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The Recall Decision Exposed: Automobile Recall Timing and Process Data Set

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  • Vivek Astvansh

    (Department of Marketing, Kelley School of Business, Indiana University, Bloomington, Indiana 47405; The Center for Education and Research in Retail, Kelley School of Business, Indiana University, Bloomington, Indiana 47405; The Institute for Corporate Governance, Kelley School of Business, Indiana University, Bloomington, Indiana 47405; Environmental Resilience Institute, Indiana University, Bloomington, Indiana 47408)

  • George P. Ball

    (Department of Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • Matthew Josefy

    (Department of Management and Entrepreneurship, Kelley School of Business, Indiana University Bloomington, Indiana 47405)

Abstract

Problem definition : There is a concerted effort across multiple academic disciplines to understand the recall decision-making process. Specifically, what steps does a manufacturer take following a product defect discovery and resulting in the product recall decision? This effort has often been limited to case studies within a particular manufacturer, largely due to the absence of consistent and comparable data across firms. Methodology/results : This data paper provides a foundation for future research on recall decisions by processing and coding textual disclosures on 2,120 recalls initiated in the United States by 27 automobile manufacturers from 2009 to 2018. For each recall, the data set provides the time the firm took to make the recall decision by comparing the defect awareness date to the recall decision date, whether the recall was associated with a supplier, the number of events in the recall decision-making process, and the date and description of each event. Managerial implications : Not only can these data enhance product recall research by providing key recall decision-making variables unavailable in related research, but an additional indication of the value of our data set also comes from National Highway Traffic Safety Administration (NHTSA), the automobile regulator in the United States. We held discussions with a senior leader at the NHTSA’s Recall Management Division related to this data set. This discussion revealed that the NHTSA does not have these data in an analyzable form and that they might be interested in using our data set for their reports, such as the NHTSA’s biennial reports to the U.S. Congress. This signal suggests that regulators, as well as researchers, practitioners, and other safety advocates, may find our data set useful.

Suggested Citation

  • Vivek Astvansh & George P. Ball & Matthew Josefy, 2022. "The Recall Decision Exposed: Automobile Recall Timing and Process Data Set," Manufacturing & Service Operations Management, INFORMS, vol. 24(3), pages 1457-1473, May.
  • Handle: RePEc:inm:ormsom:v:24:y:2022:i:3:p:1457-1473
    DOI: 10.1287/msom.2022.1085
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    References listed on IDEAS

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    1. Ujjal Kumar Mukherjee & Kingshuk K. Sinha, 2018. "Product Recall Decisions in Medical Device Supply Chains: A Big Data Analytic Approach to Evaluating Judgment Bias," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1816-1833, October.
    2. Sriram Thirumalai & Kingshuk K. Sinha, 2011. "Product Recalls in the Medical Device Industry: An Empirical Exploration of the Sources and Financial Consequences," Management Science, INFORMS, vol. 57(2), pages 376-392, February.
    3. Jay R. Galbraith, 1974. "Organization Design: An Information Processing View," Interfaces, INFORMS, vol. 4(3), pages 28-36, May.
    4. Adam J. Wowak & Michael J. Mannor & Kaitlin D. Wowak, 2015. "Throwing caution to the wind: The effect of CEO stock option pay on the incidence of product safety problems," Strategic Management Journal, Wiley Blackwell, vol. 36(7), pages 1082-1092, July.
    5. Rachna Shah & George P. Ball & Serguei Netessine, 2017. "Plant Operations and Product Recalls in the Automotive Industry: An Empirical Investigation," Management Science, INFORMS, vol. 63(8), pages 2439-2459, August.
    6. George Ball & Enno Siemsen & Rachna Shah, 2017. "Do Plant Inspections Predict Future Quality? The Role of Investigator Experience," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 534-550, October.
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    8. Kaitlin D. Wowak & George P. Ball & Corinne Post & David J. Ketchen, 2021. "The Influence of Female Directors on Product Recall Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 23(4), pages 895-913, July.
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    Cited by:

    1. Vivek Astvansh & Joseph J. Simpson, 2026. "A Firm’s Operational Risk: Data Set and Empirical Evidence," Manufacturing & Service Operations Management, INFORMS, vol. 28(1), pages 326-341, January.
    2. Vivek Astvansh & Kersi Antia & Gerard Tellis, 2025. "Product recall: a synthesis of multidisciplinary findings, and research directions," Marketing Letters, Springer, vol. 36(1), pages 65-77, March.
    3. Fan Zou & Yan Dong & Sining Song & Manus Rungtusanatham, 2023. "Product Recalls and Supply Base Innovation," Manufacturing & Service Operations Management, INFORMS, vol. 25(5), pages 1931-1946, September.
    4. Wu, Xuejiao & Li, Yi-Na & Wei, Jiuchang, 2026. "Product recall in the automobile industry: The impact of performance feedback on the decision of crisis management," Journal of Business Research, Elsevier, vol. 202(C).

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