The 2008 International Conference on e-Commerce
Toward an Integrative Model of
SCM Performance: Supply Chain
Strategy and Environmental
Uncertainty
Wen-Jin Hwang & Meng-Hsiang Hsu
National Kaohsiung First University of
Science and Technology,
Institute of Management
Agenda
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Introduction
Theoretical Background
Research Model and Hypotheses
Research Method
Data Analysis and Results
Discussion and Conclusion
Introduction
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Environmental uncertainties usually affect the supply
chain performance and determine which competitive
factors should be emphasized and evaluated to help
formulate a winning competitive strategy (Fisher 1997,
Lee 2002, Paulraj and Chen 2007).
Although ideal alignments on different topics (e.g.
business strategy and IS strategy, business strategy
and environment) had been empirically investigated
and shown to play an important role in business
performance (Bergeron et al. 2004, Sabherwal and
Chan 2001, Sanders 2005).
However, empirical research on the topic of alignment
between manufacturing SC strategy and environmental
uncertainty was extremely sparse.
Introduction (cont.)
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Ignoring the important concept of alignment, failures in
SCM from a mismatch between two or more crucial factors
(e.g. strategies and environmental uncertainties) are still in
common, and therefore, the performance of SCM is not as
good as expected.
Fisher (1997) even indicated that the root cause of the
problems plaguing many supply chains is a mismatch
between the type of environmental uncertainty and of SC
strategy.
Accordingly, Lee (2002) proposed an environmental
uncertainty framework for companies within a supply chain
when seeking to devise the right SC strategy.
Two key uncertainty factors including demand and supply
are specified and the strategy of SC is classified into four
types: efficient, responsive, risk-hedging, and agile SC in
that framework.
Introduction (cont.)
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However, that important paper on SC strategy has stayed on
an analytical or conceptual level until now.
Moreover, Lee’s (2002) study didn’t depict the ideal profiles
of SC strategy attributes that are very useful to practitioners.
To fill this gap, our study empirically examined the impact
of alignment between SC strategy and environmental
uncertainty on SCM performance by adopting a profile
deviation approach.
Furthermore, this study also constructed the theoretical SC
strategy profiles in order to provide deeper insights into the
SC strategies appropriate for environmental uncertainties.
Our study proposed a perspective to integrate both IS
capabilities and manufacturing capabilities as the
attributes of SC strategy.
Theoretical Background
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The Concept of Alignment
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Organizational researchers regard alignment as an important
concept for measuring the performance impacts of environmentstrategy coalignment (Venkatraman and Prescott 1990).
Venkatraman (1989) presented a classificatory framework to
identify six different perspectives of fit/alignment (i.e., moderation,
mediation, matching, covariation, gestalts, and profile deviation).
Strategic-alignment also has been applied to validate the effect
of alignment among strategies on performance in SCM (e.g.,
Stock et al., 2000; Paulraj and Chen, 2007; Lee, 2000).
According to prior researches, our study therefore believed that
alignment between SC strategy and environmental uncertainty
would have positive influence on SCM performance.
Theoretical Background (cont.)
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Environmental Uncertainty
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product technology, customer demand, competitor’s price
and quality, and supply uncertainties(Hitt et al., 1990).
market demand, supply, and technology uncertainties
(Paulraj and Chen, 2007).
Lee (2002) expanded Fisher’s (1997) demand framework
to include supply uncertainties, and then formulated into
four types of environmental uncertainty: low demand and
low supply, high demand and low supply, low demand and
high supply, and low demand and high supply uncertainties.
Demand uncertainty is linked to the predictability of the
demand for the product.
Supply uncertainty is another kind of uncertainty revolving
around the supply process of the product.
Theoretical Background (cont.)
 Supply
Chain Strategy
 Based on the different environmental nature of demand and supply
uncertainties within a supply chain, Lee (2002) proposed four viable SC
strategies: efficient, responsive, risk-hedging, and agile SC strategy.
 Efficient
SC strategy: The basis of competition is efficiency for
companies that have both low demand and supply uncertainties.
 Responsive SC strategy: The strategy aims at being responsive and
flexible to the changing and diverse needs of the customers. Within
responsive SC, companies encounter high demand uncertainties as well
as low supply uncertainties of products.
 Risk-hedging SC strategy: It shares the risks in supply disruption with
some pooling and sharing resource strategies in a supply chain. It faces
low demand uncertainties as well as high supply uncertainties of products.
 Agile SC strategy: Companies with an agile SC strategy face both high
demand and high supply uncertainties of products. Agile SC strategies
aim at being responsive and flexible to customer demand, while hedging
the risks of supply uncertainties.
Theoretical Background (cont.)
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Attribute Profiles of Efficient, Responsive, Risk-Hedging, and Agile
SC Strategy
Table 1. The profiles of SC strategy attributes
Manufacturing
capabilities and IS
capabilities are two
major critical
success factors for
manufacturing
within a supply
chain (Cooper and
Tracey 2005,
Dehning,
Richardson and
Zmud 2007,
Frohlich and Dixon
2001, Gunasekaran
and Ngai 2004, Lee
2002, Miller and
Roth 1994).
