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Global Journal of Flexible Systems Management

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04.07.2017 | Original Article

From Supply Chain Integration to Operational Performance: The Moderating Effect of Market Uncertainty

verfasst von: Dawei Lu, Yi Ding, Sobhan Asian, Sanjoy Kumar Paul

Erschienen in: Global Journal of Flexible Systems Management | Sonderheft 1/2018

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Abstract

This research examines the moderating effect of market uncertainty on the causal effects from supply chain integration to operational performance of a typical supply chain. Based on an extensive and critical literature review, two exploratory conceptual hypotheses have been developed for the nonlinear relationship between the supply chain integration and operational performance of the original equipment manufacturer, and how may that relationship be moderated by a specific construct of market uncertainty. Empirical survey instrument has been designed and applied to gather the data from a wide spectrum of automotive industry in China. Confirmative factor analysis and threshold regression analysis were used as the primary research methodology to test the hypotheses. We find strong support to the hypotheses from the empirical evidence, which leads to the finding that the relationship between the supply chain integration and operational performance is ‘nonlinear’, and the ‘nonlinearity’ can be significantly moderated by the market uncertainty as one of the key environmental factors for the supply chain. This study extends the current literature by contributing for the first time the discussion of an analytical model that represents the causal effects from supply chain integration to its operational performance with respect to the market uncertainty as a moderating factor.

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Agarwal, A., Shankar, R., & Tiwari, M. (2006). Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach. European Journal of Operational Research, 173(1), 211–225.CrossRef

Aláez-Aller, R., & Carlos Longás-García, J. (2010). Dynamic supplier management in the automotive industry. International Journal of Operations and Production Management, 30(3), 312–335.CrossRef

Andrews, D. W., & Ploberger, W. (1994). Optimal tests when a nuisance parameter is present only under the alternative. Econometrica, 62(6), 1383–1414.CrossRef

Ansaripoor, A. H., Asian, S., Faghih-Roohi, S., Lee, P. T. W., & Hu, Z. H., (2017). Risk quantification in maritime fleet planning problem: A CVaR approach. Working Paper.

Asian, S., Ertek, G., Haksoz, C., Pakter, S., & Ulun, S. (2016). Wind turbine accidents: A data mining study. IEEE Systems Journal. doi:10.1109/JSYST.2016.2565818.

Asian, S., Hemati, M., & Samandizadeh, K. (2009). Strategic planning evaluation in manufacturing companies through fuzzy analytic hierarchy process (FAHP). Journal of Industrial Management, 4(7), 1–20.

Asian, S., & Nie, X. (2014). Coordination in supply chains with uncertain demand and disruption risks: Existence, analysis, and insights. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(9), 1139–1154.CrossRef

Bai, J. (1997). Estimation of a change point in multiple regression models. Review of Economics and Statistics, 79(4), 551–563.CrossRef

Beamon, B. M. (1999). Measuring supply chain performance. International Journal of Operations and Production Management, 19(3), 275–292.CrossRef

Boehmke, B. C., & Hazen, B. T. (2017). The Future of Supply Chain Information Systems: The Open Source Ecosystem. Global Journal of Flexible Systems Management, 18(2), 163–168.CrossRef

Bowersox, D. J., Closs, D. J., & Stank, T. P. (1999). 21st century logistics: Making supply chain integration a reality. Michigan: Michigan State University, Council of Logistics Management.

Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), 1287–1294.CrossRef

Brown, T. A. (2015). Confirmatory factor analysis for applied research. New York: Guilford Press.

Cao, Z., Huo, B., Li, Y., & Zhao, X. (2015). The impact of organizational culture on supply chain integration: A contingency and configuration approach. Supply Chain Management: An International Journal, 20(1), 24–41.CrossRef

Chandler, A. D. (1990). Strategy and structure: Chapters in the history of the industrial enterprise. Boston: MIT press.

Coleman, L. (2011). An exploratory analysis of factors influencing initial market response and media reports following shock corporate events. Financial Review, 46(2), 313–336.CrossRef

Cousins, P. D., & Menguc, B. (2006). The implications of socialization and integration in supply chain management. Journal of Operations Management, 24(5), 604–620.CrossRef

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.CrossRef

Das, A., Narasimhan, R., & Talluri, S. (2006). Supplier integration—finding an optimal configuration. Journal of Operations Management, 24(5), 563–582.CrossRef

Davies, R. B. (1987). Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case. Biometrika, 74(1), 33–43.

