scholarly journals INTEGRATING SUSTAINABILITY INTO SUPPLIER SELECTION: A GREY-BASED TOPSIS ANALYSIS

2018 ◽  
Vol 24 (6) ◽  
pp. 2202-2224 ◽  
Author(s):  
Chunguang Bai ◽  
Joseph Sarkis

Sustainable supplier selection plays an important role in sustainable supply chain management operations and implementation. In this paper a novel formal modeling approach is conceptually developed and presented to address sustainable supplier selection. Grey theory and TOPSIS, a distance based multiple criteria method, are used for the integration and evaluation of sustainable supplier performance for sustainable supplier selection. From a research perspective, TOPSIS is improved to more effectively deal with grey numbers by integrating a degree of likelihood rather than converting grey numbers into crisp numbers functions, and it provides more flexible supplier rankings. This methodology strengthens the sustainable supplier selection process, and can be applied to other multiple criteria decision making problems. Illustrative calculations are made using data on sustainable supplier selection and evaluation published by Bai and Sarkis (2010). The technique is relatively accurate, matching well with results from a published grey rough set approach. The methodology easily implementable with minimal complex calculations required. It can also provide support for sustainable supplier selection, benchmarking, and improvement decisions. This is one of the first papers to integrate a broad set of sustainability factors for grey-based TOPSIS and supplier selection.

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Chung-Min Wu ◽  
Ching-Lin Hsieh ◽  
Kuei-Lun Chang

The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM) model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP) is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS) is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.


Author(s):  
Reza Farzipoor Saen

Supplier selection is a multiple criteria decision making problem that the selection process mainly involves evaluating a number of suppliers according to a set of common criteria for selecting suppliers to meet business needs. Suppliers usually offer volume discounts to encourage the buyers to order more. To select suppliers in the presence of both volume discounts and imprecise data, this chapter proposes an optimization method. A numerical example demonstrates the application of the proposed method.


2021 ◽  
pp. 63-70
Author(s):  
Nejah Ben Mabrouk

The objective of this paper is to examine the determinants of the supplier selection process with green consideration. Thus, this analysis gathers a collection of factors from established literature of green supplier selection (GSS), including seven categories and 58 attributes. The objective of this research is to classify the key factors which are presented as qualitative information. Fuzzy logic rules are used to transform qualitative expert knowledge into numerical data. Then, we adopt the Delphi method (DM) to filter and rate unneeded factors according to their relevance. The results indicate 24 important factors for the GSS process. Five categories are included: Performance and technology ability, Environmental management, Pollution control, Quality and Service. The most significant factors are recognized as green research and development, eco-design, green image, green packaging and remanufacturing. Finally, the debate is held on the basis of the findings and future research are also recognized and stated.


Author(s):  
Rubén Medina Serrano ◽  
Wanja Wellbrock ◽  
María Reyes González Ramirez ◽  
José Luis Gascó

The supplier selection process has become an important area of research and professional activity, and it is fundamental to understand the types and trends of research in this field. The appropriate supplier selection decision is a fundamental strategic process and plays an important role in supply chain management. In the last decade, academic research on sustainability has evolved rapidly in the supply chain literature. However, there has been scant opportunity for the research community to complete a global assessment of sustainable supplier selection activities to date. This paper seeks to address this need by exploring sustainability in supply chain management, developing a sustainable supplier selection framework with a tool for its operationalization to help managers evaluate supplier selection decisions. Our proposed model is based on the TOPSIS concept as a multiple criteria decision-making (MCDM) model and is validated through a case study. This research work follows the best-in-class approach to comply with all applicable environmental regulations and laws in the supplier selection process.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Ehtesham Rasi ◽  
Mehdi Sohanian

Purpose The purpose of this paper is to design and optimize economic and environmental dimensions in a sustainable supply chain (SSC) network. This paper developed a mixed-integer linear programing (MILP) model to incorporate economical and environmental data for multi-objective optimization of the SSC network. Design/methodology/approach The overall objective of the present study is to use high-quality raw materials, at the same time the lowest amount of pollution emission and the highest profitability is achieved. The model in the problem is solved using two algorithms, namely, multi-objective genetic and multi-objective particle swarm. In this research, to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system. Findings The differences found between the genetic algorithms (GAs) and the MILP approaches can be explained by handling the constraints and their various logics. The solutions are contrasted with the original crisp model based on either MILP or GA, offering more robustness to the proposed approach. Practical implications The model is applied to Mega Motor company to optimize the sustainability performance of the supply chain i.e. economic (cost), social (time) and environmental (pollution of raw material). The research method has two approaches, namely, applied and mathematical modeling. Originality/value There is limited research designing and optimizing the SSC network. This study is among the first to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system.


