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Improvement of technical efficiency of firm groups

Author

Listed:
  • Louisa Andriamasy

    (CAEPEM - Centre d'Analyse de l'Efficience et de la Performance en Economie et Management - UPVD - Université de Perpignan Via Domitia)

  • Walter Briec

    (CAEPEM - Centre d'Analyse de l'Efficience et de la Performance en Economie et Management - UPVD - Université de Perpignan Via Domitia)

  • Stéphane Mussard

    (CHROME - Détection, évaluation, gestion des risques CHROniques et éMErgents (CHROME) - Nîmes Université - UNIMES - Nîmes Université)

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 improves technical efficiency ; the cooperation reduces technical efficiency ; and finally the cooperation between firms yields no variation of technical efficiency, i.e. , the distance function is quasi linear. The improvement of technical efficiency is shown to be compatible with semilattice technologies. 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 & Stéphane Mussard, 2016. "Improvement of technical efficiency of firm groups," Working Papers hal-01784209, HAL.
    • Handle: RePEc:hal:wpaper:hal-01784209
    Note: View the original document on HAL open archive server: https://hal.science/hal-01784209v1
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    Cited by:

    1. Wang, Ding & Guo, Peng & Kilgour, D. Marc & Ponnambalam, Kumaraswamy & Hipel, Keith W., 2022. "The evolution of R&D collaboration in inter-organizational project networks: Effects of reference points for competitive preference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    2. Ding Wang & Peng Guo & Ning Guo, 2024. "The evolution of research and development cooperation in dynamically interorganizational project networks: Effects of reference‐point‐based expectations," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 45(2), pages 590-607, March.
    3. Mussard, Stéphane & Pi Alperin, María Noel, 2021. "Accounting for risk factors on health outcomes: The case of Luxembourg," European Journal of Operational Research, Elsevier, vol. 291(3), pages 1180-1197.
    4. Giannis Karagiannis, 2025. "Aggregation of directional distance functions and industrial efficiency: a note," Journal of Economics, Springer, vol. 144(2), pages 139-143, March.
    5. Walter Briec & Marc Dubois & Stéphane Mussard, 2021. "Technical efficiency in firm games with constant returns to scale and $$\alpha $$ α -returns to scale," Annals of Operations Research, Springer, vol. 304(1), pages 35-62, September.
    6. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2021. "A review of DEA approaches applying a common set of weights: The perspective of centralized management," European Journal of Operational Research, Elsevier, vol. 294(1), pages 3-15.
    7. Walter Briec & Marc Dubois & Stéphane Mussard, 2025. "Atkinson–Shapley rules for TU-games: on the trade-off between efficiency and inequality," Theory and Decision, Springer, vol. 98(4), pages 489-518, June.

    More about this item

    Keywords

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    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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