Devaraj, S., Krajewski, L., & Wei, J. C. (2007). Impact of eBusiness technologies on operational performance: the role of production information integration in the supply chain. Journal of Operations Management, 25(6), 1199–1216.CrossRef

Drazin, R., & Van de Ven, A. H. (1985). Alternative forms of fit in contingency theory. Administrative Science Quarterly, 514–539.

Droge, C., Vickery, S. K., & Jacobs, M. A. (2012). Does supply chain integration mediate the relationships between product/process strategy and service performance? An empirical study. International Journal of Production Economics, 137(2), 250–262.CrossRef

Ebrahimi, S. M. (2015). Examining the impact of supply chain integration on organization structure and operational performance in oil and gas supply chains: A contingency approach. Sheffield: University of Sheffield.

Faghih-Roohi, S., Ong, Y. S., Asian, S., & Zhang, A. N. (2016). Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks. Annals of Operations Research, 247(2), 715–734.CrossRef

Farrell, A. M. (2010). Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009). Journal of Business Research, 63(3), 324–327.CrossRef

Flynn, B. B., Huo, B., & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28(1), 58–71.CrossRef

Frohlich, M. T., & Westbrook, R. (2001). Arcs of integration: An international study of supply chain strategies. Journal of Operations Management, 19(2), 185–200.CrossRef

Galbraith, J. R. (1973). Designing complex organizations. Boston: Addison-Wesley Longman Publishing Co., Inc.

Germain, R., & Iyer, K. N. (2006). The interaction of internal and downstream integration and its association with performance. Journal of Business Logistics, 27(2), 29–52.CrossRef

Gimenez, C., van der Vaart, T., & Pieter van Donk, D. (2012). Supply chain integration and performance: The moderating effect of supply complexity. International Journal of Operations and Production Management, 32(5), 583–610. doi:10.1108/01443571211226506.CrossRef

Gimenez, C., & Ventura, E. (2005). Logistics-production, logistics-marketing and external integration: Their impact on performance. International Journal of Operations and Production Management, 25(1), 20–38.CrossRef

Glenn Richey, R., Jr., Chen, H., Upreti, R., Fawcett, S. E., & Adams, F. G. (2009). The moderating role of barriers on the relationship between drivers to supply chain integration and firm performance. International Journal of Physical Distribution and Logistics Management, 39(10), 826–840.CrossRef

Goldman, S. L., & Nagel, R. N. (1995). Agile competitors and virtual organizations: strategies for enriching the customer. New York: Wiley.

Goldsby, T. J., Griffis, S. E., & Roath, A. S. (2006). Modeling lean, agile, and leagile supply chain strategies. Journal of Business Logistics, 27(1), 57–80.CrossRef

Graham, G., Zailani, S., & Rajagopal, P. (2005). Supply chain integration and performance: US versus East Asian companies. Supply Chain Management: An International Journal, 10(5), 379–393.CrossRef

Hambrick, D. C. (1983). High profit strategies in mature capital goods industries: A contingency approach. Academy of Management Journal, 26(4), 687–707.CrossRef

Hansen, B. E. (1999). Threshold effects in non-dynamic panels: Estimation, testing, and inference. Journal of econometrics, 93(2), 345–368.CrossRef

Hansen, B. E. (2000). Sample splitting and threshold estimation. Econometrica. 68(3), 575–603.CrossRef

He, Y., & Zhao, X. (2012). Coordination in multi-echelon supply chain under supply and demand uncertainty. International Journal of Production Economics, 139(1), 106–115.CrossRef

Henrysson, S. (1963). Correction of item-total correlations in item analysis. Psychometrika, 28(2), 211–218.CrossRef

Huang, M.-C., Yen, G.-F., & Liu, T.-C. (2014). Reexamining supply chain integration and the supplier’s performance relationships under uncertainty. Supply Chain Management: An International Journal, 19(1), 64–78.CrossRef

Huo, B. (2012). The impact of supply chain integration on company performance: an organizational capability perspective. Supply Chain Management: An International Journal, 17(6), 596–610.CrossRef

Jakhar, S. K. (2014). Designing the green supply chain performance optimisation model. Global Journal of Flexible Systems Management, 15(3), 235–259.CrossRef

Jin, Y., Fawcett, A. M., & Fawcett, S. E. (2013). Awareness is not enough: commitment and performance implications of supply chain integration. International Journal of Physical Distribution and Logistics Management, 43(3), 205–230.CrossRef

Jonsson, P., Andersson, D., Boon-itt, S., & Yew Wong, C. (2011). The moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance. International Journal of Physical Distribution and Logistics Management, 41(3), 253–276.CrossRef

Khazaei Pool, J., Asian, S., Arabzad, S. M., Balouei Jamkhaneh, H., & Kia Lashaki, J. (2017a). Development of a model to analyze the factors affecting RFID technology acceptance in small and medium-sized enterprises. International Journal of Services and Operations Management, Forthcoming.

