Unveiling Regulatory Operations: A Data Set of the Determinants, Process, and Outcomes of Product Defect Investigations by the U.S. Automotive Safety Regulator

Problem definition : The paucity of data on governmental regulatory agencies’ product safety defect investigations has restricted our knowledge about (1) the determinants of a regulator’s decisions to open or close an investigation, (2) the process it follows between opening and closing of an investigation, and (3) the outcomes of the investigation when it is closed. Methodology/results : The authors view a safety regulator’s opening and closing of a product defect investigation as a decision of interest to the operations management discipline. This data paper describes a rich, novel, and hand-collected data set of all investigations that the National Highway Traffic Safety Administration—the U.S. regulator for automobile safety—opened and closed against 187 manufacturers between 2009 and 2021. The authors provide two Microsoft Excel data files, one capturing data for the investigations opened and the other for the investigations closed. The data files enable researchers to address three sets of research questions. First, researchers can use the “Data on Investigations Opened” file to model the determinants of a regulator’s opening of a product defect investigation. Second, researchers can mine the textual variables from both files to identify the steps involved in the investigation process. They can also use the process variables included in the data to investigate the regulator’s efficiency in opening and closing investigations. Third, researchers can use the “Data on Investigations Closed” file to better understand when and why a regulator closes an investigation and the outcomes of the closed investigations. Managerial implications : The data files can also be valuable to nonacademic stakeholders (e.g., governmental organizations and regulators, journalists, liability lawyers, politicians, and safety advocates). The authors provide an open-access website that simplifies the use of the data for a nonacademic audience and allows them to draw insights from the data via graphs and tables.