Emission strategy selection for the circular economy-based production investments with the enhanced decision support system

Abstract

The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations.