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Multi-Level Parallel Production Networks

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Abstract

Network Data Envelopment Analysis (DEA) has become a largely researched topic in the DEA literature. In this paper we consider one of the simplest network models: Parallel Network DEA models. We briefly review a large body of literature that relates to these network models. Then we proceed to discuss existing models and point out some of their pitfalls. Finally, we propose an approach that attempts to solve these pitfalls, recognising that when one computes a decision making unit (DMU) efficiency score and want to decompose it into the divisional/process efficiencies there is a component of allocative inefficiency. We develop our models at three levels of aggregation: the sub-unit (production division/process), the DMU (firm) and the industry. For each level we measure the inefficiency using the directional distance function and we relate the different levels to each other by proposing a decomposition into exhaustive and mutually exclusive components. We illustrate the application of our models to the case of Portuguese hospitals and we also propose avenues for future research, since most of the topics addressed in this paper are not only related to Parallel network models but to general network structures.

Suggested Citation

  • Antonio Peyrache & Maria C. A. Silva, 2021. "Multi-Level Parallel Production Networks," CEPA Working Papers Series WP052021, School of Economics, University of Queensland, Australia.
    • Handle: RePEc:qld:uqcepa:159
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    File URL: https://economics.uq.edu.au/files/28080/WP052021.pdf
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    6. Eric Njuki & Boris E Bravo-Ureta & Christopher J O’Donnell, 2018. "A new look at the decomposition of agricultural productivity growth incorporating weather effects," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-21, February.
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    Cited by:

    1. Antonio Peyrache & Maria C. A. Silva, 2022. "A Comment on Decomposition of Efficiency in Network Production Models," CEPA Working Papers Series WP072022, School of Economics, University of Queensland, Australia.

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    Keywords

    Data Envelopment Analysis; Multi-Level Networks; Parallel Networks; Directional Distance Function; Efficiency.;
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