汽车召回决策暴露:召回时间和过程数据集

Vivek Astvansh, George P. Ball, Matthew A. Josefy
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引用次数: 6

摘要

问题定义:有一个跨多个学科的协同努力来理解召回决策过程。具体来说,制造商在发现产品缺陷并做出产品召回决定后采取了哪些步骤?这种努力通常仅限于特定制造商的案例研究,主要是因为缺乏跨公司的一致和可比较的数据。方法/结果:本数据论文通过对2009年至2018年美国27家汽车制造商发起的2120起召回事件的文本披露进行处理和编码,为未来召回决策的研究提供了基础。对于每次召回,数据集通过比较缺陷意识日期和召回决策日期、召回是否与供应商有关、召回决策过程中的事件数量以及每个事件的日期和描述,提供公司做出召回决定所花费的时间。管理意义:这些数据不仅可以通过提供相关研究中不可用的关键召回决策变量来加强产品召回研究,而且我们的数据集的价值还来自美国国家公路交通安全管理局(NHTSA),美国的汽车监管机构。我们与NHTSA召回管理部门的一位高级领导就该数据集进行了讨论。这次讨论表明,NHTSA没有可分析形式的这些数据,他们可能有兴趣在他们的报告中使用我们的数据集,例如NHTSA向美国国会提交的两年一次的报告。这一信号表明,监管机构、研究人员、从业人员和其他安全倡导者可能会发现我们的数据集很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Recall Decision Exposed: Automobile Recall Timing and Process Data Set
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.
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