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Fuzzy AHP-TOPSIS method for ranking the solutions of environmental taxes implementation to overcome its barriers under fuzzy environment

Ahmad Khodamipour (Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, Islamic Republic of Iran)
Mahdi Askari Shahamabad (Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, Islamic Republic of Iran)
Fateme Askari Shahamabad (Faculty of Management and Economics, ValiAsr University of Rafsanjan, Rafsanjan, Islamic Republic of Iran)

Journal of Applied Accounting Research

ISSN: 0967-5426

Article publication date: 22 October 2021

Issue publication date: 28 April 2022

354

Abstract

Purpose

Many developed countries have been using environmental taxes in their economic systems for many years. These taxes have a great impact on reducing the environmental damages of companies and individuals in society. But many developing countries have not used this tool effectively yet, and some countries face barriers to the effective implementation of environmental taxes that make it difficult and unsuccessful. To increase the effectiveness of the implementation of environmental taxes, governments must prioritize barriers and solutions to overcome its barriers. The identified knowledge gap of the pre-literature review is that an overview of the identification which completely considers all barriers and solutions of environmental taxes implementation does not exist. In response to this knowledge gap, this study aims to identify and prioritize the barriers and solutions of environmental taxes implementation.

Design/methodology/approach

Ranking the barriers and solutions is a complicated multi-criteria decision making (MCDM) problem that requires consideration of multiple feasible alternatives and conflicting tangible and intangible criteria. This study addresses the prioritization of solutions of Environmental Taxes implementation by proposing hybrid MCDM methods based on the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the Fuzzy Technique for order preference by similarity to an ideal solution (Fuzzy-TOPSIS) under fuzzy environment. Fuzzy AHP is used to determine the weight of each barrier using a pairwise comparison, and fuzzy TOPSIS is used to finalize the ranking of solutions for more effective implementation of environmental taxes.

Findings

The results showed that environmental tax reform (ETR) (S3) has the highest value among the solutions for more effective implementation of environmental taxes. The result of the proposed model is validated by performing sensitivity analysis.

Research limitations/implications

This study could foster research on the discussion of these barriers and precise ways of implementing solutions to pay more attention to environmental taxes.

Practical implications

Ratings of solutions can be a guide and help governments to improve the implementation of environmental taxes or even develop this policy by being aware of the ranking of barriers and solutions.

Social implications

This paper creates a new perspective on the effective implementation of environmental taxes, which is closely related to improving environmental performance and increasing social welfare through improving the tax system.

Originality/value

For the first time, this study comprehensively identifies barriers and solutions for more effective implementation of environmental taxes and ranks them using two MCDM techniques.

Keywords

Acknowledgements

Conflict of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Citation

Khodamipour, A., Askari Shahamabad, M. and Askari Shahamabad, F. (2022), "Fuzzy AHP-TOPSIS method for ranking the solutions of environmental taxes implementation to overcome its barriers under fuzzy environment", Journal of Applied Accounting Research, Vol. 23 No. 3, pp. 541-569. https://doi.org/10.1108/JAAR-03-2021-0076

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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