Sustainable Supplier Evaluation Research Articles

Group decision making model for selection of performance indicators for sustainable supplier evaluation in agro-food supply chain

Sustainable food production is of vital importance to ensure food security, enhanced stability, environmental protection, and economic development for any developing nation. In an Agro- Food Supply Chain (AFSC), joint efforts of all supply chain actors inclined towards sustainability can contribute significantly towards sustainable production. Suppliers, who are intermediaries between Food Processing Firm (FPF) and sub-suppliers or farmers, must follow the FPF's sustainability practices at their own level, and they must monitor the enactment of these activities at their sub-supplier level. In this regard, the study focuses on developing a group consensus mathematical model to derive a broader set of performance indicators to evaluate a supplier's competency in maintaining, monitoring, and tracing sustainable performance in his sub-supplier network. A two-phased group consensus model is presented; it selects performance indicators using the Delphi method and it utilizes a feedback mechanism rooted in Group Analytical Hierarchy Process. This system is based on an iterative algorithm to generate weights that all decision makers accept. The proposed model is illustrated with an analysis of an Indian flour milling company. Kendall's concordance coefficient is employed to understand the degree of agreement among decision makers before and after the application of the proposed model. Increase in its value post-application validates the efficacy of the model. This approach for performance indicator selection for sustainable supplier evaluation research is unique in the field of AFSC. Results of the study indicate that the top ranking indicator is ‘Food Safety’ followed by ‘Payment to Sub-suppliers’. Key policy implications are drawn from the result findings which can be further integrated to support sustainable growth and development of suppliers and sub-suppliers in any AFSC.

Research on Sustainable Supplier Evaluation Index System in Architectural Design Industry

Sustainable development has been popularized and emphasized in many industries. Great attention has been paid to the sustainability performance of the whole supply chain, with evaluating suppliers’ sustainability being particularly critical. However, research on sustainable development in the consulting service industry remains to be discovered, and few academic studies have analyzed the supplier selection indices derived from this industry. This paper conducted a case study in a design institute using the Delphi method to investigate the concept and characteristics of sustainable suppliers. Keywords derived from surveys and literature were collected, sorted, and established into a comprehensive hierarchy index system for sustainability evaluation. Finally, based on the improved failure mode and effects analysis (FMEA) and analytic hierarchy process (AHP), the failure risk of the indices was analyzed with weighted risk factors to obtain the high-risk key evaluation indices, which provided a simplified scheme for enterprises to streamline the evaluation process on sustainable suppliers. The results show the reliability of the improved FMEA model by differentiating the risk value and ranking. Suggestions for sustainable improvement are provided.

Sustainable Supplier Evaluation: From Current Criteria to Reconstruction Based on ESG Requirements

The disclosure of ESG tasks, seen as companies’ performance of sustainability, has gradually became a necessity for listed enterprises. From an ESG perspective, this paper revisits and restructures the sustainable supplier evaluation criteria. Leveraging thematic analysis, this study dissected ESG reporting guidelines across stock exchanges and explored ESG annual reports and supplier codes of conduct from the listed firms. This elucidated the evaluation criteria currently in practice. The findings indicate that existing sustainable supplier evaluations cannot fully meet ESG regulatory requirements. Drawing insights from these gaps, we reconstructed the evaluation criteria through text analysis to better align with ESG mandates. This study introduces the concept of a “Relative Word Frequency Ratio” to analyze the importance of each indicator and to further determine which to retain or delete. This research offers a robust theoretical foundation and practical guidance for enhancing supplier sustainability evaluations, and the proposed sustainable supplier evaluation criteria system could provide a decision-making reference for enterprises in the choice of ESG-qualified suppliers.

Sustainable supplier selection with multidimensional overlapping criteria under carbon neutrality

PurposeSustainable supplier selection is of vital importance in sustainability decision of supply chain under carbon neutrality. Multi-criteria decision-making approaches are widely used in sustainable supplier selection and generally classified the involved criteria into three sustainable development (SD) dimensions: Environmental, Social and Economic. During the assignment of appropriate weighted scores to the criteria, most of the methods considered mutually exclusive criteria. However, some criteria cover multidimensions since ambiguity vagueness makes them difficult to classify into one dimension exclusively. The purpose of this paper is to find proper approaches addressed to multidimensional overlapping criteria in the evaluation of suppliers’ sustainability performance.Design/methodology/approachThis study proposes three approaches to resolve the multidimensional overlapping criteria issue by data envelopment analysis (DEA) methods. The first approach uses all dimensional criteria and “dimensional overlapping criteria” in a single DEA model. The second approach consists of two-stage DEA. The first stage is to find SD dimensional performances, which are used in the second stage. The third approach uses an aggregate weight-constrained DEA model with additional constraints. Such approaches are applied to an empirical case study with six dimensions.FindingsResults indicate that the third approach is better than the first two approaches in balancing the development among all dimensions instead of focusing on the superiority dimension to obtain high performance.Originality/valueDiscussing overlapping criteria in the context of sustainable supplier evaluation and other multi-criteria evaluation have a noticeable impact on evaluation systems, but appropriate approaches for this issue are currently under-researched.

