Empirical study of link between operations and financial performance for retailers

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Last Modified
  • March 20, 2019
Creator
  • Mani, Vidya
    • Affiliation: Kenan-Flagler Business School
Abstract
  • Retailers continually try to improve their store operations in order to achieve better financial performance. However, there appears to be limited empirical research that shows the influence of operations management on financial performance. We conduct an empirical study of the link between operations management and financial performance of retailers by investigating at drivers of store level operations in a single retail chain, and studying the relative firm level performance of US public retailers. We utilize data from two sources; individual proprietary store level traffic data and publicly available financial data for this study. In addition, we complement our datasets by extracting information on demographics from publicly available databases. In the first chapter, we use detailed traffic data to study whether there is understaffing at a heterogeneous group in retail stores belonging to the same retail chain. We then look at some of the underlying causes for this understaffing, including traffic forecast errors and scheduling constraints, and quantify their impact on store profits. In the second chapter, we characterize the underlying distribution of hourly traffic data that is obtained with help of traffic counters at each of the retail stores and study the impact that competition and location demographics have on the observed variability in traffic. We then explore the managerial implications of having detailed traffic information on labor planning by deriving better forecasts of traffic that would aid staffing decisions. Finally, in the third chapter, we conduct a firm level analysis of US public retailers with help of benchmarking metrics developed from operations management. We demonstrate an inverted-U relationship between abnormal inventory growth and one-year ahead earnings. We also show that equity analysts are systematically biased in their earnings forecasts as they fail to incorporate information contained in abnormal inventory growth and further, an investment strategy based on abnormal inventory growth can yield significant abnormal returns.
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  • In Copyright
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  • "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Kenan-Flagler Business School (Operations, Technology, and Innovation Management)."
Advisor
  • Swaminathan, Jayashankar M.
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Place of publication
  • Chapel Hill, NC
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  • Open access

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