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.
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- Department of Logistics, Marketing, Hospitality and Analytics - Senior Lecturer
- Huddersfield Business School
- Northern Productivity Hub - Member