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

Vivek Astvansh (), George P. Ball () and Matthew Josefy ()
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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

Manufacturing & Service Operations Management, 2022, vol. 24, issue 3, 1457-1473

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.

Keywords: product recall; time-to-recall; managerial decision making; data; automotive (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:24:y:2022:i:3:p:1457-1473

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