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On the Role of Weight Restrictions in Data Envelopment Analysis

Author

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  • Francisco Pedraja-Chaparro

    ()

  • Javier Salinas-Jimenez

    ()

  • Peter Smith

    ()

Abstract

This paper examines the role that weight restrictions play in Data Envelopment Analysis (DEA). It is argued that the decision to include a factor (input or output) in a DEA model represents an implicit judgement that the factor has a non-trivial weight. It therefore seems perverse to allow DEA to assign a trivial weight to that factor in assessing the efficiency of a unit. There is therefore a strong case for imposing restrictions on factor weights. However, many existing methods of weight restriction are in practice unwieldy. This paper proposes an alternative approach we term contingent weight restriction which is both practical and intellectually consistent with the DEA philosophy. The paper explores the implications of alternative methods of weight restriction using simulated data from a well known production process. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Francisco Pedraja-Chaparro & Javier Salinas-Jimenez & Peter Smith, 1997. "On the Role of Weight Restrictions in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 8(2), pages 215-230, May.
  • Handle: RePEc:kap:jproda:v:8:y:1997:i:2:p:215-230
    DOI: 10.1023/A:1007715912664
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    References listed on IDEAS

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    2. Schang, Laura & Hynninen, Yrjänä & Morton, Alec & Salo, Ahti, 2016. "Developing robust composite measures of healthcare quality – Ranking intervals and dominance relations for Scottish Health Boards," Social Science & Medicine, Elsevier, vol. 162(C), pages 59-67.
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    4. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
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    7. Sourour Ramzi & Mohamed Ayadi, 2016. "Assessment of Universities Efficiency Using Data Envelopment Analysis: Weights Restrictions and Super-Efficiency Measure," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 5(1), pages 40-58, February.
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    10. Perelman, Sergio & Santín, Daniel, 2009. "How to generate regularly behaved production data? A Monte Carlo experimentation on DEA scale efficiency measurement," European Journal of Operational Research, Elsevier, vol. 199(1), pages 303-310, November.
    11. Sadeghi, Aliasghar & Mohammadzadeh Moghaddam, Abolfazl, 2016. "Uncertainty-based prioritization of road safety projects: An application of data envelopment analysis," Transport Policy, Elsevier, vol. 52(C), pages 28-36.
    12. Francesca Giambona & Erasmo Vassallo, 2013. "Composite Indicator of Financial Development in a Benefit-of-Doubt Approach," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(2), pages 171-202, July.
    13. Lins, Marcos Pereira Estellita & Sollero, Maria Karla Vervloet & Caloba, Guilherme Marques & da Silva, Angela Cristina Moreira, 2007. "Integrating the regulatory and utility firm perspectives, when measuring the efficiency of electricity distribution," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1413-1424, September.
    14. Kuosmanen, Timo & Cherchye, Laurens & Sipilainen, Timo, 2006. "The law of one price in data envelopment analysis: Restricting weight flexibility across firms," European Journal of Operational Research, Elsevier, vol. 170(3), pages 735-757, May.
    15. E. Anthon Eff, 2004. "A Flexible-Weights School Effectiveness Index," Working Papers 200403, Middle Tennessee State University, Department of Economics and Finance.
    16. Lovell, Knox, 2001. "Future Research Opportunities in Efficiency and Productivity Analysis," Efficiency Series Papers 2001/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    17. repec:spr:soinre:v:136:y:2018:i:3:d:10.1007_s11205-016-1426-y is not listed on IDEAS
    18. Alejandro Nin-Pratt & Bingxin Yu, 2010. "Getting implicit shadow prices right for the estimation of the Malmquist index: the case of agricultural total factor productivity in developing countries," Agricultural Economics, International Association of Agricultural Economists, vol. 41(3-4), pages 349-360, May.
    19. Nikolaos Oikonomou & Yannis Tountas & Argiris Mariolis & Kyriakos Souliotis & Kostas Athanasakis & John Kyriopoulos, 2016. "Measuring the efficiency of the Greek rural primary health care using a restricted DEA model; the case of southern and western Greece," Health Care Management Science, Springer, vol. 19(4), pages 313-325, December.
    20. Dimitrov, Stanko & Sutton, Warren, 2010. "Promoting symmetric weight selection in data envelopment analysis: A penalty function approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 281-288, January.
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    23. Estellita Lins, M.P. & Moreira da Silva, A.C. & Lovell, C.A.K., 2007. "Avoiding infeasibility in DEA models with weight restrictions," European Journal of Operational Research, Elsevier, vol. 181(2), pages 956-966, September.

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