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Radio frequency identification (RFID)-enabled smart shelves have recently attracted enormous attention from both industry and academia. Retailers have an explosion of interest in deploying smart shelves for the automatic ordering and the reduction of inventory inaccuracy. This study explores the retailers’ optimal policy for investing in a smart shelf inventory control system. Since the decision maker’s risk attitude plays an important role in its investment in technology, we therefore specifically consider the retailers’ risk attitude. The risk attitude is measured by the mean-variance analysis. We derive analytical expressions for the benefit of the smart shelf and specify the conditions under which retailers should invest in it. We also show the explicit relationship between the retailer’s risk attitude and his optimal policy. Finally, we conduct a numerical analysis to provide managerial insights for retailers to invest in smart shelves.
Lijing Zhu; Peize Wang; Sha Xi. Mean-Variance Analysis of Retailers Deploying RFID-Enabled Smart Shelves. Information 2018, 9, 40 .
AMA StyleLijing Zhu, Peize Wang, Sha Xi. Mean-Variance Analysis of Retailers Deploying RFID-Enabled Smart Shelves. Information. 2018; 9 (2):40.
Chicago/Turabian StyleLijing Zhu; Peize Wang; Sha Xi. 2018. "Mean-Variance Analysis of Retailers Deploying RFID-Enabled Smart Shelves." Information 9, no. 2: 40.
Food waste stemmed from food contamination and ineffective quality control is a significant challenge to food management. Supply chain traceability has become an essential task of the food industry for guaranteeing food quality and safety and reducing food waste. Radio Frequency Identification (RFID) has emerged as a lead technology in the development of traceability systems, which enable automatically capturing of food information along the supply chain. However, the significant investment cost has been a major obstacle in the diffusion of traceability systems in the food industry. This study conducts a cost-benefit analysis of a RFID-enabled traceability system for a two-level perishable food supply chain, which consists of an upstream supplier and a downstream retailer. Consumer perceptions of food quality and safety are jointly considered when evaluating the value of a traceability system. The optimal decisions of the supply chain participants are derived in both centralized and decentralized systems, in terms of wholesale price, order quantity, price markdowns, and granularity level of the traceability system. The results show that a dynamic pricing policy supported by the traceability system could significantly reduce food waste and improve the retailer’s performance. We further propose a two-part tariff contract to coordinate the supply chain and to distribute benefits and costs of the traceability system between supply chain participants. This study demonstrates that a well-developed traceability system could significantly improve the supply chain performance and become a profitable investment for the food industry.
Lijing Zhu. Economic Analysis of a Traceability System for a Two-Level Perishable Food Supply Chain. Sustainability 2017, 9, 682 .
AMA StyleLijing Zhu. Economic Analysis of a Traceability System for a Two-Level Perishable Food Supply Chain. Sustainability. 2017; 9 (5):682.
Chicago/Turabian StyleLijing Zhu. 2017. "Economic Analysis of a Traceability System for a Two-Level Perishable Food Supply Chain." Sustainability 9, no. 5: 682.