Khazaei Pool, J., Arabzad, S., Asian, S., Fahimi, M., & Verij Kazemi, R. (2017b). Employing fuzzy ANP for ranking the personality of international brands in the sports shoe industry. Journal of Modelling in Management. doi:10.1108/JM2-02-2016-0009.

Kim, S. W. (2009). An investigation on the direct and indirect effect of supply chain integration on firm performance. International Journal of Production Economics, 119(2), 328–346.CrossRef

Koenker, R., & Bassett Jr, G. (1982). Robust tests for heteroscedasticity based on regression quantiles. Econometrica: Journal of the Econometric Society, 43–61.

Kotha, S., & Nair, A. (1995). Strategy and environment as determinants of performance: Evidence from the Japanese machine tool industry. Strategic Management Journal, 16(7), 497–518.CrossRef

Koufteros, X., Vonderembse, M., & Jayaram, J. (2005). Internal and external integration for product development: The contingency effects of uncertainty, equivocality, and platform strategy. Decision Sciences, 36(1), 97–133.CrossRef

Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management, 29(1), 65–83.CrossRef

Lawrence, P. R., & Lorsch, J. W. (1967). Managing differentiation and integration. Organization and Environment.

Li, J., Ning, L., Zeng, D., & Gu, X. (2014). Dynamic patterns of technology collaboration: A case study of the Chinese automobile industry, 1985–2010. Scientometrics, 101(1), 663–683.CrossRef

Li, G., Yang, H., Sun, L., & Sohal, A. S. (2009). The impact of IT implementation on supply chain integration and performance. International Journal of Production Economics, 120(1), 125–138. doi:10.1016/j.ijpe.2008.07.017.CrossRef

Liu, Z., & Cruz, J. M. (2012). Supply chain networks with corporate financial risks and trade credits under economic uncertainty. International Journal of Production Economics, 137(1), 55–67.CrossRef

Lockstroem, M., Schadel, J., Harrison, N., Moser, R., & Malhotra, M. K. (2010). Antecedents to supplier integration in the automotive industry: A multiple-case study of foreign subsidiaries in China. Journal of Operations Management, 28(3), 240–256.CrossRef

Longinidis, P., & Georgiadis, M. C. (2013). Managing the trade-offs between financial performance and credit solvency in the optimal design of supply chain networks under economic uncertainty. Computers and Chemical Engineering, 48, 264–279.CrossRef

Mozur, P. (2014). China Auto Firms Catch Up. Wall Street Journal (Online), 1–1.

Narasimhan, R., & Kim, S. W. (2002). Effect of supply chain integration on the relationship between diversification and performance: Evidence from Japanese and Korean firms. Journal of Operations Management, 20(3), 303–323.CrossRef

Neely, A., Gregory, M., & Platts, K. (1995). Performance measurement system design: a literature review and research agenda. International Journal of Operations and Production Management, 15(4), 80–116.CrossRef

Parkhe, A. (1993). Strategic alliance structuring: A game theoretic and transaction cost examination of interfirm cooperation. Academy of Management Journal, 36(4), 794–829.CrossRef

Paul, S. K., Asian, S., Goh, M., & Torabi, S. A. (2017). Managing sudden transportation disruptions under delivery delay and quantity loss. Annals of Operations Research, Forthcoming.

Petersen, K. J., Handfield, R. B., & Ragatz, G. L. (2005). Supplier integration into new product development: Coordinating product, process and supply chain design. Journal of Operations Management, 23(3), 371–388.CrossRef

Prajogo, D. I., Oke, A., & Olhager, J. (2015). Supply chain processes: linking supply logistics integration, supply performance, lean processes and competitive performance. International Journal of Operations & Production Management, 36(2), 220–238.CrossRef

Prajogo, D., & Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(1), 514–522.CrossRef

Rai, A., Patnayakuni, R., & Seth, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30(2), 225–246.CrossRef

Rodrigues, A. M., Stank, T. P., & Lynch, D. F. (2004). Linking strategy, structure, process, and performance in integrated logistics. Journal of Business logistics, 25(2), 65–94.CrossRef

Russell, J. A. (1978). Evidence of convergent validity on the dimensions of affect. Journal of Personality and Social Psychology, 36(10), 1152.CrossRef

Saeed, K. A., Malhotra, M. K., & Grover, V. (2005). Examining the impact of interorganizational systems on process efficiency and sourcing leverage in buyer–supplier dyads. Decision Sciences, 36(3), 365–396.CrossRef

Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of educational research, 99(6), 323–338.CrossRef

Scott, W. R., & Cole, R. E. (2000). The quality movement and organizational theory. Thousand Oaks: Sage.

