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Partial input to output impacts in DEA: Production considerations and resource sharing among business subunits

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  • Raha Imanirad
  • Wade D. Cook
  • Joe Zhu

Abstract

Data envelopment analysis (DEA) is a methodology for evaluating the relative efficiencies of peer decision‐making units (DMUs), in a multiple input/output setting. Although it is generally assumed that all outputs are impacted by all inputs, there are many situations where this may not be the case. This article extends the conventional DEA methodology to allow for the measurement of technical efficiency in situations where only partial input‐to‐output impacts exist. The new methodology involves viewing the DMU as a business unit, consisting of a set of mutually exclusive subunits, each of which can be treated in the conventional DEA sense. A further consideration involves the imposition of constraints in the form of assurance regions (AR) on pairs of multipliers. These AR constraints often arise at the level of the subunit, and as a result, there can be multiple and often inconsistent AR constraints on any given variable pair. We present a methodology for resolving such inconsistencies. To demonstrate the overall methodology, we apply it to the problem of evaluating the efficiencies of a set of steel fabrication plants. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013

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  • Raha Imanirad & Wade D. Cook & Joe Zhu, 2013. "Partial input to output impacts in DEA: Production considerations and resource sharing among business subunits," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(3), pages 190-207, April.
    • Handle: RePEc:wly:navres:v:60:y:2013:i:3:p:190-207
    DOI: 10.1002/nav.21528
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    Cited by:

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    7. Hao Cai & Ling Liang & Jing Tang & Qianxian Wang & Lihong Wei & Jiaping Xie, 2019. "An Empirical Study on the Efficiency and Influencing Factors of the Photovoltaic Industry in China and an Analysis of Its Influencing Factors," Sustainability, MDPI, vol. 11(23), pages 1-22, November.
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    9. Avilés-Sacoto, Sonia Valeria & Cook, Wade D. & Güemes-Castorena, David & Zhu, Joe, 2020. "Modelling Efficiency in Regional Innovation Systems: A Two-Stage Data Envelopment Analysis Problem with Shared Outputs within Groups of Decision-Making Units," European Journal of Operational Research, Elsevier, vol. 287(2), pages 572-582.
    10. Josef Jablonský, 2019. "Data Envelopment Analysis Models in Non-Homogeneous Environment," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 67(6), pages 1535-1540.
    11. Rita Shakouri & Maziar Salahi & Sohrab Kordrostami & Jie Wu, 2019. "Flexible measure in the presence of the partial input to output impacts process," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(3), pages 77-98.
    12. Touati-Tliba, Mohamed, 2024. "Comparative performance of Algeria's education districts: The Influence of colonial legacy through cultural capital," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    13. Huang-Ping Yen & Po-Chi Chen & Kung-Cheng Ho, 2021. "Analyzing Destination Accessibility From the Perspective of Efficiency Among Tourism Origin Countries," SAGE Open, , vol. 11(2), pages 21582440211, April.
    14. Avilés-Sacoto, Estefanía Caridad & Avilés-Sacoto, Sonia Valeria & Güemes-Castorena, David & Cook, Wade D., 2021. "Environmental performance evaluation: A state-level DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    15. Mohammad Nemati & Reza Kazemi Matin & Mehdi Toloo, 2020. "A two-stage DEA model with partial impacts between inputs and outputs: application in refinery industries," Annals of Operations Research, Springer, vol. 295(1), pages 285-312, December.
    16. Lívia Torres & Francisco S. Ramos, 2024. "Allocating Benefits Due to Shared Resources Using Shapley Value and Nucleolus in Dynamic Network Data Envelopment Analysis," Mathematics, MDPI, vol. 12(5), pages 1-23, February.
    17. Majid Azadi & Balal Karimi & William Ho & Reza Farzipoor Saen, 2022. "Assessing green performance of power plants by multiple hybrid returns to scale technologies," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1177-1211, December.
    18. Xiong, Xi & Yang, Guo-liang & Guan, Zhong-cheng, 2020. "A parallel DEA-based method for evaluating parallel independent subunits with heterogeneous outputs," Journal of Informetrics, Elsevier, vol. 14(3).
    19. Fukuyama, Hirofumi & Song, Yao-yao & Ren, Xian-tong & Yang, Guo-liang, 2022. "Using a novel DEA-based model to investigate capacity utilization of Chinese firms," Omega, Elsevier, vol. 106(C).
    20. Fukuyama, Hirofumi & Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2021. "Measuring the capacity utilization of the 48 largest iron and steel enterprises in China," European Journal of Operational Research, Elsevier, vol. 288(2), pages 648-665.

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