Brown Bag Talk: Complaint Mining in the Automotive Industry
Posted in: Linguistics News
Date/Time: Thursday, April 11 at 1pm
Location: SBUS Room 11
Assistant Professor of Information Management and Business Analytics, Feliciano School of Business
The screening and identification of potential safety defects is a crucial task in the recall decision making process. However, in 2015, the U.S. Office of the Inspector General published a report detailing alarming shortcomings in the use and analysis of consumer defect complaint data by regulators, which is the primary data source for defect screening and identification (U.S. Office of the Inspector General 2015). The report finds many problems, including: 1) issues with data input controls leading to inconsistencies in reporting; 2) a lack of formal statistical analysis of early warning reporting data; and 3) manual screening and misguided decision making, lacking standards and protocols. Motivated by both these identified inadequacies and the increasing magnitude and frequency in which recalls are conducted, this research utilizes the abundance of complaint, recall and defect investigation data to present statistical techniques and methods that can be utilized by NHTSA as an initial step towards more informed, automated and efficient defect investigation decision making.
Bio: Chelsey Hill is an Assistant Professor of Business Analytics in the Information Management and Business Analytics Department of the Feliciano School of Business at Montclair State University. She holds a BA in Political Science from The College of New Jersey, an MS in Business Intelligence from Saint Joseph’s University and a PhD in Business Administration with a concentration in Decision Sciences from Drexel University. Her research interests include consumer product recalls, online consumer reviews, safety and security, public policy and humanitarian operations. Her research has been published in Journal of Informetrics and the International Journal of Business Intelligence Research.