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Supply chain management (SCM) encompasses a wide variety of decision-making problems that affect business and supply chain performance. Since most of these problems involve uncertainty and hesitation on the part of decision makers (DMs), various studies have emerged recently that present SCM applications of techniques based on Hesitant Fuzzy Linguistic Term Sets (HFLTSs) and HFLTS extensions. Given the relevance of this subject and the lack of literature review studies, this study presents a systematic review of HFLTS and HFLTS extension applications to SCM decision-making problems. In order to answer a set of research questions, the selected papers were classified in accordance with a group of factors that are pertinent to the origins of these studies, SCM, HFLTSs, and decision making. The results demonstrated that the Source and Enable processes have been studied with greater frequency, while the most common problems have to do with supplier selection, failure evaluation, and performance evaluation. The companies of the automotive sector predominated in the analyzed studies. Even though most of the studies used techniques based on HFLTSs, we identified applications of seven distinct HFLTS extensions. The main contribution of this study consists of presenting an overview of the use of HFLTSs and their extensions in practical examples of SCM, highlighting trends and research opportunities. It is the first study to analyze applications of decision-making techniques that deal with hesitation in SCM. Therefore, the results can help researchers and practitioners develop new studies that involve the use of HFLTSs and HFLTS extensions in decision-making problems, given that this study systematizes elements that should be considered in the modeling, application, and validation of these methods. [ABSTRACT FROM AUTHOR]

Objective: this study proposes a hesitant fuzzy linguistic TOPSIS model for supplier segmentation based on economic, environmental, and social criteria. Proposal: the model classifies suppliers in a segmentation matrix considering their capabilities and willingness to collaborate. It was implemented using Microsoft Excel© and applied to a hydropower plant. Two employees of the company chose a set of segmentation criteria, assigned weights to these criteria, and evaluated the performance of suppliers. In the pilot application, the performance of six suppliers was analyzed and ranked according to 28 criteria. The classification results were endorsed by the decision-makers involved. Conclusion: the model provides consistent results and can assist managers in designing development programs aimed at improving the economic, environmental, and social performance of suppliers. Additionally, it can support group decisions under uncertainty and hesitation, allows the use of linguistic expressions, and does not limit the amounts of criteria or alternatives. [ABSTRACT FROM AUTHOR]

Objective: this study proposes a hesitant fuzzy linguistic TOPSIS model for supplier segmentation based on economic, environmental, and social criteria. Proposal: the model classifies suppliers in a segmentation matrix considering their capabilities and willingness to collaborate. It was implemented using Microsoft Excel© and applied to a hydropower plant. Two employees of the company chose a set of segmentation criteria, assigned weights to these criteria, and evaluated the performance of suppliers. In the pilot application, the performance of six suppliers was analyzed and ranked according to 28 criteria. The classification results were endorsed by the decision-makers involved. Conclusion: the model provides consistent results and can assist managers in designing development programs aimed at improving the economic, environmental, and social performance of suppliers. Additionally, it can support group decisions under uncertainty and hesitation, allows the use of linguistic expressions, and does not limit the amounts of criteria or alternatives. [ABSTRACT FROM AUTHOR]

• Mapping the state-of-the-art on decision-making models to supplier development. • Development of a conceptual framework to characterize decision models. • Proposal of several research opportunities on this topic based on gaps identified. • Most of the identified models focus on formulating supplier development programs. • DEA, Rough Set Theory, and Non-linear programming are the most popular techniques. Supplier development refers to the efforts of a purchasing company and its suppliers to improve supplier performance and its ability to fulfill the purchasing company's supply needs. Recently, several quantitative models have appeared in the literature that support decision-making processes regarding supplier development programs (SDPs). To update the latest research related to this subject, as well as contribute towards the establishment of a research agenda, this study presents a review of the literature on decision-making models that assist the formulating and evaluating of SDPs. This review analyzes 65 articles published in relevant journals, which are characterized in terms of several factors which are inherent to decision making in supplier development. The results show that most models focus on formulating SDPs, whereas the most common decision-making methods are Data Envelopment Analysis and Rough Set Theory. The use of multicriteria models and Fuzzy Sets has increased. The research gaps identified allowed us to propose some future research directions on the topic, calling attention to the need of developing new models considering elements that have not yet been studied in the literature, as well as performing comparative studies between them. Our results here can help orient researchers and managers in developing their decision-making processes in terms of SDP formulation and evaluation. [ABSTRACT FROM AUTHOR]

