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Incentives for RFID adoption with imperfect read rates: Wholesale price premium versus cost sharing

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  • Li-Hao Zhang
  • Huixiao Yang

Abstract

We consider a supply chain system consisting of a manufacturer and a retailer who requires RFID technology to eliminate inventory misplacement errors. The demand is uncertain and RFID read rates are imperfect. To better align their incentives, the manufacturer can make up her additional cost stemmed from RFID adoption through two compensatory schemes: Wholesale price premium (PR) and cost sharing (CS). Our analysis shows that under PR, the manufacturer surcharges a premium higher than the tag cost, whereas under CS, the retailer will bear the entire tag cost. Because profit margin is proportionally allocated to the firms at the same ratio under PR and without RFID at the break-even point, their incentives to adopt RFID under PR are perfectly aligned. Surprisingly, under CS, further increase in RFID read rates can benefit the retailer but hurts the manufacturer. Further, the manufacturer prefers PR, whereas the retailer prefers CS when the tag cost is small; but both prefer PR when the cost is medium. Contrary to previous findings, the retailer’s incentive for RFID adoption under CS is stronger than the first-best level; the reverse is true for the manufacturer. Finally, CS improves the supply chain efficiency over PR but cannot coordinate the chain.

Suggested Citation

  • Li-Hao Zhang & Huixiao Yang, 2019. "Incentives for RFID adoption with imperfect read rates: Wholesale price premium versus cost sharing," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(9), pages 1440-1456, September.
  • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:9:p:1440-1456
    DOI: 10.1080/01605682.2018.1506252
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    Cited by:

    1. Feng Tao & Yanhong Xie & Yao-Yu Wang & Fujun Lai & Kin Keung Lai, 2022. "Contract strategies in competitive supply chains subject to inventory inaccuracy," Annals of Operations Research, Springer, vol. 309(2), pages 641-661, February.
    2. Dejian Yu & Zhaoping Yan, 2022. "Combining machine learning and main path analysis to identify research front: from the perspective of science-technology linkage," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4251-4274, July.
    3. Simonetto, Marco & Sgarbossa, Fabio & Battini, Daria & Govindan, Kannan, 2022. "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda," International Journal of Production Economics, Elsevier, vol. 253(C).
    4. Yang, Huixiao & Chen, Wenbo, 2020. "Game modes and investment cost locations in radio-frequency identification (RFID) adoption," European Journal of Operational Research, Elsevier, vol. 286(3), pages 883-896.
    5. Tao, Feng & Wang, Liang & Fan, Tijun & Yu, Hao, 2022. "RFID adoption strategy in a retailer-dominant supply chain with competing suppliers," European Journal of Operational Research, Elsevier, vol. 302(1), pages 117-129.
    6. Lou, Yaqi & Feng, Lipan & He, Shuguang & He, Zhen & Zhao, Xiukun, 2020. "Logistics service outsourcing choices in a retailer-led supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).

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