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Input price variation across locations and a generalized measure of cost efficiency

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  • Ray, Subhash C.
  • Chen, Lei
  • Mukherjee, Kankana

Abstract

We propose a non-parametric model for global cost minimization as a framework for optimal allocation of a firm's output target across multiple locations, taking account of differences in input prices and technologies across locations. This should be useful for firms planning production sites within a country and for foreign direct investment decisions by multi-national firms. Two illustrative examples are included. The first example considers the production location decision of a manufacturing firm across a number of adjacent states within the US. In the other example, we consider the optimal allocation of US and Canadian automobile manufacturers across the two countries.

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  • Ray, Subhash C. & Chen, Lei & Mukherjee, Kankana, 2008. "Input price variation across locations and a generalized measure of cost efficiency," International Journal of Production Economics, Elsevier, vol. 116(2), pages 208-218, December.
    • Handle: RePEc:eee:proeco:v:116:y:2008:i:2:p:208-218
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    9. Subhash C. Ray & Kankana Mukherjee, 2000. "Decomposition of Cost Competitiveness in U.S. Manufacturing: Some State-by-State Comparisons," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 35(2), pages 133-153, July.
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    Cited by:

    1. Subhash C. Ray, 2014. "Branching Efficiency in Indian Banking: An Analysis of a Demand-Constrained Network," Working papers 2014-34, University of Connecticut, Department of Economics.
    2. Ke Wang & Yujiao Xian & Chia-Yen Lee & Yi-Ming Wei & Zhimin Huang, 2019. "On selecting directions for directional distance functions in a non-parametric framework: a review," Annals of Operations Research, Springer, vol. 278(1), pages 43-76, July.
    3. Camanho, Ana Santos & Silva, Maria Conceicao & Piran, Fabio Sartori & Lacerda, Daniel Pacheco, 2024. "A literature review of economic efficiency assessments using Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 315(1), pages 1-18.
    4. Yingying Shao & Gongbing Bi & Feng Yang & Qiong Xia, 2018. "Resource allocation for branch network system with considering heterogeneity based on DEA method," 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 1005-1025, December.
    5. Hampf, Benjamin, 2018. "Cost and environmental efficiency of U.S. electricity generation: Accounting for heterogeneous inputs and transportation costs," Energy, Elsevier, vol. 163(C), pages 932-941.
    6. Portela, Maria Conceição A. Silva & Thanassoulis, Emmanuel, 2014. "Economic efficiency when prices are not fixed: disentangling quantity and price efficiency," Omega, Elsevier, vol. 47(C), pages 36-44.
    7. Hien Thu Pham & Antonio Peyrache, 2015. "Industry Inefficiency Measures: A Unifying Approximation Proposition," CEPA Working Papers Series WP102015, School of Economics, University of Queensland, Australia.
    8. Silva Portela, Maria Conceição A., 2014. "Value and quantity data in economic and technical efficiency measurement," Economics Letters, Elsevier, vol. 124(1), pages 108-112.
    9. Leleu, Hervé & Briec, Walter, 2009. "A DEA estimation of a lower bound for firms' allocative efficiency without information on price data," International Journal of Production Economics, Elsevier, vol. 121(1), pages 203-211, September.
    10. Ayouba, Kassoum & Boussemart, Jean-Philippe & Lefer, Henri-Bertrand & Leleu, Hervé & Parvulescu, Raluca, 2019. "A measure of price advantage and its decomposition into output- and input-specific effects," European Journal of Operational Research, Elsevier, vol. 276(2), pages 688-698.
    11. Peyrache, Antonio & Zago, Angelo, 2016. "Large courts, small justice!," Omega, Elsevier, vol. 64(C), pages 42-56.
    12. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.
    13. Ray, Subhash, 2016. "Cost efficiency in an Indian bank branch network: A centralized resource allocation model," Omega, Elsevier, vol. 65(C), pages 69-81.
    14. Viera Mendelová, 2021. "Decomposition of cost efficiency with adjustable prices: an application of data envelopment analysis," Operational Research, Springer, vol. 21(4), pages 2739-2770, December.
    15. Peyrache, Antonio, 2015. "Cost constrained industry inefficiency," European Journal of Operational Research, Elsevier, vol. 247(3), pages 996-1002.
    16. Subhash C. Ray & Shilpa Sethia, 2024. "A state-level resource allocation model for emission reduction and efficiency improvement in thermal power plants," Indian Economic Review, Springer, vol. 59(1), pages 205-257, October.
    17. Karagiannis, Giannis, 2023. "Decomposition and aggregation of tone efficiencies," Omega, Elsevier, vol. 119(C).
    18. Hatami-Marbini, Adel & Arabmaldar, Aliasghar, 2021. "Robustness of Farrell cost efficiency measurement under data perturbations: Evidence from a US manufacturing application," European Journal of Operational Research, Elsevier, vol. 295(2), pages 604-620.
    19. Subhash Ray, 2012. "Productivity Change over Time and the Dynamics of Cost Competitiveness: A Nonparametric Analysis of U.S. Manufacturing Data," Working papers 2012-39, University of Connecticut, Department of Economics.
    20. Subhash C. Ray & Shilpa Sethia, 2023. "A State-Level Resource Allocation Model for Emission Reduction and Efficiency Improvement in Thermal Power Plants," Working papers 2023-08, University of Connecticut, Department of Economics.
    21. Rashed Khanjani Shiraz & Adel Hatami-Marbini & Ali Emrouznejad & Hirofumi Fukuyama, 2020. "Chance-constrained cost efficiency in data envelopment analysis model with random inputs and outputs," Operational Research, Springer, vol. 20(3), pages 1863-1898, September.

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