Fuzzy Analytic Hierarchy Process (Fuzzy AHP) has been widely adopted to support decision making problems. The Fuzzy AHP approach based on the synthetic extent analysis is the most applied approach to calculate the values of the criteria weights from fuzzy comparative matrices. The min operator is used to calculate the weights based on values of degree of possibility. If any of the degrees of possibilities is zero, the output of this operator will also be zero. Thus, the criterion weight or alternative score will be set to zero. If not prevented, this problem may lead to a distorted rank. Despite the fact that there are other propositions based on synthetic extent analysis method, none of the studies found in the literature investigate how the problem of null weights and scores can be avoided. This paper investigates different approaches of the Fuzzy AHP method to evaluate whether they can avoid the problem of null weights and scores without affecting the consistency of the results. Five different approaches based on synthetic extent analysis method were implemented and evaluated. Tests were performed considering 12 decision problems. The results indicated that the Fuzzy AHP approach proposed by Ahmed and Kilic is the most appropriate to overcome the problem of null weight of criteria and scores of alternatives without affecting the consistency of the results. Other benefits of using this approach are the simplicity of the computational implementation and better ability to differentiate the importance of the criteria when the weight values are very close. [ABSTRACT FROM AUTHOR]

Supply chain sustainability management is gaining increasing importance. Several studies propose quantitative evaluation approaches to manage sustainable supply chains. However, none of the studies focus on the selection and weighting of the metrics as a group decision process and in a way that considers the degree of difficulty of collecting data for measuring performance on a particular metric. Therefore, this paper proposes a group decision model for selecting metrics for supply chain sustainability management. The proposal is based on the combination of Hesitant Fuzzy Linguistic Term Sets (HFLTS) with the prioritization procedure of the house of quality of the Quality Function Deployment (QFD) method. HFLTS are used to represent judgments of different decision makers about the importance of supply chain sustainable performance requirements and the relationship between selected metrics and requirements. Prioritization of requirements and metrics is based on the method of distance measures between HFLTSs. The degree of difficulty of data collection is also estimated based on judgments using linguistic expressions and on distance measures of HFLTSs. An illustrative application is presented based on a first tier automobile manufacturing company. Through this illustrative example it is possible to see the benefit of using hesitant fuzzy sets to aggregate the judgments of different decision makers. It is also evident the importance of considering the degree of difficulty of data collecting as an additional argument to select and prioritize metrics. The proposed decision model can also be applied to other decision problems such as selecting criteria for sustainable supplier selection and evaluation. [ABSTRACT FROM AUTHOR]

This paper presents a Fuzzy-QFD model to support the selection of startups to participate in acceleration programs. It proposes to model the selection process by Startup Selection relating the technology transfer and the innovative business modelling. The study provides a quantitative analysis to identify the best startups for participation in accelerated programs. To achieve such a goal, the model uses a multi-criteria decision-making based on QFD (Quality Function Deployment). This study is a pioneer in presenting a model that prioritises the selection of startups by using technology transfer criteria and business modelling components. The model was applied in an acceleration program in Brazilian, and the results indicate that the model is able to rank the companies by presenting which startups stand out. Therefore, the method can be used in prioritisation problems or in the selection of companies to participate in acceleration programs that hold technology transfer in their activities. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to critically analyze the engineering education focused on sustainability in supply chain management, in courses offered by Brazilian higher education institutions. Design/methodology/approach: Topics related to sustainable supply chain management were listed from the literature and used as a framework to gather professors' opinions on how well these topics are covered in engineering courses offered in Brazil. Data analysis was performed via frequency analysis and comparative ordering using the Fuzzy technique for order preference by similarity to ideal solution technique. Findings: It was possible to evidence that most of the topics are superficially presented within other subjects and that there are few associated practical activities that enable greater learning. Comparatively, issues related to ISO standards (related to quality and environmental management systems) and compliance with environmental laws, regulations and standards were highlighted. Additionally, it was possible to verify that there is a need for further study on issues related to energy efficiency, worker training and corporate governance. Originality/value: No similar study was found in the literature. The findings presented in this paper can contribute to the improvement of engineering education in Brazil and other countries. [ABSTRACT FROM AUTHOR]

Trucks are used by many industries in different sectors as industrial equipment. For that reason, selecting a truck without considering the best attributes for the company could cause further problems. Therefore, this paper presents a systematic review of studies that approach quantitative and qualitative decision-making methods and attributes that assist precise data collection. Thus, a framework was created to describe the factors and characteristics of studies, such as application types, hybrid models, sources and data validation. As a result, 11 articles were selected out of 893, all published in English. By analyzing the selected papers, we found applications of several multicriteria methods and a quality management tool to support decision-making. In addition, all the criteria, sub-criteria and attributes adopted by all the 11 studies were summarized and classified within 12 factors in order to simplify them. [ABSTRACT FROM AUTHOR]