The current study was undertaken to identify evaluation indicators of LARG supply chain in Saipa Yadak Company initially through fuzzy screening and further to weight and prioritize them through fuzzy best-worst method. The research population comprised 20 senior managers at Saipa Yadak Company with at least 10 years of administrative experience within the supply chain management sector. The enquiry started with an extensive review of existing literature on the theoretical foundations and interviewing experts to identify indicators of LARG supply chain via fuzzy screening procedure. Having screened the indicators, we designed a paired comparison questionnaire which was piloted and distributed among the experts. The data obtained from the questionnaires were weighted and ranked using fuzzy best-worst method. The findings identified accountability, environmental function, speed of knowledge and technology, participation and support, human resource management, relation with suppliers and customers, competency, flexibility, and, cost and operation control as the most important indicator of the LARG supply chain, respectively. In addition, each indicator was weighted and prioritized to provide support for managers of at automotive industry through LARG supply chain evaluation and assist them in selecting effective solutions to reduce supply chain risks, and thereby, to facilitate decision making.

Today due to the globalization and competitive conditions of the market, decisions are generally made in group and in accordance with different attributes. In addition, all of the information is associated with uncertainty. In such situation, the emergence of inconsistency and facing with the contradictions will be obvious. Having regarded this fact, the development and application of tools that adequately address the uncertainty in decision making process and also be appropriate for group decision making is an important area of multi-criteria decision making (MCDM). Therefore, in this paper, firstly we developed the traditional best-worst method (BWM) and proposed an interval-valued intuitionistic fuzzy best-worst method (IVIFBWM), then introduced a novel approach for fuzzy multi-attribute group decision making based on the proposed method. Finally, in order to demonstrate how the introduced approach can be applied in practice, it is implemented in an Iranian investment company and the experimental results are examined. From the experimental results, we can extract that not only the introduced approach is simple in calculation but also it is convenient in implementation especially in interval-valued intuitionistic fuzzy environments.

The frequency of chronic diseases such as cardiovascular diseases has significantly increased in recent years. This study is a developmental research which is categorized as descriptive-survey in terms of data collection method. The aim of this study is to prioritize 22 districts of Tehran for the purpose of prevention from cardiovascular diseases. In the present study, after extraction of the effective factors on the prevalence of cardiovascular diseases from previous studies, the weight of each factor with their specific data for each 22 districts of Tehran (collected from relevant organizations) is obtained using two levels of Fuzzy Delphi method and one level of fuzzy best-worst method, for confirming or denying factors and weighting them based on the opinion of 25 cardiologists, respectively, and transferred to Arc GIS software for prioritizing 22 districts of Tehran.Using a combination of fuzzy best-worst method, which is one of the newest methods for making multi-criteria decision, and GIS, for weighting parameters and prioritizing 22 districts of Tehran, gives an acceptable worth to the present study.Our results-after classification, drawing, and combination of maps- indicated that the 8th district (except a little part in the west) is the best district, and 16th and 19th districts (approximately whole district) are in the last priority for prevention of cardiovascular diseases. Other districts respectively placed in the second to 21th places.

Today, productivity is one of the most important factors in economic growth. At the organizational level, a high level of productivity indicates optimal performance to gain a competitive advantage. Despite the important role of productivity of service organizations in economic growth, few studies have been conducted in this context. The purpose of this study is to evaluate service productivity by a combined fuzzy best-worst method and data envelopment analysis.
In the first stage, carrying out a comprehensive review of the research literature, indicators of service productivity evaluation were identified. Then, the evaluation indicators were weighed using the fuzzy best-worst method. After weighing the indicators and determining the importance of each of them, using the data envelopment analysis approach, the efficiency, effectiveness, and productivity of Mazandaran Electricity Distribution Company were evaluated for five consecutive years from 2016 to 2020.
In this study, efficiency, effectiveness, and productivity were simultaneously evaluated using quantitative and qualitative indicators affecting the evaluation of the productivity of electricity distribution companies.
The obtained results would help to assess service productivity by emphasizing both quantitative and qualitative aspects of services and paying attention to the dimensions of efficiency and effectiveness simultaneously. Productivity improvement strategies were also suggested based on the achieved results of the current study.

In this study, we combine an interval type-2 fuzzy best-worst method (IT2FBWM) with the interval VIKOR method for the first time to evaluate and prioritize sustainable suppliers in circular supply chains. To weigh the criteria, an interval type-2 best worst approach is employed, and the interval VIKOR methodology is utilized to assess the suppliers in the presence of uncertainty. Risk is presented in all supply chain activities, and its occurrence affects all dimensions of the supply chain and can cause damage to them and, therefore, must be appropriately managed. A new mixed-integer linear programming model is then formulated to identify each risk's optimal strategy or response. The multi-objective model minimizes total costs and response time and maximizes risk responses to secondary and primary risks. An improved version of augmented ε-constraint method (AUGMECON2) is also employed to produce separate Pareto-optimal solutions. Finally, the suggested strategy is applied to four main suppliers in the food company. The findings of the proposed integrated approach demonstrate the applicability and efficiency in the food industry.

