IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v322y2023i2d10.1007_s10479-022-04937-4.html
   My bibliography  Save this article

A novel median-based optimization model for eco-efficiency assessment in data envelopment analysis

Author

Listed:
  • Andreas Dellnitz

    (Leibniz-Fachhochschule School of Busines)

  • Madjid Tavana

    (La Salle University
    University of Paderborn)

  • Rajiv Banker

    (Temple University)

Abstract

Economic-environmental performance or eco-efficiency is a topic of great interest due to the “green movement.” Data Envelopment Analysis (DEA) is a non-parametric method for measuring the eco-efficiencies in comparable Decision-Making Units (DMUs) under various technology assumptions, e.g., constant or variable returns to scale. In the case of variable returns to scale, the returns to scale (RTS) values show whether the DMUs under consideration have the correct scale size or can be improved by upsizing or downsizing. However, sometimes the RTS values for some DMUs are unusually high or low and hence useless in practice. The RTS-mavericks test is devised to propose RTS bounds to fix this flaw. However, these bounds can be ineffective in practice. Even if this flaw is rectified, it needs to be clarified how the concept of RTS-mavericks influences eco-efficiency analysis. For the case of a single technology and a combination of two technologies (a so-called pollution-generating technology), we derive RTS equations and develop new median-based optimization problems to correct this flaw and show that the new concept can lead to non-convex technologies. We also demonstrate the applicability and exhibit the efficacy of the proposed model in the context of eco-efficiency analysis in the European Union.

Suggested Citation

  • Andreas Dellnitz & Madjid Tavana & Rajiv Banker, 2023. "A novel median-based optimization model for eco-efficiency assessment in data envelopment analysis," Annals of Operations Research, Springer, vol. 322(2), pages 661-690, March.
    • Handle: RePEc:spr:annopr:v:322:y:2023:i:2:d:10.1007_s10479-022-04937-4
    DOI: 10.1007/s10479-022-04937-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-04937-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-022-04937-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    2. Kuosmanen, Timo & Kortelainen, Mika, 2007. "Valuing environmental factors in cost-benefit analysis using data envelopment analysis," Ecological Economics, Elsevier, vol. 62(1), pages 56-65, April.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Podinovski, Victor V. & Bouzdine-Chameeva, Tatiana, 2015. "Consistent weight restrictions in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 244(1), pages 201-209.
    5. Hsihui Chang & Hiu Choy & Iny Hwang, 2015. "An empirical study of returns to scale of CPA firms in the post SOX era," Annals of Operations Research, Springer, vol. 229(1), pages 253-264, June.
    6. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    7. Dakpo, K Hervé & Lansink, Alfons Oude, 2019. "Dynamic pollution-adjusted inefficiency under the by-production of bad outputs," European Journal of Operational Research, Elsevier, vol. 276(1), pages 202-211.
    8. Kloss, Mathias, 2017. "Factor productivity in EU agriculture: A microeconometric perspective," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 89, number 89, September.
    9. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
    10. Marcel Clermont & Julia Schaefer, 2019. "Identification of Outliers in Data Envelopment Analysis," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 475-496, October.
    11. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    12. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    13. Khezrimotlagh, Dariush & Cook, Wade D. & Zhu, Joe, 2020. "A nonparametric framework to detect outliers in estimating production frontiers," European Journal of Operational Research, Elsevier, vol. 286(1), pages 375-388.
    14. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    15. B Zhang & J Wang & L Meng & C Zhu & R Nie, 2014. "Estimating returns to scale of Chinese airport airside activities using the CCR-0-objective RTS method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(5), pages 755-762, May.
    16. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    17. Russell G. Thompson & F. D. Singleton & Robert M. Thrall & Barton A. Smith, 1986. "Comparative Site Evaluations for Locating a High-Energy Physics Lab in Texas," Interfaces, INFORMS, vol. 16(6), pages 35-49, December.
    18. Podinovski, Victor V. & Førsund, Finn R. & Krivonozhko, Vladimir E., 2009. "A simple derivation of scale elasticity in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 197(1), pages 149-153, August.
    19. Banker, Rajiv D. & Chang, Hsihui, 2006. "The super-efficiency procedure for outlier identification, not for ranking efficient units," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1311-1320, December.
    20. Golany, Boaz & Yu, Gang, 1997. "Estimating returns to scale in DEA," European Journal of Operational Research, Elsevier, vol. 103(1), pages 28-37, November.
    21. A. Davoodi & M. Zarepisheh & H. Rezai, 2015. "The nearest MPSS pattern in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 163-176, March.
    22. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    23. Ali Bahari & Ali Emrouznejad, 2014. "Influential DMUs and outlier detection in data envelopment analysis with an application to health care," Annals of Operations Research, Springer, vol. 223(1), pages 95-108, December.
    24. Zhang, Bing & Bi, Jun & Fan, Ziying & Yuan, Zengwei & Ge, Junjie, 2008. "Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach," Ecological Economics, Elsevier, vol. 68(1-2), pages 306-316, December.
    25. Alirezaee, Mohammadreza & Hajinezhad, Ensie & Paradi, Joseph C., 2018. "Objective identification of technological returns to scale for data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 266(2), pages 678-688.
    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. Andreas Dellnitz & Andreas Kleine & Madjid Tavana, 2024. "An integrated data envelopment analysis and regression tree method for new product price estimation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(4), pages 1189-1211, December.
    2. Omid Valizadeh & Mojtaba Ghiyasi, 2023. "Assessing telecommunication contractor firms using a hybrid DEA-BWM method," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(4), pages 189-200.

