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Optimal Procurement Strategy Under Supply Risk

Author

Listed:
  • HARESH GURNANI

    (Department of Management, University of Miami, Coral Gables, Florida 33124, USA)

  • MEHMET GÜMÜŞ

    (Desautels Faculty of Management, McGill University, Montreal, Quebec H3A 1G5, Canada)

  • SAIBAL RAY

    (Desautels Faculty of Management, McGill University, Montreal, Quebec H3A 1G5, Canada)

  • TRIDIP RAY

    (Department of Economics, Indian Statistical Institute, New Delhi, 110 016, India)

Abstract

With the rapid expansion of global business, newer suppliers with cheaper but possibly unreliable technologies have entered the marketplace to win orders from buyer firms by beating the price of their perfectly reliable (but expensive) competitors. We model the procurement problem as a Nash game where the buyer has to allocate its purchases between an expensive but reliable supplier, and a cheaper but unreliable supplier. The suppliers specify prices for different proportions of the order awarded to them. Our analysis shows that, when perfect information is available about the reliability level of the unreliable supplier, the Nash equilibrium is a sole-sourcing allocation and that the supplier selection decision depends on the reliability and cost differentials between the two suppliers. In addition, we model the case when the buyer and the reliable supplier have limited information about the reliability of the unreliable supplier. Even in such an asymmetric scenario, the buyer's equilibrium allocation is a sole-sourcing outcome, but depending on system conditions either a separating or a pooling equilibrium is possible. An interesting insight into the effect of information asymmetry is that it can result in higher or lower profits/costs for the channel partners (compared to the perfect information case). As such, the buyer may even benefit from information asymmetry regarding unreliable supplier due to its impact on the degree of competition between the two suppliers.

Suggested Citation

  • Haresh Gurnani & Mehmet Gümüş & Saibal Ray & Tridip Ray, 2012. "Optimal Procurement Strategy Under Supply Risk," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(01), pages 1-31.
  • Handle: RePEc:wsi:apjorx:v:29:y:2012:i:01:n:s0217595912400064
    DOI: 10.1142/S0217595912400064
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    Citations

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    Cited by:

    1. Shuang Xiao & Guo Li & Yunjing Jia, 2017. "Estimating the Constant Elasticity of Variance Model with Data-Driven Markov Chain Monte Carlo Methods," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-23, February.
    2. Gülcan Petriçli & Gül Gökay Emel, 2016. "Determining Strategy Based Supplier Pre-Qualification Criteria With Fuzzy Relational Maps," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 4(2), pages 11-40, September.
    3. Xiao Huang & Tamer Boyacı & Mehmet Gümüş & Saibal Ray & Dan Zhang, 2016. "United We Stand or Divided We Stand? Strategic Supplier Alliances Under Order Default Risk," Management Science, INFORMS, vol. 62(5), pages 1297-1315, May.
    4. Congjun Rao & Yong Zhao & Junjun Zheng & Mark Goh & Cheng Wang, 2017. "Bidding Behavior and Equilibrium Excursion of Uniform Price Auction Mechanism," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(06), pages 1-17, December.
    5. Jie Xiang & Juliang Zhang & T. C. E. Cheng & Jose Maria Sallan & Guowei Hua, 2019. "Efficient Multi-Attribute Auctions Considering Supply Disruption," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(03), pages 1-28, June.
    6. Thyago Celso Cavalcante Nepomuceno & Késsia Thais Cavalcanti Nepomuceno & Thiago Poleto & Victor Diogho Heuer de Carvalho & Ana Paula Cabral Seixas Costa, 2022. "When Penalty Fails: Modeling Contractual Misincentives With Evidence From Portugal ITO Agreements," SAGE Open, , vol. 12(4), pages 21582440221, December.
    7. Pan, Wenting & So, Kut C. & Xiao, Guang, 2022. "Benefits of backup sourcing for components in assembly systems under supply uncertainty," European Journal of Operational Research, Elsevier, vol. 302(1), pages 158-171.

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