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Model and measure the relative efficiency of a four-stage production process. An NDEA multiplier relational model under different systems of resource distribution preferences between sub-processes

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  • Pinto, Claudio

Abstract

Measuring the relative efficiency of a production process with the DEA considers the production process as a “black box” that uses inputs to transform them into outputs. In reality, many production processes are carried out by carrying out several interconnected activities that are usually grouped into phases that are in turn interconnected. For this reason, measuring the relative efficiency of a production process within the DEA technique requires shaping it as a network system (in others words to consider the production process as interconnected sub-process). In the case of network systems, the NDEA approach has developed many models to measure their relative efficiency: independent models, connected models and relational models. In particular, the relational model allows to measure at the same time both the efficiency of the system and the efficiency of the sub-process once the operations between the latter have been considered. In our opinion, many real production processes can be modelled as a network of four sub-processes that are differently interconnected with each other. In this paper we will model a production process as a network of four sub-processes with shared variables and fixed preferences about the allocation of system resources between them. To measure the relative efficiency of the process and its parts we will develop an input-oriented NDEA model in the multiplier version. To solve the model we will use virtual data under several resources allocation preference’s structure. Then we will conclude that 1) a production process with four interconnected sub-processes can represent a large number of real production processes, so the NDEA model developed here can potentially be used for many applications, 2) the resource allocation preference system inter-sub-process influences the measurement of relative efficiency.

Suggested Citation

  • Pinto, Claudio, 2019. "Model and measure the relative efficiency of a four-stage production process. An NDEA multiplier relational model under different systems of resource distribution preferences between sub-processes," MPRA Paper 92617, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:92617
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    References listed on IDEAS

    as
    1. Kao, Chiang, 2009. "Efficiency decomposition in network data envelopment analysis: A relational model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 949-962, February.
    2. Thomas Sexton & Herbert Lewis, 2003. "Two-Stage DEA: An Application to Major League Baseball," Journal of Productivity Analysis, Springer, vol. 19(2), pages 227-249, April.
    3. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    4. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    5. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    6. Chien Wang & Ram Gopal & Stanley Zionts, 1997. "Use of Data Envelopment Analysis in assessing Information Technology impact on firm performance," Annals of Operations Research, Springer, vol. 73(0), pages 191-213, October.
    7. Wanke, Peter & Maredza, Andrew & Gupta, Rangan, 2017. "Merger and acquisitions in South African banking: A network DEA model," Research in International Business and Finance, Elsevier, vol. 41(C), pages 362-376.
    8. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    9. Hiroyuki Kawaguchi & Kaoru Tone & Miki Tsutsui, 2014. "Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model," Health Care Management Science, Springer, vol. 17(2), pages 101-112, June.
    10. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    11. Kao, Chiang, 2009. "Efficiency measurement for parallel production systems," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1107-1112, August.
    12. Cook, Wade D. & Liang, Liang & Zhu, Joe, 2010. "Measuring performance of two-stage network structures by DEA: A review and future perspective," Omega, Elsevier, vol. 38(6), pages 423-430, December.
    13. Bruce Hollingsworth, 2008. "The measurement of efficiency and productivity of health care delivery," Health Economics, John Wiley & Sons, Ltd., vol. 17(10), pages 1107-1128, October.
    14. Chen, Yao & Du, Juan & David Sherman, H. & Zhu, Joe, 2010. "DEA model with shared resources and efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(1), pages 339-349, November.
    15. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2001. "DEA-like models for efficiency evaluations of specialized and interdependent units," European Journal of Operational Research, Elsevier, vol. 132(2), pages 274-286, July.
    16. Rolf Färe & Gerald Whittaker, 1995. "An Intermediate Input Model Of Dairy Production Using Complex Survey Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(2), pages 201-213, May.
    17. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    18. Prieto, Angel M. & Zofio, Jose L., 2007. "Network DEA efficiency in input-output models: With an application to OECD countries," European Journal of Operational Research, Elsevier, vol. 178(1), pages 292-304, April.
    19. Fare, Rolf & Grosskopf, Shawna, 2000. "Network DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 35-49, March.
    20. Kao, Chiang, 2014. "Efficiency decomposition for general multi-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 232(1), pages 117-124.
    21. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, October.
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    1. Claudio Pinto, 2021. "Measure the Relative Efficiency of a Four-Stage Production Process with NDEA," International Journal of Business and Management, Canadian Center of Science and Education, vol. 15(10), pages 1-35, July.

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    More about this item

    Keywords

    network DEA; performances management; internal structure; inputs-outputs system.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General

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