Research On Sustainable Supplier Evaluation And Selection Within Complex And Uncertain Environment

With increasing global concerns toward environmental protection and sustainable development,sustainable supply chain management(SSCM)has drawn much attention of academicians and practitioners.Selecting an optimal sustainable supplier is a critical part of SSCM,which can be viewed as a complex multi-criteria decision making problem.The application of sustainable supplier evaluation and selection(SSES)can be presented in the situation of multiple suppliers throughout a product's life-cycle.Consequently,it is significant for organizations to choose the environmentally,socially and economically powerful suppliers.However,the existing SSES methods suffer from many important deficiencies when used in the real world.This paper,through conducting a bibliometric review on SSES literature,puts forward three novel models to enhance the performance of the current SSES methods.The main contributions of this dissertation can be summarized as follows:(1)Lots of models and approaches have been published to handle the SSES problems.Thus,we first systematically review the scientific literature related to SSES methods by using the academic database of Scopus.Following a methodological review process,a total of 151 journal articles published between 2009 and 2019 were identified.The main purpose of this study is to address the following research questions:(a)What SSES methods have been proposed in the literature;(b)What are the criteria considered for SSES problems;(c)What are the weighting methods used for deriving criteria weights;and(d)What are the uncertainty methods adopted for managing experts' evaluation information.Moreover,the statistical analyses on year,journal,country,and application area have been analyzed in order to provide a roadmap to researchers studied in this field.(2)An SSES model by combining picture fuzzy distance operators and VIKOR method is developed for evaluating and selecting the most suitable sustainable supplier.In this model,picture fuzzy sets are utilized to evaluate the alternative suppliers based on selection criteria.Further,a picture fuzzy-ordered weighted distance(PFOWD)-VIKOR technique is adopted to rank the alternative suppliers.Finally,a practical case in the beef supply chain is given to explain this model,and the results are compared with relevant representative approaches to verify its feasibility and superiority.(3)An SSES model by using interval-valued intuitionistic uncertain linguistic sets(IVIULSs)and grey relational analysis(GRA)-technique for order preference by similarity to ideal solution(TOPSIS)method is proposed for the evaluation and selection of green suppliers.Vrious qualitative assessments of alternatives provided by decision makers are described by the IVIULSs.Then,the GRA-TOPSIS method is extended and employed to prioritize the alternative suppliers.Finally,an illustrative example in the agri-food industry is presented to verify the proposed SSES model and demonstrate its practicality and effectiveness.(4)An SSES model is designed to deal with SSES problem within the large group setting.More concretely,IVIULSs are applied for assessing the performance of green suppliers concerning each criterion.Ant colony algorithm is utilized to cluster decision makers into several subgroups.The linear programming technique for multidimensional analysis of preference(LINMAP)is adopted for the determination of the weights of criteria objectively.Finally,an extended multi-objective optimization by a ratio analysis plus full multiplicative form(MULTIMOORA)approach is utilized to generate the ranking of alternative suppliers.The practicality and usefulness of the developed large group SSES framework is illustrated using an empirical example of a real estate company.