient enterprise: overcoming vulnerabil-
ity for competitive advantage, MIT Press, Massachussetts,
Cambridge.
Sheffi, Y. (2001), “Supply chain management under the threat of
international terrorism”, International Journal of Logistics
Sheffi, Y. and Rice Jr., J.B. (2005), “A supply chain view of the re-
silient enterprise”, MIT Sloan Management Review, Vol.47,
No.1, pp.41-48.
Simmie, J. and Martin, R. (2010), “The economic resilience of re-
gions: towards an evolutionary approach”, Cambridge Jour-
nal of Regions, Economy and Society, Vol.3, pp.27–43.
Stecke, K.E. and Kumar, S. (2009), “Sources of supply chain dis-
ruptions, factors that breed vulnerability, and mitigating
strategies”, Journal of Marketing Channels, Vol.16, No.3,
pp.193-226.
Stuart, F. I., McCutcheon, D. M., Handfield, R. B., McLachlin, R.,
& Samson, D. (2002), “Effective case research in operations
management: a process perspective”, Journal of Operations
Svahn, S. and Westerlund, M. (2009), “Purchasing strategies in
supply relationships”, Journal of Business & Industrial Mar-
keting, Vol.24, No.3, pp.173-181.
Tachizawa, E.M. and Gimenez, C. (2010), “Supply flexibility
strategies in Spanish firms: Results from a survey”, Inter-
national Journal of Production Economics, Vol.124, No.1,
pp.214-224.
Tang, C.S. (2006a), “Perspectives in supply chain risk manage-
ment”, International Journal of Production Economics,
Vol.103, No.2, pp.451-488.
Tang, C.S. (2006b), “Robust strategies for mitigating supply chain
disruptions”, International Journal of Logistics Research and
Applications: A Leading Journal of Supply Chain Manage-
ment, Vol.9, No.1, pp. 33-45.
Treiblmaier, H., (2014), “The next step in supply chain resilience
research: From an assessment tool toward theoretical inte-
gration”, 21th Annual IPSERA Conference, Palermo, Italy.
Van der Vegt, G.S.; Essens, P.; Wahlstrom, M. and George, G.,
(2015), “Managing Risk and Resilience”, Academy of Man-
agement Journal, Vol.58, No.4, pp.971–980.
Voss, C. (2008), “Case Research in operations management”. In:
Researching Operations Management, edited by Karlsson, C.
(2009), London: Routledge.
Wieland, A., (2013), “Selecting the right supply chain based on
risks”, Journal of Manufacturing Technology Management,
Vol. 24 No. 5, pp. 652-668.
World Economic Forum (2015), “Global Risks 2015, tenth edi-
tion”, Insight Report, Geneva, pp.1-65.

Yi, C.Y., Ngai, E.W.T. and Moon, K-L (2011), “Supply chain flex-
ibility in an uncertain environment: exploratory findings
from five case studies”, Supply Chain Management, Vol.16,
No.4, pp.271-283.
Yin, R., (2009), “Case study”, 4 Edition. R. Yin, ed., United States
of America: SAGE Publications.
Zsidisin, G.A., Panelli, A. and Upton, R. (2000), “Purchasing
organization involvement in risk assessments, contingency
plans, and risk management: an exploratory study”, Supply
Chain Management, Vol.5, No.4, pp.187-197.
Zsidisin, G.A., Melnyk, S.A. and Ragatz, G.L. (2005), “An institu-
tional theory perspective of business continuity planning for
purchasing and supply management”, International Journal
of Production Research, Vol.43, No.16, pp.3401-3420.
Zsidisin, G.A. and Wagner, S.M. (2010), “Do perceptions become
reality? the moderating role of supply chain resiliency on
disruption occurrence”, Journal of Business Logistics, Vol.31,
No.2, pp.1-20.
Carla Roberta Pereira: holds a bachelor degree in Production Engineering in State University of Maringa
(2008), masters (2011) and PhD (2014) in Industrial Engineering in Federal University of São Carlos. Nowa-
days she is a lecturer at PUC-Campinas, where teaches courses about Logistics and Supply Chain Manage-
ment, Planning and Production Control, and Project Management for Engineering and Business students.
Andrea Lago da Silva: Professor at Department of Production Engineering (UFSCar) since 1994. She has a
PhD in Business (FEA/USP,1999) and Msc in Production Engineering (UFSC, 1993. She teaches Marketing,
Services Operations. Her areas of research are SCM and Services Operations. She had published in a number
of Brazilian/International outlets like RAE/FGV, Gestão & Produção, Sloan Management Review and SCM:int
journal.

Modelling Collaborative Transportation Management:
Current State And Opportunities For Future Research
Liane Okdinawati
School of Business and Management, Bandung Institute of Technology
aneu.okdinawati@sbm-itb.ac.id
Togar M. Simatupang
togar@sbm-itb.ac.id
Yos Sunitiyoso
ABSTRACT: Collaborative Transportation Management (CTM) aims to reduce inefficiency, im-
prove services, and provide mutual outcome to all parties. CTM has raised significant interest of both
researchers and practitioners. Sharing information is the most basic form of coordination in supply
chains to integrate CTM models at strategic, tactical, and operational levels. However, little has been
known about the state of the art of CTM models. This paper presents a comprehensive review on the
current state of CTM models. The overview of the CTM models is organized by classifying the previ-
ous literatures on different collaborative structures and different levels of planning. This paper also
presents the relevant solution techniques used for each planning level. A review on the current state
of CTM models concludes by highlighting the unaddressed areas or the gaps existing in the current
literatures and by suggesting directions for future research in CTM.
Keywords: Collaborative Transportation Management (CTM), collaborative structure, planning level,
solution method, supply chain management, information sharing, model.
96

Okdinawati, L., Simatupang, T. M., Sunitiyoso, Y.: Modelling Collaborative Transportation Management: Current State And Opportunities For Future Research
1. INTRODUCTION
Logistics nowadays is influenced by globalization in
responding to changing demand of the consumer,
mass production, and customization (Gereffi, 2001).
The globalization increases business competitive-
ness and provides competitive advantages to dif-
ferent parties in the supply chain, especially in the
transportation area. These situations along with
the rising operating costs cause fierce competition
among transportation companies and force them
to run an efficient operation. An efficient operation
requires a type of collaboration where each party in-
volved in the transportation area has the same objec-
tive to get a better operation result and is more con-
cerned with the optimization objectives for all of the
parties involved rather than for an individual one
(Mason et al., 2007).
Collaborative Transportation Management (CTM)
is an emerging model of collaboration in the trans-
portation area (Tyan et al., 2003). VICS (2004) and
Li and Chan (2012) define CTM as a holistic process
that not only does it bring all parties together in the
supply chain to drive inefficiencies out of the trans-
portation planning and execution process but also it
improves the operating performances of all parties
through collaboration. Some of the benefits of CTM
are the reduction in increase load capacity usage,
the travelling time, and reduction in transportation
costs, particularly the back-haul costs, when two
transportations combine to minimize the distance
(VICS, 2004). Several researchers such as Brown-
ing and White (2000), Sutherland (2003), Esper and
Williams (2003), and Bishop (2004) state the needs
to incorporate CTM into logistics to avoid logistics
bottlenecks, reduce inefficiency, and provide mu-
tual benefits for all collaborative parties. In addition,
CTM can reduce the inventory-holding cost, increase
the responsiveness, and synchronize the activities in
logistics efficiently (Ozener, 2008).
CTM in the supply chain has become a topic of great
interest to researchers and practitioners. Many re-
searchers have developed models of CTM in the
supply chain that emphasizes different issues, such
as on operation efficiency, cost minimization, profit
maximization, or a combination of them as their ob-
jectives. However, the issues on behavioral aspects
that arise from the collaborative transportation have
not been explored. Although the CTM models could
be used in different types of collaboration, depend-
ing on the subject and scope of collaboration, many
researchers have only used the CTM models in the
scope of vertical collaboration and operational level.
In consequence, there are still many research areas
that could be addressed to effectively consider and
evaluate any possible applications of the models in
different scopes of collaboration to create optimal
scenarios for collaborative parties in different plan-
ning levels.
Due to the lack of CTM literatures and the aim to de-
velop a better understanding on CTM, a systematic
literature review that can point out both the impor-
tance of CTM in the supply chain and the explora-
tion of various CTM models is required. This paper
provides a literature review on the state of the art in
the CTM areas, the unaddressed CTM areas, and the
research gaps in CTM by classifying the previous
literatures into several categories, which are based
on four dimensions, such as collaborative structure,
general characteristics, collaborative planning lev-
els, and solution methodologies.
This paper is organized as follows. First, CTM is de-
fined based on the summary of the previous litera-
tures. Second, the methods for the systematic review
are described. Third, the classification of the existing
literatures is also described. Fourth, the previous
literatures are examined based on the classification.
Next, the discussion on the results of the systematic
review is presented. Finally, the conclusion and re-
search opportunities are presented.
2. COLLABORATIVE TRANSPORTATION MAN-
AGEMENT (CTM)
In logistics and transportation areas, many oppor-
tunities arise from developing collaboration when
firms work together to achieve common goals that
bring mutual benefits to all parties (Min et al., 2005).
Similar to that, Simatupang and Sridharan (2002)
state that a better result for all collaborative parties
can be achieved by working together through data
information sharing, a joint decision making, and
benefit sharing.
Under the Voluntary Inter-industry Commerce
Standards (VICS, 2004), it is stated that CTM com-
plements logistics collaboration after an order is
generated via Collaboration Planning Forecasting
Replenishment (CPFR). CPFR requires trading part-
ners to collaborate on sales and demand planning
activities as well as on an order placement that uses
technologies to improve both the accuracy of sales
order forecast and the subsequent replenishment
orders. Several transportation and distribution ac-

tivities that are not included in CPFR, such as: ship-
ments, modes or carrier assignments, scheduling,
tracks, and traces can be done by CTM (VICS, 2004).
CTM represents a new application of logistics col-
laboration to ensure that the benefits of CPFR are
properly executed and expanded in the transporta-
tion area.
According to Tyan et al. (2003), CTM is a new busi-
ness model, which is based on information sharing
in which carriers, as a strategic partner in logistic
collaboration, is included. Esper and Williams (2003)
state that CTM adds value to a collaborative rela-
tionship and an entire collaboration process, includ-
ing transportation that provide services. In addition,
Feng and Yuan (2007) and Chan and Zhang (2011)
state that CTM is based on an interaction among lo-
gistics parties in order to improve the flexibility in
the physical distributions and to minimize the inef-
ficiency in the transportation components.
In this paper, CTM is defined as a transportation
process which is based on the interaction, coordina-
tion, and collaboration among the shippers, receiv-
ers, and transportation service providers involved in
the logistics process. The aims of CTM are not only
to reduce inefficiency and cost in the transportation
but also to provide mutual benefits to all parties.
3. METHOD
The research method for conducting the systematic
review on CTM in the supply chain can be seen in
Figure 1. The first step was conducting the web-based
search from Proquest, Science Direct, SpringerLink,
Taylor and Francis database, and recommendation
from peers to identify the potential relevant articles,
raging from Dissertation Abstracts, Papers, and Sci-
ences Citation Index (SCI). The search used different
combinations of keywords, such as: “supply chain”
and “supply chain collaboration”; “transportation”
and “collaborative transportation”; “collabora-
tive formation” and “collaborative structure”; and
“planning level” and “planning horizon”. In addi-
tion, the keywords such as “solution method” were
used to find every related article in this field. From
these keywords combinations, 228 articles from dif-
ferent journals and publications were found. In the
second step, to search for the relevant publications,
the key word “CTM” was used. With the keyword,
65 articles were obtained. In this step, both irrelevant
articles and the same articles were removed (some
articles were obtained by using different search en-
gines). These articles come from the database con-
taining abstracts and the full papers.
In the third step, an in-depth content analysis to the
65 articles was performed. Based on the analysis
of the titles as well as the abstracts of both the ar-
ticles and the full papers, 27 of the 65 articles were
selected. The 27 articles were selected because they
contained the topic concerning the significance of
CTM, the implementation of CTM, the contribution
of various CTM models, the planning levels of CTM,
and methodologies of CTM. The articles that did not
contain the relevant topic on CTM were therefore
excluded. The remaining 38 articles were excluded
because they focused on urban transportation, not
on CTM models. Figure 2 shows the distribution of
the CTM literatures by year. It can be seen that in the
last couple of years the number of articles has been
increased. However, there has been no relevant con-
tribution to the CTM models between 2014 and 2015.
Figure 1. Methods of Literature Review

Figure 2. Literature Review by Year
Figure 2. Literature Review by Year
3.1 THE CLASSIFICATION OF CTM MODELS
Based on analysis of literatures, to systematically classify the literatures the
classification framework for the literature review of CTM is based on four
dimensions. The four dimensions of the classification namely collaborative structure,
general characteristics, collaborative planning level, and solution methodologies. The
classification of the literatures can be seen in Figure 3.
The first dimension describes the distinction between the parties involved and
the scope of the collaboration made under the collaborative structure categories, i.e.,
vertical, horizontal, and lateral collaboration. This refers to CTM definition where the
parties of supply chain as receiver, shipper, and carrier establish collaboration in
transportation in several collaborative structures based on the interaction between
logistics parties. The second dimension reflects the general characteristics of each
collaboration and CTM models. In the previous literatures, each collaboration and
CTM model were developed to understand the transportation problem and to evaluate
the benefits of collaboration in transportation area for all collaborative parties. Each
collaboration also caused several problems in the process. Based on analysis of
literatures, CTM also employed the planning horizon and decision-making process in
4
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4
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Dissertation
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Journal
Journal
Proceeding
Journal
Dissertation
Journal
Thesis
2003 2004 2005 2006 2006 2007 2008 2009 2009 2010 2011 2011 2012 2012 2013 2013
No. of Article
3.1 The Classification of CTM Models
Based on analysis of literatures, to systematically
classify the literatures the classification framework
for the literature review of CTM is based on four di-
mensions. The four dimensions of the classification
namely collaborative structure, general characteris-
tics, collaborative planning level, and solution meth-
odologies. The classification of the literatures can be
seen in Figure 3.
The first dimension describes the distinction be-
tween the parties involved and the scope of the col-
laboration made under the collaborative structure
categories, i.e., vertical, horizontal, and lateral col-
laboration. This refers to CTM definition where the
parties of supply chain as receiver, shipper, and car-
rier establish collaboration in transportation in sev-
eral collaborative structures based on the interaction
between logistics parties. The second dimension
reflects the general characteristics of each collabora-
tion and CTM models. In the previous literatures,
each collaboration and CTM model were developed
to understand the transportation problem and to
evaluate the benefits of collaboration in transporta-
tion area for all collaborative parties. Each collabo-
ration also caused several problems in the process.
Based on analysis of literatures, CTM also employed
the planning horizon and decision-making process
in the collaboration process to coordinate the plans
of several partners to achieve CTM objectives. Plan-
ning and decision-making process in CTM can be
formulated into different planning levels, depend-
ing on the time horizon and the importance of the
problem. Therefore, the third dimension of collab-
orative planning perspective is based on the plan-
ning decisions level, such as: strategic, tactical, and
operational planning level.
The fourth dimension is used to review and clas-
sify the literatures according to the relevant solution
method of each CTM model. Several methods are
used to optimize and solve complicated problems
related to CTM. It is very important and very chal-
lenging to find a solution method for the problems
related to CTM.
Figure 3: The Classification of CTM Models

