Sustainable Supplier Selection Research Articles

A Two-Stage Sustainable Supplier Selection Model Considering Disruption Risk

The global spread of the pandemic has changed many aspects of life and placed the supply chain at risk of disruption. To solve the problem of supplier selection under the risk of supply chain disruption, in this paper, we propose a two-stage evaluation model to address the issue of supplier selection in the context where a pandemic requires a lockdown. First, we incorporate the lead time into the epidemic model that predicts the evolution of the pandemic to identify suppliers that have a high risk of disruption caused by the pandemic’s evolution. Second, we propose a best–worst method combined with regret theory to rank candidate suppliers. Our model provides a dynamic link between the pandemic’s evolution and supplier selection, and it allows selecting suppliers according to various criteria while avoiding supply chain disruptions due to inappropriate supplier selection. We validate the proposed model on a real case study with epidemic data from China. This paper is the first to consider the impact of lockdowns during the pandemic on supplier selection. We develop a novel MCDM model BWM-RT for supplier selection; our model can be an effective decision support approach to help decision makers better cope with the risk of supply chain disruptions.

Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) Method: A Comprehensive Bibliometric Analysis

This paper explores the evolution, applications, and prospective developments of a very popular multi-criteria decision-making (MCDM) method called Measurement of Alternatives and Ranking according to COmpromise Solution Method (MARCOS). Employing an extensive bibliometric analysis, the study examines 115 pertinent articles sourced from the Scopus database spanning over the years from 2020 to 2024. This study also provides an evaluation of the methodological significance and outlines potential future directions of MARCOS method. The outcomes indicate "Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS)" by Stević et al. (2020) as the most cited paper. Journals such as "Sustainability (Switzerland)", "Mathematics" and "Expert Systems with Applications" stand out among the most cited journals. "University of East Sarajevo" is an institution distinguished for its prolific research in this field. "Stević Ž." Has been identified as the most cited and published author. The most frequently used keywords are "MARCOS", "MARCOS method", and "MCDM". CRiteria Importance Through Intercriteria. Correlation (CRITIC) method is a weighting model often integrated with MARCOS method. The results of the study provide researchers and practitioners in the field of MCDM with an important insight into the current state of the MARCOS methodology, highlighted studies and potential future developments. It also provides a comprehensive overview of the importance of this method in the multi-criteria decision-making literature, shedding light on future research directions.

Study on the Method of Selecting Sustainable Food Suppliers Considering Interactive Factors

The existing sustainable supplier selection methods are not sufficient to deal with the problem of sustainable food supplier selection with the interaction of criteria under uncertainty. Therefore, this paper proposes a method of sustainable food supplier selection based on an extended decision model. Firstly, a processing method for supplier evaluation information is constructed using the Pythagorean fuzzy set has the function of processing complex uncertain information. Secondly, to obtain the objective weights of decision experts, a Pythagorean fuzzy weighted distance measure model is constructed, and an expert information fusion method based on a weighted power mean operator is proposed to construct the group decision matrix. Then, the decision experiment and evaluation experiment methods are integrated with the traditional MARCOS method, to construct a sustainable food supplier selection method considering the interaction of factors. This method can effectively deal with the complicated and uncertain problem of sustainable food supplier selection with interactive factors. Finally, the feasibility of the proposed method is verified by an example of sustainable food supplier selection. In addition, parameter sensitivity analysis and multi-method comparative analysis verified the rationality of the proposed selection method for sustainable food supplier selection.

Decision Support System for Single-Valued Neutrosophic Aczel–Alsina Aggregation Operators Based on Known Weights

Multiattribute decision making (MADM) approach is a well-known decision-making process utilized in a variety of fields such as solid waste management, renewable energy resources, air quality assurance, hotel location decision, sustainable supplier selection, partner recognition, green supplier enterprises, game theory, construction development authority, and weapon group target estimation. The aggregation operators (AOs) are essential components of the decision-making process and have a great capability to deal with ambiguous and unpredictable information in the different fields of fuzzy environments. In this article, we expressed the theory concepts of single-valued neutrosophic (SVN) sets (SVNS) and also characterized their basic operations. The power aggregation tools are allowed to input arguments to support each other among different arguments. Recently, Aczel–Alisna aggregation tools conquered great attention from several research scholars. We also exposed some reliable operations of Aczel–Alsina aggregation models under the consideration of SVN information. We established a series of new approaches, including the “single-valued neutrosophic Aczel–Alsina power weighted average” (SVNAAPWA) operator and “single-valued neutrosophic Aczel–Alsina power weighted geometric” (SVNAAPWG) operators. To show the effectiveness and compatibility of derived approaches, some prominent characteristics are also established. We constructed a MADM technique to solve an application of engineering and construction materials under consideration of our derived methodologies. An experimental case study is also presented to determine a suitable optimal option from a group of options. To find the flexibility of our proposed work, we provided a comparative study that compares the results of existing AOs with our proposed work. A comprehensive overview is also presented here.

