Evaluating ESG corporate performance using a new neutrosophic AHP-TOPSIS based approach
Abstract
Corporate sustainability reports’ credibility of environmental, social, and governance (ESG) information has received a significant focus of attention in the businesses landscape. Over the last years, various methodologies and multicriteria approaches have been developed to assess the ESG performance of companies. To consider the uncertainty that arises from imprecision and subjectivity in evaluating ESG criteria, this paper proposes to develop a novel hybrid methodology that combines AHP and TOPSIS techniques under a neutrosophic environment. We test the suggested proposal through a real case study of the leading companies in the oil and gas industry. Moreover, we conduct a sensitivity analysis for evaluating any discrepancies in the ranking due to using different fuzzy numbers and weighting vectors.
First published online 05 July 2022
Keyword : fuzzy sets, triangular neutrosophic numbers, possibility measures, sustainability reporting, greenwashing, ESG
How to Cite
Reig-Mullor, J., Garcia-Bernabeu, A., Pla-Santamaria, D., & Vercher-Ferrandiz, M. (2022). Evaluating ESG corporate performance using a new neutrosophic AHP-TOPSIS based approach. Technological and Economic Development of Economy, 28(5), 1242–1266. https://doi.org/10.3846/tede.2022.17004
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Set and Systems, 20, 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
Brans, J. P., Mareschal, B., & Vincke, P. (1984). Prométhée: a new family of outranking methods in multicriteria analysis. In J. P. Brans (Ed.), Operational research’24 (pp. 477–490). North-Holland.
Broumi, S., Nagarajan, D., Bakali, A., Talea, M., Smarandache, F., & Lathamaheswari, M. (2019). The shortest path problem in interval valued trapezoidal and triangular neutrosophic environment. Complex & Intelligent Systems, 5(4), 391–402. https://doi.org/10.1007/s40747-019-0092-5
Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247. https://doi.org/10.1016/0165-0114(85)90090-9
Chang, D.-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655. https://doi.org/10.1016/0377-2217(95)00300-2
Chowdhury, P., & Paul, S. K. (2020). Applications of MCDM methods in research on corporate sustainability. Management of Environmental Quality: An International Journal, 31(2), 385–405. https://doi.org/10.1108/MEQ-12-2019-0284
Dahl, R. (2010). Greenwashing: Do you know what you´re buying? Environmental Health Perspectives, 118(6), A246–A252. https://doi.org/10.1289/ehp.118-a246
Dahlsrud, A. (2008). How corporate social responsibility is defined: An analysis of 37 definitions. Corporate Social Responsibility and Environmental Management, 15(1), 1–13. https://doi.org/10.1002/csr.132
Das, S., Roy, B. K., Kar, M. B., Kar, S., & Pamučar, D. (2020). Neutrosophic fuzzy set and its application in decision making. Journal of Ambient Intelligence and Humanized Computing, 11(11), 5017–5029. https://doi.org/10.1007/s12652-020-01808-3
De Bakker, P. I. W., Yelensky, R., Pe’Er, I., Gabriel, S. B., Daly, M. J., & Altshuler, D. (2005). Efficiency and power in genetic association studies. Nature Genetics, 37(11), 1217–1223. https://doi.org/10.1038/ng1669
Deli, I., & Subas, Y. (2014). Single valued neutrosophic numbers and their applications to multicriteria decision making problem. Neutrosophic Set Systems, 2(1), 1–13.
Deli, I., & Şubaş, Y. (2017). A ranking method of single valued neutrosophic numbers and its applications to multi-attribute decision making problems. International Journal of Machine Learning and Cybernetics, 8. https://doi.org/10.1007/s13042-016-0505-3
Deng, H. (1999). Multicriteria analysis with fuzzy pairwise comparison. 1999 IEEE International Fuzzy Systems Conference Proceedings. FUZZ-IEEE ’99. IEEE. https://doi.org/10.1109/FUZZY.1999.793038
Deveci, M., Erdogan, N., Cali, U., Stekli, J., & Zhong, S. (2021). Type-2 neutrosophic number based multi-attributive border approximation area comparison (MABAC) approach for offshore wind farm site selection in USA. Engineering Applications of Artificial Intelligence, 103(February), 104311. https://doi.org/10.1016/j.engappai.2021.104311
Escrig-Olmedo, E., Rivera-Lirio, J. M., Muñoz-Torres, M. J., & Fernández-Izquierdo, M. Á. (2017). Integrating multiple ESG investors’ preferences into sustainable investment: A fuzzy multicriteria methodological approach. Journal of Cleaner Production, 162, 1334–1345. https://doi.org/10.1016/j.jclepro.2017.06.143
Garg, H., & Nancy. (2020). Multiple attribute decision making based on immediate probabilities aggregation operators for single-valued and interval neutrosophic sets. Journal of Applied Mathematics and Computing, 63(1–2), 619–653. https://doi.org/10.1007/s12190-020-01332-9
Ghorabaee, M. K., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS). Informatica, 26(3), 435–451. https://doi.org/10.15388/Informatica.2015.57
Giri, B. C., Molla, M. U., & Biswas, P. (2020). TOPSIS Method for Neutrosophic Hesitant Fuzzy Multi-Attribute Decision Making. Informatica, 31(1), 35–63. https://doi.org/10.15388/20-INFOR392
Hwang, C., & Yoon, K. (1981). Multiple attributes decision making: Methods and applications. Springer. https://doi.org/10.1007/978-3-642-48318-9