3.1.1 Collaborative Structure
According to VICS (2004) CTM focuses on enhancing
the interaction and collaboration not only between
the three principal parties: a shipper, a receiver, and
a carrier, but also among the secondary participants
such as the third-party logistics service providers
(3PL). In this paper, CTM among the parties is classi-
fied into three categories: vertical, horizontal, and lat-
eral collaboration based on a collaborative structure,
depending on the parties involved and the scope of
the collaboration (Simatupang and Sridharan, 2002;
Soosay et al., 2006; and Zamboni, 2011).
Vertical Collaboration concerns two or more orga-
nizations, such as a receiver, a shipper, and a car-
rier, which share their responsibilities, resources,
and data information to serve relatively similar end
customers. Horizontal Collaboration concerns two or
more unrelated or competing organizations that co-
operate by sharing their private information or re-
sources such as joint transportation mode between
two carriers. Lateral Collaboration aims to gain more
flexibility by combining and sharing capabilities
both vertically and horizontally.
3.1.2 General Characteristics
CTM is formulated based on several general char-
acteristics such as fundamental issues, mechanisms,
and performance metrics. Certain issues arising
from the logistics process are recorded in the previ-
ous literatures. The issues are on increasing an ef-
ficient and reliable product delivery, increasing a
usage capacity, reducing cost, and increasing com-
petitiveness. Furthermore, the mechanisms of CTM
by both resources and information sharing are de-
veloped to ensure a common unity of effort and en-
sure benefits for all collaborative parties. Engaging
the parties in CTM not only gives significant benefits
for them but also improve their understanding on
CTM and management of CTM. The performance
metrics used by previous researchers covered cost,
transportation parameters, inventory investment,
and inventory level reduction.
3.1.3 Collaborative Planning Level
Several problems could be arising during the col-
laboration process. Because of these problems, the
third category is based on the collaborative planning
levels among the collaborative parties. This type of
category would potentially help distinguish all par-
ties’ proper planning, decision-making, and coordi-
nation of decisions in achieving their expected goals
of CTM. There are three levels of a collaborative
planning proposed for each transportation problem
that represent decision making process depending
on the time horizon (VICS, 2004; Ilyas et al., 2005;
and Meyr et al., 2005).
The first level is the strategic level. It functions as the
front-end agreement, the foundation for the entire
supply chain process, and as an essential part of sup-
ply chain management. Strategic level is classified
into strategic partnership model and the network model.
Strategic Partnership Model is a formalized agreement
to develop a collaboration relationship. To make the
relationship works, benefit, risk, and commitment
sharing are determined, and limitations that could
reduce potential benefits are identified. Network
Model uses static route/continuous movement pro-
grams to optimize the loading management. Carri-
ers may collaborate either with shippers and or with
other carriers.
The second collaborative planning level is the tac-
tical level that focuses on shipment requirements to
improve transportation utilization and efficiency.
Tactical level is classified into order and shipment fore-
casting model and carrier assignment model. The pur-
pose of Order and Shipment Forecasting Model is to im-
prove the efficiency and utilization of transportation
mode, while the purpose of Carrier Assignment Model
is to map different carrier used in the logistics pro-
cess. Carrier Assignment Model is developed based on
a shipment order.
The third collaborative planning level is the opera-
tional level, which covers the process flow to fulfill
the customer’s orders on daily basis, and it is con-
cerned with the efficient operation. This level has
three models: scheduling model, route model, and order
processing model. Scheduling Model is developed on a
daily basis based on a carrier assignment in the tac-
tical planning level by optimizing shipments. Route
Model is developed based on the network model in
the strategic level to reduce transportation costs ef-
fectively through reduced distances and traveling
time. Order Processing Model is developed based on
an information system and a technology used to
support information exchange.
3.1.4 Solution Methodologies
The current literatures indicate that many techniques
have been proposed to solve problems and calculate

optimization in the CTM area. These proposed solu-
tion techniques could be classified into five catego-
ries. Framework as the first solution technique is di-
vided into a theoretical framework and a conceptual
framework. The aim of the framework is to improve
the understanding on how CTM concepts perform.
Analytics as the second solution technique uses math-
ematical models that have a closed form of solution
and is used to describe changes in a system. The
third solution technique is heuristics. Heuristics is not
guaranteed to be an optimal solution, but it is used to
speed up the process of finding an optimal solution.
The fourth solution technique is metaheuristics. It is a
higher-level solution procedure that provides a suf-
ficiently good solution for an optimization problem,
especially for a problem with incomplete or imperfect
information and having a limited computation ca-
pacity. The last solution technique is simulation. This
technique is used to show the effects of an action on
either a system or a real life.
4. FINDINGS
The review of literatures is divided into three major
groups. The first group of literature review exam-
ines the state of the art of the previous literatures,
which are essential for the development of the verti-
cal collaboration. The second group of literature re-
view examines the state of the art of the horizontal
collaboration, and the last group of literature review
examines the lateral collaboration. The previous lit-
eratures of each group are summarized in Appen-
dix 1. To differentiate one group of literature review
from another one, the general characteristics as de-
cision variables, CTM models in three collaborative
planning levels, and solution methods are used as
the classification bases, can be seen in Table 1.

Table 1. Classification of Literature Review
AUTHOR
GENERAL CHARACTERISTICS CTM MODEL
SOLUTION
METHODFUNDAMEN-TAL
ISSUES
COLLABORA-
TION MECHA-
NISM
PERFORMANCE
INDICATORS
STRATEGIC
LEVEL
TACTICAL
LEVEL
OPERATION-
AL LEVEL
VERTICAL COLLABORATION
Tyan et al.
(2003)
Capacity issue,
improving service
levels, reducing
cost, and increasing
competitiveness
Information and
data sharing,
sharing benefit
Transportation
parameters
Order
Processing
Model
ANALYTICS
(Empirical
Research)
Esper and
William
(2003)
Reducing cost,
inefficient and
unreliable product
delivery
Information and
data sharing
Cost saving,
transportation
parameters
Order
Processing
Model
ANALYTICS
(Empirical
Research)
Caplice and
Seffi (2003)
Reducing cost,
and increasing
competitiveness
Information and
data sharing,
sharing benefit
Cost saving,
transportation
parameters
Strategic
Partnership
Model
ANALYTICS
(Optimization-
Based
Procurement)
Feng et al.
(2005)
Capacity issue,
reducing cost,
inefficient and
unreliable product
delivery
Information and
data sharing
Cost saving,
transportation
parameters,
inventory level/cost
Carrier
Assignment
Model
SIMULATION
(Beer Game)
Audy et al.
(2006)
Reducing cost,
inefficient and
unreliable product
delivery
Sharing resources,
information and
data sharing
Strategic
Partnership
Model
FRAMEWORK
(Business Model
Coalition)
Ergun et al.
(2007)
Reducing cost Sharing resources
Cost saving,
transportation
parameters
Network
Model
HEURISTICS
(Greedy Merge
Heuristics)

Table 1. Classification of Literature Review (Cont.)
AUTHOR
SOLUTION
METHODFUNDAMEN-
TAL ISSUES
COLLABORA-
TION MECHA-
NISM
PERFORMANCE
INDICATORS
STRATEGIC
LEVEL
TACTICAL
LEVEL
OPERATIONAL
LEVEL
Feng and Yuan
(2007)
Improving
service levels and
reducing cost
Information and
data sharing
Cost saving,
transportation
parameters
Order Processing
Model
ANALYTICS
Empirical
Research)
Kayikci (2009)
Improving
service levels,
reducing cost,
and increasing
competitiveness
Information and
data sharing
Cost saving,
revenue, customer
satisfaction,
inventory level/
cost
Strategic
Partnership
Model
ANALYTICS
(Partial Least
Square)
Chen et al.
(2010)
Reducing cost
Information and
data sharing
Cost saving, inven-
tory level/cost
Order Processing
Model
ANALYTICS
(Transcendental
Logarithmic)
Silva et al.
(2011)
Reducing cost
Information and
data sharing, shar-
ing benefit, and
managing trust
Revenue
Strategic
Partnership
Model
SIMULATION
(Agent-Based
& System
Dynamic)
Gonzalez-Feliu
and Morana
(2011)
Reducing cost
Sharing resources,
information and
data sharing, shar-
ing risk
Strategic
Partnership
Model
FRAMEWORK
(Logistics
Sharing)
Li and Chan
(2012)
Improving service
levels, reducing
cost, inefficient
and unreliable
delivery
Information and
data sharing, shar-
ing risk
Cost saving, trans-
portation param-
eters, revenue, and
inventory level/
cost
Order Processing
Model
SIMULATION
(Agent-Based)

AUTHOR
FUNDAMENTAL
ISSUES
SOLUTION
METHODCOLLABORATION
MECHANISM
PERFORMANCE
INDICATORS
STRATEGIC
LEVEL
TACTICAL
LEVEL
OPERATIONAL
LEVEL
Moll (2012)
Improving service
levels and increasing
competitiveness
Information and
data sharing, sharing
benefit
Cost saving,
transportation
parameters, and
revenue
Scheduling
Model
ANALYTICS
(Empirical Research)
Wen (2012)
Increasing
competitiveness,
inefficient and
unreliable product
delivery
Information and data
sharing

Strategic
Partnership
Model
ANALYTICS
(Factor Analysis)
HORIZONTAL COLLABORATION
Song and Regan (2003)
Reducing cost
and increasing
competitiveness
Sharing resources,
sharing benefit
Cost saving
Strategic
Partnership
Model
ANALYTICS
(Quasi Linier)
Nadarajah (2008)
Reducing cost
and increasing
competitiveness
Sharing resources
Cost saving,
revenue
Route Model
METAHEURISTICS
(Tabu Search &
Guided Local
Search)
Asawasakulsorn (2009)
Capacity issue and
reducing cost
Sharing resources,
managing trust
Strategic
Partnership
Model
ANALYTICS
(Simple & Multi
Regression)
Fisk et al. (2010)
Reducing cost,
inefficient and
unreliable product
delivery
Sharing resources,
sharing benefit
Cost saving,
transportation
parameters
Strategic
Partnership
Model
ANALYTICS
(Linier
Programming)

AUTHOR
FUNDAMENTAL
ISSUES
SOLUTION
METHODCOLLABORATION
MECHANISM
PERFORMANCE
INDICATORS
STRATEGIC
LEVEL
TACTICAL
LEVEL
OPERATIONAL
LEVEL
Liu et al. (2010)
Reducing cost,
increasing
competitiveness
Sharing resources,
sharing benefit
Cost saving
Strategic
Partnership
Model
SIMULATION
(Weighted Relative
Savings Model)
Audy et al. (2010) Reducing cost
Sharing resources,
sharing benefit
Cost saving
Strategic
Partnership
Model
SIMULATION
(Game Theory-Equal
Profit Method)
Peeta and Hernandez
(2011)
Capacity issue,
reducing cost,
inefficient and
unreliable product
delivery
Sharing resources,
information and data
sharing
Cost saving,
transportation
parameters, revenue
Route Model
SIMULATION
(Mixed Logit-
Simulation
Based Maximum
Likelihood)
Taherian (2013)
Reducing cost,
inefficient and
unreliable product
delivery
Sharing resources
Cost saving,
transportation
parameters, revenue
Strategic
Partnership
Model
ANALYTICS
(Empirical Research)
LATERAL COLLABORATION
VICS (2004)
Capacity issue,
improving service
level, reducing
cost, increasing
competitiveness,
inefficient delivery
Sharing resources,
sharing, managing
trust, sharing benefit,
sharing risks
Cost saving,
transportation
parameters,
revenue, customer
satisfaction,
Strategic
Partnership
Model
FRAMEWORK
(Selecting Partner)

AUTHOR
FUNDAMENTAL
ISSUES
SOLUTION
METHODCOLLABORATION
MECHANISM
PERFORMANCE
INDICATORS
STRATEGIC LEVEL
TACTICAL
LEVEL
OPERATIONAL
LEVEL
Sutherland (2006)
Capacity issue,
improving service
level, reducing
cost, increasing
competitiveness,
inefficient and
unreliable product
delivery
Sharing resources,
sharing, managing
trust, sharing benefit,
sharing risks
Cost saving,
transportation
parameters, revenue,
customer satisfaction,
Strategic
Partnership
Model
FRAMEWORK
(Selecting Partner)
Mason et al. (2007)
Reducing cost,
inefficient and
unreliable product
delivery
Sharing resources,
information and
benefit
Cost saving,
transportation
parameters, revenue,
customer satisfaction,
Order Processing
Model
ANALYTICS
(Empirical
Research)
Ozener (2008) Reducing cost
Sharing resources,
information and
benefit
Cost saving
Network
Model
Route Model
HEURISTICS
(Shapley Value
& Mixed
Integer Linier
Programming)
Gonzalez-Feliu et
al. (2013)
Reducing cost
Sharing resources,
sharing benefit
Cost saving
Strategic
Partnership
Model
SIMULATION
(Clustering Phase)