Network reliability evaluation of a supply chain under supplier sustainability

The United Nations’ sustainable development goals have brought attention to the pressing issue of enhancing supply chain sustainability and ensuring equitable order allocation. In contrast to the previous research, this study involves sustainability in network reliability evaluation. A new algorithm is proposed for computing network reliability, the probability that the current supply chain not only meets demand, budget, and suppliers’ production capacity but also considers the level of supplier sustainability. In the constructed multistate supply chain network (MSCN), a node represents a supplier, warehouse, assembler, or market, and a route connecting the nodes represents a carrier. The capacity of each carrier, represented by the available delivery containers, should not be deterministic as they may be partially reserved by other markets. Grounded in the Method Based on the Removal Effects of Criteria (MEREC) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the supplier sustainability can be assessed, facilitating the selection of sustainable suppliers and the determination of feasible order allocations, which are essential for various industries. An audio production cooperation is used as a case study to demonstrate the utility of the proposed algorithm.

Spherical fuzzy symmetric point criterion-based approach using Aczel–Alsina prioritization: application to sustainable supplier selection

Spherical fuzzy symmetric point criterion-based approach using Aczel–Alsina prioritization: application to sustainable supplier selection

Lean, Agile, Resilient, Green, and Sustainable (LARGS) Supplier Selection Using Multi-Criteria Structural Equation Modeling under Fuzzy Environments

This study aims to propose an integrated approach for supplier selection based on the lean, agile, resilience, green, and sustainable (LARGS) paradigm. This approach was validated using structural equation modelling (SEM) and the intuitionistic fuzzy TOPSIS method. A comprehensive literature review was conducted, identifying twenty-six criteria, which were then consolidated into five main criteria. A questionnaire was distributed to 237 individuals from manufacturing companies listed on the Tehran Stock Exchange, and the collected data were analyzed using third-order factor analysis and the partial least squares method. Subsequently, the proposed integrated approach was applied to evaluate four suppliers in an intuitionistic fuzzy environment, utilizing expert opinions and a case study on the automotive industry. The results demonstrate the effectiveness and practicality of the proposed approach in terms of prioritizing and selecting suitable suppliers according to LARGS criteria. In conclusion, this study contributes to the existing literature by proposing an integrated approach that addresses the decision-making challenges in supplier selection. This approach offers a practical tool for managers seeking to enhance sustainable supply chain performance from the LARGS perspective.

Vendor Selection Criteria and Construction Project Performance in Rivers Nigeria.

The study focused on Vendor Selection Criteria and Construction Project Performance in Rivers Nigeria. It adopted a survey approach; utilized structured questionnaire to collect data from 71 on-site construction project managers and engineers; data obtained were ranked according to their priority using Relative Importance Index (RII), and Chi-Square Analysis. Linear regression coefficients were drawn as estimates of construction project performance. The results showed that 22 criteria, grouped into four supplier selection dimensions: capability, quality, costs and sustainability. These indicators showed significant interaction with construction project performance. However, supplier flexibility did not yield significant outcome on construction project performance. The results suggest that supplier capability, supplier quality, supplier costs, and supplier sustainability selection variables are important sources of enhanced performance for construction project management. Keywords: Construction management; Vendor selection; Project performance; Relative importance index; Sustainable supplier selection.

Changes in Sustainable Development in Manufacturing in Cases of Unexpected Occurrences—A Systematic Review

Nowadays, managers are facing the challenge of operating in situations of high uncertainty: delayed deliveries, lack of energy or rising energy and gas costs, the need to replace energy sources, and changing supply and sales markets. In the literature, two dominant trends in the activities of enterprises in the face of crises can be distinguished: (I) changes in supply chain management (increased flexibility by searching for local suppliers); and (II) transition to digital production and investment in technologies in the concept of Industry 4.0 or even Industry 5.0, such as artificial intelligence, 3D printing, robots, cyber-physical systems, digital manufacturing, and blockchain. A gap in the research has been observed in examining the impacts of these actions on the implementation of sustainable solutions and designating organizational changes in manufacturing. The main goal of this study is to review the literature using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) for data collection and, secondly, the methodology of Systematic Literature Review (SLR) and Mapping in Literature Reviews (MLR). Our literature review of the selected databases is based on 566 published articles in 2020–2022. The achieved results indicate the main organizational changes in the context of sustainable development in manufacturing, namely in the business management area (adopting Sustainable Project Management (SPM), Sustainable Supply Chain Management practices, Sustainable Supplier Selection (SSS), and Resilient Manufacturing Strategy (RMS)) and in the production area (adopting Internet of Things (IoT)-enabled Additive Manufacturing assists, simulation software, and Life Cycle Assessment. The findings of our study revealed key relationships between the adoption of fifth-generation industrial technologies and the sustainable development of manufacturing.

