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Risk averse supply portfolio selection with supply, demand and spot market volatility

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  • Merzifonluoglu, Yasemin

Abstract

Enterprise Risk Management (ERM) has become one of the most essential subjects in business management. This paper establishes how risk modeling can be applied to supply chain management, specifically to supply portfolio procurement decisions of a firm. In a single period setting, parts can be procured via traditional forward contracts, option contracts or spot purchases. Customer demand and spot prices are random and possibly correlated and firm׳s primary suppliers are subject to complete disruptions and yield uncertainties. This paper analyzes several scenarios where the spot market is not available, available for buying only, and available for both buying and selling. This article develops and solves mathematical models considering the risk neutral and risk averse (CVaR) objectives independently or simultaneously. For the special case of normally distributed random variables and a risk neutral objective, optimality properties were developed. A broad numerical study examines the sensitivity of procurement strategies to key problem parameters such as, risk attitude, demand and spot price volatilities, correlation between demand and spot prices and terms of option contracts.

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  • Merzifonluoglu, Yasemin, 2015. "Risk averse supply portfolio selection with supply, demand and spot market volatility," Omega, Elsevier, vol. 57(PA), pages 40-53.
    • Handle: RePEc:eee:jomega:v:57:y:2015:i:pa:p:40-53
    DOI: 10.1016/j.omega.2015.03.006
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    4. Gongli Luo & Xiaoqing Liu & Felix T. S. Chan, 2023. "Optimal Ordering Decisions in Portfolio Procurement Considering Spot Price Fluctuation," Sustainability, MDPI, vol. 15(14), pages 1-13, July.
    5. Xu, Xinsheng & Ji, Ping & Chan, Felix T.S., 2022. "On maximizing a loss-averse buyer’s expected utility in a multi-sourcing problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 388-404.
    6. 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.
    7. Golmohammadi, Amirmohsen & Hassini, Elkafi, 2019. "Capacity, pricing and production under supply and demand uncertainties with an application in agriculture," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1037-1049.
    8. Sawik, Tadeusz, 2016. "Integrated supply, production and distribution scheduling under disruption risks," Omega, Elsevier, vol. 62(C), pages 131-144.
    9. Vijaya Dixit & Manoj Kumar Tiwari, 2020. "Project portfolio selection and scheduling optimization based on risk measure: a conditional value at risk approach," Annals of Operations Research, Springer, vol. 285(1), pages 9-33, February.
    10. Shahrbanoo Rezaei & Iman Ghalehkhondabi & Majid Rafiee & Soudabeh Namdar Zanganeh, 2020. "Supplier selection and order allocation in CLSC configuration with various supply strategies under disruption risk," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 908-934, September.
    11. Patricia Rogetzer & Lena Silbermayr & Werner Jammernegg, 2018. "Sustainable sourcing of strategic raw materials by integrating recycled materials," Flexible Services and Manufacturing Journal, Springer, vol. 30(3), pages 421-451, September.
    12. Merzifonluoglu, Yasemin, 2017. "Integrated demand and procurement portfolio management with spot market volatility and option contracts," European Journal of Operational Research, Elsevier, vol. 258(1), pages 181-192.
    13. Alavi Fard, Farzad & He, Jian & Ivanov, Dmitry & Jie, Ferry, 2019. "A utility adjusted newsvendor model with stochastic demand," International Journal of Production Economics, Elsevier, vol. 211(C), pages 154-165.
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