4.1 Vertical Collaboration
In this section, the collaboration among parties in the
same supply chain, known as the vertical collabora-
tion will be discussed. Each collaborative planning
level will be discussed separately. In addition, the
general characteristics and the variety of solution
methodologies will be discussed.
4.1.1 Strategic Level
The strategic planning model to improve perfor-
mances takes into account the long-term interests of
all collaborative parties and their decisions on both
suitable businesses and operational policies. Audy
et al. (2006) and Gonzalez-Feliu and Morana (2011)
used a similar approach to develop a framework for
the strategic partnership model. Audy et al. (2006)
proposed a series of business models to build a col-
laborative transportation coalition. Also, Gonzalez-
Feliu and Morana (2011) developed a conceptual
framework model that summarizes the organiza-
tional model and sharing analysis factors, including
information sharing in the context of the press distri-
bution sector in France.
The models in the above-mentioned research (Audy
et al., 2006; Gonzalez-Feliu and Morana, 2011), need
to be implemented and their performance indicators
need to be measured to facilitate the evaluation of
the strategic decisions. In Audy et al. (2006), man-
aging trust and sharing risk were not included as
a mechanism of collaboration. On the other hand
Gonzales-Feliu and Morana (2011) included sever-
al types of risk (financial risk, technology risk, and
policy risk) but still did not include how the col-
laborative parties interact and how the collaborative
parties manage a trust.
Caplice and Seffi (2003) discussed the network
model in which shippers could procure transporta-
tion services by underpinning the optimization of
a conditional bidding for carriers so that the ship-
pers can quantify and compare the levels of services
with the carriers’ rates. The approach introduced by
Caplice and Seffi (2003) can be used as a marketing
tool by carriers to help a better understanding for
shippers’ clients on how to place value on their spe-
cific services. The limitation of this research is that
they only used one aspect of the process, which is a
procurement that uses a bidding method. Therefore,
the sharing information process, the impact of the
bidding method, the interaction, and the synergies
among collaborative parties are still not covered.
Wen (2012) on the other hand, used the Exploratory
Factor Analysis to identify the key factors associated
with CTM practices, such as the logistics capability and
competitive advantage for carriers. Similarly, Kayikci
(2009) showed the impact of CTM’s implementation
process on intermodal freight transportation by devel-
oping a path model. Both studies provide empirical
evidence to support a conceptual framework regard-
ing the impact of CTM for carriers and the implemen-
tation of CTM practices. The limitation of the research
(Wen, 2012 and Kayikci, 2009) is that quantifying the
benefits and impacts of CTM for carriers and supply
chain partners was not carried out.
Ergun et al. (2007) used heuristics as a solution meth-
od to assist the identification of dedicated truckload’s
continuous moving tours for the time-constrained
lane-covering problem. Ergun et al. (2007) conducted
computational experiments on slightly simplified in-
stances, in which they did not consider loading and
unloading times, and they used the algorithm that ig-
noredHoursofServiceregulations.Inaddition,Silvaet
al. (2011) studied the problem of reducing freight costs
in the export process between the industries of manu-
facture goods and the maritime carriers. They used the
strategic scope of relationship to see the collaboration
role of each party in response to either party-to-party
interactions or each party’s interaction with the envi-
ronment. They used the System Dynamics (SD) and
Agent Based Modeling and Simulation (ABMS) as
their solution methodologies. Due to the limitation of
factual data in this research, the suggested results did
not represent the real world’s negotiations and infor-
mation sharing in them. Silva et al. (2011) also omitted
both the risk and trust mechanism in the model.
4.1.2 Tactical Level
Companies make medium-term decisions at the tacti-
cal level to define the process based on a general plan-
ning at a strategic level. Feng et al. (2005) proposed a
concept of CTM and a framework for evaluating CTM.
They also elaborated how CTM affects the supply
chain’s total costs and transportation capacity utiliza-
tion. The simulation of beer game model was used to
consider transportation capacity. The limitation of this
research is that it had no complete analysis of actual
CTM to obtain more real effects on the supply chain.
4.1.3 Operational Level
The operational level deals with the day-to-day pro-
cess, a decision-making, and a planning that make

supply chain process run smoothly, achieve maxi-
mum benefits, and increase performances. Moll
(2012) shows that a short-term timetable planning
in an operational process could achieve high pro-
ductivity of freight railways. However, the potential
benefits are not equally divided for all collaborative
parties, due to a heterogenic transportation plan-
ning process. This research contributes to a better
understanding of operational level of Switzerland’s
rail freight and shows the applicability of research
in practices. Because the approach is incompatible
with the operational process of the freight railways
in Europe, this research could not be used as the
foundation for the implementation of collaboration
on an operational strategy.
Many researchers (Tyan et al., 2003; Esper and Wil-
liam, 2003; Feng and Yuan, 2007; and Chen et al.,
2010) pointed out that information sharing and in-
formation technology in CTM could increase per-
formances. Feng and Yuan (2007), Tyan et al. (2003)
and Chen et al. (2010) used Notebook industry in
Taiwan as their case study. Tyan et al. (2003) pointed
out the benefits of CTM in three performance in-
dicators, such as: shipment volume, delivery per-
formance, and delivery cycle time. However, Feng
and Yuan (2007) used different performance indica-
tors, such as: on-time delivery, shipment visibility,
transportation cost, and tracking cycle time to em-
phasize the benefits of CTM. Chen et al. (2010) tried
to use a different approach by developing the cost
function based on an actual operation. Chen et al.
(2010) showed that the higher accuracy of CTM and
the higher degree of information sharing resulted in
saving costs in the supply chain.
In addition, Esper and William (2003) used a differ-
ent industry to point out information sharing and
information technology in CTM by measuring trans-
portation cost, on-time performance, asset utiliza-
tion, and administrative cost. The limitations of this
research (Tyan et al., 2003; Esper and William, 2003;
Feng and Yuan, 2007; Chen et al., 2010) are that both
the interaction among collaborative parties and col-
laborative parties’ problems related to trust, technol-
ogy risk, and operational risk, when associated with
information technology in CTM, were not explored.
Li and Chan (2012), on the other hand, proposed the
interactions among different supply chain partners
under a demand disruption. This research showed
that CTM was efficient to handle risk in the supply
chain when a demand disruption occurred. How-
ever, this research only used a virtual company as
its calculation basis. Therefore, a company that uses
reliable data needs to be explored to provide better
evidence on the benefits of information sharing in
CTM. The limitation of conducting research in this
operational level is that there is no previous studies
that point out how each collaborative party interact
with another party in making its decision on a deliv-
ery route.
4.2 Horizontal Collaboration
In horizontal collaboration, the total cost of supply
chain is used as a key issue in performance measure-
ment (Prakash and Deshmukh, 2010).
The strategic level provides an overall direction by
determining the objectives, developing policies, and
plans based on the consideration of resource alloca-
tion and environment (Nag et al., 2007). With the
same direction, Song and Regan (2003) proposed the
feasibility of the auction as a basis for the procure-
ment in the horizontal collaboration. They conclude
that the auction method is more efficient than both
the long-term agreement and the spot market. The
limitations of this research were that Song and Re-
gan (2003) did not explore how information sharing
process in the auction process was conducted and
how transportation companies could separate prof-
itable opportunities from unprofitable ones in the
auction procurement.
Asawasakulsorn (2009) developed five selection cri-
teria, based on economic concept, to select partners
to join the collaboration. There are some limitations
in this research, i.e., using a non-probabilistic sam-
pling. Therefore, the relationship among all collab-
orative parties could not be measured, and the bene-
fits of collaboration could not be evaluated. Taherian
(2013) developed a practical guideline for compa-
nies that intend to engage in the horizontal collabo-
ration. Taherian (2013) evaluated the benefits of the
total savings by a network synergy of 6 companies
that were engaged in the horizontal collaboration.
The limitation of this research is that Taherian (2013)
did not evaluate the performance indicators other
than the cost savings.
Audy et al. (2010) and Frisk et al. (2010), on the other
hand, used a different approach to develop a policy in
the strategic level by proposing an agreement among
collaborative parties on how cost savings could be

shared among them. Both research pointed out the
cost could be shared among collaborative parties,
and the impact of cost sharing could be evaluated.
The limitation of the research conducted by Audy et
al. (2010) is that they excluded the evaluation on how
cost savings could be shared among collaborative
parties. On the other hand, Frisk et al. (2010) evaluat-
ed the impact of cost sharing more comprehensively
on backhauling, time periods, geographical distri-
butions, and coalition sizes. The limitation of the re-
search (Audy et al., 2010; and Frisk et al., 2010) is that
they excluded the negotiation process when the com-
panies have different negotiating powers. They also
did not evaluate how information was shared among
collaborative parties,, how collaborative parties inter-
acted, and how trust among collaborative parties is
maintained, and how cost was shared equally.
Liu et al. (2010) demonstrated a profit allocation
mechanism among collaborative parties to ensure the
establishment and sustainability of the alliance for
small and medium sized LTL carriers. The results of
the simulation for the real-life data showed the effec-
tiveness of the proposed model. However, due to the
limitation of the horizontal collaboration in the trans-
portation industry, the research conducted by Liu
et al. (2010) only used three carrier companies as its
samples. Therefore, this research needs to adopt the
model that is proposed for the practical application.
The decisions in this level include taking orders for
shipment and the movement of goods from a point
of origin to a destination point. Only two research-
ers (Peeta and Hernandez, 2011; and Nadarajah,
2008) developed a route models for the operation-
al level. Peeta and Hernandez (2011) explored the
LTL collaboration from the perspective of small to
medium-sized LTL carriers. This research indicated
that the carrier collaboration increased the capacity
utilization thereby increasing the revenue of emp-
ty-haul trips and decreasing the impacts to the fuel
cost. Peeta and Hernandez (2011) used a combina-
tion of multivariate techniques and the mixed logit
model to determine the probability of a carrier. The
significance of variables illustrates that LTL carriers
are concerned with the potential economic impacts
and the possibility of forming collaborative allianc-
es. The limitation of this research is that it did not
quantify and explore the impact of performance in-
dicators of collaborative parties on the benefits for
the parties engaged in the horizontal collaboration.
Nadarajah (2008), on the other hand, proposed a
carrier collaboration framework in order to reduce
deadhead miles and to increase carriers’ revenue.
In addition, this research explores CTM related to
green transportation by showing that CTM can re-
duce congestion and pollution by using metaheuris-
tics as its solution method. However, Nadajarah
(2008) did not explore how the collaborative parties
interact to one another in order to align each collab-
orative party’s own objectives.
4.3 Lateral Collaboration
Many companies get involved in either the vertical
collaboration or horizontal collaboration. However,
combining both the vertical and horizontal collabo-
ration into practice is not easy to implement. The
objective of the lateral collaboration is to get the
benefits from both the vertical collaboration and
horizontal collaboration (Mason et al., 2007).
VICS (2004) and Sutherland (2006) used the frame-
work model to describe the variables that are rel-
evant to the transportation problems by using the
CTM approach as a guidance to solve the problems.
According to VICS (2004) and Sutherland (2006)
there are four key variables for CTM, and they ex-
plain what key enablers that facilitate the success of
CTM. Both research also reported the performance
benefits of CTM’s pilot initiatives in various compa-
nies and settings in the U.S. starting in 1999.
Ozener (2008) developed the network model and
combined it with the routing model. Ozener (2008)
developed his research in three stages. At the first
stage, the shippers offered continuous move routes
to the carriers in return for the reduction in per mile
charges. Both the second stage and the third stage
will be explained on the operational level. The limi-
tation of this study is that Ozener (2008) did not ex-
plore the negotiation process and did not explore
the risk that could be arising in an uncertain condi-
tion in both the network and route model.
On the other hand, Gonzalez-Feliu et al. (2013) de-
veloped an integrated approach between the vertical
and horizontal collaboration in transportation and
proposed a framework to support the main strate-
gic planning decisions from a group viewpoint. This
framework evaluates a strategic planning decision
based on a hierarchical cluster analysis and a deci-

sion ranking method by using five possible strate-
gies for collaborative transportation. Gonzales-Feliu
et al. (2013) showed that the method could be ap-
plied to support a group of heterogeneous decision
makers in implementing collaboration strategy.
However, the method was not able to capture both
the real interactions and the real negotiations in the
process. Its other performance criteria, such as the
quality and service accuracy in a strategic decision-
making also needs to be evaluated
Both the second stage and the third stage of the re-
search conducted by Ozener (2008) relate not only to
the development of the route model to reduce both
the transportation and distribution cost but also to
the evaluation of fair benefits sharing among them.
The example is the carriers exchange loads among
themselves to reduce empty repositioning and to in-
crease truck utilization. At the third stage, under the
vendor management inventory, the replenishment
among customers due to their locations, usage rates,
and storage capacities, may be exploited to reduce
the distribution costs. This model was developed
to serve the nearby customers on the same route at
the same time. One result of the research done by
Ozener (2008) showed that the proposed methods
performed significantly better than the proportional
allocation methods used in practice. Another result
also demonstrated that the proposed methods are
computationally efficient.
Mason et al. (2007) conducted three case studies to
illustrate the advantages of collaboration among
supply chain partners that used information tech-
nology system, such as: Internet and RFID. Several
performances that were evaluated in this research
were cost reduction, service levels, visibility, end
customer satisfaction, and many others. The limita-
tions of this research are that Mason et al. (2007) did
not evaluate the transportation performance indica-
tors, the risk arising from the information sharing
and information technology, and the interaction
among the parties who were engaged, and how trust
was developed and maintained by each party.
5. DISCUSSION
This paper reviews 27 articles gathered from Pro-
quest, Science Direct, Taylor and Francis database.
This paper also includes athe recommendation from
peers that relate to the description, implementa-
tion, planning levels, and methodologies of CTM,
and contribution of various CTM models. From 27
articles reviewed show the benefits of CTM on the
vertical, horizontal, and lateral collaboration. Vari-
ous performance indicators are evaluated to point
out the benefits of implementing CTM. Even though
all of the articles point out the benefits of CTM, there
are still some limitations of the previous research.
The vertical collaboration, also known as the tradi-
tional collaboration, is the most well formed type
collaboration used in the area of CTM. However
there are several limitations existing in the current
literatures. Wen (2012), Caplice and Seffi (2003), and
Kayikci (2009) developed a strategic partnership
model although quantifying the benefits and im-
pacts of CTM on the carriers and supply chain part-
ners was not integrated into it. However, previous
researchers only identified the benefits and impacts
of CTM by indicating several performance indicators
without analyzing the interactions and relationships
of a partnership’s elements, such as: commitment,
trust management of collaborative parties, conflict
resolution, and risk sharing. On the other hand,
Silva et al. (2011) tried to explore the shortcomings
of previous literatures by examining the interactions
among collaborative parties and benefits of CTM.
In tactical level, only one article was found. It was
written by Feng et al. (2005). They developed a car-
rier assignment model to evaluate effects of CTM on
the supply chain, such as: total costs and transpor-
tation capacity utilization. Nevertheless, there is no
complete analysis of actual CTM in evaluating up-
stream suppliers of manufacturers and downstream
retailers or customers of the distributors to obtain
more real effects of CTM on the supply chain. More-
over, no literature discusses the research in the order
and shipment forecasting model.
Some research has been dedicated to develop order-
processing models to point out the benefits of CTM
(Tyan et al., 2003; Esper and William, 2003; Feng and
Yuan, 2007; and Chen et al., 2010). However, point-
ing out the benefits of CTM is not enough only by
presenting how CTM works in the operational level.
Li and Chan (2012), on the other hand, seem to an-
swer the shortcomings of the previous research by
showing the operational interactions among sup-
ply chain partners under a demand disruption. This
research only explored one risk in the supply chain
and used a virtual company as its calculation basis.
Several risks, such as technology risks and opera-
tional risks, arise from the collaborative transporta-