2019 ◽  
Vol 11 (03) ◽  
pp. 1950029
Author(s):  
Ashoke Kumar Bera ◽  
Dipak Kumar Jana ◽  
Debamalya Banerjee ◽  
Titas Nandy

In today’s highly turbulent and competitive environment, the success of the organization depends on the performance of its suppliers. However, supplier selection problems are complex as they involve a large number of criteria and, frequently, some of the criteria cannot be evaluated precisely. Moreover, fluctuations of supplier performances and unknown information always exist in real-world decision-making. It is a complex multiple-criteria decision-making (MCDM) problem as it involves a trade-off among various criteria with vagueness and imprecision and also involves a group of experts with diverse opinion. Therefore, to make more practical decisions, this paper is intended to propose an integrated technique for order preference by similarity to ideal solution (TOPSIS) in fuzzy environment with multi-choice goal programming (MCGP) to handle the supplier assessment and order allocation for a battery manufacturing organization. Using linguistic variables, the decision-makers assess the rating of suppliers as well as the importance of various factors. Linguistic variables are expressed in trapezoidal fuzzy numbers (TrFN). Fuzzy-TOPSIS method is proposed to obtain the rank of suppliers and MCGP method is used to allocate suitable orders to the selected suppliers. A case study is implemented to find the applicability and validity of the proposed model. Finally, sensitivity analysis is performed to observe the effect of weights of criteria on supplier evaluation problem.


Author(s):  
Congjun Rao ◽  
Mark Goh ◽  
Junjun Zheng

Against the backdrop of responsible economic development, sustainable supply chain management (SSCM) is key to achieving the sustainable development for enterprise and industry. In this regard, sustainable supplier selection is crucial in SSCM. By integrating the three dimensions of sustainability, economic, environmental and social, this paper presents a new evaluation system for supplier selection from a sustainability perspective. Specifically, we design a decision mechanism for sustainable supplier selection based on linguistic 2-tuple grey correlation degree. In this proposed mechanism, the hybrid attribute values whereby real numbers, interval numbers and linguistic fuzzy variables coexist are transformed into linguistic 2-tuples. A ranking method based on linguistic 2-tuple grey correlation degree is then presented to rank the suppliers. An application example is presented to highlight the implementation, availability and feasibility of the proposed decision making mechanism.


Author(s):  
Sarfaraz Hashemkhani Zolfani ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani

Purpose – sustainability in industrial organizations is becoming one of the predominant concepts in the context of modern industrialization due to global warming, economic significance, and social awareness. These have prompted a huge concern toward sustainable supply chain management (SSCM) to be adopted and promoted as an innovative business model. Supplier evaluation and selection play a significant role in SSCM for taking appropriate procurement decisions. Research methodology – a hybrid MADM model based on Best Worst Method (BWM) and Combined Comprise Solution (CoCoSo) method. Findings – a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach. The results show the potentiality of the proposed model in resolving complex sustainability issues in the SCM environment. Research limitations – other weighting techniques like the analytic network process (ANP) and decision making trial and evaluation laboratory (DEMATEL) approaches can also be combined and performances can be compared. Practical implications – the proposed model can be used by the organizations to select the most appropriate suppliers who contribute to the movement of the SC towards sustainability. Originality/Value – a multi-criteria evaluation model has been proposed for solving a sustainable supplier selection problem while considering economic, environmental and social criteria simultaneously by integrating BWM-COCOSO methods


2019 ◽  
Vol 11 (10) ◽  
pp. 2820 ◽  
Author(s):  
Xiaodong Wang ◽  
Jianfeng Cai ◽  
Jichang Xiao

Sustainable supplier selection has become a strategic activity to enhance the competitiveness of sustainable supply chain management. Research on sustainable supplier selection is considering increasingly more practical factors, such as the uncertainty of decision context and the fuzzy recognition of experts. Evaluation values on different criteria with different characteristic should be represented in their suitable information types to reflect the characteristic accurately and represent experts’ judgments entirely. Moreover, it is difficult, or costly, to build a decision criteria set in which all criteria are independent to each other because of the interaction of technical, economic, environmental and social factors. Therefore, the aim of this paper is to propose a novel decision-making framework for sustainable supplier selection which considers the interaction among criteria with heterogeneous decision information. The proposed framework can not only allow the experts to express their judgments completely, but also improve the efficiency of decision-making. First, a normalized dominance decision matrix based on normalized closeness is built with the heterogeneous decision matrix. Then, a defined discrete Choquet integral multi-criteria distance measure is used to compute the comprehensive associated closeness and rank the alternative sustainable suppliers. This framework provides a new way to handle the interaction among criteria for sustainable supplier selection from the perspective of multi-criteria distance measure, and a novel methodology to solve the problems that the evaluation values cannot be aggregated directly. Finally, an example is given to illustrate the proposed framework for sustainable supplier selection with a comparison analysis.


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