In this paper‎, ‎a new approach for decision-making and marketing forecast based on fuzzy logic fuzzy expert system is presented regarding the tourism development plan of the Majma Hamiyari Association by Abbas Bashiri‎. ‎In other words‎, ‎let's look at system marketing using the reverse fund design calculation method in attracting different strata according to the input and output variables‎. ‎In fact‎, ‎we offer the marketing manager a plan to focus the most time and capital for advertising on the segment where this calculation method has the greatest impact on attracting customers‎. ‎This study suggests an infrastructure for determining the factors affecting tourism‎. ‎Hence‎, ‎the newest multi-criteria decision-making method‎, ‎the fuzzy best-worst method was used to calculate the relative importance of indices and fuzzy evaluation based on distance from average solution technique was applied as a multi-attribute decision-making method to rank effective factors in tourism‎. ‎The statistical population of this research consists of directors and experts in the tourism industry in Mazandaran‎. ‎Due to the results of this study‎, ‎providing Banking facilities to users ranks first among other options for the economy itself.

In real-world decision-making problems, we often face multiple criteria that should be considered in the decision process. Also, the collected data are often non-crisp and reported with a degree of hesitation. In this study, using intuitionistic fuzzy numbers that can model these non-crisp and hesitant data, we propose a simple yet effective method for solving real-world multi-criteria decision-making problems. We applied our proposed approach to the intuitionistic fuzzy Best-Worst Method, which is one of the famous techniques for solving multi-criteria decision-making problems. However, the proposed method can be easily generalized to the other multi-criteria decision-making methods in intuitionistic fuzzy environments, too. Finally, the ability of the proposed approach to solve these types of problems is shown by an illustrative example.

The purpose of the current research is to identify the dimensions and components of knowledge flow processes and examine their importance in defense knowledge-based companies. The population and statistical sample of this research is 25 experts. For this purpose, using the fuzzy Delphi method, 5 dimensions and 25 components of knowledge flow processes were identified and screened. Then the weighting and prioritization of each of the research variables in knowledge-based organizations was done with the fuzzy best-worst method. The results show that the dimension of knowledge retention ranks first and dimensions: knowledge creation; knowledge transfer; Knowledge acquisition and knowledge application were ranked second to fifth in Lingo software. Then, the intensity of the relationships between the dimensions of the knowledge flow processes was evaluated using the fuzzy Dimethel method. The results of this research can provide a comprehensive view to knowledge management experts and researchers regarding the dimensions and components of knowledge flow and their prioritization in knowledge-based organizations.

Today, the tourism industry is one of the most dynamic developing sectors of the world economy and an important factor in the social and economic development of regions and countries. It is known as one of the three first-class profitable industries in the world, which in order to expand and develop requires the cooperation and agreement of environmental, cultural, economic, political and social factors at the community level, in this regard, the phenomenon what has now negatively affected the tourism industry in Iran and the world is the Corona (Covid-19) crisis. This study suggests an infrastructure for determining the factors affecting health tourism. Therefore, the newest multi-criteria decision-making method, fuzzy best-worst method was used to calculate the relative importance of indices and Fuzzy evaluation based on distance from average solution technique was applied as a multi-attribute decision-making method to rank effective factors in health tourism. The statistical population of this research consists of directors and experts in the tourism industry Mazandaran.  Based on the results of this study, improving the level of tourist security in the province ranks first among other options for the economy itself.

The purpose of this research was to identify and rank the factors affecting the establishment of       two-way supply chain in Shahrekord food packaging companies. This research was applied in two qualitative and quantitative parts, in the identification part, the qualitative method of theme analysis was used, and in the quantitative part, the fuzzy BWM quantitative method was used. The statistical population of the research was the experts of Shahrekord food packaging companies, 11 of whom were selected as a sample. The total codes obtained from the interviews with 11 experts participating in the interview, 7 inclusive themes include management commitment, supply chain agility, trust among supply chain partners, supply chain adaptability, innovation, supply chain efficiency and information technology. In this section, the fuzzy best-worst method was used for weighting and prioritizing the 7 main criteria of the research. Based on this, supply chain agility ranks first and the rest of the components include management commitment, supply chain adaptability, innovation, trust among supply chain partners, information technology, and supply chain efficiency.