tion, particularly when it relates to the order pro-
cessing model was not explored.
The horizontal collaboration has been gaining at-
tention as a new business model that can make the
transportation and logistics sector more efficient, ef-
fective, and sustainable. However, until today there
are still limitations related to the horizontal collabo-
ration in practice and research area due to its com-
plex nature. All previous research focused on the
horizontal collaboration at the strategic level only
developed strategic partnership models. Asawa-
sakulsorn (2009) and Taherian (2013) did not evalu-
ate the performance indicators except for the cost
savings on the horizontal collaboration. Audy et al.
(2010), Fisk et al. (2010), and Liu et al. (2010) pro-
vided the evaluation of performance indicators on
the horizontal collaboration. However, they did not
evaluate information sharing process, interactions
among collaborative parties, and trust management
that related to information sharing among collabor-
ative parties in order to share the cost equally.
On the other hand, Peeta and Hernandez (2011) de-
veloped a route model, but this research did not
quantify and explore the impact and the benefits of
CTM in the horizontal collaboration. In addition,
the research done by Nadarajah (2008) showed
that by conducting CTM, congestion and pollution
could be reduced. The limitation of the research
in the horizontal collaboration, particularly at the
operational level, is that the research emphasized
neither on the interaction and information sharing
among all parties in the collaboration nor on how
the uncertainty in operational process could impact
the decision-making.
In order to manage the transportation within the
supply chain setting, it is important to understand
the characteristics of modern supply chain manage-
ment by combining both the horizontal and vertical
forms of collaboration (Mason et al, 2007). The lateral
collaboration is also being exploited as a new collab-
oration approach to create superior value adding so-
lutions to many supply chains. In the strategic level,
VICS (2004) and Sutherland (2006) used the frame-
work model to give guidance for a decision-making
to use the CTM models in each planning level and
in selecting partners for CTM, as one of the stages
in the strategic level. In addition, Gonzalez-Feliu et
al. (2013) developed a decision-making model in the
strategic level. However, Gonzalez-Feliu et al. (2013)
did not take into account the negotiation process, in-
formation sharing, interactions among collaborative
parties, trusts management, and risk management
as the foundations in a decision-making process.
Concerning the operational level, Mason et al. (2007)
illustrates that the use of information technology
will increase the performance indicators in CTM.
However, he did not quantify the performance in-
dicators. Therefore, it is difficult to evaluate how
significant the advantages of collaboration for each
party are. Mason et al. (2007) also did not evaluate
the risks arising from the information sharing and
information technology that were used by all par-
ties, the interactions that happened among the col-
laborative parties, and the trust management that
was built in the collaboration process. In addition to
several limitations explained previously, no one has
done research in the tactical level both in the hori-
zontal and lateral collaboration. For this reason, any
research in this area will give a better understanding
on how CTM can be developed in the tactical level.
Based on the above-mentioned categories, there are
six research gaps that are found from previous lit-
eratures. The first research gap is that many of the
previous research only focused on the optimization
of CTM, causing a gap in the exploration of the be-
haviors and the interactions among parties involved
in CTM. Therefore this gap prevents a more realis-
tic understanding on the CTM. The behaviors and
interactions among the collaborative parties may
significantly influence how operating systems work,
perform, and improve (Gino and Pisano, 2008). The
second research gap is the limitations regarding the
integration of an information structure, based on
information sharing, into CTM. Such integration is
necessary to formulate a foundation to develop a de-
cision in each planning level and each stage of the
collaboration process in order to improve the visibil-
ity and the accuracy of a decision-making.
The third research gap is that all previous research
did not explore the integration of decision-making
into the models in order to get a better result in
implementing CTM. Distributed decision-making
among collaborative parties leads to increasing agil-
ity by synchronizing decisions for each collaborative
party that has different objectives and different per-
spectives (Wadhwa and Rao, 2003).
The fourth research gap is that the previous lit-
eratures did not explore how to integrate different
stages of the collaboration process into CTM. Inter-
dependent stages of collaboration process among
collaborative parties are necessary to be developed

in order to capture the interactions among the col-
laborative parties involved in a transportation plan-
ning and execution processes.
The fifth research gap is that all previous literatures
did not explore and evaluate the incentive align-
ment to share risks and benefits for all collabora-
tive parties equally. The incentive alignment can be
used as an instrument for motivating and inducing
all collaborative parties involved in CTM to join the
collaboration by sharing costs, risks, and rewards.
The last research gap is that all the previous litera-
tures already explored several performance indica-
tors to capture the benefits of CTM for all collab-
orative parties. However, the previous literatures
did not explore and evaluate how value co-created
among collaborative parties, based on customer val-
ue and customer expectations, become the benefits
of CTM other than the performance metrics.
To address these research gaps, a proposed frame-
work is developed based on the characteristics of
behavior, hierarchical decision-making processes, a
soft system approach, and collaborative approach.
Behavioral in Operation Management is defined as
the study of human behavior and cognition and
their impacts on operating systems and processes
(Gino and Pisano, 2008). Carter et al. (2007) also
mention that the aim of behavior in Operation Man-
agement is to understand people’s decision-making
processes in order to improve the operation of the
supply chain. A hierarchical decision-making process is
a decision system in which multiple decision makers
are involved in a business process and in which it
has a strategic, tactical, and operational levels (Liu,
2010). This hierarchical decision-making process is
designed by decisions of each level based on certain
rules and behaviors of each individual involved in
each collaborative structure. Soft system is also used
when facing a dynamic and unpredictable situation
as well as when goals and objective cannot clearly
qualify (Checkland, 2001). Soft system is applied to
analyze problem situations in which human percep-
tions, behaviors, or actions are dominating factors so
that the goals can be negotiable (Checkland, 2001).
In addition, collaboration approach, in several stages,
is used in order to capture the interactions, actions,
and the effects of decision-making in CTM. The col-
laboration stages, namely forming, preparation,
design, planning, implementation, and evaluation
stage, were adopted from Dwyer et al. (1987).
The behaviors of multi-agent’s hierarchical decision-
making process, as the proposed framework, can be
seen in Figure 4. The proposed framework helps to
understand and explore the behaviors of the collab-
orative parties in CTM, the interaction with other
parties, and the parties’ abilities to make decision in
strategic, tactical, and operational level in meeting
the goals in each collaboration structure (i.e. verti-
cal, horizontal, and lateral). The behavioral aspect
for hierarchical decision-making process in CTM is
developed in order to deliver services that lead to
value co-creation of collaborative parties. In addi-
tion, the proposed framework is also developed to
gain a systematic understanding of how and when
different objectives and perspectives of collaborative
parties affect decision-making process in each col-
laborative structure.

Figure 4. The Proposed Framework of The Behaviors of
Multi-agent’s Hierarchical Decision-Making Processes

6. CONCLUSIONS
Academics and practitioners recognize CTM as a
business strategy to eliminatie inefficiencies in the
transportation component. Despite the growing in-
terest in CTM, there are several issues that remain
unaddressed. There are 27 articles that have been
reviewed and classified based on four categories.
The first category is based on the different collabora-
tive structures, namely: the vertical, horizontal, and
lateral collaboration. The second category is based
on the general characteristics of fundamental issues
and collaboration mechanisms. The third category is
based on the time horizons of collaborative planning
levels such as the strategic, tactical, and operation-
al level. The last category is based on the solution
method used to solve the problems that are ap-
proached by CTM models. Based on the systematic
reviews, several research gaps have been outlined.
Future research on CTM could be taken by develop-
ing behavioral models in order to capture the inter-
actions among collaborative parties. Future research
should also be focused on the integration of the in-
formation structure into both a collaboration process
and a hierarchical decision-making. Future research
can also be focused on using an incentive alignment
to persuade collaborative parties to behave in ways
that are best for all by distributing the risks, costs,
and rewards fairly among the involved parties. In
addition, how useful is the value co-creation of CTM
for all collaborative parties can be evaluated.
For future research an agent-based simulation can be
proposed as a solution method for a CTM model. This
simulation can be used to represent all the details and
behaviors of collaborative parties in each collabora-
tive planning level. Furthermore, this simulation can
also be used to re-create and enhance the ability to
understand, predict, and control a decision-making
for the CTM that uses a behavioral approach.
7. REFERENCES
Asawasakulsorn, A. (2009). Transportation Collaboration: Part-
ner Selection Criteria and Inter-Organizational System (IOS)
Design Issues for Supporting Trust. International Journal of
Business and Information, 4 (2), 199–220.
Audy, J.F., D’Amours, S. & Rönnqvist, M. (2006). Business Mod-
els for Collaborative Planning in Transportation: An Appli-
cation to Wood Products. Frontiers of E-Business Research.
Audy, J.F., D’Amours, S., &. Rousseau, L.M. (2010). Cost allo-
cation in the establishment of a collaborative transportation
agreement-an application in the furniture industry. The Jour-
nal of the Operational Research Society, 62 (6), 960–970.
Bishop, S.B. (2002). Collaborative transportation management
benefits. 2001 Annual Conference Proceedings.
Browning, B., & White, A. (2000). Collaborative Transportation
Management. Logility Inc. http://www. vics. Org (accessed
October 4, 2013).
Caplice, C., & Sheffi, Y. (2003). Optimization-Based Procurement
For Transportation Services. Journal of Business Logistics, 24
(2), 109–128.
Carter, C. R., Kaufmann, L., & Michel, A. (2007). Behavioral Sup-
ply Management: A Taxonomy of Judgment and Decision-
Making Biases. International Journal of Physical Distribution
and Logistics Management, 37(8), 631–669.
Chan, F.T.S., & Zhang, T. (2011). The impact of collaborative
transportation management on supply chain performance: A
simulation approach. Expert Systems With Applications. March
38 (3), 2319-2329.
Chen, D.J., Chen, H.C., & Lai, S.H. (2010). The Effect of Adopt-
ing Collaborative Transportation Management by Taiwanese
Computer Manufacturers- Model Building and Empirical
Studies. International Journal of Information and Management
Sciences, 21, 481-499.
Checkland, P.B. (2001). Soft Systems Methodology in Action. John
Wiley & Sons. England.
Dwyer, R.F., Schurr, P. H., & Oh, S. (1987). Developing Buyer-
Seller Relationships. The Journal of Marketing, 51 (2), 11-27.
Ergun, O., Kuyzu, G., & Savelsbergh, M. (2007). Reducing Truck-
load Transportation Costs Through Collaboration. Transpor-
tation Science, 41(2), 206–221.
Esper, T.L., & Williams, L.R. (2003). The value of Collaborative Trans-
portation Management (CTM): its relationship to CPFR and In-
formation Technology. Transportation Journal, 42 (4), 55–65.
Feng, C.M., Yuan, C.Y., & Lin, Y.C. (2005). The System Frame-
work For Evaluating The Effect Of Collaborative Transpor-
tation Management On Supply Chain. Journal of the Eastern
Asia Society for Transportation Studies, 6: 2837–2851.
Feng, C.M., & Yuan, C.Y. (2007). Application of collaborative
transportation management to global logistics: An interview
case study. International Journal of Management, 24 (4), 623–636.
Frisk, M., Gothe-Lundgren, M., Jornsten, K., & Ronnqvist, M.
(2010). Cost Allocation in Collaborative Forest Transporta-
tion. European Journal of Operational Research, 205 (2), 448–458.
Gereffi, G., Humphrey, J., & Kaplinsky, R. (2001). Introduction: Glo-
balisation, value chains and development. IDS bulletin, 32 (3), 1-8.
Gino, F., & Pisano, G. (2008). Toward a Theory of Behavioral Op-
erations. Manufacturing & Service Operations Management, 10
(4), 676–691.
Gonzales-Feliu, J., & Morana, J. (2011). Case study from France.
Technologies for Supporting Reasoning Communities and Collab-
orative Decision Making: Cooperative Approaches, 252–271.
Gonzalez-Feliu, J., Morana, M., Grau, J.M.S., & Ma, T.Y. (2013).
Design and scenario assessment for collaborative logistics
and freight transport systems. International Journal of Trans-
port Economics, 207–240.

