1. 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 The 2008 International Conference on e-Commerce

2. Agenda Introduction Theoretical Background Research Model and Hypotheses Research Method Data Analysis and Results Discussion and Conclusion

3. Introduction 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.

4. Introduction (cont.) 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.

5. Introduction (cont.) 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.

6. Theoretical Background The Concept of Alignment Organizational researchers regard alignment as an important concept for measuring the performance impacts of environment- strategy 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.

7. Theoretical Background (cont.) Environmental Uncertainty 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.

8. 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.

9. Theoretical Background (cont.) 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 HighMedium Low Flexibility LowHighLowHigh Quality High Delivery High MediumHigh Service LowMediumHigh Operational support systems HighLowMediumLow Market information Systems LowHigh Interorganizational Systems HighMediumHighLow Strategic decision support systems HighMediumLowHigh Table 1. The profiles of SC strategy attributes Attribute Profiles of Efficient, Responsive, Risk-Hedging, and Agile SC Strategy

10. Theoretical Background (cont.) SCM Performance 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 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.

11. Research model Manufacturing capabilities: price, flexibility, quality, delivery, and service. Information system capabilities: operational support, market information, inter-organizational, and strategic decision support systems.

12. Hypotheses 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.

13. 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.

14. Research Method Sample and Data Collection 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%.

15. Research Method (cont.) Measurement The 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.

16. 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 inter- construct correlations; hence the test of discriminant validity was acceptable.

17. Data Analysis A profile deviation is recommended to assess the alignment between two multivariate constructs. The data-analysis process was divided into four broad steps: Step 1: T he value of both demand and supply uncertainty variable of observation was computed and then compared to the sample mean value separately. Step 2: T he normalization of research variables was employed to compute normalized score of SC strategy variables. Step 3: T he 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: F ive research hypotheses were tested.

18. Results

19. Discussion and Conclusion 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.

20. The End Thank you for your attention