    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. Trinks, Arjan & Mulder, Machiel & Scholtens, Bert, 2020. "An Efficiency Perspective on Carbon Emissions and Financial Performance," Ecological Economics, Elsevier, vol. 175(C).
    2. Andreas Dellnitz & Elmar Reucher & Andreas Kleine, 2021. "Efficiency evaluation in data envelopment analysis using strong defining hyperplanes," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(2), pages 441-465, June.
    3. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    4. Pham, Manh D. & Zelenyuk, Valentin, 2019. "Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets," European Journal of Operational Research, Elsevier, vol. 274(1), pages 186-198.
    5. Corrado Lo Storto, 2016. "Ecological Efficiency Based Ranking of Cities: A Combined DEA Cross-Efficiency and Shannon’s Entropy Method," Sustainability, MDPI, vol. 8(2), pages 1-29, January.
    6. Andreas Dellnitz & Andreas Kleine & Wilhelm Rödder, 2018. "CCR or BCC: what if we are in the wrong model?," Journal of Business Economics, Springer, vol. 88(7), pages 831-850, September.
    7. Walheer, Barnabé, 2018. "Scale efficiency for multi-output cost minimizing producers: The case of the US electricity plants," Energy Economics, Elsevier, vol. 70(C), pages 26-36.
    8. Andreas Dellnitz & Andreas Kleine & Madjid Tavana, 2024. "An integrated data envelopment analysis and regression tree method for new product price estimation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(4), pages 1189-1211, December.
    9. Feng Li & Qingyuan Zhu & Jun Zhuang, 2018. "Analysis of fire protection efficiency in the United States: a two-stage DEA-based approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 23-68, January.
    10. Zelenyuk, Valentin, 2015. "Aggregation of scale efficiency," European Journal of Operational Research, Elsevier, vol. 240(1), pages 269-277.
    11. Podinovski, Victor V., 2017. "Returns to scale in convex production technologies," European Journal of Operational Research, Elsevier, vol. 258(3), pages 970-982.
    12. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    13. Petros Hadjicostas & Andreas Soteriou, 2010. "Different orders of one-sided scale elasticities in multi-output production," Journal of Productivity Analysis, Springer, vol. 33(2), pages 147-167, April.
    14. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    15. Dellnitz, Andreas & Tavana, Madjid, 2024. "Data envelopment analysis: From non-monotonic to monotonic scale elasticities," European Journal of Operational Research, Elsevier, vol. 318(2), pages 549-559.
    16. Margaréta Halická & Mária Trnovská, 2018. "Negative features of hyperbolic and directional distance models for technologies with undesirable outputs," 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 887-907, December.
    17. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    18. Zarepisheh, M. & Soleimani-damaneh, M., 2009. "A dual simplex-based method for determination of the right and left returns to scale in DEA," European Journal of Operational Research, Elsevier, vol. 194(2), pages 585-591, April.
    19. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    20. Filip Fidanoski & Kiril Simeonovski & Violeta Cvetkoska, 2021. "Energy Efficiency in OECD Countries: A DEA Approach," Energies, MDPI, vol. 14(4), pages 1-21, February.

    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:spr:annopr:v:322:y:2023:i:2:d:10.1007_s10479-022-04937-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.