Sezen, B. (2008). Relative effects of design, integration and information sharing on supply chain performance. Supply Chain Management: An International Journal, 13(3), 233–240.CrossRef

Shalender, K., & Singh, N. (2015). Marketing flexibility: Significance and implications for automobile industry. Global Journal of Flexible Systems Management, 16(3), 251–262.CrossRef

Sharifkhani, M., Khazaei Pool, J., & Asian, S. (2016). The impact of leader-member exchange on knowledge sharing and performance: An empirical investigation in the oil and gas industry. Journal of Science and Technology Policy Management, 7(3), 289–305.CrossRef

Sinha, K. K., & Van de Ven, A. H. (2005). Designing work within and between organizations. Organization Science, 16(4), 389–408.CrossRef

Somarin, A. R., Asian, S., & Chen, S. (2016). Dynamic priority repair policy for service parts supply chain. In 2016 IEEE international conference on industrial engineering and engineering management (IEEM) (pp. 798–802). IEEE.

Somarin, A. R., Asian, S., Jolai, F., & Chen, S. (2017a). Flexibility in service parts supply chain: a study on emergency resupply in aviation MRO. International Journal of Production Research, Forthcoming.

Somarin, A. R., Chen, S., Asian, S., & Wang, D. Z. (2017b). A heuristic stock allocation rule for repairable service parts. International Journal of Production Economics, 184, 131–140.CrossRef

Song, M., & Di Benedetto, C. A. (2008). Supplier’s involvement and success of radical new product development in new ventures. Journal of operations management, 26(1), 1–22.CrossRef

Sousa, R., Oliveira, P., van der Vaart, T., Pieter van Donk, D., Gimenez, C., & Sierra, V. (2012). Modelling the integration-performance relationship: Collaborative practices, enablers and contextual factors. International Journal of Operations and Production Management, 32(9), 1043–1074.CrossRef

Sousa, R., & Voss, C. A. (2008). Contingency research in operations management practices. Journal of Operations Management, 26(6), 697–713.CrossRef

Stank, T. P., Keller, S. B., & Closs, D. J. (2001). Performance benefits of supply chain logistical integration. Transportation Journal, 41(2/3), 32–46.

Stonebraker, P. W., & Afifi, R. (2004). Toward a contingency theory of supply chains. Management Decision, 42(9), 1131–1144.CrossRef

Stratton, R., & Warburton, R. D. (2003). The strategic integration of agile and lean supply. International Journal of Production Economics, 85(2), 183–198.CrossRef

Swink, M., Narasimhan, R., & 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), 148–164.CrossRef

Swink, M., & Song, M. (2007). Effects of marketing-manufacturing integration on new product development time and competitive advantage. Journal of Operations Management, 25(1), 203–217.CrossRef

Tan, S. (2009). Misuses of KR-20 and Cronbach’s alpha reliability coefficients. Egitim ve Bilim, 34(152), 101.

Tavakoli, M. R., Asian, S., & Hemati, M. (2012). Using a fuzzy MADM in the Balanced SCORE card for the performance improvement in Iranian steel industries. Iranian Journal of Trade Studies (IJTS), 16(61), 51–80.

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.CrossRef

Terjesen, S., Patel, P. C., & Sanders, N. R. (2012). Managing differentiation–integration duality in supply chain integration*. Decision Sciences, 43(2), 303–339.CrossRef

Thompson, J. D. (1967). Organizations in action: Social science bases of administrative theory. Piscataway: Transaction publishers.

Turkulainen, V. (2008). Managing cross-functional interdependencies—the contingent value of integration. Helsinki: Teknillinen korkeakoulu.

Turkulainen, V., & Ketokivi, M. (2012). Cross-functional integration and performance: What are the real benefits? International Journal of Operations and Production Management, 32(4), 447–467.CrossRef

Tushman, M. L., & Nadler, D. A. (1978). Information processing as an integrating concept in organizational design. Academy of Management Review, 3(3), 613–624.

