Keep Your Friends Close? Supply Chain Design and Disruption Risk

Decision Sciences

Volumn 46, Issue 3, 2015, Pages 491-526

  Habermann, Marco ^a   Blackhurst, Jennifer ^b   Metcalf, Ashley Y ^a  

^a OHIO UNIVERSITY   (United States)

^b IOWA STATE UNIVERSITY   (United States)

Author keywords

Supply Chain Design; Supply Chain Disruption Survey Research; Supply Chain Risk Management

Indexed keywords

EID: 84930413406     PISSN: 00117315     EISSN: 15405915     Source Type: Journal    
DOI: 10.1111/deci.12138     Document Type: Article

References (91)

1. Alcácer, J. (2006). Location choices across the value chain: How activity and capability influence collocation. Management Science, 52(10), 1457-1471.
2. Allon, G., & Van Mieghem, J. (2010). Global dual sourcing: Tailored base-surge allocation to near and offshore production. Management Science, 56(1), 110-124.
3. Autry, C., Grawe, S., Daugherty, P., & Richey, R. G. (2010). The effects of technological turbulence and breadth of supply chain technology acceptance and adoption. Journal of Operations Management, 28, 522-536.
4. Bergkvist, L., & Rossiter, J. R. (2009). Tailor-made single-item measures of doubly concrete constructs. International Journal of Advertising, 28(4), 607-621.
5. Blackhurst, J., Craighead, C., Elkins, D., & Handfield, R. (2005). An empirically derived agenda for quantitative tools to analyze and reduce supply chain disruption impacts. International Journal of Production Research, 43(19), 4067-4081.
6. Blackhurst, J., Dunn, K., & Craighead, C. (2011). An empirically-derived framework of global supply resiliency. Journal of Business Logistics, 32(4), 374-391.
7. Bounds, A., Tighe, C., & Guthrie, J. (2009). Linked companies at risk of a domino effect. Financial Times, October 29, 5.
8. Bozarth, C., Warsing, D., Flynn, B., & Flynn, E. J. (2009). The impact of supply chain complexity on manufacturing plant performance. Journal of Operations Management, 27, 78-93.
9. Bozarth, C., Blackhurst, J., & Handfield, R. (2007). Following the thread: Industry cluster theory, the New England cotton textiles industry, and implications for future supply chain strategy research. Production and Operations Management, 16(1), 154-157.
10. Braunscheidel, M. J., & Suresh, N. C. (2009). The organizational antecedents of a firm's supply chain agility for risk mitigation and response. Journal of Operations Management, 27(2), 119-140.
11. Breusch, T., & Pagan, A. (1980). The LM test and its application to model specification in econometrics. Review of Economic Studies, 47, 239-254.
12. Camburn, E., Correnti, R., & Taylor, J. (2000). Using qualitative techniques to assess the validity of teachers' responses to survey items. Proceedings of the Annual Meeting of the American Educational Research Association, New Orleans, LA. April 24-28.
13. Chan, F., Kumar, N., Tiwari, M., Lau, H., & Choy, K. (2008). Global supplier selection: A fuzzy-AHP approach. International Journal of Production Research, 46(14), 3825-3857.
14. Chen, F., Drezner, Z., Ryan, J. K., & Simchi-Levi, D. (2000). Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Science, 46(3), 436-443.
15. Choi, T. Y., & Krause, D. R. (2006). The supply base and its complexity: Implications for transaction costs, risks, responsiveness, and innovation. Journal of Operations Management, 24(5), 637-652.
16. Chopra, S., & Sodhi, M. (2004). Managing risk to avoid supply-chain breakdown. MIT Sloan Management Review, 46(1), 52-61.
17. Chopra, S., Reinhardt, G., & Mohan, U. (2007). The importance of decoupling recurrent and disruption risks in a supply chain. Naval Research Logistics, 54, 544-555.
18. Christopher, M, Mena, C, Khan, O., & Yurt, O. (2011). Approaches to managing global supply chain disruption risk. Supply Chain Management: An International Journal, 16(2), 67-81.
19. Christopher, M., & Peck, H. (2004). Building the resilient supply chain. International Journal of Logistics Management, 15(2), 1-13.
20. Craighead, C., Blackhurst, J., Rungtusanatham, M., & Handfield, R. (2007). The severity of supply chain disruptions: Design characteristics and mitigation capabilities. Decision Sciences, 38(1), 131-156.
21. Deane, J., Craighead, C., & Ragsdale, C. (2009). Mitigating environmental and density risk in global sourcing. International Journal of Physical Distribution & Logistics Management, 39(10), 861.
22. de Treville, S., Shapiro, R. D., & Hameri, A.-P. (2004). From supply chain to demand chain: The role of lead time reduction in improving demand chain performance. Journal of Operations Management, 21(6), 613-627.
23. Devaraj, S., Hollingworth, D., & Schroeder, R. (2004). Generic manufacturing strategies and plant performance. Journal of Operations Management, 22, 313-333.
24. DeWitt, T., Giunipero, L., & Melton, H. (2006). Clusters and supply chain management: The Amish experience. International Journal of Physical Distribution and Logistics Management, 36(4), 289-308.
