Abstract

Inventory inaccuracy refers to the discrepancy between the actual inventory and the recorded inventory information. Inventory inaccuracy is prevalent in retail stores. It may result in a higher inventory level or poor customer service. Earlier studies of inventory inaccuracy have traditionally assumed risk-neutral retailers whose objective is to maximize expected profits. We investigate a risk-averse retailer within a newsvendor framework. The risk aversion attitude is measured by conditional-value-at-risk (CVaR). We consider inventory inaccuracy stemming both from permanent shrinkage and temporary shrinkage. Two scenarios of reducing inventory shrinkage are presented. In the first scenario, the retailer conducts physical inventory audits to identify the discrepancy. In the second scenario, the retailer deploys an automatic tracking technology, radiofrequency identification (RFID), to reduce inventory shrinkage. With the CVaR criterion, we propose optimal policies for the two scenarios. We show monotonicity between the retailer’s ordering policy and his risk aversion degree. A numerical analysis provides managerial insights for risk-averse retailers considering investing in RFID technology.

Highlights

  • Inventory inaccuracy occurs when the inventory shown in the information system does not match that of the physically available inventory [1]

  • Inventory inaccuracy is prevalent in retail stores

  • We utilized CVaR to explore a risk-averse retailer’s optimal ordering policy subject to inventory shrinkage and investigated his incentive to invest in radiofrequency identification (RFID) technology

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Summary

Introduction

Inventory inaccuracy occurs when the inventory shown in the information system does not match that of the physically available inventory [1]. Among the few studies that have dealt analytically with the inventory inaccuracy problem, Rekik et al [4] considered a risk-neutral retailer subject to misplacement errors They showed the impact of misplacement errors on ordering decisions and explored the benefits of obtaining information about these errors. Rekik et al [5] analyzed a retailer’s ordering policy in a multiperiod setting, where the records were inaccurate due to theft They investigated the contribution of perfect RFID technology to improve the inventory system. The contribution of this paper is threefold: (i) applying CVaR to optimize retailers’ inventory policies subject to inaccurate inventory, (ii) investigating the impact of different types of inventory shrinkage on retailers’ decisions, and (iii) providing managerial insights for risk-averse retailers to invest in RFID technology.

A Modeling Framework for Risk-Averse Retailers Subject to Inventory Shrinkage
The Risk Measure Criterion
Numerical Analysis
Findings
Conclusion

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