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Application of a fuzzy hierarchical model to the assessment of corporate social and environmental sustainability

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  • Vassilis S. Kouikoglou
  • Yannis A. Phillis

Abstract

Corporate responsibility has many facets. A corporation should organize its operations so that its environmental impact is minimal, its economic state is viable, labor conditions are good, and compliance with laws and regulations is satisfactory, among others. Corporate responsibility is intimately connected to corporate sustainability which expresses the economic, environmental, and social standing of a company. A responsible corporation embraces the principle of transparency of data pertaining to its performance and its policies and strives for strategies that enhance its sustainability. A model is presented that uses hierarchical fuzzy reasoning to assess corporate sustainability, given a number of inputs, called basic indicators. Inputs are normalized according to their sustainability status and then combined to obtain a sustainability index on [0, 1] for each facet of the corporation. A sensitivity analysis pinpoints the most important indicators affecting sustainability. Two case studies of multinational cement companies are presented in detail. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment.

Suggested Citation

  • Vassilis S. Kouikoglou & Yannis A. Phillis, 2011. "Application of a fuzzy hierarchical model to the assessment of corporate social and environmental sustainability," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 18(4), pages 209-219, July.
    • Handle: RePEc:wly:corsem:v:18:y:2011:i:4:p:209-219
    DOI: 10.1002/csr.241
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    References listed on IDEAS

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    1. Graafland, J.J. & Eijffinger, S.C.W. & Smid, H., 2004. "Benchmarking of corporate social responsibility: Methodological problems and robustness," MPRA Paper 20771, University Library of Munich, Germany.
    2. Phillis, Yannis A. & Andriantiatsaholiniaina, Luc A., 2001. "Sustainability: an ill-defined concept and its assessment using fuzzy logic," Ecological Economics, Elsevier, vol. 37(3), pages 435-456, June.
    3. Andriantiatsaholiniaina, Luc A. & Kouikoglou, Vassilis S. & Phillis, Yannis A., 2004. "Evaluating strategies for sustainable development: fuzzy logic reasoning and sensitivity analysis," Ecological Economics, Elsevier, vol. 48(2), pages 149-172, February.
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    Cited by:

    1. Sepehr Hendiani & Huchang Liao & Morteza Bagherpour & Manuela Tvaronavičienė & Audrius Banaitis & Jurgita Antucheviciene, 2020. "Analyzing the Status of Sustainable Development in the Manufacturing Sector Using Multi-Expert Multi-Criteria Fuzzy Decision-Making and Integrated Triple Bottom Lines," IJERPH, MDPI, vol. 17(11), pages 1-19, May.
    2. Eleonora Bottani & Maria Carmen Gentilotti & Marta Rinaldi, 2017. "A Fuzzy Logic-Based Tool for the Assessment of Corporate Sustainability: A Case Study in the Food Machinery Industry," Sustainability, MDPI, vol. 9(4), pages 1-29, April.
    3. Luciano Barcellos‐Paula & Carlos Agüero‐Olivos, 2022. "The strengthening of corporate governance based on applied fuzzy logic," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(5), pages 1736-1746, September.
    4. Maximilian Zarte & Agnes Pechmann & Isabel L. Nunes, 2021. "Fuzzy Inference Model for Decision Support in Sustainable Production Planning Processes—A Case Study," Sustainability, MDPI, vol. 13(3), pages 1-29, January.

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