25. Dillman, D. A. (2000). Mail and Internet Surveys: The Tailored Design Method. Wiley Publishers, New York.
26. Dillon, R., & Tinsley, C. (2008). How near-misses influences decision making under risk: A missed opportunity for learning. Management Science 54(8), 1425-1440.
27. Duncker, K. (1945). On problem-solving. In J. F. Dashiell (Ed.), Psychological Monographs. Washington, DC: American Psychological Association. 1-114.
28. Ellis, S. C., Henry, R. M., & Shockley, J. (2010). Buyer perceptions of supply disruption risk: A behavioral view and empirical assessment. Journal of Operations Management, 28(1), 34-46.
29. Ellram, L. M., Tate, W. L., & Petersen, K. (2013). Offshoring and reshoring: An update on the manufacturing location decision. Journal of Supply Chain Management, 49(2), 14-22.
30. Gerwin, D., & Ferris, J. S. (2001). Organizing new product development projects in strategic alliances. Organization Science, 15, 22-27.
31. Green, W. H. (2000). Econometric Analysis (5th ed.), New York: Prentice Hall.
32. Gulati, R., & Puranam, P. (2009). Renewal through reorganization: The value of inconsistencies between formal and informal organizations. Organization Science, 20(2), 422-440.
33. Habermann, M. (2009). Identifying and Mitigating the Antecedents of Supply Chain Disruptions-3 Essays. Dissertation. University of Minnesota, ProQuest, UMI Dissertations Publishing.
34. Hawkins, L. (2003). GM posts 30% drop in net income; "more optimism" is voiced for year despite weakness in U.S. Wall Street Journal, July 18, A2.
35. Hendricks, K., & Singhal, V. (2005). Association between supply chain glitches and operating performance. Management Science, 51(5), 695-711.
36. Hinds, P. J., & Mortensen, M. (2005). Understanding conflict in geographically distributed teams: The moderating effects of shared identity, shared context, and spontaneous communication. Organization Science, 16(1), 290-307.
37. Hopp, W., & Spearman, M. (2001). Factory Physics (2nd ed.). McGraw-Hill/Irwin, New York.
38. Indurkhya, A. (2005). Impact of missing data and imputation methods on multiple test procedures. In N. Balakrishnan, N. Kannan, & H. N. Nagaraja (Eds.), Advances in Ranking and Selection, Multiple Comparisons, and Reliability. Boston: Birkhauser, 179-189.
39. Jüttner, U., & Maklan, S. (2011). Supply chain resilience in the global financial crisis: An empirical study. Supply Chain Management: An International Journal, 16(4), 246-259.
40. Kessler, E. H. (2000). Tightening the belt: Methods for reducing product development costs associated with new product innovations. Journal of Engineering and Technology Management, 17, 59-92.
41. Kern, D., Moser, R., Hartmann, E., & Moder, M. (2012). Supply risk management: Model development and empirical analysis. International Journal of Physical Distribution and Logistics Management, 42(1), 60-82.
42. Kleindorfer, P. R., & Saad, G. H. (2005). Managing disruption risks in supply chains. Production and Operations Management, 14, 53-68.
43. Knemeyer, A., Zinn, W., & Eroglu, C. (2009). Proactive planning for catastrophic events in supply chains. Journal of Operations Management, 27(2), 141-153.
44. Koufteros, X. A., Vonderembse, M. A., & Doll, W. J. (1998). Developing measures of time-based manufacturing. Journal of Operations Management, 16(1), 21-41.
45. Kouvelis, P., Chambers, C., & Wang, H. (2006). Supply chain management research and production and operations management: Review, trends, and opportunities. Production and Operations Management, 15(3), 449-469.
46. Li, G., Li, Y., Wang, S., & Yan, H. (2006). Enhancing agility by timely sharing of supply information. Supply Chain Management: An International Journal, 11(5), 425-435.
47. Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198-1202.
48. Little, R. J. A., & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). New York: John Wiley.
49. Manuj, I., & Mentzer, J. T. (2008). Global supply chain disruption risk management. Journal of Business Logistics, 29, 133-155
50. Melnyk, S. A., Pagell, M., Jorae, G., & Sharpe, S. A. (1995). Applying survival analysis to operations management: Analyzing the differences in donor classes in the blood donation process. Journal of Operations Management, 13(3), 339-356.
51. Nahm, A. Y., Vonderembse, M. A., & Koufteros, X. A. (2003). The impact of organizational structure on time based manufacturing and plant performance. Journal of Operations Management, 21(3), 281-306.
52. Nolan, M. J., & Chandler, K. (1996). Use of Cognitive Laboratories and Recorded Interviews in the National Household Education Survey. Washington, DC: National Center for Educational Statistics.
53. Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). New York: McGraw-Hill.
54. Pare, M. (2010). Supplier park drives VW. Chattanooga Times Free Press, April 23.
55. Patti, A. (2006). Economic clusters and the supply chain: A case study. Supply Chain Management, 11(3), 266-270.
56. 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.
