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Improvement of Technical Efficiency of Firm Groups

Author

Listed:
  • Louisa Andriamasy

    () (CAEPEM, IAE, Université de Perpignan)

  • Walter Briec

    () (CAEPEM, IAE, Université de Perpignan)

  • Stephane Mussard

    () (CHROME, Université de Nîmes; LAMETA, Université de Montpellier; GREDI, Universite de Sherbrooke; LISER, Luxembourg)

Abstract

Cooperation between firms can never improve the technical efficiency of any coalition of firms. This standard result of the productivity measurement literature is based on the directional distance function computed on firm groups. Directional distance functions are usually defined on the standard sum of input/output vectors. In this paper, the aggregation of input/output vectors is generalized thanks to an isomorphism in order to capture three results: the cooperation mproves technical efficiency ; the cooperation reduces technical efficiency ; and finally the cooperation between firms yields no variation of technical efficiency. In this case, the firms merge according to their inputs only because constraints are imposed on outputs, and conversely, they may merge according to the outputs they can produce because some limitations are imposed on the use of inputs.

Suggested Citation

  • Louisa Andriamasy & Walter Briec & Stephane Mussard, 2016. "Improvement of Technical Efficiency of Firm Groups," Cahiers de recherche 16-01, Departement d'Economique de l'École de gestion à l'Université de Sherbrooke.
  • Handle: RePEc:shr:wpaper:16-01
    as

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    File URL: http://gredi.recherche.usherbrooke.ca/wpapers/GREDI-1601.pdf
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    References listed on IDEAS

    as
    1. Charles Blackorby & R. Russell, 1999. "Aggregation of Efficiency Indices," Journal of Productivity Analysis, Springer, vol. 12(1), pages 5-20, August.
    2. Briec, Walter & Mussard, Stéphane, 2014. "Efficient firm groups: Allocative efficiency in cooperative games," European Journal of Operational Research, Elsevier, vol. 239(1), pages 286-296.
    3. Charles Blackorby & David Donaldson & Maria Auersperg, 1981. "A New Procedure for the Measurement of Inequality within and among Population Subgroups," Canadian Journal of Economics, Canadian Economics Association, vol. 14(4), pages 665-685, November.
    4. Lozano, S., 2012. "Information sharing in DEA: A cooperative game theory approach," European Journal of Operational Research, Elsevier, vol. 222(3), pages 558-565.
    5. Briec, Walter & Liang, Qi Bin, 2011. "On some semilattice structures for production technologies," European Journal of Operational Research, Elsevier, vol. 215(3), pages 740-749, December.
    6. Fare, Rolf & Grosskopf, Shawna & Li, Sung-Ko, 1992. " Linear Programming Models for Firm and Industry Performance," Scandinavian Journal of Economics, Wiley Blackwell, vol. 94(4), pages 599-608.
    7. Post, Thierry, 2001. "Transconcave data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 132(2), pages 374-389, July.
    8. Lozano, S., 2013. "DEA production games," European Journal of Operational Research, Elsevier, vol. 231(2), pages 405-413.
    9. Robert G. Chambers, 2002. "Exact nonradial input, output, and productivity measurement," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(4), pages 751-765.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Aggregation; Cooperative games; Distance functions; Productivity; Technical efficiency;

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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