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Nonparametric Production Technologies with Multiple Component Processes

Author

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  • Victor V. Podinovski

    (School of Business and Economics, Loughborough University, Loughborough LE11 3TU, United Kingdom)

  • Ole Bent Olesen

    (Department of Business and Economics, The University of Southern Denmark, DK-5230 Odense M, Denmark)

  • Cláudia S. Sarrico

    (ISEG Lisbon School of Economics and Management, Universidade de Lisboa, 1200-781 Lisboa, Portugal; and CIPES Centre for Research in Higher Education Policies, 4450-137 Matosinhos, Portugal)

Abstract

We develop a nonparametric methodology for assessing the efficiency of decision-making units operating in a production technology with several component processes. The latter is modeled by the new multiple hybrid returns-to-scale (MHRS) technology, formally derived from an explicitly stated set of production axioms. In contrast with the existing models of data envelopment analysis (DEA), the MHRS technology allows the incorporation of component-specific and shared inputs and outputs that represent several proportional (scalable) component production processes as well as nonproportional inputs and outputs. Our approach does not require information about the allocation of shared inputs and outputs to component processes or any assumptions about this allocation. We demonstrate the usefulness of the suggested approach in an application in the context of secondary education and also in a Monte Carlo study based on a simulated data generating process.

Suggested Citation

  • Victor V. Podinovski & Ole Bent Olesen & Cláudia S. Sarrico, 2018. "Nonparametric Production Technologies with Multiple Component Processes," Operations Research, INFORMS, vol. 66(1), pages 282-300, January.
    • Handle: RePEc:inm:oropre:v:66:y:2018:i:1:p:282-300
    DOI: 10.1287/opre.2017.1667
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    2. Barnabé Walheer, 2019. "Disaggregation for efficiency analysis," Journal of Productivity Analysis, Springer, vol. 51(2), pages 137-151, June.
    3. Ren, Xian-tong & Fukuyama, Hirofumi & Yang, Guo-liang, 2022. "Eliminating congestion by increasing inputs in R&D activities of Chinese universities," Omega, Elsevier, vol. 110(C).
    4. Roets, Bart & Verschelde, Marijn & Christiaens, Johan, 2018. "Multi-output efficiency and operational safety: An analysis of railway traffic control centre performance," European Journal of Operational Research, Elsevier, vol. 271(1), pages 224-237.
    5. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    6. Chu, Junfei & Shao, Caifeng & Emrouznejad, Ali & Wu, Jie & Yuan, Zhe, 2021. "Performance evaluation of organizations considering economic incentives for emission reduction: A carbon emission permit trading approach," Energy Economics, Elsevier, vol. 101(C).
    7. Mehdiloo, Mahmood & Podinovski, Victor V., 2021. "Strong, weak and Farrell efficient frontiers of technologies satisfying different production assumptions," European Journal of Operational Research, Elsevier, vol. 294(1), pages 295-311.
    8. Antonio Peyrache & Maria C. A. Silva, 2023. "Efficiency decomposition for multi-level multi-components production technologies," Journal of Productivity Analysis, Springer, vol. 60(3), pages 273-294, December.
    9. Victor V. Podinovski & Tatiana Bouzdine-Chameeva, 2021. "Optimal solutions of multiplier DEA models," Journal of Productivity Analysis, Springer, vol. 56(1), pages 45-68, August.
    10. Wu, F. & Zhou, P. & Zhou, D.Q., 2020. "Modeling carbon emission performance under a new joint production technology with energy input," Energy Economics, Elsevier, vol. 92(C).
    11. Podinovski, Victor V. & Bouzdine-Chameeva, Tatiana, 2019. "Cone extensions of polyhedral production technologies," European Journal of Operational Research, Elsevier, vol. 276(2), pages 736-743.
    12. Antonio Peyrache & Maria C. A. Silva, 2022. "Efficiency and Productivity Analysis from a System Perspective: Historical Overview," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 173-230, Springer.
    13. Majid Azadi & Balal Karimi & William Ho & Reza Farzipoor Saen, 2022. "Assessing green performance of power plants by multiple hybrid returns to scale technologies," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1177-1211, December.
    14. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
    15. Papaioannou, Grammatoula & Podinovski, Victor V., 2023. "Multicomponent production technologies with restricted allocations of shared inputs and outputs," European Journal of Operational Research, Elsevier, vol. 308(1), pages 274-289.
    16. Podinovski, Victor V., 2019. "Direct estimation of marginal characteristics of nonparametric production frontiers in the presence of undesirable outputs," European Journal of Operational Research, Elsevier, vol. 279(1), pages 258-276.

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