green-color-2017-solid-green-color-2560x1600-dark-green-solid-color-background.jpg

News

News Blog

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

In the second Spotlight of 2018 we talk to Dr. John Ni about recalls; specifically discover to recall within the automotive industry. Dr Ni co-authored the article with Dr Xiaowen Huang and is one of the current early view publications available here:

"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."
The full article can be found here
DOI: 10.1111/jscm.12160

 
Jacqueline JagoRecall