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Evaluation of cycle-count policies for supply chains with inventory inaccuracy and implications on RFID investments

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  • Kök, A. Gürhan
  • Shang, Kevin H.

Abstract

Inventory record inaccuracy leads to ineffective replenishment decisions and deteriorates supply chain performance. Conducting cycle counts (i.e., periodic inventory auditing) is a common approach to correcting inventory records. It is not clear, however, how inaccuracy at different locations affects supply chain performance and how an effective cycle-count program for a multi-stage supply chain should be designed. This paper aims to answer these questions by considering a serial supply chain that has inventory record inaccuracy and operates under local base-stock policies. A random error, representing a stock loss, such as shrinkage or spoilage, reduces the physical inventory at each location in each period. The errors are cumulative and are not observed until a location performs a cycle count. We provide a simple recursion to evaluate the system cost and propose a heuristic to obtain effective base-stock levels. For a two-stage system with identical error distributions and counting costs, we prove that it is more effective to conduct more frequent cycle counts at the downstream stage. In a numerical study for more general systems, we find that location (proximity to the customer), error rates, and counting costs are primary factors that determine which stages should get a higher priority when allocating cycle counts. However, it is in general not effective to allocate all cycle counts to the priority stages only. One should balance cycle counts between priority stages and non-priority stages by considering secondary factors such as lead times, holding costs, and the supply chain length. In particular, more cycle counts should be allocated to a stage when the ratio of its lead time to the total system lead time is small and the ratio of its holding cost to the total system holding cost is large. In addition, more cycle counts should be allocated to downstream stages when the number of stages in the supply chain is large. The analysis and insights generated from our study can be used to design guidelines or scorecard systems that help managers design better cycle-count policies. Finally, we discuss implications of our study on RFID investments in a supply chain.

Suggested Citation

  • Kök, A. Gürhan & Shang, Kevin H., 2014. "Evaluation of cycle-count policies for supply chains with inventory inaccuracy and implications on RFID investments," European Journal of Operational Research, Elsevier, vol. 237(1), pages 91-105.
  • Handle: RePEc:eee:ejores:v:237:y:2014:i:1:p:91-105
    DOI: 10.1016/j.ejor.2014.01.052
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    References listed on IDEAS

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    Cited by:

    1. Ahmed Musa & Al-Amin Abba Dabo, 2016. "A Review of RFID in Supply Chain Management: 2000–2015," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 17(2), pages 189-228, June.
    2. Li, Ming & Wang, Zheng & Chan, Felix T.S., 2016. "A robust inventory routing policy under inventory inaccuracy and replenishment lead-time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 290-305.
    3. Li Chen, 2021. "Fixing Phantom Stockouts: Optimal Data‐Driven Shelf Inspection Policies," Production and Operations Management, Production and Operations Management Society, vol. 30(3), pages 689-702, March.
    4. Achal Bassamboo & Antonio Moreno & Ioannis Stamatopoulos, 2020. "Inventory Auditing and Replenishment Using Point‐of‐Sales Data," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1219-1231, May.
    5. 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.
    6. Cannella, Salvatore & Framinan, Jose M. & Bruccoleri, Manfredi & Barbosa-Póvoa, Ana Paula & Relvas, Susana, 2015. "The effect of Inventory Record Inaccuracy in Information Exchange Supply Chains," European Journal of Operational Research, Elsevier, vol. 243(1), pages 120-129.
    7. Adam J. Mersereau, 2015. "Demand Estimation from Censored Observations with Inventory Record Inaccuracy," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 335-349, July.
    8. Dai, Hongyan & Li, Jianbin & Yan, Nina & Zhou, Weihua, 2016. "Bullwhip effect and supply chain costs with low- and high-quality information on inventory shrinkage," European Journal of Operational Research, Elsevier, vol. 250(2), pages 457-469.
    9. Biswal, Arun Kumar & Jenamani, Mamata & Kumar, Sri Krishna, 2020. "The impact of RFID adoption on donor subsidy through for-profit and not-for-profit newsvendor: Implications for Indian Public Distribution system," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    10. Wang, Fuqiang & Fang, Xiaoping & Chen, Xiaohong & Li, Xihua, 2016. "Impact of inventory inaccuracies on products with inventory-dependent demand," International Journal of Production Economics, Elsevier, vol. 177(C), pages 118-130.
    11. Shabani, Amir & Maroti, Gabor & de Leeuw, Sander & Dullaert, Wout, 2021. "Inventory record inaccuracy and store-level performance," International Journal of Production Economics, Elsevier, vol. 235(C).
    12. Feng Tao & Tijun Fan & Kin Keung Lai & Lin Li, 2017. "Impact of RFID technology on inventory control policy," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(2), pages 207-220, February.
    13. Biswal, Arun Kumar & Jenamani, Mamata & Kumar, Sri Krishna, 2018. "Warehouse efficiency improvement using RFID in a humanitarian supply chain: Implications for Indian food security system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 205-224.
    14. Goldbeck, Nils & Angeloudis, Panagiotis & Ochieng, Washington, 2020. "Optimal supply chain resilience with consideration of failure propagation and repair logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    15. Rong Li & Jing‐Sheng Jeannette Song & Shuxiao Sun & Xiaona Zheng, 2022. "Fight inventory shrinkage: Simultaneous learning of inventory level and shrinkage rate," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2477-2491, June.
    16. Cannella, Salvatore & Dominguez, Roberto & Framinan, Jose M., 2017. "Inventory record inaccuracy – The impact of structural complexity and lead time variability," Omega, Elsevier, vol. 68(C), pages 123-138.

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