Tyagi, M., Kumar, P., & Kumar, D. (2015). Assessment of critical enablers for flexible supply chain performance measurement system using fuzzy DEMATEL approach. Global Journal of Flexible Systems Management, 16(2), 115–132.CrossRef

Van der Vaart, T., & van Donk, D. P. (2008). A critical review of survey-based research in supply chain integration. International Journal of Production Economics, 111(1), 42–55.CrossRef

Van Hoek, R. I. (1998). “Measuring the unmeasurable”-measuring and improving performance in the supply chain. Supply Chain Management: An International Journal, 3(4), 187–192.CrossRef

Vazquez-Bustelo, D., Avella, L., & Fernández, E. (2007). Agility drivers, enablers and outcomes: Empirical test of an integrated agile manufacturing model. International Journal of Operations and Production Management, 27(12), 1303–1332.CrossRef

Vickery, S. K., Jayaram, J., Droge, C., & Calantone, R. (2003). The effects of an integrative supply chain strategy on customer service and financial performance: An analysis of direct versus indirect relationships. Journal of Operations Management, 21(5), 523–539.CrossRef

Wilden, R., Gudergan, S. P., Nielsen, B. B., & Lings, I. (2013). Dynamic capabilities and performance: Strategy, structure and environment. Long Range Planning, 46(1), 72–96.CrossRef

Williams, L. J., Hartman, N., & Cavazotte, F. (2010). Method variance and marker variables: A review and comprehensive CFA marker technique. Organizational Research Methods, 13(3), 477–514.CrossRef

Williamson, O. E. (1981). The economics of organization: The transaction cost approach. American Journal of Sociology, 87(3), 548–577.CrossRef

Williamson, O. E. (1989). Transaction cost economics. Handbook of industrial organization, 1, 135–182.CrossRef

Williamson, O. E. (1991). Comparative economic organization: The analysis of discrete structural alternatives. Administrative Science Quarterly, 36(2), 269–296.CrossRef

Won Lee, C., Kwon, I.-W. G., & Severance, D. (2007). Relationship between supply chain performance and degree of linkage among supplier, internal integration, and customer. Supply Chain Management: An International Journal, 12(6), 444–452.CrossRef

Wong, C. Y., Boon-Itt, S., & Wong, C. W. (2011a). The contingency effects of environmental uncertainty on the relationship between supply chain integration and operational performance. Journal of Operations Management, 29(6), 604–615.CrossRef

Wong, C. W., Lai, K.-H., & Cheng, T. (2011b). Value of information integration to supply chain management: roles of internal and external contingencies. Journal of Management Information Systems, 28(3), 161–200.CrossRef

Wong, E. M., Ormiston, M. E., & Tetlock, P. E. (2011c). The effects of top management team integrative complexity and decentralized decision making on corporate social performance. Academy of Management Journal, 54(6), 1207–1228.CrossRef

Wook Kim, S. (2006). Effects of supply chain management practices, integration and competition capability on performance. Supply Chain Management: An International Journal, 11(3), 241–248.CrossRef

Xinqiao, P., & Junfeng, W. (2001). A study of market size and enterprise quantity of china’s auto industry. Economic Research Journal, 11, 006.

Yu, W., Chavez, R., Feng, M., & Wiengarten, F. (2014). Integrated green supply chain management and operational performance. Supply Chain Management: An International Journal, 19(5/6), 683–696. doi:10.1108/scm-07-2013-0225.CrossRef

Yusuf, Y., Gunasekaran, A., Adeleye, E., & Sivayoganathan, K. (2004). Agile supply chain capabilities: Determinants of competitive objectives. European Journal of Operational Research, 159(2), 379–392.CrossRef

Zhang, D. Z. (2011). Towards theory building in agile manufacturing strategies—Case studies of an agility taxonomy. International Journal of Production Economics, 131(1), 303–312.CrossRef

Zhao, G., Feng, T., & Wang, D. (2015). Is more supply chain integration always beneficial to financial performance? Industrial Marketing Management, 45, 162–172.CrossRef

Zhao, L., Huo, B., Sun, L., & Zhao, X. (2013). The impact of supply chain risk on supply chain integration and company performance: A global investigation. Supply Chain Management: An International Journal, 18(2), 115–131.CrossRef

Titel: From Supply Chain Integration to Operational Performance: The Moderating Effect of Market Uncertainty
verfasst von: Dawei Lu
Yi Ding
Sobhan Asian
Sanjoy Kumar Paul
Publikationsdatum: 04.07.2017
Verlag: Springer India
Erschienen in: Global Journal of Flexible Systems Management / Ausgabe Sonderheft 1/2018
Print ISSN: 0972-2696
Elektronische ISSN: 0974-0198
DOI: https://doi.org/10.1007/s40171-017-0161-9

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