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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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    12. 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.
    13. 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.
    14. 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.
    15. 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).
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    18. 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).
    19. 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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