llyas, R.M., Shankar, R., & Banwet, D. K. (2005). Interventional
Roadmap for Digital Enablement Leading to Effective Value-
chain Management in the Manufacturing Sector. Global Busi-
ness Review, 6 (2), 207–229.
Kayikci, Y. (2009). Performance Improvement In Intermodal
Freight Transportation System Through Efficient Collabora-
tive Transportation Management. Proceedings of the 14th In-
ternational Symposium on Logistics, 701–709.
Li, J., & Chan, F.T.S. (2012). The impact of collaborative transpor-
tation management on demand disruption of manufacturing
supply chains. International Journal of Production Research,
50(19), 5635–5650.
Liu, P., Wu, Y., & Xu, N. (2010). Allocating Collaborative Profit
in Less-than-Truckload Carrier Alliance. Journal of Service Sci-
ence & Management, 3 (1), 143–149.
Mason, R., Lalwani, C., & Boughton, R. (2007). Combining verti-
cal and horizontal collaboration for transport optimization.
Supply Chain Management: An International Journal, 12 (3),
187–199.
Meyr, H., Wagner, M., & Rohde, J. (2005). Structure of Advanced
Planning Systems” Supply Chain Management and Advanced
Planning, 109–116. Springer Berlin Heidelberg.
Min, S., Roath, A.S., Daugherty, P.J., Genchev, S.E., Chen, H.,
Arndt, A.D., & Richey, R.G. (2005). Supply chain collabora-
tion: what’s happening. The International Journal of Logistics
Management, 16 (2), 237–256.
Moll, S.M. (2012). Productivity Improvement For Freight Rail-
ways Through Collaborative Transport Planning. Disserta-
tion ETH ZURICH.
Nadarajah, S. (2008). Collaborative Logistics in Vehicle Routing.
University of Waterloo.
Nag, R., Hambrick, D.C., & Chen, M.J. (2007). What is strategic
management really? Inductive derivation of a consensus
definition of the field. Strategic Management Journal, 28 (9),
935–955.
Ozener, O. (2008). Collaboration in Transportation. Georgia In-
stitute of Technology.
Peeta, S., & Hernandez, S.H. (2011). Modeling of Collabora-
tive Less-than-truckload Carrier Freight Networks. USDOT
Region V Regional University Transportation Center Final
Report.
Prakash, A., & Deshmukh, S.G. (2010). Horizontal Collaboration
in Flexible Supply Chains: A Simulation Study. Journal of
Studies on Manufacturing, 1(1), 54-58.
Silva, V.M.D., Coelho, A.S., & Novaes, A.G.N. (2011).The role of
collaboration through manufactured goods’ exportation pro-
cess under System Dynamics analysis. Proceedings of the 29th
International Conference of The System Dynamics Society, 24–28.
Simatupang, M.T., & Sridharan, R. (2002). The Collaborative
Supply Chain. The International Journal of Logistics Manage-
ment, 13(1),15–30.
Song, J., & Regan, A.C. (2003). An Auction Based Collaborative
Carrier Network. Transport Research Part E: Logistics and
Transportation Review, 2.
Soosay, C.A., Hyland, P., & Mario, F. (2006). Supply chain collab-
oration: capabilities for continuous innovation. Supply Chain
Management: An International Journal, 13 (2), 160–169.
Sutherland, J.L. (2003). Collaborative transportation manage-
ment– creating value through increased transportation effi-
ciencies. Business Briefing – Pharmagenerics.
Sutherland, J.L. (2006). Collaborative transportation manage-
ment: A solution to the current transportation crisis. CVCR
white paper 602. Lehigh University, Pennsylvania, U.S.A.
Taherian, H. (2013). Outbound Transportation Collaboration-Do
It Yourself (DIY). Thesis Engineering System Division, MIT.
Tyan, J.C., Wang, F.K., & Du, T. (2003). Applying collaborative
transportation management in global third party logistics.
International Journal of Computer Integrated Manufacturing,
16(4-5), 283–291.
VICS (CTM sub-committee of the voluntary inter-industry
commerce standards logistic committee). (2004). Collabora-
tive Transportation Management White Paper. Version 1.0.
http://www.vics.org (accessed October 4, 2013).
Wadhawa, S., & Rao, K.S. (2003). Flexibility and agility for enter-
prise synchronization: knowledge and innovation manage-
ment towards flexibility. Studies in Informatics and Control, 12
(2), 111-128.
Wen, Y.H. (2012). Impact of collaborative transportation man-
agement on logistics capability and competitive advantage
for the carrier. Transportation Journal, 51 (4), 452–473.
Zamboni, S. (2011). Supply Chain Collaboration and Open In-
novation: Toward a New Framework for Network Dynamic
Innovation Capabilities. Universita Degli Studi Di Bergamo.

APPENDIX 1. A List of Previous Literatures Review
AUTHOR MAIN OBJECTIVE OF THE PAPER
APPLICATION OF THE
MODELS
Tyan et al. (2003)
Analyze an effective collaboration in global
supply chain (GSC) execution to reduce
delivery time and improve delivery reliability.
3PL provider in a notebook
computer GSC
Esper and William
(2003)
Portray the holistic value of supply chain
collaboration by discussing CTM and the role
of information technology and its benefits.
Case study: 3PL Transplace
Caplice and Seffi
(2003)
Analyze the optimization-based procurement
process to securing and managing a strategic
relationship.
US truckload (TL) transportation
Feng et al. (2005)
Evaluating the benefits of CTM by simulating
3-scenario model on the manufactures,
distributions and carriers in supply chain.
Manufacturer-Carier-Distributor
in Taiwan
Audy et al. (2006)
Design a framework to describe collaboration
in transportation, and a different business
models associated with collaboration in
transport are proposed.
Five industrial application in
wood fiber transportation
Ergun et al. (2007)
Generate optimization technology to assist
in the identification of repeatable, dedicated
truckload continuous move tours with little
truck repositioning.
US Industry
Feng and Yuan (2007)
Analyze the application integrating CTM
with enterprise resource planning (ERP)
via information technology (IT) to facilitate
transportation capacity planning and achieve
prompt delivery within the shortest time
possible.
First International Computer Inc
and UPS Taiwan branch
Kayikci (2009)
Evaluate performance outcomes depend on the
communication quality, long-term orientation
and satisfaction, the quality of information and
the intensity of joint information sharing.
Different industries in Europe
both transport users and transport
service providers
Chen et al. (2010)
Explore the cost difference after the computer
industry introduced CTM and the association
analysis between the inventory element and the
transportation element.
TFT–LCD

APPENDIX 1. A List of Previous Literatures Review (Cont.)
APPLICATION OF THE
MODELS
Silva et al. (2011)
Analyze the behavior of the collaboration
in order to reduce freight costs.
Maritime logistics of
manufacture export
companies in Brazil
Gonzalez-Feliu
and Morana
(2011)
Develop a conceptual schema focus on
socio-economic and legislative aspects
in order to define the main concepts
related to logistics sharing agreements
that representing the most important
organizational aspects.
French press distribution
sector
Li and Chan
(2012)
Determine the impact of CTM on the
performance of manufacturing supply
chains using two supply chain models
(with and without CTM) in order to
show the impact of CTM under demand
disruption.
Virtual Companies
Moll (2012)
Identified and assessed twelve potential
forms of collaborative approaches in order
to improve the efficiency of locomotives
and train drivers, the effectiveness of
single wagon load trains, and also increase
freight rail productivity.
SBB Cargo-Swiss Freight
Railway
Wen (2012)
Examine the impacts of CTM on logistics
capability and competitive advantage
of carriers within a supply chain, and
analyzes the relationships between
logistics capability and competitive
advantage.
The carriers and
transportation service
providers in Taiwan
Song and Regan
(2003)
Examine and develop a new auction
based carrier collaboration mechanism
for complex decision problems associated
with subcontracting, bidding, and bid
selection are investigated.
Trucking industry in US
Nadarajah (2008)
Develop simple examples where a firm
can enhance its transportation efficiencies
through Less-than-Truckload collaboration
to reduced cost and improved customer
service.
Less-Than-Truckload (LTL)

APPLICATION OF THE
MODELS
Asawasakulsorn
(2009)
Develop partner selection criteria
during the formation stage based on
economic, social perspectives, and inter-
organizational system (IOS) design factors
regarding trust.
Shipper and carrier
company in Thailand
Fisk et al. (2010)
Evaluate sharing mechanisms and propose
a new allocation method, with the aim
that the participants relative profits are as
equal as possible.
Forest industry in Sweden
Liu et al. (2010)
Develop the LTL collaboration game and
propose allocation method to distribute
profits/savings among the participants that
are fair, reasonable, and easy
to implement.
LTL industry
Audy et al. (2010)
Evaluate different coordination
mechanisms scenarios to ensure cost and
delivery time reductions as well as gain in
market geographic coverage.
Canadian furniture
industry
Peeta and
Hernandez
(2011)
Modeled LTL collaborative paradigms
from the supply and demand perspectives
to identify potential collaborative
opportunities and encourage collaboration
by increasing capacity utilization for
member carriers.
Less-Than-Truckload (LTL)
Taherian (2013)
Design a practical guideline to engage
in collaboration by Do-It-Yourself
(DIY) approach and focus on passive
collaboration by addressing how to qualify
potential collaboration partners, how to
evaluate the associated savings, and how to
make it work.
LTL and TL shipments
VICS (2004)
Provides an overview of CTM, a process
for bringing trading partners and
transportation service providers together
for the sake of “win-win” outcomes among
all parties.
Various companies in US
as pilot project
Sutherland
(2006)
Demonstrate how supply chain partners
collaborate on transportation process
become more adaptable to day-to-day
demand changes as well as resilient in the
event of major supply chain disruptions
Various companies in US
as pilot project

APPLICATION OF THE
MODELS
Mason et al.
(2007)
Demonstrate that lateral collaboration are
emerging for better transport optimization,
that exploit the competitive power of
collaboration, both vertically with supply
chain partners and horizontally with other
logistics service providers (LSPs).
The road freight transport
industry in the UK and
Europe
Ozener (2008)
Develop framework and evaluate
collaborative approaches to identify
collaborative opportunities among
shippers and among carriers to reduce
transportation cost and distribution cost.
Industrial gas company
in US
Gonzalez-Feliu et
al. (2013)
Determine collaborative freight transport,
its links with supply chain management,
and aims at framing an assessment method
to help decision makers in strategic
collaborative logistics, transport design,
and planning.
LTL transport operators
Liane Okdinawati is a PhD Student at the School of Business and Management in Bandung Institute of
Technology, Indonesia. Her research interest is focus on transportation management, collaboration transpor-
tation, and interaction among parties in supply chain management that related to transportation areas. She
took her Master degree in Transportation Department in Bandung Institute of Technology.
Togar M. Simatupang is a Professor of Operations and Supply Chain Management at the School of Business
and Management in Bandung Institute of Technology. He received his PhD degree from Massey University,
New Zealand. He has extensively published in logistics and supply chain management journals. He has been
attributed Highly Commended Award by Emerald Literati Network for his research in SCM.
Yos Sunitioso is an assistant professor at the School of Business Management. He graduated from a doctoral
study at University of the West of England (UWE) Bristol. He has research interest the social-psychological
aspects of decision-making and behavior, sustainability, and the application of agent-based modeling and
simulation. The results of his research have been published in several journals.

Building Resilient Supply Chains Through Flexibility:
a Case Study in Healthcare
Marcelo Bradaschia
Fundação Getulio Vargas - EAESP
mbradaschia@gmail.com
Susana Carla Farias Pereira
Fundação Getulio Vargas – EAESP
Susana.pereira@fgv.br
ABSTRACT: This research seeks to understand how the capability of flexibility manifests itself for the
formation of resilience in service supply chains. The survey was conducted through a single case study
of a hospital chain that was impacted by the H1N1 pandemic in 2009. This analyzed chain was formed
by the hospital, doctors, nurses, the Ministry of Health, State Secretary of Health of São Paulo and the
pharmaceutical industry. As a result, the following categories of flexibility manifestation were identi-
fied: redesign, alteration/creation, prioritization, redundancy/availability/robustness and elimination.
120

Bradaschia, M., Pereira, S. C. F.: Building Resilient Supply Chains Through Flexibility:a Case Study in Healthcare
1. INTRODUCTION
The increased competition and pressure for con-
stant innovations led companies to seek efficiency in
its operations and chains (CHRISTOPHER; PECK,
2004). Because of that, companies have become lean-
er in their processes, reducing inventories and ac-
tivities with fewer maneuver options; increased the
outsourcing activities in order to focus on its core
business, thus increasing the amount of links in the
chains, making it longer and more complex; and,
sought lower costs and higher quality, causing sev-
eral activities to be located in other countries, frag-
menting the chains in political contexts, economics
and diverse societies (BLACKHURST et al., 2011;
CRAIGHEAD et al., 2004; PETTIT et al., 2013; PET-
TIT et al., 2010).
The mere existence of supply chains already make
them exposed to suffering disruptions, and since
these factors described serve to increase their vul-
nerability, negative reflexes can appear in all their
links, even to the final consumer (CRAIGHEAD et
al., 2007; PONOMAROV; HOLCOMB, 2009).
Generally speaking, in recent years the research re-
lated to Supply Chain Risk Management focused
on the study of strategies for risk mitigation either
by reducing the probability of the occurrence of ad-
verse events to the chain or on mitigating its effects
once they happen, with the understanding that they
can be anticipated (JÜTTNER; MAKLAN, 2011). On
the other hand, the increasing occurrence of dis-
rupting events has led researchers and executives to
question this traditional look of risk management,
where normally they do not consider risks with low
probability of occurrence or uncertainty, or events
that cannot be anticipated (JÜTTNER; MAKLAN,
2011; PETTIT et al., 2013; PETTIT et al., 2010). In ad-
dition, the strategy to evaluate and develop plans
for mitigating each of the potential risks could prove
to be expensive and time consuming, often times not
taking priority in a day to day corporate schedule
(PETTIT et al., 2010).
In this regard, recent research has been devoted to
understanding factors that make a supply chain
resilient in different situations, in order to cover
this gap in traditional research of risk (JÜTTNER;
MAKLAN, 2011; PETTIT et al., 2013; PETTIT et
al., 2010). Resilience of supply chains is defined as
“The adaptive capacity of the supply chain to pre-
pare for unexpected events, respond to disruptions,
and recover from them by maintaining continuity
of operations at the desired level of connectedness
and control over structure and function” (PONO-
MAROV; HOLCOMB, 2009, p. 131). Despite the in-
crease in the number of written works on the topic,
understanding the factors that enable or form the
resiliency is still in its infancy (BLACKHURST et
al., 2011).
Recent work has positioned resilience as a charac-
teristic of the company or supply chain, originated
from capabilities (BRANDON-JONES et al., 2014;
JÜTTNER; MAKLAN, 2011; PETTIT et al., 2013; PET-
TIT et al., 2010), formed in an idiosyncratic manner
from practices and resources (WU et al., 2010). Also
under this vision of capabilities, there are still differ-
ent views about which are responsible for forming a
resilient supply chain, being the most cited collabo-
ration, visibility and agility (CHRISTOPHER; PECK,
2004A; JÜTTNER; MAKLAN, 2011; SCHOLTEN et
al., 2014). On the other hand, there are other capa-
bilities in the literature that do not have share con-
sensus among different authors, such as the ability
to re-design the supply chain (Christopher & Peck,
2004), velocity (JÜTTNER; MAKLAN, 2011), agility
and flexibility (PETTIT et al., 2013b).
However, the capability of flexibility is considered
by many authors as fundamental to the forma-
tion of resilient chains as it is responsible for creat-
ing options for the supply chain and the different
nodes involved to deal with problems (JÜTTNER;
MARKLAN, 2011; SCHOLTEN et al., 2014; BLACK-
HURST et al. 2011; TANG; TOMLIN, 2008; PETTIT
et al., 2010). On the other hand, as far as has been
verified, there are no studies focused on the forms of
manifestation of this capability.
This research seeks to answer the following ques-
tion: how does the capability of flexibility manifest
itself contributing for the formation of resilient sup-
ply chains?
As context, a healthcare chain that was affected by
the H1N1 pandemic that struck Brazil in 2009 was
analyzed. The study is based on a single case study
of a healthcare supply chain from a well-recognized
hospital in the city of São Paulo, that was positioned
as the focal company of the supply chain, and other
links, such as the Ministry of Health, State Secretary
of Health of São Paulo and the pharmaceutical in-
dustry responsible for the production and commer-
cialization of the anti-viral medicine used for pro-
phylaxis and the treatment of the disease.