An interactive possibilistic programming approach for sustainable supplier selection and inventory management problem in the physical internet

PurposeThis paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.Design/methodology/approachTo address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.FindingsVarious numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.Originality/valueDue to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

A [formula omitted]-Number Slacks-Based Measure DEA model-based framework for sustainable supplier selection with imprecise information

The focus of this study is to develop a decision-making framework for selecting sustainable suppliers with imprecise information. Sustainable supplier selection poses a significant challenge for managers and decision-makers seeking a long-term competitive edge. Due to the presence of unreliable, or partially reliable imprecise information in practice, incorporation of the reliability degree of imprecise information in the decision models becomes necessary. Since Z-numbers can incorporate the reliability degree of imprecise information, the Z-number-based “Data Envelopment Analysis (DEA)” approach can be used for decision-making. The current study introduces a super-efficiency DEA approach, namely “Z-number Slacks-Based Measure (ZN-SBM)”, which is further used to construct a framework for selecting sustainable suppliers. Unlike the existing Z-number-based DEA approaches, the proposed ZN-SBM model can assume “constant returns-to-scale”, “variable returns-to-scale”, “non-increasing returns-to-scale”, and “non-decreasing returns-to-scale” conditions. Moreover, the developed framework is free from strategic weight manipulation. To demonstrate the efficacy of this framework in sustainable supplier selection, we present a case study of the automotive industry. Further, the robustness of the proposed framework is investigated through a sensitivity analysis. The results of this study reveal that the proposed framework can be effectively applied as a high-performing decision-support tool for decision-making under imprecision in the domain of sustainable supplier selection.

An integrated decision-making process for sustainable supplier selection and order allocation in the automotive industry

A sustainable supplier selection problem can be concisely defined as a classical supplier selection problem that incorporates environmental and social criteria to select and monitor suppliers’ performances, creating the sustainable supplier selection and order allocation (SSS&OA) problem. Finding the optimal order allocation to suppliers in the automotive industry is crucial as it can significantly improve the social, environmental, and economic performance of the whole supply chain. Therefore, this research aims to find an optimal order allocation plan for suppliers using an augmented ε-constraint optimization method in the automotive industry while considering all three dimensions of sustainability. Using a previously established comprehensive framework, this paper has adapted the solution approach of an existing bi-objective order allocation model that was used to make sourcing decisions. The results showed a higher total value of sustainable purchasing is achieved by the augmented ε-constraint optimization method compared to the traditional max-min method.

Quality Function Deployment: A Bibliometric-Based Overview

Quality function deployment (QFD), an important technique in quality management, has been studied extensively and has already been tested in various areas of real-world applications. In this article, we provide a bibliometric analysis on the development of QFD between 1983 and 2019 on the basis of 1856 literature works retrieved from the Web of Science Core Collection database. The results indicate that QFD is considered to have come into its flourishing stage over the past decade, and more than 3000 scholars from 1400 institutions and 82 countries/regions have made important contributions to its development. In addition, we elaborate the research contents and the evolutionary process of eight research branches of QFD, with full-scale details, combining the traditional survey and the bibliometric method. Finally, in order to envisage its future development, this article initially proposes the research potential evaluation model, which is used to assess research potential through two indicators: “recent attention (RA)” and “maturity.” Through applying this model to QFD, the findings show that integrating environmental issues into QFD has been an increasing trend in this area, stimulating the growth of a series of promising research domains, such as environmental product development and sustainable supplier selection, among others. In the end, some general trends of this area are recommended to open insights for further research.

Greening the pillars of pharmaceuticals: Sustainable supplier selection in emerging economies

The pharmaceutical industry is vital for global health, supplying necessary medicines, yet its conventional supply chain has notable environmental and social impacts. Amid a growing sustainability focus across sectors, the pharmaceutical industry must also adopt sustainable practices throughout its supply chain. This includes lessening its ecological impact, curbing waste, and endorsing social responsibility. Assessing a supplier's environmental performance, or "green performance," is of great interest. This involves gauging their eco-friendly actions like energy efficiency, waste management, and carbon footprint reduction. Metrics cover certifications, resource conservation, and responsible sourcing. In a study within a renowned Bangladeshi pharmaceutical firm, a key drugs manufacturer, seven criteria were used to evaluate suppliers' green performance. For this multi-criteria decision-making (MCDM) task, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied, considering a fuzzy environment. It ranked alternative suppliers via a widely used approach using linguistic terms expressed as Triangular Fuzzy Numbers (TFN). Important weights were determined via the Center of Area (COA) method. The study revealed supplier 4 as the top performer in green performance among five alternatives. This study introduces an innovative strategy for manufacturing decision-makers to choose the most suitable green supplier. It's anticipated to aid decision-makers in emerging economy pharmaceutical industries, facilitating the efficient evaluation of economically viable and environmentally sustainable suppliers for the long term.

