IDEAS home Printed from https://ideas.repec.org/a/spr/sumafo/v29y2021i3d10.1007_s00550-021-00511-x.html
   My bibliography  Save this article

Upper and lower satisficing levels in efficiency analysis: a corporate social responsibility perspective

Author

Listed:
  • Malte L. Peters

    (Federal University of Applied Administrative Sciences, Faculty of Finance)

  • Stephan Zelewski

    (University of Duisburg-Essen, Campus Essen, Faculty of Business Administration and Economics)

Abstract

The analysis of efficiency and especially the analysis of so-called eco-efficiency have been broadly considered within the scope of Sustainable Development (SD) and Corporate Social Responsibility (CSR). Moreover, upper satisficing levels for output factors and lower satisficing levels for input factors have been already discussed within this context. In particular, upper satisficing levels for output factors can be viewed as relevant from a CSR perspective, since they can be used to remove the incentive to produce unnecessary high output quantities in order to receive better efficiency scores. However, lower satisficing levels for output factors and upper satisficing levels for input factors have not been addressed in the discussion so far. In this paper, a data transformation model to simultaneously consider lower and upper satisficing levels for output factors as well as for input factors is presented. The proposed model takes up the idea of linear representation of logical constraints. Subsequently, the benefits and perils of this approach are discussed from a CSR perspective. It is shown that changes in efficiency scores or even in efficiency rank positions due to considering satisficing levels can be indicators of behavior that is desirable from a CSR perspective.

Suggested Citation

  • Malte L. Peters & Stephan Zelewski, 2021. "Upper and lower satisficing levels in efficiency analysis: a corporate social responsibility perspective," Sustainability Nexus Forum, Springer, vol. 29(3), pages 187-195, December.
  • Handle: RePEc:spr:sumafo:v:29:y:2021:i:3:d:10.1007_s00550-021-00511-x
    DOI: 10.1007/s00550-021-00511-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00550-021-00511-x
    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/s00550-021-00511-x?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. Sarkis, Joseph & Cordeiro, James J., 2012. "Ecological modernization in the electrical utility industry: An application of a bads–goods DEA model of ecological and technical efficiency," European Journal of Operational Research, Elsevier, vol. 219(2), pages 386-395.
    2. 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.
    3. Behrouz Arabi & Susila Munisamy Doraisamy & Ali Emrouznejad & Alireza Khoshroo, 2017. "Eco-efficiency measurement and material balance principle: an application in power plants Malmquist Luenberger Index," Annals of Operations Research, Springer, vol. 255(1), pages 221-239, August.
    4. Xiancun Hu & Chunlu Liu, 2017. "Slacks-based data envelopment analysis for eco-efficiency assessment in the Australian construction industry," Construction Management and Economics, Taylor & Francis Journals, vol. 35(11-12), pages 693-706, December.
    5. Mohit Goswami & Abhijeet Ghadge, 2020. "A supplier performance evaluation framework using single and bi-objective DEA efficiency modelling approach: individual and cross-efficiency perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 3066-3089, May.
    6. 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.
    7. Manning, Stephan & Reinecke, Juliane, 2016. "A modular governance architecture in-the-making: How transnational standard-setters govern sustainability transitions," Research Policy, Elsevier, vol. 45(3), pages 618-633.
    8. Leonardo Becchetti & Giovanni Trovato, 2011. "Corporate social responsibility and firm efficiency: a latent class stochastic frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(3), pages 231-246, December.
    9. Monastyrenko, Evgenii, 2017. "Eco-efficiency outcomes of mergers and acquisitions in the European electricity industry," Energy Policy, Elsevier, vol. 107(C), pages 258-277.
    10. 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.
    11. Ankit Bansal & Rajesh Kr. Singh & Siddhant Issar & Jayson Varkey, 2014. "Evaluation of vendors ranking by EATWOS approach," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 11(3), pages 290-311, October.
    12. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    13. 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.
    14. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "Measurement of Returns to Scale and Damages to Scale for DEA-based operational and environmental assessment: How to manage desirable (good) and undesirable (bad) outputs?," European Journal of Operational Research, Elsevier, vol. 211(1), pages 76-89, May.
    15. Harald Dyckhoff, 2018. "Multi-criteria production theory: foundation of non-financial and sustainability performance evaluation," Journal of Business Economics, Springer, vol. 88(7), pages 851-882, September.
    16. Zhongbao Zhou & Wenbin Liu, 2015. "DEA Models with Undesirable Inputs, Intermediates, and Outputs," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 15, pages 415-446, Springer.
    17. Kirsten A. Cook & Andrea M. Romi & Daniela Sánchez & Juan Manuel Sánchez, 2019. "The influence of corporate social responsibility on investment efficiency and innovation," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 46(3-4), pages 494-537, March.
    18. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    19. Dyckhoff, H. & Allen, K., 2001. "Measuring ecological efficiency with data envelopment analysis (DEA)," European Journal of Operational Research, Elsevier, vol. 132(2), pages 312-325, July.
    20. Alexander Dahlsrud, 2008. "How corporate social responsibility is defined: an analysis of 37 definitions," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 15(1), pages 1-13, January.
    21. Thomas Dyllick & Kai Hockerts, 2002. "Beyond the business case for corporate sustainability," Business Strategy and the Environment, Wiley Blackwell, vol. 11(2), pages 130-141, March.
    22. Jie Wu & Qingyuan Zhu & Junfei Chu & Qingxian An & Liang Liang, 2016. "A DEA-based approach for allocation of emission reduction tasks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(18), pages 5618-5633, September.
    23. Liu, Wenbin & Zhou, Zhongbao & Ma, Chaoqun & Liu, Debin & Shen, Wanfang, 2015. "Two-stage DEA models with undesirable input-intermediate-outputs," Omega, Elsevier, vol. 56(C), pages 74-87.
    24. Pornsit Jiraporn & Napatsorn Jiraporn & Adisak Boeprasert & Kiyoung Chang, 2014. "Does Corporate Social Responsibility (CSR) Improve Credit Ratings? Evidence from Geographic Identification," Financial Management, Financial Management Association International, vol. 43(3), pages 505-531, September.
    25. Hall, Jeremy K. & Daneke, Gregory A. & Lenox, Michael J., 2010. "Sustainable development and entrepreneurship: Past contributions and future directions," Journal of Business Venturing, Elsevier, vol. 25(5), pages 439-448, September.
    26. Chen-En Hou & Wen-Min Lu & Shiu-Wan Hung, 2019. "Does CSR matter? Influence of corporate social responsibility on corporate performance in the creative industry," Annals of Operations Research, Springer, vol. 278(1), pages 255-279, July.
    27. Clarke, Kevin A., 2020. "Logical Constraints: The Limitations of QCA in Social Science Research," Political Analysis, Cambridge University Press, vol. 28(4), pages 552-568, October.
    28. Yantuan Yu & Hui Hu & Yun Zhang & Zhujia Yin, 2019. "Metafrontier Eco-Efficiency and Its Convergence Analysis for China: A Multidimensional Heterogeneity Perspective," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(7), pages 1531-1549, May.
    29. 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.
    30. Yaisawarng, Suthathip & Klein, J Douglass, 1994. "The Effects of Sulfur Dioxide Controls on Productivity Change in the U.S. Electric Power Industry," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 447-460, August.
    31. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
    32. Victoria Wojcik & Harald Dyckhoff & Sebastian Gutgesell, 2017. "The desirable input of undesirable factors in data envelopment analysis," Annals of Operations Research, Springer, vol. 259(1), pages 461-484, December.
    Full references (including those not matched with items on IDEAS)

