IDEAS home Printed from https://ideas.repec.org/a/bpj/jossai/v9y2021i4p378-398n6.html
   My bibliography  Save this article

A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

Author

Listed:
  • Chen Chunhua
  • Liu Haohua

    (School of Business Administration, Jiangxi University of Finance and Economics, Nanchang330013, China)

  • Tang Lijun

    (Plymouth Business School, University of Plymouth, PlymouthPL48AA, United Kingdom)

  • Ren Jianwei

    (Transportation Institute, Inner Mongolia University, Hohhot010070, China)

Abstract

DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.

Suggested Citation

  • Chen Chunhua & Liu Haohua & Tang Lijun & Ren Jianwei, 2021. "A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 378-398, August.
    • Handle: RePEc:bpj:jossai:v:9:y:2021:i:4:p:378-398:n:6
    DOI: 10.21078/JSSI-2021-378-21
    as

    Download full text from publisher

    File URL: https://doi.org/10.21078/JSSI-2021-378-21
    Download Restriction: no
    File URL: https://libkey.io/10.21078/JSSI-2021-378-21?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
    ---><---

    References listed on IDEAS

    as
    1. Pal, Debdatta & Mitra, Subrata K., 2016. "An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 1-12.
    2. Wanke, Peter & Barros, C.P., 2016. "Efficiency in Latin American airlines: A two-stage approach combining Virtual Frontier Dynamic DEA and Simplex Regression," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 93-103.
    3. Samet Güner & Erman Coşkun, 2019. "Estimating the operational and service efficiency of bus transit routes using a non-radial DEA approach," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 249-268, September.
    4. Yuan, Qianqian & Fang Chin Cheng, Charles & Wang, Jiayu & Zhu, Tian-Tian & Wang, Ke, 2020. "Inclusive and sustainable industrial development in China: An efficiency-based analysis for current status and improving potentials," Applied Energy, Elsevier, vol. 268(C).
    5. Li, Ye & Cui, Qiang, 2018. "Airline efficiency with optimal employee allocation: An Input-shared Network Range Adjusted Measure," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 150-162.
    6. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2007. "Measurement of returns to scale using a non-radial DEA model: A range-adjusted measure approach," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1918-1946, February.
    7. Tavassoli, Mohammad & Badizadeh, Taliva & Farzipoor Saen, Reza, 2016. "Performance assessment of airlines using range-adjusted measure, strong complementary slackness condition, and discriminant analysis," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 42-46.
    8. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    9. Ke Wang & Xueying Yu, 2017. "Industrial Energy and Environment Efficiency of Chinese Cities: An Analysis Based on Range-Adjusted Measure," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1023-1042, July.
    10. Ramli, Noor Asiah & Munisamy, Susila, 2015. "Eco-efficiency in greenhouse emissions among manufacturing industries: A range adjusted measure," Economic Modelling, Elsevier, vol. 47(C), pages 219-227.
    11. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    12. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis," Energy Policy, Elsevier, vol. 38(10), pages 5902-5911, October.
    13. Chen, Po-Chi & Yu, Ming-Miin & Shih, Jou-Chen & Chang, Ching-Cheng & Hsu, Shih-Hsun, 2019. "A reassessment of the Global Food Security Index by using a hierarchical data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 272(2), pages 687-698.
    14. Lukas Steinmann & Peter Zweifel, 2001. "The Range Adjusted Measure (RAM) in DEA: Comment," Journal of Productivity Analysis, Springer, vol. 15(2), pages 139-144, March.
    15. Qiang Cui & Ye Li, 2018. "Airline environmental efficiency measures considering materials balance principles: an application of a network range-adjusted measure with weak-G disposability," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 61(13), pages 2298-2318, November.
    16. Kuosmanen, Timo & Matin, Reza Kazemi, 2009. "Theory of integer-valued data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 192(2), pages 658-667, January.
    17. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    18. Miao, Zhuang & Chen, Xiaodong & Baležentis, Tomas & Sun, Chuanwang, 2019. "Atmospheric environmental productivity across the provinces of China: Joint decomposition of range adjusted measure and Luenberger productivity indicator," Energy Policy, Elsevier, vol. 132(C), pages 665-677.
    19. Shih-Heng Yu, 2019. "Benchmarking and Performance Evaluation Towards the Sustainable Development of Regions in Taiwan: A Minimum Distance-Based Measure with Undesirable Outputs in Additive DEA," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(3), pages 1323-1348, August.
    20. Aida, Kazuo & Cooper, William W. & Pastor, Jésus T. & Sueyoshi, Toshiyuki, 1998. "Evaluating Water Supply Services in Japan with RAM: a Range-adjusted Measure of Inefficiency," Omega, Elsevier, vol. 26(2), pages 207-232, April.
    21. Halkos, George & Petrou, Kleoniki Natalia, 2019. "Treating undesirable outputs in DEA: A critical review," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 97-104.
    22. Wang, H. & Pan, Chen & Wang, Qunwei & Zhou, P., 2020. "Assessing sustainability performance of global supply chains: An input-output modeling approach," European Journal of Operational Research, Elsevier, vol. 285(1), pages 393-404.
    23. Zelenyuk, Valentin, 2020. "Aggregation of inputs and outputs prior to Data Envelopment Analysis under big data," European Journal of Operational Research, Elsevier, vol. 282(1), pages 172-187.
    24. William Cooper & Kyung Park & Jesus Pastor, 2001. "The Range Adjusted Measure (RAM) in DEA: A Response to the Comment by Steinmann and Zweifel," Journal of Productivity Analysis, Springer, vol. 15(2), pages 145-152, March.
    25. Chen, Xiaodong & Wu, Ge & Li, Ding, 2019. "Efficiency measure on the truck restriction policy in China: A non-radial data envelopment model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 140-154.
    26. Shih-Heng Yu & Chia-Wei Hsu, 2020. "A unified extension of super-efficiency in additive data envelopment analysis with integer-valued inputs and outputs: an application to a municipal bus system," Annals of Operations Research, Springer, vol. 287(1), pages 515-535, April.
    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. Radojko LUKIC, 2022. "Measurement and Analysis of the Dynamics of Financial Performance and Efficiency of Trade in Serbia Based on the DEA Super-Radial Model," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 23(5), pages 630-645, December.

