IDEAS home Printed from https://ideas.repec.org/p/qld/uqcepa/159.html
   My bibliography  Save this paper

Multi-Level Parallel Production Networks

Author

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
    as

    Download full text from publisher

    File URL: https://economics.uq.edu.au/files/28080/WP052021.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hughes, Neal & Lawson, Kenton & Davidson, Alistair & Jackson, Tom & Sheng, Yu, 2011. "Productivity pathways: climate-adjusted production frontiers for the Australian broadacre cropping industry," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100563, Australian Agricultural and Resource Economics Society.
    2. Paul Schreyer, 2001. "The OECD Productivity Manual: A Guide to the Measurement of Industry-Level and Aggregate Productivity," International Productivity Monitor, Centre for the Study of Living Standards, vol. 2, pages 37-51, Spring.
    3. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, January.
    4. Ruhul A. Salim & Nazrul Islam, 2010. "Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 561-582, October.
    5. Eric Njuki & Boris E Bravo-Ureta & Víctor E Cabrera, 2020. "Climatic effects and total factor productivity: econometric evidence for Wisconsin dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 1276-1301.
    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.
    7. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    8. V. Eldon Ball & Jean-Christophe Bureau & Richard Nehring & Agapi Somwaru, 1997. "Agricultural Productivity Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1045-1063.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. C. J. O’Donnell, 2021. "Estimating the Effects of Weather and Climate Change on Agricultural Productivity," CEPA Working Papers Series WP032021, School of Economics, University of Queensland, Australia.
    2. Salem Gheit, 2022. "A Stochastic Frontier Analysis of the Human Capital Effects on the Manufacturing Industries’ Technical Efficiency in the United States," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 8(3), pages 215-238, July.
    3. Chancellor, Will & Hughes, Neal & Zhao, Shiji & Soh, Wei Ying & Valle, Haydn & Boult, Christopher, 2021. "Controlling for the effects of climate on total factor productivity: A case study of Australian farms," Food Policy, Elsevier, vol. 102(C).
    4. Eric Njuki & Boris E Bravo-Ureta & Víctor E Cabrera, 2020. "Climatic effects and total factor productivity: econometric evidence for Wisconsin dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 1276-1301.
    5. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    6. Kox, Henk L.M. & Leeuwen, George van & Wiel, Henry van der, 2010. "Competitive, but too small - productivity and entry-exit determinants in European business services," MPRA Paper 24389, University Library of Munich, Germany.
    7. Kangile, Rajabu Joseph, 2015. "Efficiency In Production By Smallholder Rice Farmers Under Cooperative Irrigation Schemes In Pwani And Morogoro Regions, Tanzania," Research Theses 265681, Collaborative Masters Program in Agricultural and Applied Economics.
    8. Veronika Fenyves & Tibor Tarnóczi & Zoltán Bács & Dóra Kerezsi & Péter Bajnai & Mihály Szoboszlai, 2022. "Financial efficiency analysis of Hungarian agriculture, fisheries and forestry sector," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(11), pages 413-426.
    9. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.
    10. Ajayi, V. & Pollitt, M., 2022. "Changing times: Incentive regulation, corporate reorganisations, and productivity in the Great Britain’s gas networks," Cambridge Working Papers in Economics 2254, Faculty of Economics, University of Cambridge.
    11. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2021. "How does public spending affect technical efficiency? Some evidence from 15 European countries," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 108-130, January.
    12. Helvoigt, Ted L. & Adams, Darius M., 2009. "A stochastic frontier analysis of technical progress, efficiency change and productivity growth in the Pacific Northwest sawmill industry," Forest Policy and Economics, Elsevier, vol. 11(4), pages 280-287, July.
    13. Bopp, Carlos & Jara-Rojas, Roberto & Bravo-Ureta, Boris & Engler, Alejandra, 2022. "Irrigation water use, shadow values and productivity: Evidence from stochastic production frontiers in vineyards," Agricultural Water Management, Elsevier, vol. 271(C).
    14. Castiglione, Concetta & Infante, Davide & Zieba, Marta, 2023. "Public support for performing arts. Efficiency and productivity gains in eleven European countries," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    15. 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.
    16. Hanousek, Jan & Kočenda, Evžen & Mašika, Michal, 2012. "Firm efficiency: Domestic owners, coalitions, and FDI," Economic Systems, Elsevier, vol. 36(4), pages 471-486.
    17. Karim L. Anaya & Michael G. Pollitt, 2014. "Does Weather Have an Impact on Electricity Distribution Efficiency? Evidence from South America," Working Papers EPRG 1404, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    18. Vittadini, Giorgio & Sturaro, Caterina & Folloni, Giuseppe, 2022. "Non-Cognitive Skills and Cognitive Skills to measure school efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    19. Nazrul Islam & Vilaphonh Xayavong & Ross Kingwell, 2014. "Broadacre farm productivity and profitability in south-western Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), pages 147-170, April.
    20. Nehring, Richard F. & Christensen, Lee A. & O'Donoghue, Erik J. & Sandretto, Carmen L., 2003. "Manure and Commercial Fertilizer Nutrients Relative to Cropland and Pasture Requirements: Is the Pollution Risk Growing on Corn/Livestock Farms?," 2003 Annual meeting, July 27-30, Montreal, Canada 21980, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    More about this item

    Keywords

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:qld:uqcepa:159. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SOE IT (email available below). General contact details of provider: https://edirc.repec.org/data/decuqau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.