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Association Between Supply Chain Glitches and Operating Performance

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Author Info

  • Kevin B. Hendricks

    ()
    (Richard Ivey School of Business, The University of Western Ontario, London, Ontario N6A 3K7, Canada)

  • Vinod R. Singhal

    ()
    (College of Management, Georgia Institute of Technology, Atlanta, Georgia 30332)

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    Abstract

    This paper empirically documents the association between supply chain glitches and operating performance. The results are based on a sample of 885 glitches announced by publicly traded firms. Changes in various operating performance metrics for the sample firms are compared against a sample of control firms of similar size and from similar industries. In the year leading up to the announcement, the control-adjusted mean percent changes in operating income, return on sales, and return on assets for the sample firms are -107%, -114%, and -92%, respectively. During this same period, the control-adjusted changes in the level of return on sales and return on assets are -13.78% and -2.32%, respectively. Relative to controls, firms that experience glitches report on average 6.92% lower sales growth, 10.66% higher growth in cost, and 13.88% higher growth in inventories. More importantly, firms do not quickly recover from the negative economic consequences of glitches. During the two-year time period after the glitch announcement, operating income, sales, total costs, and inventories do not improve. We also find that it does not matter who caused the glitch, what the reason was for the glitch, or what industry a firm belongs to---glitches are associated with negative operating performance across the board.

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    File URL: http://dx.doi.org/10.1287/mnsc.1040.0353
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 51 (2005)
    Issue (Month): 5 (May)
    Pages: 695-711

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    Handle: RePEc:inm:ormnsc:v:51:y:2005:i:5:p:695-711

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    Related research

    Keywords: supply chain glitches; empirical analysis; operating performance;

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    Cited by:
    1. Mohebbi, Esmail & Hao, Daipeng, 2008. "An inventory model with non-resuming randomly interruptible lead time," International Journal of Production Economics, Elsevier, vol. 114(2), pages 755-768, August.
    2. Uskonen, Jukka & Tenhiälä, Antti, 2012. "The price of responsiveness: Cost analysis of change orders in make-to-order manufacturing," International Journal of Production Economics, Elsevier, vol. 135(1), pages 420-429.
    3. Lichtenthaler, Ulrich, 2010. "Determinants of proactive and reactive technology licensing: A contingency perspective," Research Policy, Elsevier, vol. 39(1), pages 55-66, February.
    4. Marc Bollecker & Wilfrid Azan, 2008. "Les frontières de la recherche en contrôle de gestion : une analyse des cadres théoriques mobilisés," Post-Print halshs-00522395, HAL.
    5. Klibi, Walid & Martel, Alain, 2012. "Scenario-based Supply Chain Network risk modeling," European Journal of Operational Research, Elsevier, vol. 223(3), pages 644-658.
    6. Thomas J Holmes & David K Levine & James A Schmitz Jr, 2008. "Monopoly and the Incentive to Innovate When Adoption Involves Switchover Disruptions," Levine's Working Paper Archive 122247000000001920, David K. Levine.
    7. Wagner, Stephan M. & Neshat, Nikrouz, 2010. "Assessing the vulnerability of supply chains using graph theory," International Journal of Production Economics, Elsevier, vol. 126(1), pages 121-129, July.
    8. Richard Kum-yew Lai, 2005. "Inventory and the Stock Market," Finance 0509006, EconWPA.
    9. Alexandru Constăngioară, 2013. "Performance Metrics in Supply Chain Management. Evidence from Romanian Economy," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 15(33), pages 170-179, February.
    10. Ivanov, Dmitry & Sokolov, Boris, 2013. "Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 313-323.
    11. Wuttke, David A. & Blome, Constantin & Henke, Michael, 2013. "Focusing the financial flow of supply chains: An empirical investigation of financial supply chain management," International Journal of Production Economics, Elsevier, vol. 145(2), pages 773-789.
    12. Blome, Constantin & Schoenherr, Tobias, 2011. "Supply chain risk management in financial crises--A multiple case-study approach," International Journal of Production Economics, Elsevier, vol. 134(1), pages 43-57, November.
    13. Chiang, Wen-Chyuan & Russell, Robert & Xu, Xiaojing & Zepeda, David, 2009. "A simulation/metaheuristic approach to newspaper production and distribution supply chain problems," International Journal of Production Economics, Elsevier, vol. 121(2), pages 752-767, October.

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