2. REVIEW OF THE LITERATURE
This section will present the theoretical review re-
lated to resilience and the capability of flexibility.
2.1 Resilience in Supply Chains
In recent years, some authors began to argue that tra-
ditional models of risk management are not capable
of addressing risks of disruption since many of them
cannot be anticipated or a specific strategy to miti-
gate them can be economically unviable (JÜTTNER;
MAKLAN, 2011; JÜTTNER et al., 2003; MITROFF;
ALPASLAN, 2003; PETTIT et al., 2010). For this rea-
son, another line of research has been deepening in
the understanding of resilience in order to under-
stand what allows certain chains to pass through
situations of disruption, suffering less impact than
others, and rapidly returning their operations to the
desired situation.
According to the vision of Jüttner and Maklan
(2011) the reduction of the probability of occur-
rence of risk, although it also may lead to a reduc-
tion in vulnerability, does not necessarily have an
effect on the increasing of the resilience since, in
the event of risk becoming reality, the company
can suffer from drastic consequences. Thus, ac-
cording to these authors, resilience is related to
the mitigation of the effects of risk, whether in re-
lationship to its gravity or its recovery time, and
not to the reduction of the likelihood of its occur-
rence.
The essential factor for resiliency of a supply chain is
its ability to adapt so that it can return the operations
to the desired state (PONOMAROV; HOLCOMB,
2009). In this sense, some works position resilience
as a multidimensional capability.
The discussion of the concept of capabilities has
been refined in recent years, inserted into the
theoretical lens of RBT (Resource Based Theory)
(BARNEY 1991; PETERAF 1993) and its evolutions
(TEECE et al., 1997; BARNEY 1996, 2001; PETER-
AF; BARNEY, 2003).
Although there is no consensus about the capabili-
ties that form resilient supply chains, several works
consider that flexibility is one of the most essential to
its formation (CHRISTOPHER; PECK, 2004; SHEF-
FI; RICE, 2005; JÜTTNER; MARKLAN, 2011; PET-
TIT et al., 2013; SCHOLTEN et al., 2014).
2.2 Flexibility
Jüttner and Marklan (2011) define the capability of
flexibility as “The ease with which a supply chain
can change its range number (i.e. the number of pos-
sible “options”) and range heterogeneity (i.e. the
degree of difference between the “options”) in or-
der to cope with a range of market changes/ events
while performing comparably well” (p. 251). Skip-
per and Hanna (2009) discuss that flexibility is usu-
ally related to the immediate ability of adapting to
new situations. Therefore, the existence of flexibility
in disrupting events is important since it offers alter-
natives for the supply chain to circumventing situa-
tions which hamper the implementation of activities
that are essential to its operation.
For example, Pettit et al. (2013, p. 49) point out that
flexibility in the provision and execution of orders
are important to the supply chain. For provisioning,
flexibility is defined as the ability of the supply chain
or its entities to quickly change its sources or ways
of receiving input. Flexibility in the execution of or-
ders is the ability of the chain or its entities to quickly
change the outputs or the way it delivers its orders.
The authors also describe adaptability, defined as
the ability to modify operations, as important to re-
silience, reinforcing the definition of flexibility pre-
sented earlier of Jüttner and Marklan (2011).
In order for flexibility to exist, it is necessary that
resources are available and there is ability to coor-
dinate them so they may become options to the situ-
ation. The coordination of resources, according to
Craighead et al. (2007), can occur before or after the
occurrence of the disruptive event, which suggests
that flexibility can be planned and have its execu-
tion previously operationalized or articulated. In
this sense, the existence of contingency plans can in-
crease the level of flexibility of a company, reinforc-
ing its importance in the mitigation phase of disrup-
tion (SKIPPER; HANNA, 2009).
The modularization of processes and design of prod-
ucts, for example, is a way to increase the agility and
flexibility, to the extent that it can bring alternatives
for reassessing the production lines (KLEINDOR-
FER & SAAD, 2005; TANG 2006).
Various practices described by Tang et al. (2006)
can increase the flexibility of companies and sup-
ply chains, as for example: the postponement of
production; the implementation of strategic stocks;
the use of a flexible supplier base; the use of the ap-

proach of make or buy; the planning of transport
alternatives; and the active management of revenue
and price, directing the consumption to products
with greater availability.
The resources used to achieve flexibility in supply
chains can be both tangible and intangible. An ex-
ample presented by Pettit et al. (2013) are financial
resources, which are important for the absorption of
oscillations in chains.
The use of security stocks is also described in the lit-
erature as being important for the formation of flex-
ibility in disruptive situations. One of the strategies
for self-protecting from disruptive events described
by Bode et al. (2011) is called buffering. This strategy
has a built-in view of the focal company, in the cre-
ation of self-protection mechanisms for dealing with
external events, working as a buffer to absorb shocks.
According to the authors, this can be based, for exam-
ple, in the use of security stocks, flexible production
processes, redundant suppliers, and the design of
products that are not dependent on just one supplier.
Differently, Sheffi and Rice (2005) believe that the use
of emergency stocks do not refer to the construction
of flexibility but for redundancy, which they regard
as distinct concepts. They argue that, although both
have a positive relationship with resilience, flexibil-
ity entails lower costs and could become a source of
competitive advantage. The argument comes from
the vision that flexibility does not involve the need
for idle resources, while redundancy does. Some
common examples in companies are the use of emer-
gency/security stocks, the use of a multiple base of
suppliers, even while causing a higher cost, or the
maintaining of slack operations. Similarly, Scholten
et al. (2014) distinguishes flexibility of redundancy.
Tang and Tomlin (2008) have already presented that
the existence of operational buffer enables flexibil-
ity. In this paper, the authors perform simulations to
identify the amount of flexibility necessary to deal
with risks of supply, demand and of process. In their
study, flexibility is positioned as a quantitative vari-
able, relating it to different practices, such as the use
of multiple vendors, the use of flexible supply con-
tracts, the use of flexible manufacturing processes,
the postponement of products in production lines
and the use of flexible pricing politics to influence
demand. The result shows that even the existence
of small levels of operational buffer is sufficient to
increase flexibility. This occurs once the existence of
this buffer reveals the interoperability of the opera-
tion, i.e. that different processes can be executed in
different locations. Jüttner and Marklan (2011) also
hold the view that the redundancy “is one of the
routes for flexibility.”
Christopher and Peck (2004) argue that the defini-
tion of supply risk mitigation is not only about the
decision to keep multiple vendors within the base,
but to understand the implications for the business,
since, in some situations, establishing a relationship
with a deep bond with the supplier may be the safest
strategy (BODE et al., 2011). The possibility of con-
version of an operation is also related to flexibility,
as in the case of migrating the operation to different
locations in case there is a problem with one of them
(CHRISTOPHER; PECK, 2004). The authors point
out the necessity of structuring supply chains that
maintain various open options in case a disruptive
event happens. Additionally, they reinforce that the
search for efficiency may not be the best decision,
but that maintaining redundancy in key processes
can be a better alternative.
At the individual level, Weick (1993) shows that the
ability of improvisation is important so that an or-
ganization can go through stressful situations, as
will be the case of a disruption. Improvisation in-
volves the ability to recombine available resources
for a specific task. In this vision of improvisation,
the author also includes creativity, defining it as the
ability to use what you already know in different
situations. In this way, creativity and, consequently,
improvisation, are related to flexibility, to the extent
that they are responsible for the increase in available
options for dealing with a given situation.
Sheffi and Rice (2005) argue that risk perception as
well as collaboration, play an important part in flexibil-
ity, since you usually cannot recover from a disruptive
situation without the involvement of different areas of
the business and entities of the supply chain, no matter
how close one is to the direct effects that affect it.
In addition to the points described related to the con-
struction of flexibility, there are others that can diffi-
cult its existence, such as strict internal and external
regulations, as well as the complexity and require-
ments of materials that make the amount of avail-
able options limited (BLACKHURST et al., 2011).
3. METHODOLOGY
The study on resilience in supply chains is still in
its infancy (BLACKHURST et al., 2011), therefore,

there is still a great deal of disagreement about the
concept and what composes the theme. This empiri-
cal research was carried out by a single case study
of a healthcare chain in Brazil. Single case studies,
despite having a smaller external validity, allow
the researcher to go deeper into the case (SIGGEL-
KOW, 2007). In addition, single cases are especially
relevant when they are regarded as critical, extreme
and revelatory of the question posed by the research
(MILES et al., 2013; YIN 2014).
For this research, the unit of analysis considered
was the service supply chain. The service supply
chain chosen for this research is embedded in the
context of health management and refers specifical-
ly to a hospital chain. As the main objective of this
chain is to provide care for patients, the hospital is
positioned as the focal company, considered as the
service provider (BALTACIOGLU et al., 2007). Ad-
ditionally, the context in which the unit of analysis
is embedded is the pandemic of the H1N1 virus that
struck Brazil in 2009.
The links that were selected were chosen in order
to represent the entities most affected or that influ-
enced by actions the H1N1 outbreak in 2009. The en-
tities selected were validated based on preliminary
interviews with health professionals involved in
H1N1 pandemic in 2009.
Hospital: the focal company to be studied from the
chain. Responsible for the care of patients, the hospital is
the last link in the supply chain, since problems that oc-
curred in previous links have the potential to impact pa-
tient care and, consequently, their goal of treating them.
Doctors: responsible for the diagnosis and medica-
tion of patients. Along with the nurses, they are on
the front line of care and have to deal with the day-
to-day situations.
Nurses: responsible for the treatments of the patient,
focused on their physical, social and mental well-being.
In this context, doctors and nurses are being consid-
ered as links in the chain and not only as hospital
staff workers, since in many situations these profes-
sionals provide services to more than one entity.
Pharmaceutical Industry: responsible for the sup-
ply of medicines for the treatment of patients. In the
case of this study, interviews were conducted with
industry professionals responsible for the supply of
Oseltamivir Phosphate, the main antiviral used for
the treatment of the H1N1 virus.
Secretary of Epidemiological Surveillance of the
Ministry of Health: responsible for the manage-
ment of the National System of Epidemiological
Surveillance and Environment in Health. There are
attributes of this body that should be highlighted:
the national coordination of epidemiological ac-
tions and disease control; technical assistance to the
states; provision of diagnostic kits; management
of epidemiological information systems, including
the consolidation of data from the states and the
dissemination of information and epidemiological
analyses; monitoring, supervision and control of the
implementation of the actions related to epidemiol-
ogy including the evaluation of the epidemiological
surveillance systems of the states (CONASS 2003).
State Secretary of Health of São Paulo (SES-SP)/
Center for Epidemiological Surveillance: the state
body that sets state health policies, in accordance
with the guidelines defined by the Unified Health
System (Sistema Único de Saúde – SUS) (CONASS
2003). The SES-SP has eight company departments,
including the Coordination of Disease Control
(CCD), whose mission is to “Coordinate the state
response to disease, aggravations and existing or
potential risks, within the framework of public
health, with emphasis on planning, monitoring,
evaluation, production and the dissemination of
knowledge, for the promotion, prevention and the
control of the health conditions of the population,
in line with regional characteristics and the princi-
ples and guidelines of SUS” (CONASS , 2003, p. 2).
Within this organization, you find the Epidemio-
logical Surveillance Center.
3.1 Sample Selection
Unlike quantitative analysis for the case studies, the
selection of the sample should not be random, as
in the case of quantitative research, but instead in
a theoretical way (EISENHARDT, 1989; YIN, 2014).
The choice of the object is related to the possibility of
the case contributing to the research question (STU-
ART et al., 2002), whereas the generalization sought
with the findings obtained through case studies is
not statistic, as in the case of quantitative research,
but analytical (YIN, 2014).
A hospital in São Paulo, considered to be highly
complex, was chosen for this work. This hospital is
considered to be one of the main Brazilian centers of
the dissemination of techno-scientific information,
known for being a center of excellence and reference

in the field of teaching, research and service. It has
more than 2,000 beds and 15,000 professionals in dif-
ferent areas of expertise. According to the social re-
action related to the H1N1 virus, this and other high
complexity hospitals were widely sought after by a
large volume of people for diagnosis and treatment
of the disease, raising the risk of disruptions in the
chain and becoming a relevant context to the study.
The health professionals who provide services to
the hospital were selected after interviews with
the administration team, so that professionals in-
dicated had a relevant participation in the defined
context.
As in the hospital, so in the other links, the inter-
viewed professionals were protagonists with rel-
evant roles in the preparation of mitigation plans or
during the pandemic of 2009. The specific positions
are not described in order to ensure the confidenti-
ality of the respondents, but all possessed roles as
directors, managers or supervisors of areas related
to the event. In total, sixteen semi-structured inter-
views were conducted.
One concern that existed in the conception of this
study was the fact that the H1N1 pandemic studied
took place almost five years ago, which could lead to
inaccuracies in the data collected. To mitigate these
problems, we used a large number of interviews,
apart from the information collected from differ-
ent links allowing triangulation of information. The
completion of the analysis with secondary informa-
tion also contributed to minimizing this problem.
3.2 Data Collection
In order to answer the research questions, the collection
of data was conducted through semi-structured inter-
views. The interviews lasted from 30 to 120 minutes,
and on average, they were 75 minutes long. All the in-
terviews were conducted in person and recorded with
previous authorization and subsequently transcribed
for use as sources of analysis. There was only one excep-
tion that was not recorded due to technical problems. In
this case, a memo was written right after the interview
in order to reduce the probability of losing content.
The transcripts were produced as close as possible
to the actual interviews by outsourced capable pro-
fessionals. That allowed the analysis to happen in
parallel with the other interviews (Eisenhardt &
Graebner, 2007; Miles et al., 2013; Yin 2014).
The interview protocol was based on the theoretical
review performed. The goal of the protocol was to
guide the interview, with the objective of assisting
the researcher in covering the relevant issues.
The research protocol was previously validated
with academics of operations management as well
as health professionals in order to ensure that it was
adherent to the theme and context studied (YIN,
2014). All of the information was analyzed with the
support of the Atlas TI software, version 7 for Mac.
Table 1 summarizes the information pertaining to per-
sons who were interviewed, describing to which link
they belonged, the relationship they had with the en-
tity in 2009, as well as the name that will be used dur-
ing the analysis to identify the information presented.

