Discovery‐to‐Recall in the Automotive Industry: A Problem‐Solving Perspective on Investigation of Quality Failures

召回 质量(理念) 产品(数学) 汽车工业 任务(项目管理) 营销 透视图(图形) 心理学 计算机科学 业务 认知心理学 经济 工程类 人工智能 管理 数学 哲学 几何学 认识论 航空航天工程
作者
John Ni,Xiaowen Huang
出处
期刊:Journal of Supply Chain Management [Wiley]
卷期号:54 (2): 71-95 被引量:41
标识
DOI:10.1111/jscm.12160
摘要

Several recent high‐profile product recalls raise the question of why companies take so long to recall defective products from the market. The recall timing decision is not a simple task, as companies constantly face multiple, often competing goals during the recall process. In this research, we examine variations in large automakers’ recall timing decisions after an initial report of a suspected quality failures. Drawing upon problem‐solving theory, we theorize about how five recall attributes impact discovery‐to‐recall, defined as the time between a defective product's initial discovery and its officially announced recall. To test our hypotheses, we assembled a vehicle recall investigation dataset from recall reports filed by the six largest automakers that sold passenger cars in the United States from 2000 to 2012. Results from event history analysis reveal that discovery‐to‐recall is longer for: (1) recalls that are triggered by external initial reports, rather than internal initial reports; (2) recalls that are attributed to suppliers, rather than automakers; (3) recalls that are associated with design flaws, as opposed to manufacturing flaws; and (4) recalls with more models involved. We also find that cumulative recall experience, measured as the total number of previous recalls, shortens discovery‐to‐recall. These findings improve our understanding of why the timing of vehicle recalls varies considerably at the individual recall level. They also highlight the value of problem‐solving theory in vehicle recall research, as well as quality management research.
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