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ORCID

Emrah Kulakli – 0000-0002-4867-2629

Serhat Yüksel – 0000-0002-9858-1266

Serkan Eti – 0000-0002-4791-4091

Hasan Dinçer – 0000-0002-8072-031X

Keywords

competition law; sustainability; regulatory strategies; spherical fuzzy sets; antitrust policy

Abstract

The increasing emphasis on sustainability has intensified tensions with competition law, particularly when cooperative initiatives create risks for market competition or consumer welfare. The main challenge is to identify regulatory strategies that balance sustainability objectives with competitive market principles. This requires a systematic assessment of both sustainability benefits and competition related risks. Existing studies largely rely on legal discussions or case-based evaluations and provide limited quantitative guidance for prioritizing regulatory approaches. This study addresses this gap by proposing a structured decision-making framework to reduce conflicts between sustainability goals and competition law. A hybrid model is developed by integrating spherical fuzzy sets with the LOPCOW method, a distance-based experts’ weighting approach, and the AROMAN technique. The model effectively captures uncertainty and improves the robustness of strategy evaluation. The results show that market foreclosure risk and short-term price effects are the most influential criteria, while sustainability safe harbour frameworks and ex ante regulatory approval mechanisms are the most suitable regulatory strategies. The study contributes to the literature by offering a transparent and replicable evaluation tool and suggests regulatory approaches that emphasize legal certainty, proportionality, and preventive regulation to support sustainabilityoriented cooperation without weakening competition.

Acknowledgements

Funding

This article received no funding.

Declaration of Conflict of Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and publication of this article.

Declaration about the scope of AI utilisation

The author did not use AI in the preparation of this article.

Page Count

35

Received Date

26.01.2026

Accepted Date

25.03.2026

DOI

10.7172/1689-9024.YARS.2026.19.33.6

JEL Code

K21, Q56

Publisher

University of Warsaw

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