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Choices and Uses of DEA Weights

In: Handbook on Data Envelopment Analysis

Author

Listed:
  • William W. Cooper

    (University of Texas at Austin)

  • José L. Ruiz

    (Universidad Miguel Hernández)

  • Inmaculada Sirvent

    (Universidad Miguel Hernndez)

Abstract

We review the literature of extensions and enhancements of the DEA basic methodology from the perspective of the problems that can be addressed by dealing with the dual multiplier formulation of the DEA models. We describe different approaches that allow incorporating into the analysis price information, reflecting meaningful trade-offs, incorporating value information and managerial goals, making a choice among alternate optima for the weights, avoiding non-zero weights, avoiding large differences in the values of multipliers, improving discrimination and ranking units. We confine attention to the methodological aspects of these approaches and show in many instances how others have used these approaches in applications in practise.

Suggested Citation

  • William W. Cooper & José L. Ruiz & Inmaculada Sirvent, 2011. "Choices and Uses of DEA Weights," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 93-126, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-6151-8_4
    DOI: 10.1007/978-1-4419-6151-8_4
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    Cited by:

    1. Zabala-Iturriagagoitia, Jon Mikel & Aparicio, Juan & Ortiz, Lidia & Carayannis, Elias G. & Grigoroudis, Evangelos, 2021. "The productivity of national innovation systems in Europe: Catching up or falling behind?," Technovation, Elsevier, vol. 102(C).
    2. Samet Güner, 2018. "Incorporating value judgments into port efficiency measurement models: insights from Turkish ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(4), pages 569-586, December.
    3. Ioannis E. Tsolas, 2021. "Efficiency and Determinants of Capital Structure in the Greek Pharmaceutical, Cosmetic and Detergent Industries," JRFM, MDPI, vol. 14(12), pages 1-13, December.
    4. Kohl, Sebastian & Brunner, Jens O., 2020. "Benchmarking the benchmarks – Comparing the accuracy of Data Envelopment Analysis models in constant returns to scale settings," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1042-1057.
    5. Kiyotaka Masuda, 2018. "Energy Efficiency of Intensive Rice Production in Japan: An Application of Data Envelopment Analysis," Sustainability, MDPI, vol. 10(1), pages 1-11, January.
    6. Martin Bod’a & Martin Dlouhý & Emília Zimková, 2018. "Unobservable or omitted production variables in data envelopment analysis through unit-specific production trade-offs," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 813-846, December.
    7. Seyed Amir Nasri & Behdad Ehsani & Seyed Javad Hosseininezhad & Nasser Safaie, 2023. "A sustainable supplier selection method using integrated Fuzzy DEMATEL–ANP–DEA approach (case study: Petroleum Industry)," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 12791-12827, November.
    8. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    9. Panagiotis Ravanos & Giannis Karagiannis, 2021. "Using VEA to assess effectiveness in the development of human capabilities," Economic Change and Restructuring, Springer, vol. 54(1), pages 75-99, February.
    10. Balk, Bert M. & (René) De Koster, M.B.M. & Kaps, Christian & Zofío, José L., 2021. "An evaluation of cross-efficiency methods: With an application to warehouse performance," Applied Mathematics and Computation, Elsevier, vol. 406(C).
    11. Güner, Samet & Antunes, Jorge Junio Moreira & Seçkin Codal, Keziban & Wanke, Peter, 2024. "Network centrality driven airport efficiency: A weight-restricted network DEA," Journal of Air Transport Management, Elsevier, vol. 116(C).
    12. Ioannis E. Tsolas, 2021. "Firm Credit Scoring: A Series Two-Stage DEA Bootstrapped Approach," JRFM, MDPI, vol. 14(5), pages 1-12, May.
    13. Alcaide-López-de-Pablo, David & Dios-Palomares, Rafaela & Prieto, Ángel M., 2014. "A new multicriteria approach for the analysis of efficiency in the Spanish olive oil sector by modelling decision maker preferences," European Journal of Operational Research, Elsevier, vol. 234(1), pages 241-252.
    14. Ruiz, José L. & Segura, José V. & Sirvent, Inmaculada, 2015. "Benchmarking and target setting with expert preferences: An application to the evaluation of educational performance of Spanish universities," European Journal of Operational Research, Elsevier, vol. 242(2), pages 594-605.
    15. Somayeh Razipour-GhalehJough & Farhad Hosseinzadeh Lotfi & Gholamreza Jahanshahloo & Mohsen Rostamy-malkhalifeh & Hamid Sharafi, 2020. "Finding closest target for bank branches in the presence of weight restrictions using data envelopment analysis," Annals of Operations Research, Springer, vol. 288(2), pages 755-787, May.
    16. Barbero, Javier & Zabala-Iturriagagoitia, Jon Mikel & Zofío, José L., 2021. "Is more always better? On the relevance of decreasing returns to scale on innovation," Technovation, Elsevier, vol. 107(C).

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    Keywords

    Data envelopment analysis; Weights;

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