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The Event Study Method in Logistics Research: Overview and a Critical Analysis

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  • Lincoln C. Wood

    (Department of Management, University of Otago, Dunedin, New Zealand & School of Management, Curtin University, Western Australia)

  • Jason X. Wang

    (Department of Management, University of Otago, Dunedin, New Zealand)

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.

Suggested Citation

  • Lincoln C. Wood & Jason X. Wang, 2018. "The Event Study Method in Logistics Research: Overview and a Critical Analysis," International Journal of Applied Logistics (IJAL), IGI Global, vol. 8(1), pages 57-79, January.
  • Handle: RePEc:igg:jal000:v:8:y:2018:i:1:p:57-79
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    Cited by:

    1. Bag, Surajit & Yadav, Gunjan & Wood, Lincoln C. & Dhamija, Pavitra & Joshi, Sudhanshu, 2020. "Industry 4.0 and the circular economy: Resource melioration in logistics," Resources Policy, Elsevier, vol. 68(C).
    2. Lincoln C. Wood & Linh N. K. Duong & Jason X. Wang, 2022. "Business Process Improvement for Sustainable Technologies Investments in Construction: A Configurational Approach," Sustainability, MDPI, vol. 14(9), pages 1-14, May.

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