Table 1: Relationships of the Interviewees
Source: Original Compilation
3.3 Data Analysis
The data analysis protocol was adapted from Scholten
et al. (2014), which in turn, was derived from Miles
et al. (2013). This approach is based on the reduction
and analysis of data in a process called encoding.
As described in Miles et al. (2013), codes are as-
signed to the descriptive or inferred information
during a study, which are represented symbolically
as a phrase or word that refers to the original idea.
In the words of the authors, “the code is a construct
generated by the researcher that symbolizes and as-
signs the meaning interpreted for each individual
piece of data for future purposes of detection of
patterns, categorizations, generation of theory and
other analytical processes” (MILES et al 2013). The
data to be classified can vary from words, sentenc-
es, paragraphs, even entire pages. According to the
authors, the encoding is an activity of data conden-
sation, and is part of the process of analysis, which
they recommend performing in two steps:
The first coding cycle deals with the raw data, and
has the main function of reducing the information
so they can be later sorted in the second cycle. Three
of the most common strategies described by Miles et
al. (2013) are: a) descriptive encoding, where the aim
is to summarize the topic in question with a word
(usually a noun) or short sentence; b) encoding in
vivo, which uses literal words or phrases used by
respondents who reflect their own language, and;
c) encoding processes, where typically gerunds are
used to describe actions observed in the data or
the interaction with time, showing trends or issues
which are emerging, for example.
Miles et al. (2013), suggests two approaches for the
first cycle of coding, the inductive and deductive,
that could happen at the same time. In the deductive
approach, the researcher starts with an initial list of
codes that may have been based on an initial concep-
tual model, a list of research questions, hypotheses
or variables that the researcher brings to the study.
The second cycle of encoding usually deals with the
generated code in the first cycle, in order to group
them in a smaller amount and more parsimonious
categories that symbolize themes and constructs
(Miles et al., 2013; Scholten et al., 2014). The iden-
tification of these patterns allow the researcher to
condense a large volume of data (Miles et al., 2013).

The analysis process followed the steps detailed in Table 2.
Tabel 2: Analysis protocol
Literature Review: based on a review of the literature, the main capabilities responsible for form-
ing the resilience have been identified. Codes have been created for each of these items in the Atlas
TI software.
Coding based on Literature: the data was coded using the codes created based on the literature
(item 1)
Inductive Coding: throughout the process of analysis and understanding of the case, additional
codes were created that were relative to the observed events, such as: protection stock, organiza-
tional structure, lack of preparation, support from senior management, etc.
Grouping of the Codes: the codes created in item 3 were grouped according to the objective of the
research,
Linking with the capability of flexibility: the codes created in the groups of item 4 were linked with
the capability of flexibility,
Consistency with the literature: the result of the analyses was contrasted with the literature to
ensure its consistency.
Source: Original compilation
4. DISCUSSION
During the 2009 pandemic, the chain had to deal
with various situations where their usual processes
and resources were not prepared to deal with the
new context. So, it was necessary to create options.
Through the process of analysis, various forms of
manifestation of flexibility were identified, where
the prior existence of resources was a common el-
ement (TANG, 2006). The various forms identified
are summarized in Figure 1.
Figure 1: Manifested forms of flexibility

The letters in Figure 1 could refer to entities, pro-
cesses or activities, depending on the situation. To
simplify the explanation of the forms of manifes-
tation (Table 3), the letters will be simply referred
as resources, with the proper explanation already
made. The letters that are in the white square refer
to the objective to be achieved, and the “X” shows
the path that is not feasible in the particular context.
Table 3 presents the 5 forms of manifestation of flex-
ibility identified in the analysis and examples pre-
sented during the interviews
Table 3: Forms of manifestation of flexibility and examples
Form of Manifestation Example
Redesign: the ability of the supply chain
to adapt by changing the resource that is
obstructing its operation. In the figure,
this is illustrated by the exchange of the
resource A for the resource B. An exam-
ple is the use of a different supplier to
provide specific input.
Whomever said that they wouldn’t be able to attend the demand, went
looking for partners. - HP_ADM
The alternative that we have left are the emergency purchases, which
are acquired though the Foundation funds. What is verified is the pos-
sibility of acquiring this material from a second or third party vendor.
- HP_SUPR
Alteration /Creation: In this case, for
example, a resource B is adapted, turn-
ing this resource into a resource more
appropriate than the original one. An
example of this is the training of profes-
sionals to carry out additional activities
not foreseen initially. The composition
of different resources can also lead to
creation of a new one.
Disposable masks were used by different professionals including the
doormen, who were the first [people] to come in contact with [suspected
patients]. […] at that time, they [doormen] had also been trained on
what to ask, how to act when a sick person arrived... They were lay
people. They didn't have this ability to investigate and it wasn't even
their role. - HP_ENF
[…]then we processed in the [Hospital] in a weekend 2000 bottles. We
got the antiviral powder and made the medication for the children. -
SE_VEP_1
We said that we were playing MacGyver here in the Hospital. - HP_UTI
Prioritization: In this situation, a re-
source C is prioritized at the expense of
resource B, since it was more important
at that moment, as was the case with the
prioritization of ICU beds in the Hospi-
tal for H1N1 patients.
[…] at the time, everybody, regardless if you were ICU of Cardiology,
ICU of Pneumology, ICU of Surgery, when they had a bed, the first
thing they do was to call me. "Someone needs ICU?" We would transfer
someone there in order to receive other patients. - HP_UTI
The [laboratory] […] practically stopped all other functions. All was
geared for just H1N1 analysis […] We worked through the weekend -
SE_VEP_1
Redundancy: in this case, existing re-
sources have buffer or the ability to bear
a greater load, enabling the resource D.
[…]We had enough stock to get going. We will use it and later replen-
ish it. You have to keep an eye on the stock so it doesn’t zero out. -
HP_ADM
So what we did, basically, all States had emergency stocks, so you used
it, you replaced it later. Whenever ran out of the product. - MS_VEP_2
They were asking for people to put in extra On-Calls “Contribute by
giving an extra On-Call”. - HP_CGC_2
Elimination: The elimination of an in-
termediate resource B can be the solu-
tion for enabling a determined option C
that was not initially available.
[…] when the pandemic started, we had some blisters available in the
States that were close to reach their expiration date. Then ANVISA did
the revalidation. We performed tests and validated it. - MS_VEP_3

In the next few sessions, these categories related to the
forms of manifestation of flexibility identified from
the analysis of the data will be explored in depth.
4.1 Redesign
The possibility of changing the design of the chain is
a factor that allows the entities impacted to increase
the amount of options available at the time of crisis
(Christopher and Peck, 2004a).
The most usual way, as identified within the lit-
erature, is the possibility of changing the suppliers
(CHRISTOPHER; PECK, 2004; PETTIT et al., 2013;
PETTIT et al., 2010). This was also identified during
the research at the healthcare chain.
According to the bidding law, contracts which are
performed between the Hospital and its suppliers
possess a very hard character. In this way, the re-
placement of suppliers could prove complex, even
though there was evidence of redesign of the chain
at the level of suppliers.
On the other hand, the importance of processes
that enable this redesign when necessary were also
identified. In the case of the Hospital, there is the
possibility that certain purchases with a nature of
emergency will be carried out using the funds of
the Foundation its is linked to. In this context, the
purchases are not made through bidding law, which
would give more flexibility.
Through the use of the Foundation, a resource that
the Hospital has (BARNEY, 1996; WU et al., 2010), it
was possible that the redesign of the chain could hap-
pen in order to create a new option for the situation.
4.2 Alteration and Creation of Resources
Within the analysis of the case, situations were en-
countered in which a given resource was not avail-
able, or the way that it was available was not ade-
quate to deal with a particular situation.
In these situations, there is a possibility that these re-
sources could be altered or recombined in a way that
will carry a new function creating options for the sup-
ply chain or its entities to deal with disruptive situa-
tions, increasing their resilience. Pettit et al. (2010), for
example, refers to the adaptability of processes and
Christopher and Peck (2004) to conversion.
These situations usually involve a certain degree of
courage and pioneering spirit on the part of its em-
ployees, since often times, the alternatives created
had not been previously tested, in particular when
these alternatives are experimented during the crisis.
One of the main factors for the resilience of the Hos-
pital during the pandemic was the accomplishment
of the tests internally for verifying the infection of
patients by the H1N1, as it was the critical path for
several other decisions concerning movements, hos-
pitalizations and treatment of patients
The network of laboratories set up by the Govern-
ment had no capacity to deal with the volume of
tests needed to support the health units of the State.
The Hospital adapted its available resources, such
as the existing laboratory and its professionals to
perform the tests internally. This decision was con-
sidered one of the key elements to reduce opera-
tional impacts. In addition to the physical location
and the technical expertise of the professionals in-
volved, there was a resource, a relationship between
the CDC (Centers for Disease Control and Preven-
tion, in Atlanta, USA) and the Hospital laboratory
professionals (DYER; SINGH, 1998), which made it
possible to access the specific knowledge needed to
prepare the exams (HARDY et al., 2003).
Some resources, such as human resources, present-
ed itself possessing a high degree of adaptability to
different situations and roles. During the 2009 pan-
demic, the preparation of professionals to perform
functions which they were not initially prepared
was an important factor that increased the amount
of options available to deal with the events. Two
cases that exemplify this statement were: training
the doormen to perform screenings of patients at
the entrance of the Hospital, since they were the
first people to come in contact with them; and the
training of nurses in the emergency room to con-
duct sample collection of materials for examination
through the use of a swab in patients suspected of
infection with H1N1.
With regards to improvisation, as pointed out by
Weick (1993) its existence proved to be relevant to
the construction of flexibility in the case analyzed.
The improvisation implicitly contains the concept
of creativity, which is related to the ability to adapt
previous knowledge to new situations (WEICK,
1993). For this reason, improvisation is an element
capable of providing new options in situations of
disruptions, thereby increasing the flexibility and
consequently, resilience.

An event that exemplifies the use of improvisation
during the 2009 pandemic was the need for defin-
ing the dosages of the drug Oseltamivir to be ad-
ministered to patients in specific situations, for ex-
ample, with renal failure, since the knowledge was
not available in the literature. In order to define this
dosage, a medical board was formed to discuss the
issue and, in this way, make the decision based on
knowledge available at that point.
Several professionals at the Hospital that were in-
terviewed described the necessity to improvise on
a daily basis and not just during disruptive events.
Therefore, the prior existence of the ability to impro-
vise was accessed during the 2009 pandemic, prov-
ing its importance in that situation.
4.3 Prioritization
In the study, there were situations where neces-
sary resources existed, but were allocated to other
functions or activities. This allocation, at the time of
the disruption, can be of minor importance and, in
this way, may be replaced by another of greater rel-
evance (CRAIGHEAD et al., 2007).
During the 2009 pandemic, for example, the ICU
beds in the different departments of the Hospital
were prioritized for the infectious diseases depart-
ment. This way, if there were any beds available in
other departments, they would be provided as a pri-
ority to patients infected with the H1N1 virus.
Activities that often trigger prioritization cause ad-
verse effects in activities for which the resources
were originally allocated. Often times, these resourc-
es belong to other areas or even entities within the
chain. In this way, the existence of a chain of com-
mand proved to be important so that decisions can
be executed (CHRISTOPHER; PECK, 2004; CRAIG-
HEAD et al., 2007).
Another example within the supply chain was the
prioritization given to performing tests in the main
laboratory of the government. Craighead et al.
(2007) reinforces the importance of the coordination
of resources for building resilient supply chains.
Flexibility through prioritization proved possible
by the existence of resources and by the existence
of decision-making mechanisms, thusly proving to
be an important way of making feasible alternatives
during the 2009 pandemic.
4.4 Redundancy, Availability and Robustness
Although authors like Sheffi and Rice (2005) argue
that there is a difference between flexibility and re-
dundancy, empirically, these concepts proved to be
difficult to separate. Several authors have argued
that the existence of very lean processes increase
risk (BLACKHURST et al., 2011; CRAIGHEAD et
al., 2007; PETTIT et al., 2013; PETTIT et al., 2010), as
they diminish the possibilities of maneuverability.
The evidence of the case studied show that the exis-
tence of idle resources, even in a small degree, is an
important factor for resilience.
The most common example in the literature (BODE
et al., 2011; SHEFFI; RICE, 2005) also identified in
the case analyzed was the existence of emergency
stocks, which allowed, especially in the case of the
Hospital, to get past the disruptive situation with
little impact related from the lack of supplies. In
general, the professionals interviewed stressed that
there was no lack of supplies to treat patients, such
as the personal protection equipment (PPE), during
the pandemic, despite many problems that the sup-
pliers were facing to deal with the demand.
Despite the suppliers having an important role of
ensuring that the Hospital had the needed supplies
available, the existence of emergency stock was im-
portant in allowing time for adaptation. In addition
to the existence of stockpiles in the central ware-
house of the Hospital, it was possible to use materi-
als from others departments´ warehouses.
In the case of the distribution of medicines between
the Ministry of Health and State Secretaries, the ex-
istence of stocks also proved to be an important fac-
tor by giving time for the supply chain to adjust.
The availability of materials from suppliers or dis-
tributors can also be considered as an element of
redundancy or availability of resources (SHEFFIE;
RICE, 2005). This availability of resources from oth-
er entities was also used as an alternative by the gov-
ernment when the decision was made to withdraw
the drugs available in drug stores so that they could
be distributed by the Health Ministry. The existence
of these drugs was a key factor so that the Ministry
could meet the demand allocating it according to the
necessity in the early months of the pandemic in the
country, since the process of distributing the medi-
cine powder was not yet ready.
The use of available time from human resources also
contributed to the resiliency during the 2009 pan-
demic. Two examples, the increasing workload of

professionals through overtime or alternative forms
of work, and the use of physical resources in times
that are idle. In respect to the time of the profession-
als, it was common in the Hospital to offer overtime
in order to meet the increased demand for attending
patients. On-Call shifts by phone were transformed
into in-person shifts in order to increase the number
of people working at the hospital.
Another point that does not have consensus in the
literature, are the differences between resilience and
robustness (BRANDON-JONES et al., 2014; CHRIS-
TOPHER; PECK, 2004A; WIELAND; WALLEN-
BURG, 2013). The evidence identified in the research
suggests that the existence of robust processes can
be a viable factor of resilience, once robust processes
allow to increase the load on them, such as including
new activities.
An example is the prior existence of a structure for
emergency purchases in the Hospital. This structure
was essential in enabling the purchase of materials
for the institution in order to meet the sudden in-
crease in demand. Another example was the use of
existing logistics processes in the Ministry of Health
to distribute the drugs to the States.
In this way, these processes can be considered as
available options and can be framed in the defini-
tion of capability of flexibility.
4.5 Elimination
The ability to eliminate existing processes also pre-
sented itself as a way to create flexibility, to the ex-
tent that it enabled options that initially were not
available.
Blackhurst et al. (2011) reinforces that the existence
of regulations and rigid processes work against re-
silience. In this way, it is possible to conclude that
the elimination of these factors could increase resil-
ience. In the case study, an example that corrobo-
rates with this statement was the elimination of bu-
reaucratic barriers, such as the one that occurred by
the government when it worked together with An-
visa, to validate lots of drugs that were close to their
expiration date.
This enabled a considerable volume of medicine,
which was suitable for use, to be made available
to the service network, at a time when there was a
shortage.
5. CONCLUSION
The capability of flexibility has a main function of
generating new options for the chain and its enti-
ties in order to deal with situations of disruption,
and thus plays an important role for resilience
(JÜTTNER; MARKLAN, 2011; SCHOLTEN ET AL.,
2014). In this research, the importance of the capa-
bility of flexibility for the formation of resilience in
service chains was verified, as well as the different
forms of manifestation in disruptive situations.
The redesign allows the entity or the supply chain
to access other options by exchanging one resource
for another one available (CHRISTOPHER; PECK,
2004). An example that represents this manifestation
is the use of another supplier when there are prob-
lems with the original.
The change and creation of resources is achieved
from knowledge and skills present in the members
of the chains or its entities (FAISAL et al., 2006). The
ease with which resources can be modified and the
ability of the members to improvise were important
alternatives in the case analyzed.
Prioritization became apparent in the case analyzed
when a resource that was allocated to a given func-
tion could be allocated to another more relevant
function during the disruptive event. As there may
be a trade off, because this change could lead to
negative effects to the original function, the impor-
tance of decision-making mechanisms proved to be
important in the case studied, corroborating with
Christopher and Peck (2004).
Redundancy, availability and robustness also proved
important for the formation of flexibility. The exis-
tence of buffers, which can be evidenced, for example,
by the existence of emergency stocks, is an important
option for the entities of the supply chain studied.
The possibility of using resources beyond the original
planned, as the allocation of extra time by the pro-
fessionals or the existence of robust processes that al-
low scalability are also important for the formation of
flexibility (JÜTTNER; MARKLAN, 2011). In this way,
this work also argues that mechanisms for redundan-
cy and robustness are important for the formation of
resilience, positioning them as part of the capability
of flexibility and not as unrelated concepts.
Finally it was found that the flexibility is also favored
by the possibility of the elimination of processes, re-
sources or activities that impede the objective, such
as the elimination of rules or bureaucracy.

As was shown, there are several categories with po-
tential to contribute to the formation of flexibility.
The common factor is the previous existence of re-
sources for it to manifest. A proposition which can
be made in this regard is that, the choice or construc-
tion a priori of resources is important for the forma-
tion of flexibility, just as is the recruitment of quali-
fied professionals.
6. LIMITATIONS AND FUTURE RESEARCH
In spite of the care given to methodology, as is in
all research, this also presents some limitations that
need to be considered.
A first limitation refers to the elapsed time since the
occurrence of the event that took place approximate-
ly 5 years ago. In addition to the difficulty of iden-
tifying professionals from the different entities that
were in the functions of interest in this period, at
various times it was noted the difficulty of these in-
formants to remember with accuracy the dates and
events. To mitigate these effects, interviews were
conducted with various people involved in order to
triangulate the data. The use of some documentary
sources also assisted in this matter, since the event
was deeply covered by the media. It is important to
consider that there might be inaccuracies related to
the data collected.
The second limitation relates to the single case
study. Several authors reinforce the limitations in-
volved in only one case study (EISENHARDT, 1989;
MILES et al., 2013; YIN, 2014), since the conclusions
may reduce the external validity of the survey. Nev-
ertheless, it is worth mentioning that some entities
are analyzed only in relation to the context in ques-
tion, such as, for example, the Health Ministry, the
pharmaceutical industry, and the Secretary of State,
as in the case of São Paulo.
7. BIBLIOGRAPHY
Baltacioglu, T., Ada, E., Kaplan, M. D., Yurt And, O., E Cem Ka-
plan, Y. (2007). A new framework for service supply chains.
The Service Industries Journal, 27(2), 105-124.
Barney, J. (1991). Firm resources and sustained competitive ad-
vantage. Journal of Management, 17(1), 99-120.
Barney, J. (1996). The resource-based theory of the firm. Organi-
zation Science.
Barney, J. (2001). The resource-based view of the firm: Ten
years after 1991. Journal of Management, 27(6), 625-641.
doi:10.1177/014920630102700601
Blackhurst, J., Dunn, K. S., E Craighead, C. W. (2011). An empiri-
cally derived framework of global supply resiliency. Journal
of Business Logistics, 32(4), 374-391.
Bode, C., Wagner, S. M., Petersen, K. J., Ellram, L. M. (2011). Un-
derstanding responses to supply chain disruptions: Insights
from information processing and resource dependence per-
spectives. Academy of Management Journal, 54(4), 833-856.
Brandon-Jones, E., Squire, B., Autry, C., E Petersen, K. J. (2014). A
contingent resource-based perspective of supply chain resil-
ience and robustness. Journal of Supply Chain Management.
Braunscheidel, M. J., E Suresh, N. C. (2009). The organizational
antecedents of a firm’s supply chain agility for risk mitiga-
tion and response. Journal of Operations Management, 27(2),
119-140. doi:10.1016/j.jom.2008.09.006
Christopher, M., Peck, H. (2004). Building the resilient supply
chain. International Journal of Logistics Management, the,
15(2), 1-14.
CONASS (2003). Para entender a gestão do SUS. Brasília, Brasil:
CONASS - Conselho Nacional de Secretários de Saúde.
Craighead, C. W., Blackhurst, J., Rungtusanatham, M. J., Hand-
field, R. B. (2007). The severity of supply chain disruptions:
Design characteristics and mitigation capabilities. Decision
Sciences, 38(1), 131-156.
Craighead, C. W., Karwan, K. R., E Miller, J. L. (2004). The ef-
fects of severity of failure and customer loyalty on service re-
covery strategies. Production and Operations Management,
13(4), 307-321.
Dyer, J. H., E Singh, H. (1998). The relational view: Cooperative
strategy and sources of interorganizational competitive ad-
vantage. Academy of Management Review, 23(4), 660-679.
Eisenhardt, K. M. (1989). Building theories from case study re-
search. The Academy of Management Review, 14(4), 1-19.
doi:10.2307/258557
Ellram, L. M., Tate, W. L., Billington, C. (2004). Understanding
and managing the services supply chain. Journal of Supply
Chain Management, 40(4), 17-32.
Faisal, M. N., Banwet, D. K., E Shankar, R. (2006). Supply chain
risk mitigation: Modeling the enablers. Business Process
Management Journal, 12(4), 535-552.
Hardy, C., Phillips, N., E Lawrence, T. B. (2003). Resources,
knowledge and influence: The organizational effects of inter-
organizational collaboration*. Journal of Management Stud-
ies, 40(2), 321-347.
Jüttner, U., Maklan, S. (2011). Supply chain resilience in the glob-
al financial crisis: An empirical study. Supply Chain Man-
agement: An International Journal, 16(4), 246-259.
Jüttner, U., Peck, H., Christopher, M. (2003). Supply chain risk
management: Outlining an agenda for future research. In-
ternational Journal of Logistics: Research and Applications,
6(4), 197-210.
Miles, M. B., Huberman, A. M., E Saldaña, J. (2013). Qualitative
data analysis: A methods sourcebook. SAGE Publications,
Incorporated.

Mitroff, I. I., Alpaslan, M. C. (2003). Preparing for evil. Harvard
Business School Pub.
Peteraf, M. A. (1993). Intra-Industry structure and the response
toward rivals. Managerial and Decision Economics, 14(6),
519-528.
Peteraf, M. A., Barney, J. B. (2003). Unraveling the resource-based
tangle. Managerial and Decision Economics, 24(4), 309-323.
Pettit, T. J., Croxton, K. L., Fiksel, J. (2013). Ensuring supply chain
resilience: Development and implementation of an assess-
ment tool. Journal of Business Logistics, 34(1), 46-76.
Pettit, T. J., Fiksel, J., Croxton, K. L. (2010). Ensuring supply chain
resilience: Development of a conceptual framework. Journal
of Business Logistics, 31(1), 1-21.
Ponomarov, S. Y., E Holcomb, M. C. (2009). Understanding the
concept of supply chain resilience. The International Journal
of Logistics Management, 20(1), 124-143.
Scholten, K., Scott, P. S., E Fynes, B. (2014). Mitigation processes
– antecedents for building supply chain resilience. Supply
Chain Management: An International Journal, 19(2), 211-228.
Seuring, S. A. (2008). Assessing the rigor of case study research in
supply chain management. Supply Chain Management: An
International Journal, 13(2), 128-137.
Sheffi, Y., Rice Jr, J. B. (2005). A supply chain view of the resilient
enterprise. MIT Sloan Management Review, 47(1).
Siggelkow, N. (2007). Persuasion with case studies. Academy of
Management Journal, 50(1), 20-24.
Skipper, J. B., Hanna, J. B. (2009). Minimizing supply chain dis-
ruption risk through enhanced flexibility. International Jour-
nal of Physical Distribution & Logistics Management, 39(5),
404-427.
Stuart, I., McCutcheon, D., Handfield, R., McLachlin, R., E Sam-
son, D. (2002). Effective case research in operations manage-
ment: A process perspective. Journal of Operations Manage-
ment, 20(5), 419-433.
Tang, C. (2006). Robust strategies for mitigating supply chain
disruptions. International Journal of Logistics, 9(1), 33-45.
Tang, C., Tomlin, B. (2008). The power of flexibility for mitigat-
ing supply chain risks. International Journal of Production
Economics, 116(1), 12-27.
Teece, D. J., Pisano, G., E Shuen, A. (1997). Dynamic capabilities
and strategic management. Strategic Management Journal,
18(7), 509-533.
Weick, K. E. (1993). The collapse of sensemaking in organiza-
tions: The mann gulch disaster. Administrative Science
Quarterly, 628-652.
Wieland, A., E Wallenburg, C. M. (2013). The influence of rela-
tional competencies on supply chain resilience: A relational
view. International Journal of Physical Distribution E Logis-
tics Management, 43(4), 300-320.
Wu, S. J., Melnyk, S. A., E Flynn, B. B. (2010). Operational capa-
bilities: The secret ingredient. Decision Sciences, 41(4), 721-
754.
Yin, R. K. (2014). Case study research: Design and methods. Sage
publications.
Susana Carla Farias Pereira: Dr. Pereira is Associate Professor of Operations and Supply Chain Manage-
ment at Fundação Getulio Vargas in São Paulo, Brazil (FGV-EAESP). She holds a Doctor degree in Business
Administration from FGV-EAESP, a Master of Science in Construction Management from the University of
Birmingham in England, and a Bachelor’s Degree of Civil Engineering from Universidade Federal de Mato
Grosso do Sul in Brazil. She is currently working as Head of the Department of Operations Management at
FGV-EAESP, President of the Organizing and Scientific Committee of International Production, Logistics and
Operations Management Symposium (SIMPOI), member of the Scientific Committee of Operations Manage-
ment Division of the Annual Meeting of the National Graduate Association (EnANPAD), and member of the
Editorial Board of Journal of Operations and Supply Chain Management (JOSCM). Dr. Pereira also works as
a researcher for the Center for Excellence in Logistics and Supply Chain (GVcelog) and Global Manufacturing
Research Group (GMRG). Her main research interests are in supply chain risk management, services supply
chain, and humanitarian operations.
Marcelo Bradaschia: Mr. Bradaschia has a master degree in Operations and Suppy Management at Fundação
Getúlio Vargas in São Paulo, Brazil (FGV-EAESP). The mais research focus is related to risk management and
supply chain resilience. He is also founder of the Clay Innovation consulting company and Fintechlab.com.
br, a hub specialized in the fintech market in Brazil. Bradaschia has also a specialization degree in product
development at Instituo Europeu di Design, Customer Value at Kellog University and Banking at Fundação
Getúlio Vargas.

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