The Event Study Method in Logistics Research

Abstract

Logistics researchers often want to understand how particular management changes or external factors influence a firm. While this can be accomplished using operational or survey data, the authors outline an alternative approach using the event study method where inferences are made with the estimated magnitude and direction of abnormal returns. The calculated abnormal returns can be used as a dependent variable in a cross-sectional regression to understand which managerial decisions may affect these outcomes. As the method remains little used by logistics researchers, the authors outline key assumptions and design considerations. They review recent articles and provide suggestions for logistics researchers improve the rigor of their research designs. This article aims to provide an overview of the method for logistics and supply chain researchers with a focus on developing the capability to design an effective study and to evaluate research articles to assess methodological weaknesses that may lead to untrustworthy results.

Stock Market Reactions to Auto Manufacturers’ Environmental Failures

“…To generate our sample, we first undertook an initial search with preliminary keywords following guidelines in Wood and Wang (2018). As we identified announcements, we developed a more comprehensive set of keywords.…”

“…Two additional checks determined whether there were other confounding events and to ensure there were sufficient stock returns data, enabling the event to be considered in further analysis. First, a confounding event check on the event sample of 53 cases was used to determine whether other financially relevant events also occurred during the event window (McWilliams and Siegel 1997; Wood and Wang 2018). Thus, a three-day event window (the date before and after the initial announcement) was analysed for each firm, and confounding events, if any, were recorded and the event was excluded.…”

Business Process Improvement for Sustainable Technologies Investments in Construction: A Configurational Approach

“…To isolate the stock market reaction to the announcements, we used the market model [30,31], as it is frequently used in comparable research [32] and has good data availability.…”