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Equivalent Inventory Metrics: A Behavioral Perspective

Author

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  • Tobias Stangl

    (Department of Supply Chain Management and Management Science, University of Cologne, 50923 Cologne, Germany)

  • Ulrich W. Thonemann

    (Department of Supply Chain Management and Management Science, University of Cologne, 50923 Cologne, Germany)

Abstract

We analyze how performance metrics that contain equivalent information affect actual decisions. We consider two such performance metrics from supply chain management, days of supply and inventory turn rate, where one is the inverse of the other. We argue that individuals’ assessment of performance is also affected by the metric as opposed to solely based on the inventory value that actually matters. We perform three laboratory studies and analyze how decisions are affected by the metric used to indicate inventory performance. The first study considers alternative inventory optimizations, out of which one must be selected. The second study analyzes a decision maker who must decide on the effort to invest in optimizing inventory of a specific product. The third study corresponds to the economic order quantity model. Our behavioral models suggest that decisions are affected by the metric that is used to indicate performance, and we find support for the predictions in laboratory experiments with human subjects: Under the inventory turn rate metric, individuals overvalue inventory reductions. Compared to decisions under the days of supply metric, they choose worse inventory optimization options, invest more effort optimizing inventory of specific products, and choose higher ordering cost.

Suggested Citation

  • Tobias Stangl & Ulrich W. Thonemann, 2017. "Equivalent Inventory Metrics: A Behavioral Perspective," Manufacturing & Service Operations Management, INFORMS, vol. 19(3), pages 472-488, July.
  • Handle: RePEc:inm:ormsom:v:19:y:2017:i:3:p:472-488
    DOI: 10.1287/msom.2017.0620
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    2. Jinrui Pan & Jason Shachat & Sijia Wei, 2022. "Cognitive Stress and Learning Economic Order Quantity Inventory Management: An Experimental Investigation," Decision Analysis, INFORMS, vol. 19(3), pages 229-254, September.
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    5. Robert J. Batt & Jordan D. Tong, 2020. "Mean Service Metrics: Biased Quality Judgment and the Customer–Server Quality Gap," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 975-995, September.

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