IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v278y2019i1d10.1007_s10479-017-2399-1.html
   My bibliography  Save this article

Efficiency evaluation in the presence of undesirable outputs: the most favorable shadow price approach

Author

Listed:
  • Chiang Kao

    (National Cheng Kung University)

  • Shiuh-Nan Hwang

    (Ming Chuan University)

Abstract

Undesirable outputs are generally by-products of producing desirable ones, and they can thus be reduced only with an accompanying reduction in the latter. To capture this notion, the shadow price of the undesirable output must be negative, as opposed to positive for the desirable output. Based on this condition, this paper proposes a data envelopment analysis model that allows the production units being evaluated to determine the shadow prices for both the desirable and undesirable outputs by themselves so that the measured efficiency score will achieve the highest possible level. The proposed model satisfies the assumption of weak disposability of outputs. It is also shown that it falls into one category of the directional distance function model that has been widely applied in modeling undesirable outputs. However, different from the conventional directional distance measures, the proposed model is able to provide efficiency measures in the range of zero and one for easy comparison among inefficient production units.

Suggested Citation

  • Chiang Kao & Shiuh-Nan Hwang, 2019. "Efficiency evaluation in the presence of undesirable outputs: the most favorable shadow price approach," Annals of Operations Research, Springer, vol. 278(1), pages 5-16, July.
  • Handle: RePEc:spr:annopr:v:278:y:2019:i:1:d:10.1007_s10479-017-2399-1
    DOI: 10.1007/s10479-017-2399-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-017-2399-1
    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/s10479-017-2399-1?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. Zanella, Andreia & Camanho, Ana S. & Dias, Teresa G., 2015. "Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(2), pages 517-530.
    2. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    3. Gongbing Bi & Yan Luo & Jingjing Ding & Liang Liang, 2015. "Environmental performance analysis of Chinese industry from a slacks-based perspective," Annals of Operations Research, Springer, vol. 228(1), pages 65-80, May.
    4. Chiang Kao, 2017. "Network Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-3-319-31718-2, September.
    5. Coggins, Jay S. & Swinton, John R., 1996. "The Price of Pollution: A Dual Approach to Valuing SO2Allowances," Journal of Environmental Economics and Management, Elsevier, vol. 30(1), pages 58-72, January.
    6. R. Färe & S. Grosskopf & G. Whittaker, 2013. "Directional output distance functions: endogenous directions based on exogenous normalization constraints," Journal of Productivity Analysis, Springer, vol. 40(3), pages 267-269, December.
    7. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    8. 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.
    9. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    10. 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.
    11. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    12. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    13. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    14. 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.
    15. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    16. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
    17. Charnes, A. & Cooper, W. W., 1984. "The non-archimedean CCR ratio for efficiency analysis: A rejoinder to Boyd and Fare," European Journal of Operational Research, Elsevier, vol. 15(3), pages 333-334, March.
    18. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
    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. Afzalinejad, Mohammad, 2020. "Reverse efficiency measures for environmental assessment in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

    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. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
    2. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    3. Kao, Chiang & Hwang, Shiuh-Nan, 2021. "Measuring the effects of undesirable outputs on the efficiency of production units," European Journal of Operational Research, Elsevier, vol. 292(3), pages 996-1003.
    4. 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.
    5. Cherchye, Laurens & Rock, Bram De & Walheer, Barnabé, 2015. "Multi-output efficiency with good and bad outputs," European Journal of Operational Research, Elsevier, vol. 240(3), pages 872-881.
    6. Abad, Arnaud & Briec, Walter, 2019. "On the axiomatic of pollution-generating technologies: Non-parametric production analysis," European Journal of Operational Research, Elsevier, vol. 277(1), pages 377-390.
    7. Cordero Ferrera, Jose Manuel & Alonso Morán, Edurne & Nuño Solís, Roberto & Orueta, Juan F. & Souto Arce, Regina, 2013. "Efficiency assessment of primary care providers: A conditional nonparametric approach," MPRA Paper 51926, University Library of Munich, Germany.
    8. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    9. Ke Wang & Yi-Ming Wei & Zhimin Huang, 2017. "Environmental efficiency and abatement efficiency measurements of China¡¯s thermal power industry: A data envelopment analysis based materials balance approach," CEEP-BIT Working Papers 108, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Cordero, José Manuel & Alonso-Morán, Edurne & Nuño-Solinis, Roberto & Orueta, Juan F. & Arce, Regina Sauto, 2015. "Efficiency assessment of primary care providers: A conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 235-244.
    11. Annageldy Arazmuradov, 2016. "Economic prospect on carbon emissions in Commonwealth of Independent States," Economic Change and Restructuring, Springer, vol. 49(4), pages 395-427, November.
    12. Atkinson, Scott E. & Tsionas, Mike G., 2021. "Generalized estimation of productivity with multiple bad outputs: The importance of materials balance constraints," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1165-1186.
    13. George Halkos & George Papageorgiou, 2016. "Spatial environmental efficiency indicators in regional waste generation: a nonparametric approach," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 59(1), pages 62-78, January.
    14. Kao, Chiang, 2020. "Measuring efficiency in a general production possibility set allowing for negative data," European Journal of Operational Research, Elsevier, vol. 282(3), pages 980-988.
    15. Adler, Nicole & Volta, Nicola, 2016. "Accounting for externalities and disposability: A directional economic environmental distance function," European Journal of Operational Research, Elsevier, vol. 250(1), pages 314-327.
    16. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.
    17. Charles, Vincent & Kumar, Mukesh & Irene Kavitha, S., 2012. "Measuring the efficiency of assembled printed circuit boards with undesirable outputs using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 136(1), pages 194-206.
    18. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    19. Chang, Dong-Shang & Yang, Fu-Chiang, 2011. "Assessing the power generation, pollution control, and overall efficiencies of municipal solid waste incinerators in Taiwan," Energy Policy, Elsevier, vol. 39(2), pages 651-663, February.
    20. Bian, Yiwen & Yang, Feng, 2010. "Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon's entropy," Energy Policy, Elsevier, vol. 38(4), pages 1909-1917, April.

    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:278:y:2019:i:1:d:10.1007_s10479-017-2399-1. 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.