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Primal and dual multi-output flexibility measures

Author

Listed:
  • Swetlana Renner

    ()

  • Thomas Glauben

    ()

  • Heinrich Hockmann

    ()

  • Pierre Ouellette

    ()

Abstract

Flexibility is a crucial component of competitive advantage, especially under conditions of dynamically changing environments. In this theoretical paper, we present alternative flexibility measures that can be used to calculate the ability of the production technology to accommodate output variations at lower costs. We refine the existing short-run multi-output flexibility measure to the long-run using three alternative total cost functions in order to capture the impact of fixed costs on adjustment ability. The proposed new long-run flexibility measures are based on alternative definitions of the long-run total cost function considering various assumptions about the decision-making process. We derive primal flexibility measures by using the dual relationships between these cost functions and the corresponding input distance functions. The proposed measures allow us to investigate both short-run and long-run flexibility using different representations of the production technology, and thus to examine various aspects of the firm’s ability to adjust. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Swetlana Renner & Thomas Glauben & Heinrich Hockmann & Pierre Ouellette, 2015. "Primal and dual multi-output flexibility measures," Journal of Productivity Analysis, Springer, vol. 44(2), pages 127-136, October.
  • Handle: RePEc:kap:jproda:v:44:y:2015:i:2:p:127-136
    DOI: 10.1007/s11123-015-0449-8
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    References listed on IDEAS

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    1. Rungsuriyawiboon, Supawat & Stefanou, Spiro E., 2007. "Dynamic Efficiency Estimation: An Application to U.S. Electric Utilities," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 226-238, April.
    2. Hajargasht, Gholamreza & Coelli, Tim & Rao, D.S. Prasada, 2008. "A dual measure of economies of scope," Economics Letters, Elsevier, vol. 100(2), pages 185-188, August.
    3. Pierre Lasserre & Pierre Ouellette, 1999. "Dynamic Factor Demands and Technology Measurement under Arbitrary Expectations," Journal of Productivity Analysis, Springer, vol. 11(3), pages 219-241, June.
    4. Swetlana Renner & Thomas Glauben & Heinrich Hockmann, 2014. "Measurement and decomposition of flexibility of multi-output firms," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 41(5), pages 745-773.
    5. Mills, David E & Schumann, Laurence, 1985. "Industry Structure with Fluctuating Demand," American Economic Review, American Economic Association, vol. 75(4), pages 758-767, September.
    6. Renner, Swetlana & Glauben, Thomas & Hockmann, Heinrich, 2012. "Measurement And Decomposition Of Flexibility Of Multi-Output Firms," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 124865, International Association of Agricultural Economists.
    7. George Stigler, 1939. "Production and Distribution in the Short Run," Journal of Political Economy, University of Chicago Press, vol. 47, pages 305-305.
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    9. Mills, David E, 1984. "Demand Fluctuations and Endogenous Firm Flexibility," Journal of Industrial Economics, Wiley Blackwell, vol. 33(1), pages 55-71, September.
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    11. Larry G. Epstein, 1981. "Duality Theory and Functional Forms for Dynamic Factor Demands," Review of Economic Studies, Oxford University Press, vol. 48(1), pages 81-95.
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    More about this item

    Keywords

    Flexibility measure; Duality; Distance function; Cost function; D24;

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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