    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. Dyckhoff, Harald & Souren, Rainer, 2022. "Integrating multiple criteria decision analysis and production theory for performance evaluation: Framework and review," European Journal of Operational Research, Elsevier, vol. 297(3), pages 795-816.
    2. Victoria Wojcik & Harald Dyckhoff & Sebastian Gutgesell, 2017. "The desirable input of undesirable factors in data envelopment analysis," Annals of Operations Research, Springer, vol. 259(1), pages 461-484, December.
    3. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    4. 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.
    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. Harald Dyckhoff, 2018. "Multi-criteria production theory: foundation of non-financial and sustainability performance evaluation," Journal of Business Economics, Springer, vol. 88(7), pages 851-882, September.
    7. 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.
    8. Halkos, George & Petrou, Kleoniki Natalia, 2018. "A critical review of the main methods to treat undesirable outputs in DEA," MPRA Paper 90374, University Library of Munich, Germany.
    9. 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.
    10. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    11. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    12. Taleb, Mushtaq & Khalid, Ruzelan & Ramli, Razamin & Ghasemi, Mohammad Reza & Ignatius, Joshua, 2022. "An integrated bi-objective data envelopment analysis model for measuring returns to scale," European Journal of Operational Research, Elsevier, vol. 296(3), pages 967-979.
    13. Khoshroo, Alireza & Izadikhah, Mohammad & Emrouznejad, Ali, 2022. "Total factor energy productivity considering undesirable pollutant outputs: A new double frontier based malmquist productivity index," Energy, Elsevier, vol. 258(C).
    14. Harald Dyckhoff, 2019. "Multi-criteria production theory: convexity propositions and reasonable axioms," Journal of Business Economics, Springer, vol. 89(6), pages 719-735, August.
    15. 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.
    16. 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.
    17. 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.
    18. Qingxian An & Haoxun Chen & Jie Wu & Liang Liang, 2015. "Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output," Annals of Operations Research, Springer, vol. 235(1), pages 13-35, December.
    19. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    20. Yigang Wei & Yan Li & Meiyu Wu & Yingbo Li, 2020. "Progressing sustainable development of “the Belt and Road countries”: Estimating environmental efficiency based on the Super‐slack‐based measure model," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 521-539, July.

    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:sumafo:v:29:y:2021:i:3:d:10.1007_s00550-021-00511-x. 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.