Sustainable Supplier Selection in the Manufacturing Sector Using Integrated MCDM Techniques

Sustainable Supplier Selection in the Manufacturing Sector Using Integrated MCDM Techniques

A Literature survey on application of MCDM approaches for the sustainable supplier selection in manufacturing industries

A Literature survey on application of MCDM approaches for the sustainable supplier selection in manufacturing industries

Three-dimensional dynamic trust-driven consensus model for social network group decision-making with application to sustainable supplier selection in a circular economy

The trust degree between individuals plays an important role in social network group decision-making (SNGDM). The majority of current literature assumes that the trust degree between individuals is constant. However, the trust values among decision-makers (DMs) are subject to change over time. Thus, it is necessary to identify potential dynamic trust that is compatible with the actual SNGDM to support the consensus reaching. For this purpose, this article investigates consensus building that considers dynamic trust among DMs in SNGDM with linguistic distribution assessments (LDAs). Firstly, the three-dimensional trust degree among DMs is constructed from three perspectives: the trust relationship from social networks, the confidence level of DMs, and the similarity of DMs' preferences. Secondly, an optimization model is developed with the objective of maximizing consensus to determine how trust degree is assigned to each perspective, thereby determining the weights of DMs. Then, a double feedback-based consensus mechanism incorporating both opinion evolution and trust evolution is developed. Under the guidance of consensus mechanism, an improved SNGDM approach with LDAs is presented. Finally, we demonstrate our proposed approach through a case study of sustainable supplier selection in a circular economy. Comparative analysis and sensitive analysis verify our approach’s effectiveness.

ANALYSIS OF BOLT SUPPLIER SELECTION USING AHP-TOPSIS AND FUZZY-AHP METHOD COMPARISON (PT STECHOQ ROBOTIKA INDONESIA)

Nowadays, problems in the industry are increasingly dynamic, including the problem of sustainable supplier selection. Suppliers will significantly affect the stability of the supply chain, especially issues of accuracy, quality, and delivery time. PT Stechoq Robotika Indonesia is an R&D and manufacturing company that produces appropriate technology with bolt components supplied by seven suppliers. Cases of late deliveries that reach four working days have disrupted the smooth running of production, so it is necessary to review current suppliers with objective methods. This study evaluates bolt suppliers by comparing AHP-TOPSIS and FAHP methods according to specified criteria (price, quality, delivery time, accuracy, service). Both ways produce the same highest-value bolt supplier, Supplier #7, and there is a slight difference for the second and third-order suppliers, namely Supplier #1 or Supplier #3. The study results are used as recommendations in determining the main suppliers, supporting suppliers, and replacement or re-evaluation for the three suppliers with the lowest rank (Supplier #6, Supplier #5, and Supplier #4).

Sustainable Supplier Selection through Multi-Criteria Decision Making (MCDM) Approach: A Bibliometric Analysis

Background: The primary objective of this study was to examine the advancements in sustainable supplier selection through multi-criteria decision making (MCDM) from the years 2013 to 2022. In the recent past, researchers have carried out a significant amount of research in this field over the course of several years; Methods: a total of 121 scientific publications sourced from the Scopus database were chosen for analysis, employing the bibliometric method and graphical visualization of the VOS viewer application to visually analyze and map research networks and collaboration patterns, aiding in the evaluation of scientific impact and knowledge dissemination; Results: the findings of this study indicate that the research trend in sustainable supplier selection through MCDM witnessed its most significant growth in the year 2019. Researchers predominantly disseminated their scientific findings through articles, accounting for 81% of the publications, followed by conference papers at 14%, and book chapters at 2.5%; Conclusions: the primary area of focus in these studies pertains to decision-making processes involved in sustainable supplier selection. The implications and theoretical contributions derived from this research, coupled with the latest advancements, serve as a foundation for further exploration and development of sustainable supplier selection research through MCDM.

Obviating some of the theoretical barriers of analytical hierarchy process by a revised eigenvector method: a case study in sustainable supplier selection

Obviating some of the theoretical barriers of analytical hierarchy process by a revised eigenvector method: a case study in sustainable supplier selection