Ilinitch, A. Y., Soderstrom, N. S., & E. Thomas, T. (1998). Measuring corporate environmental performance. Journal of Accounting and Public Policy, 17(4), 383–408. https://doi.org/https://doi.org/10.1016/S0278-4254(98)10012-1
Junaid, M., Xue, Y., Syed, M. W., Li, J. Z., & Ziaullah, M. (2020). A neutrosophic ahp and topsis framework for supply chain risk assessment in automotive industry of Pakistan. Sustainability, 12(1). https://doi.org/10.3390/SU12010154
Kamran, H. W., Pantamee, A. A., Patwary, A. K., Ghauri, T. A., Long, P. D., & Nga, D. Q. (2021). Measuring the association of environmental, corporate, financial, and social CSR: Evidence from fuzzy TOPSIS nexus in emerging economies. Environmental Science and Pollution Research International, 28(9), 10749–10762. https://doi.org/10.1007/s11356-020-11336-4
Keshavarz-Ghorabaee, M. (2021). Assessment of distribution center locations using a multi-expert subjective–objective decision-making approach. Scientific Reports, 11(1), 19461. https://doi.org/10.1038/s41598-021-98698-y
Keshavarz-Ghorabaee, M., Amiri, M., Hashemi-Tabatabaei, M., & Ghahremanloo, M. (2021a). Sustainable public transportation evaluation using a novel hybrid method based on fuzzy BWM and MABAC. The Open Transportation Journal, 15(1), 31–46. https://doi.org/10.2174/1874447802115010031
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2018). Simultaneous evaluation of criteria and alternatives (SECA) for Multi-criteria decision-making. Informatica, 29(2), 265–280. https://doi.org/10.15388/Informatica.2018.167
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2021b). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13(4). https://doi.org/10.3390/sym13040525
Khatter, K. (2020). Neutrosophic linear programming using possibilistic mean. Soft Computing, 24(22), 16847–16867. https://doi.org/10.1007/s00500-020-04980-y
Kilic, H. S., Yurdaer, P., & Aglan, C. (2021). A leanness assessment methodology based on neutrosophic DEMATEL. Journal of Manufacturing Systems, 59, 320–344. https://doi.org/10.1016/j.jmsy.2021.03.003
Li, X., & Huang, X. (2019). The three-way decisions method based on theory of reliability with SV-triangular neutrosophic numbers. Symmetry, 11(7). https://doi.org/10.3390/sym11070888
Liern, V., & Pérez-Gladish, B. (2018). Ranking corporate sustainability: A flexible multidimensional approach based on linguistic variables. International Transactions in Operational Research, 25(3), 1081–1100. https://doi.org/https://doi.org/10.1111/itor.12469
Lu, K., Liao, H., & Zavadskas, E. K. (2021). An overview of fuzzy techniques in supply chain management: Bibliometrics, methodologies, applications and future directions. Technological and Economic Development of Economy, 27(2), 402–458. https://doi.org/10.3846/tede.2021.14433
Luo, S., Pedrycz, W., & Xing, L. (2021). Pricing of satellite image data products: Neutrosophic fuzzy pricing approaches under different game scenarios. Applied Soft Computing, 102, 107106. https://doi.org/10.1016/j.asoc.2021.107106
Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126–4148. https://doi.org/10.1016/j.eswa.2015.01.003
Mikhailov, L., & Tsvetinov, P. (2004). Evaluation of services using a fuzzy analytic hierarchy process. Applied Soft Computing Journal, 5(1), 23–33. https://doi.org/10.1016/j.asoc.2004.04.001
Nafei, A. H., Javadpour, A., Nasseri, H., & Yuan, W. (2021). Optimized score function and its application in group multiattribute decision making based on fuzzy neutrosophic sets. International Journal of Intelligent Systems, 36(12), 7522–7543. https://doi.org/10.1002/int.22597
Opricovic, S. (1998). Visekriterijumska optimizacija sistema u gradjevinarstvu [Multicriteria optimization of civil engineering systems]. Faculty of Civil Engineering, University of Belgrade, Belgrade (in Serbian).
Roy, B. (1996). Multicriteria methodology for decision aiding (Vol. 12). Springer Science & Business Media. https://doi.org/10.1007/978-1-4757-2500-1
Roy, P. K., & Shaw, K. (2022). Modelling a sustainable credit score system (SCSS) using BWM and fuzzy TOPSIS. International Journal of Sustainable Development & World Ecology, 29(3), 195–208. https://doi.org/10.1080/13504509.2021.1935360
Saaty, T. L. (1980). The analytic hierarchy process. McGraw-Hill Inc.
Saaty, T., & Vargas, L. (2006). Decision making with the analytic network process. Economic, political, social and technological applications with benefits, opportunities, costs and risks (Vol. 95). Springer. https://doi.org/10.1007/0-387-33987-6
Smarandache, F. (1999). A unifying field in logics, neutrosophy: Neutrosophic probability, set and logic. American Research Press.
Stankevičiene, J., & Mencaite, E. (2012). The evaluation of bank performance using a multicriteria decision making model: A case study on Lithuanian commercial banks. Technological and Economic Development of Economy, 18(1), 189–205. https://doi.org/10.3846/20294913.2012.668373
Tavana, M., Zareinejad, M., Di Caprio, D., & Kaviani, M. A. (2016). An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics. Applied Soft Computing Journal, 40, 544–557. https://doi.org/10.1016/j.asoc.2015.12.005
Turksen, I. B. (1986). Interval valued fuzzy sets based on normal forms. Fuzzy Sets and Systems, 20(2), 191–210. https://doi.org/10.1016/0165-0114(86)90077-1
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