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Real options approach-based demand forecasting method for a range of products with highly volatile and correlated demand

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  • Huang, Ming-Guan

Abstract

To achieve a competitive edge needed for marketing highly competitive products, modern enterprises have actively sought to provide the marketplace with an expansive range of products with high random volatility of demand and correlations between demands of product. Consequently, traditional forecasting methods for separately forecasting demand for these products are likely to yield significant deviations. Therefore, this study develops a real options approach-based forecasting model to accurately predict future demand for a given range of products with highly volatile and correlated demand. Additionally, this study also proposes using Monte Carlo simulation to solve the demand forecasting model. The real options approach associated with Monte Carlo simulation not only deals effectively with random variation involving a particular demand stochastic diffusion process, but can handle the correlations in product demand.

Suggested Citation

  • Huang, Ming-Guan, 2009. "Real options approach-based demand forecasting method for a range of products with highly volatile and correlated demand," European Journal of Operational Research, Elsevier, vol. 198(3), pages 867-877, November.
    • Handle: RePEc:eee:ejores:v:198:y:2009:i:3:p:867-877
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    Cited by:

    1. Fernandes, Rui & Gouveia, Borges & Pinho, Carlos, 2013. "A real options approach to labour shifts planning under different service level targets," European Journal of Operational Research, Elsevier, vol. 231(1), pages 182-189.
    2. Bogdan Rębiasz, 2019. "The valuation of real options in a hybrid environment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(1), pages 97-119.
    3. Trigeorgis, Lenos & Tsekrekos, Andrianos E., 2018. "Real Options in Operations Research: A Review," European Journal of Operational Research, Elsevier, vol. 270(1), pages 1-24.
    4. Vafa Arani, Hamed & Rabbani, Masoud & Rafiei, Hamed, 2016. "A revenue-sharing option contract toward coordination of supply chains," International Journal of Production Economics, Elsevier, vol. 178(C), pages 42-56.
    5. Rios-Festner, Daniel & Blanco, Gerardo & Olsina, Fernando, 2020. "Long-term assessment of power capacity incentives by modeling generation investment dynamics under irreversibility and uncertainty," Energy Policy, Elsevier, vol. 137(C).
    6. Rios, Daniel & Blanco, Gerardo & Olsina, Fernando, 2019. "Integrating Real Options Analysis with long-term electricity market models," Energy Economics, Elsevier, vol. 80(C), pages 188-205.

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