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學(xué)術(shù)動(dòng)態(tài)

學(xué)術(shù)動(dòng)態(tài)

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題目:Towards a Better Understanding of Defect Investigations and Product Recalls in the U.S. Automobile Industry

作者: 編輯:賈峰菊 發(fā)布時(shí)間:2021-01-12

主講人:沈鵬 博士

時(shí)間:1月13日上午9點(diǎn)開始

地點(diǎn):bwin必贏唯一官網(wǎng)314室

騰訊會(huì)議ID:834631772

歡迎大家參加!


主講人簡介:

Peng Shen (沈鵬)is currently a Ph.D. Candidate in the Department of Economics at Indiana University Bloomington. He expects to graduate in July, 2021. Peng's research interests include product recall management, regulation policy, empirical marketing strategy, applied econometrics and time series analysis.


講座簡介:

Business press and public safety advocates often accuse product manufacturers of taking too long to investigate a potential product defect and initiate a recall, should the defect be confirmed. These stakeholders have demanded that the relevant regulator open its parallel investigation of the defect. Such demands assume that the regulator’s parallel investigation can influence the manufacturer, expediting the manufacturer’s recall (i.e. an "influenced recall") completion. Our research provides empirical evidence against this assumption. Using a sample of 2,181 automobile recalls, 297 of which were preceded by a regulatory investigation (influenced recall), we document that, relative to an uninfluenced recall, an influenced recall completes 11.25% slower.

To further study the detailed mechanisms of this delaying effect, we dig deeper into the manufacturer's defect investigations. When a manufacturer discovers that its products have a safety defect, it investigates the defect, devises a solution, initiates a product recall, and remedies the defective product units. In the context of vehicle recalls in the U.S., the law requires the manufacturer to create a narrative, as part of its regulatory filing, of the steps it took to investigate the defect. We first collect the textual narratives of 1,402 defect investigation reports by 16 vehicle manufacturers during 2011–2018. Applying theory and methods in computational linguistics, we use the lexical diversity of the narrative as a measure of the manufacturer’s knowledge gained during the defect investigation. We show that the manufacturer gains more knowledge when the regulatory influence during the investigation is low, and this more knowledge gained in the investigation accelerates the manufacturer's repair of the recalled vehicles.


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