    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. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2009. "An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties," European Journal of Operational Research, Elsevier, vol. 196(2), pages 764-794, July.
    2. Chunhua Chen & Jianwei Ren & Lijun Tang & Haohua Liu, 2020. "Additive integer-valued data envelopment analysis with missing data: A multi-criteria evaluation approach," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-20, June.
    3. Barros, C.P. & Wanke, Peter & Dumbo, Silvestre & Manso, Jose Pires, 2017. "Efficiency in angolan hydro-electric power station: A two-stage virtual frontier dynamic DEA and simplex regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 588-596.
    4. Ramón Sala-Garrido & Manuel Mocholí-Arce & María Molinos-Senante & Alexandros Maziotis, 2021. "Comparing Operational, Environmental and Eco-Efficiency of Water Companies in England and Wales," Energies, MDPI, vol. 14(12), pages 1-14, June.
    5. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    6. Maria Silva Portela & Pedro Borges & Emmanuel Thanassoulis, 2003. "Finding Closest Targets in Non-Oriented DEA Models: The Case of Convex and Non-Convex Technologies," Journal of Productivity Analysis, Springer, vol. 19(2), pages 251-269, April.
    7. 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).
    8. Sala-Garrido, Ramon & Mocholi-Arce, Manuel & Maziotis, Alexandros & Molinos-Senante, María, 2023. "The carbon and production performance of water utilities: Evidence from the English and Welsh water industry," Structural Change and Economic Dynamics, Elsevier, vol. 64(C), pages 292-300.
    9. Lin, Shuguang & Shi, Hai-Liu & Wang, Ying-Ming, 2022. "An integrated slacks-based super-efficiency measure in the presence of nonpositive data," Omega, Elsevier, vol. 111(C).
    10. Halická, Margaréta & Trnovská, Mária, 2021. "A unified approach to non-radial graph models in data envelopment analysis: common features, geometry, and duality," European Journal of Operational Research, Elsevier, vol. 289(2), pages 611-627.
    11. Mehdiloozad, Mahmood & Mirdehghan, S. Morteza & Sahoo, Biresh K. & Roshdi, Israfil, 2015. "On the identification of the global reference set in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(3), pages 779-788.
    12. Wanke, Peter & Barros, C.P., 2016. "Efficiency in Latin American airlines: A two-stage approach combining Virtual Frontier Dynamic DEA and Simplex Regression," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 93-103.
    13. Cui, Qiang & Jin, Zi-yin, 2020. "Airline environmental efficiency measures considering negative data: An application of a modified network Modified Slacks-based measure model," Energy, Elsevier, vol. 207(C).
    14. Ramli, Noor Asiah & Munisamy, Susila, 2015. "Eco-efficiency in greenhouse emissions among manufacturing industries: A range adjusted measure," Economic Modelling, Elsevier, vol. 47(C), pages 219-227.
    15. Kristof Witte & Rui Marques, 2010. "Influential observations in frontier models, a robust non-oriented approach to the water sector," Annals of Operations Research, Springer, vol. 181(1), pages 377-392, December.
    16. Chien-Ming Chen, 2014. "Evaluating eco-efficiency with data envelopment analysis: an analytical reexamination," Annals of Operations Research, Springer, vol. 214(1), pages 49-71, March.
    17. Cui, Qiang & Arjomandi, Amir, 2021. "Airline energy efficiency measures based on an epsilon-based Range-Adjusted Measure model," Energy, Elsevier, vol. 217(C).
    18. W. Cooper & L. Seiford & K. Tone & J. Zhu, 2007. "Some models and measures for evaluating performances with DEA: past accomplishments and future prospects," Journal of Productivity Analysis, Springer, vol. 28(3), pages 151-163, December.
    19. Premachandra, I.M. & Bhabra, Gurmeet Singh & Sueyoshi, Toshiyuki, 2009. "DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique," European Journal of Operational Research, Elsevier, vol. 193(2), pages 412-424, March.
    20. Jeong-Dong Lee & Seogwon Hwang & Tai-Yoo Kim, 2005. "The Measurement of Consumption Efficiency Considering the Discrete Choice of Consumers," Journal of Productivity Analysis, Springer, vol. 23(1), pages 65-83, January.

    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:bpj:jossai:v:9:y:2021:i:4:p:378-398:n:6. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.