Vehicle Consumer Complaint Reports Involving Severe Incidents: Mining Large Contingency Tables

Abstract

According to 2010–2014 Fatality Analysis Reporting System (FARS) data, nearly 6.35% of fatal crashes happened as a result of vehicles’ pre-existing manufacturing defects. The National Highway Traffic Safety Administration’s (NHTSA) vehicle complaint database incorporates more than 1.37 million complaint reports (as of June 1, 2017). These reports contain extended information on vehicle-related disruptions. Around 5% of these reports involve some level of injury or fatalities. This study had two principal objectives, namely (1) perform knowledge discovery to understand the latent trends in consumer complaints, and (2) identify clusters with high relative reporting ratios from a large contingency table of vehicle models and associated complaints. To accomplish these objectives, 67,201 detailed reports associated with injury or fatalities from the NHTSA vehicle complaint database were examined. Exploratory text mining and empirical Bayes (EB) data mining were performed. Additionally, this study analyzed five years (2010–2014) of FARS data to examine the research findings. Results show that major vehicular defects are associated with air bags, brake systems, seat belts, and speed controls. The EB metrics identified several key ‘ vehicle model with major defect’ groups that require more attention. This study demonstrates the applicability of consumer complaints in identifying major vehicular defects as well as key groups of ‘ vehicle model with major defect.’ The findings of this study will provide a significant contribution to the reduction of crashes from vehicle-related disruptions. The research presented in this paper is crucial given the ongoing advancement of connected and automated vehicle technologies.

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