The construction industry is an important industry because of its effects on different aspects of human life experiences and circumstances. Environmental concerns have been considered in designing and planning processes of construction supply chains in the recent past. One of the most crucial problems in managing supply chains is the process of evaluation and selection of green suppliers. This process can be categorized as a multi-criteria decision-making (MCDM) problem. The aim of this study is to propose a novel and efficient methodology for evaluation of green construction suppliers with uncertain information. The framework of the proposed methodology is based on weighted aggregated sum product assessment (WASPAS) and the simple multi-attribute rating technique (SMART), and Fermatean fuzzy sets (FFSs) are used to deal with uncertainty of information. The methodology was applied to a green supplier evaluation and selection in the construction industry. Fifteen suppliers were chosen to be evaluated with respect to seven criteria including “estimated cost”, “delivery efficiency”, “product flexibility”, “reputation and management level”, “eco-design”, and “green image pollution”. Sensitivity and comparative analyses were also conducted to assess the efficiency and validity of the proposed methodology. The analyses showed that the results of the proposed methodology were stable and also congruent with those of some existing methods.

Sustainability has become one of the most important issues in the field of supply chain management (SCM). In recent years, many studies have been conducted about how to select a sustainable supplier and different methods have been proposed for this purpose in fuzzy and deterministic environments. A review of the research literature reveals that decision-makers have paid more attention to the results of fuzzy-based studies because they are more accurate and precise in collecting data. The purpose of this paper is to present a new model with a triangular fuzzy approach for sustainable supplier selection (SSS) in the supply chain. The proposed fuzzy model is based on the best-worst method (BWM) and α-cut analysis in which the decision-maker (DM) can determine the alpha value between 0.1 and 0.9, depending on the level of uncertainty. A high value of alpha indicates low uncertainty and its low value indicates a high uncertainty in decision-making. To illustrate the model and demonstrate its capability, a real SSS case in Iran Khodro Company (IKCO), was examined by three experts in the automotive industry and the decision criteria were selected based on the literature review and expert opinions. The results show that the first supplier (ISACO Parts Supply Company) is the most sustainable supplier.

Modern technologies have changed human life and created a generation of customers who have different needs compared to the past. Considering Industry 4.0 and its drivers, the implementation of digital banking (DB) has faced various challenges that are caused by emerging trends. Both Industry 4.0 and DB are contemporary concepts, and decision-makers are often faced with uncertainties in their decisions regarding the implementation of DB and its indicators. For this purpose, a novel multi-criteria group decision-making approach has been developed utilizing the best–worst method (BWM) and α-cut analysis as well as trapezoidal fuzzy numbers (TFNs). By reviewing the literature and using experts’ opinions, the DB implementation criteria are determined, and considering an uncertain environment, the criteria are prioritized using the proposed method. Then, the available DB models and alternatives are examined based on the decision criteria and the importance of each criterion. This research contributes to the existing literature by identifying and prioritizing the criteria necessary for the successful implementation of DB, taking into account emerging trends and technological advances driven by Industry 4.0. Subsequently, the study prioritizes the prevalent models of DB based on these criteria. This study proposes a decision-support framework for dealing with ambiguity, lack of information, insufficient knowledge, and uncertainty in decision-making. The framework uses TFNs to account for imprecision and doubt in decision-makers’ preferences. Additionally, the study presents a fuzzy multi-criteria group decision-making approach that enables a group of experts to arrive at more reliable results. The proposed approach can help improve the quality of decision-making in complex and uncertain situations. The results of this research show that human resources, rules and regulations, and customer satisfaction are the most important criteria for implementing DB. In addition, the open, blockchain, and social banking models are the crucial models that significantly cover the implementation criteria for DB.

Background: The transportation sector has wide-ranging effects on the human societies. Public transportation has a key and undeniable role in the lives of people in society and affects important aspects such as economic, social, cultural and environmental. Therefore, assessing the sustainability of public transportation in urban areas can be considered as a challenge for transportation policy makers. Methods: In this study, a novel hybrid multi-criteria decision-making (MCDM) method is proposed to evaluate sustainable public transportation in Tehran. Evaluation criteria have been identified using the literature and experts’ opinion. The proposed method integrates the fuzzy best-worst method (FBWM) and the multi-attributive border approximation area comparison (MABAC) method. a group of three experts determined the weight and importance of each criterion using FBWM. The MABAC method was then used to rank sustainable public transport alternatives. Results: The results indicate the reliability of the proposed method. Also, we can see that the results are congruent with the actual conditions of public transportation. The studied alternatives have been evaluated, and according to the decision criteria, metro and e-hailing have been the most sustainable alternatives. It is noteworthy that the economic and financial sustainability, service availability and environment sustainability have been the most important criteria. Conclusion: The proposed framework in this study can be used by public transportation planners and policy makers to identify sustainable options in order to consider facilities and implement incentive policies in this field. Also, the results of the proposed method used in this study can be used as a suitable guidance to assess the sustainability of public transportation.