SC strategy
attributes
Efficient
SC
Responsive
SC
Risk-hedging
SC
Agile SC
Price
High
Medium
Medium
Low
Flexibility
Low
High
Low
High
Quality
High
High
High
High
Delivery
High
High
Medium
High
Service
Low
Medium
High
High
Operational
support systems
High
Low
Medium
Low
Market information
Systems
Low
High
High
High
Interorganizational
Systems
High
Medium
High
Low
Strategic decision
support systems
High
Medium
Low
High
Theoretical Background (cont.)
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SCM Performance
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Brewer and Speh (2000) applied Kaplan and Norton’s (1996) balanced
scorecard (BSC) framework to develop a framework of SCM
performance measures.
Four SCM performance perspectives of the Brewer and Speh’s
framework
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Customer benefits link to the customer perspective,
Financial benefits link to the financial perspective,
Process improvements link to the internal business process
perspective, and
Development improvements link to the innovation and
learning perspective
Brewer and Speh’s BSC as a strategy implementation tools, with its
emphasis on balancing non-financial and financial measures, measuring
performance across the SC, and linking measures with the SC strategy
and customer service, is used in many companies and different context
(Seuring et al. 2003).
Therefore, this study adopted Brewer and Speh’s BSC approach to deal
with manufacturing SC performance evaluation.
Research model
 Manufacturing
capabilities: price, flexibility, quality, delivery, and
service.
 Information system capabilities: operational support, market
information, inter-organizational, and strategic decision support systems.
Hypotheses
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A greater alignment between an organization's environmental
uncertainties and SC strategy indicates that the systems are targeted
on areas that are critical to its success.
Consequently, the right SC strategy to match environmental
uncertainty may be expected to contribute to the SCM performance
to a greater extent (Lee, 2002; Fisher, 1997 ).
H1:The alignment between environmental
uncertainty and SC strategy is positively associated
with perceived SCM performance.
Hypotheses (cont.)
H2:Under low demand and low supply environmental uncertainty, the alignment
between SC strategy and the efficient SC strategy is positively associated with
perceived SCM performance
 H3:Under high demand and low supply environmental uncertainty, the alignment
between SC strategy and the responsive SC strategy is positively associated with
perceived SCM performance.
 H4:Under low demand and high supply environmental uncertainty, the alignment
between SC strategy and the risk-hedging SC strategy is positively associated with
perceived SCM performance.
 H5:Under high demand and high supply environmental uncertainty, the alignment
between SC strategy and the agile SC strategy is positively associated with perceived
SCM performance.
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Research Method
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Sample and Data Collection
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Survey questionnaires were used to collect the data
among Taiwan manufacturing companies.
The unit of analysis of our study was the main product
line of the manufacturing firm within a SC.
A total of 330 survey questionnaires were distributed to
respondents, and 276 questionnaires were returned. The
gross response rate was 83.6 %.
A total of 33 questionnaires were dropped from the final
dataset for various reasons. Therefore, this dataset
yielded 243 usable cases, for an effective response rate of
73.6%.
Research Method (cont.)
Measurement
items for manufacturing capabilities of SC strategy —
price, flexibility, quality, delivery, and service — were
revised from Frohlich and Dixon’s (2001) research.
 The items for information system capabilities of SC
strategy were applied from previous Sabherwal and Chan’s
(2001) study.
 Demand and supply uncertainties were adapted from
Premkumar et al.’s ( 2005) study.
 The items for SCM performance were adapted from
Brewer and Speh’s (2000) BSC framework.
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Research Method (cont.)
Reliability and Validity of Research Constructs
 A confirmatory factor analysis (CFA) was performed to determine
measurement reliability and validity in terms of composite reliability,
convergent validity, and discriminant in this study.
 Composite reliabilities of all factors in this study exceeded 0.84,,
indicating the existence of internal consistence.
 The t-test of all the loadings suggests they are significant (p < 0.001),
which provides evidence of convergent validity. Moreover, each
indicator loaded more highly on constructs it was intended to measure
than on any other construct in this study. The results suggested sufficient
convergent validity.
 Our study considered both loadings and cross-loadings to evaluate
discriminant validity by using confirmatory factor analysis. In this study,
the square roots of AVEs range from 0.800 to 1.000 and exceed the interconstruct correlations; hence the test of discriminant validity was
acceptable.
Data Analysis
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A profile deviation is recommended to assess the
alignment between two multivariate constructs.
The data-analysis process was divided into four
broad steps:
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Step 1: The value of both demand and supply uncertainty
variable of observation was computed and then compared to the
sample mean value separately.
Step 2: The normalization of research variables was employed
to compute normalized score of SC strategy variables.
Step 3: The alignment between each firm’s SC strategy and its
appropriate ideal SC strategy was computed and three tasks were
involved in this step
Step 4: Five research hypotheses were tested.
Results
Discussion and Conclusion
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First, this study empirically tested and supported Lee’s (2002)
uncertainty framework of SC strategy. The results verified an
alignment between environmental uncertainties and SC
strategies could positively impact on SCM performance.
Second, our ideal profiles of SC strategy’s attributes and Lee’s
uncertainty framework can serve as a guideline to managers
wishing to strengthen specific SC capabilities under distinct
environmental uncertainties.
Finally, in this study, we proposed the profiles of SC strategy’s
attributes through the integration of both IS capabilities and
manufacturing capabilities. Researchers and SCM practitioners
could find this perspective of integration is helpful to future
study and practice.
The End
Thank you for your attention