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Assessing the supply chain performance: a causal analysis

Author

Listed:
  • Erkan Bayraktar

    (American University of the Middle East)

  • Kazim Sari

    (Beykent University)

  • Ekrem Tatoglu

    (University of Sharjah
    Ibn Haldun University)

  • Selim Zaim

    (Istanbul Sehir University)

  • Dursun Delen

    (Oklahoma State University)

Abstract

Measuring the performance-related factors of a unit within a supply-chain is a challenging problem, mainly because of the complex interactions among the members governed by the supply chain strategy employed. Synergistic use of discrete-event simulation and structural equation modeling allows researchers and practitioners to analyze causal relationships between order-fulfillment characteristics of a supply-chain and retailers’ performance metrics. In this study, we model, simulate, and analyze a two-level supply-chain with seasonal linear demand, and using the information therein, develop a causal model to measure the links/relationships among the order-fulfillment factors and the retailer’s performance. According to the findings, of all the order-fulfillment characteristics of a supply-chain, the forecast inaccuracy was found to be the most important in mitigating the bullwhip effect. Concerning the total inventory cost and fill-rate as performance indicators of retailers, the desired service level had the highest priority, followed by the lead-time and forecast inaccuracy, respectively. To reduce the total inventory cost, the bullwhip effect seems to have the lowest priority for the retailers, as it does not appear to have a significant impact on the fill rate. Although seasonality (to some extent) influences the retailer’s performance, it does not seem to have a significant impact on the ranking of the factors affecting retailers’ supply-chain performance; except for the case where the backorder cost is overestimated.

Suggested Citation

  • Erkan Bayraktar & Kazim Sari & Ekrem Tatoglu & Selim Zaim & Dursun Delen, 2020. "Assessing the supply chain performance: a causal analysis," Annals of Operations Research, Springer, vol. 287(1), pages 37-60, April.
    • Handle: RePEc:spr:annopr:v:287:y:2020:i:1:d:10.1007_s10479-019-03457-y
    DOI: 10.1007/s10479-019-03457-y
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    References listed on IDEAS

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