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Most productive scale size versus demand fulfillment: A solution to the capacity dilemma

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  • Lee, Chia-Yen

Abstract

The field of economics associates capacity planning with economic scale size and finds the characteristics of the production function whereas the operations management community focuses on demand fulfillment to reduce the loss of sales or inventory for profit maximization. However, there is a troublesome capacity trade-off for firms that need to achieve economic scale size and demand fulfillment simultaneously; in particular, a firm's demand is variable and some of the variation is random. This study proposes a multi-objective mathematical program with data envelopment analysis (DEA) constraints to set an efficient target which shows a trade-off between the most-productive-scale-size (MPSS) benchmark and a potential demand fulfillment benchmark. The study also employs the minimax regret (MMR) approach and the stochastic programming (SP) technique to address target variations caused by demand fluctuations. The result shows how capacity planning via the proposed models can help managers address the capacity dilemma.

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  • Lee, Chia-Yen, 2016. "Most productive scale size versus demand fulfillment: A solution to the capacity dilemma," European Journal of Operational Research, Elsevier, vol. 248(3), pages 954-962.
    • Handle: RePEc:eee:ejores:v:248:y:2016:i:3:p:954-962
    DOI: 10.1016/j.ejor.2015.07.061
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    Cited by:

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    2. Saeed Assani & Jianlin Jiang & Ahmad Assani & Feng Yang, 2019. "Estimating and decomposing most productive scale size in parallel DEA networks with shared inputs: A case of China's Five-Year Plans," Papers 1910.03421, arXiv.org, revised Oct 2019.
    3. Hajar Haghighatpisheh & Sohrab Kordrostami & Alireza Amirteimoori & Farhad Hosseinzadeh Lotfi, 2022. "Optimal scale sizes in input–output allocative data envelopment analysis models," Annals of Operations Research, Springer, vol. 315(2), pages 1455-1476, August.
    4. Mustapha Daruwana Ibrahim & Sahand Daneshvar & Hüseyin Güden & Bela Vizvari, 2020. "Target setting in data envelopment analysis: efficiency improvement models with predefined inputs/outputs," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1319-1336, December.
    5. Eshagh Esfandiar & Robabeh Eslami & Mohammad Khoveyni & Alireza Gilani, 2023. "Identifying the closest most productive scale size unit in data envelopment analysis," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 623-660, June.
    6. Fangqing Wei & Yanan Fu & Feng Yang & Chun Sun & Sheng Ang, 2023. "Closest target setting with minimum improvement costs considering demand and resource mismatches," Operational Research, Springer, vol. 23(3), pages 1-29, September.

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