57. Pettus, E. W. (2013). Nissan building park for suppliers at Miss. plant. Bloomberg Businessweek, July 30.
58. Perrow, C. (1999). Normal Accidents: Living with High Risk Technologies. New York: Basic Books.
59. Phimister, J., Oktem, U., Kleindorfer, P., & Kunreuther, H. (2003). Near-miss incident management in the chemical process industry. Risk Analysis, 23(3), 445-459.
60. Porter, M. E. (1990). The Competitive Advantage of Nations. New York: Free Press.
61. Porter, M. E. (1998). Clusters and the new economics of competition. Harvard Business Review, November-December, 77-90.
62. Reichhart, A., & Holweg, M. (2008). Co-located supplier clusters: Forms, functions and theoretical perspectives. International Journal of Operations & Production Management, 28(1), 53-78.
63. Rossiter, J. R. (2002). The C-OAR-SE procedure for scale development in marketing. International Journal of Research in Marketing, 19, 305-335.
64. Rubin, D. B. (1976). Inference and missing data. Biometrika, 63, 581-592.
65. Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. London: Chapman & Hall.
66. Shah, R., & Goldstein, S. (2006). Use of structural equations modeling in operations management research: Looking back and forward. Journal of Operations Management, 24(2), 148-169.
67. Shah, R., & Ward, P. T. (2007). Defining and developing measures of lean production. Journal of Operations Management, 25(4), 785-805.
68. Shriver, K. A. (1984). Revising computer documentation for comprehension: Ten exercises in protocol-aided revision. CDC Technical Report Number 14. Pittsburgh, PA: Carnegie Mellon University.
69. Shriver, K. A. (1991). Plain language for expert or lay audiences: Designing text using protocol-aided revision. National Center for the Study of Writing and Literacy Technical Report Number 46. Berkeley, CA.
70. Sheffi, Y. (2002). Supply chain management under the threat of international terrorism. International Journal of Logistics Management, 12(1), 1-11.
71. Sheffi, Y. (2005). The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage. Cambridge, MA, MIT Press.
72. Sheffi, Y. (2010). Logistics intensive clusters. Época/Epoch, 20(1-2), 11-17
73. Sheffi, Y., & Rice, J. (2005). A supply chain view of the resilient enterprise. MIT Sloan Management Review, 47(1), 41-48.
74. Singleton, R. A., & Straits, B. C. (1999). Approaches to Social Research (3rd ed.). Oxford: Oxford University Press.
75. Speier, C., Whipple, J. M., Closs, D. J., & Voss, M. D. (2011). Global supply chain design considerations: Mitigating product safety and security risks. Journal of Operations Management, 29(7/8), 721-736.
76. Stinchcombe, A. (1968). Constructing Social Theories. New York: Harcourt, Brace and World.
77. Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: Scale development and model testing. Journal of Operations Management, 24(2), 170-188.
78. Swink, M., Talluri, S., & Pandejpong, T. (2006). Faster, better, cheaper: A study of NPD project efficiency and performance tradeoffs. Journal of Operations Management, 24(5), 542-562.
79. Takahashi, Y. (2012). Japanese car makers post output rises. Wall Street Journal, January 27.
80. Tang, C., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain disruption risks. International Journal of Production Economics, 116(1), 12-27.
81. Tomlin, B. (2006). On the value of mitigation and contingency strategies for managing supply chain disruption risks. Management Science, 52(5), 639-657.
82. Vande Ven, A. H. (2007). Engaged Scholarship: A Guide for Organizational and Social Research. Oxford, UK: Oxford University Press.
83. Wagner, S., & Bode, C. (2006). An empirical investigation into supply chain vulnerability. Journal of Purchasing and Supply Management, 12, 301-312.
84. Wagner, S. M., & Bode, C. (2008). An empirical examination of supply chain performance along several dimensions of risk. Journal of Business Logistics, 29, 307-325.
85. Wald, A. (1943). Tests of statistical hypothesis concerning several parameters when the number of observations is large. Transactions of the American Mathematical Society, 54, 426-482.
86. Wooldridge, J. M. (2009). Introductory Econometrics: A Modern Approach (4th ed.). Mason, OH: Cengage Learning.
87. Wu, L., Yue, X., & Sim, T. (2006). Supply clusters: A key to China's cost advantage. Supply Chain Management Review, 10(2), 46-51.
88. Yates, J. F., & Stone, E. R. (1992). Risk-Taking Behavior. Wiley series in human performance and cognition. Oxford, England: John Wiley & Sons.
89. Zellner, A. (1962). An efficient method of estimating seemingly unrelated regression equations and tests for aggregation bias. Journal of the American Statistical Association, 57(298), 348-368.
90. Zsidisin, G. (2003). Managerial perceptions of supply risk. Journal of Supply Chain Management, 39(1), 14-25.
91. Zsidisin, G., & Wagner, S. (2010). Do perceptions become reality? The moderating role of supply chain resiliency on disruption occurrence. Journal of Business Logistics, 31(2), 1-20.