Sustainable Supplier Selection and Order Allocation Using an Integrated ROG-Based Type-2 Fuzzy Decision-Making Approach

The sustainable Supplier Evaluation and Selection and Order Allocation (SSOA) problem has received significant attention in supply chain management due to its potential to enhance a company’s performance, improve customer satisfaction, and reduce costs. In this study, an integrated methodology is proposed to address the SSOA problem. The methodology combines multiple techniques to handle the uncertainties associated with supplier evaluation, including a new ranking method based on the concept of Radius of Gyration (ROG) for interval type-2 fuzzy sets. The methodology also incorporates both subjective weights obtained using the Simple Multi-Attribute Rating Technique (SMART) and expert preferences, and objective weights calculated using the Method based on the Removal Effects of Criteria (MEREC) method to determine the weights of evaluation criteria. Some criteria for sustainable development are used to evaluate supplier performance, resulting in type-2 fuzzy sets, which are evaluated using the Weighted Aggregated Sum Product Assessment (WASPAS) method. The ROG-based ranking method is employed to calculate the relative scores of suppliers. Finally, a multi-objective decision-making (MODM) mathematical model is presented to identify suitable suppliers and allocate their order quantities. The methodology is demonstrated in a sustainable SSOA problem and is shown to be efficient and effective, as the ROG-based ranking method allows for more accurate supplier performance evaluation, and the use of the criteria highlights the importance of sustainability in supplier selection and order allocation. The methodology’s practicality is further supported by the analysis conducted in this study, which demonstrates the methodology’s ability to handle the uncertainties associated with supplier evaluation and selection. The proposed methodology offers a comprehensive approach to the SSOA problem that can effectively handle the uncertainties in supplier evaluation and selection and promote sustainable practices in supply chain management.

A data-driven decision support system for sustainable supplier evaluation in the Industry 5.0 era: A case study for medical equipment manufacturing

Effective supplier management is critical for an enterprise’s success, as supplier procurement accounts for up to approximately 70% to 80% of total manufacturing costs. Correct supplier selection can ensure the competitiveness of the enterprise and contribute to supply chain integration and innovation. In recent years, supplier evaluation frameworks based on Industry 4.0 concepts have contributed to the development of the industry. However, the novel concepts of Industry 5.0 require examination from a people-oriented and sustainable perspective. Unfortunately, at the present time, supplier evaluation frameworks based on Industry 5.0 are lacking. Therefore, the primary task of this study is to develop a novel and comprehensive supplier evaluation framework for the Industry 5.0 era. This study proposes a data-driven decision support system to execute the supplier evaluation process. First, variable precision- dominance-based rough set approach (VC-DRSA) is applied to extract the core criteria, to remove the noise factors and to generate decision rules for the decision-makers’ reference. Second, the criterion importance through intercriteria correlation (CRITIC) approach is adopted to obtain the dependency weights of the core criteria and their ranking. Finally, a modified classifiable technique for order preference by similarity to ideal solution (CTOPSIS) is used to integrate the final performance values of suppliers when new alternative suppliers are added. The research concept is in line with the conception of data-driven decision support in business intelligence and does not rely on the subjective judgments and opinions of experts. Data provided by a multinational medical equipment manufacturer are used as an example to demonstrate the proposed model. VC-DRSA retains nine core criteria from the original twenty criteria, which greatly reduces the labor and cost of supplier audits. In addition, the CRITIC results show that digital transformation, real-time information sharing, and organizational culture transformation are the three main factors affecting the development of enterprises towards Industry 5.0. The results show that CTOPSIS can be used to quickly assess the ratings of new alternative suppliers are listed.

How Do the Criteria Affect Sustainable Supplier Evaluation? - A Case Study Using Multi-Criteria Decision Analysis Methods in a Fuzzy Environment

Choosing a battery supplier is a vital decision-making problem, for which it is essential to obtain stable evaluations. For such sustainable supplier evaluation, multi-criteria decision analysis (MCDA) methods are often used, as their ability to handle uncertain data gives experts more significant opportunities to consider a broader range of cases. However, given the great number of MCDA approaches, it is challenging to find out which approach is the most appropriate. Therefore, this paper presents a sensitivity analysis on evaluating battery suppliers by ARAS, EDAS, MAIRCA, TOPSIS, and VIKOR methods in a fuzzy environment. The provided study presented similar results for the considered MCDA methods confirmed by the WS similarity measure of rankings and the weighted Spearman correlation . On the other hand, the sensitivity analysis conducted on the considered methods indicated that the most relevant criteria for this problem are transportation cost, delivery time, and warranty period.

Sustainable Supplier Evaluation in an Automotive Company Using Fuzzy Multi-Criteria Decision-Making Methods

Sustainable supplier management literature is mainly on sustainable supplier selection but sustainable supplier performance monitoring & evaluation studies are scarce. Furthermore, the studies do not differentiate the sustainability evaluation criteria between the supplier selection and monitoring & evaluation stages. To bridge this gap, this study aimed to monitor & evaluate sustainability performance of the suppliers of a focal manufacturing company in automotive sector with the TBL approach. Toward that end, we questioned and tried to identify first the sustainable supplier selection and monitoring & evaluation differentiating criteria, and then, how we can rank and rate the sustainable suppliers for developmental purposes in the monitoring & evaluation phase. 21 criteria were determined for sustainable supplier performance in monitoring & evaluation by a detailed literature review and taking the opinions of the focal company. Then, decision makers assessed sustainability dimensions and determined criteria related to these dimensions. The weights of dimensions and criteria were calculated by Interval-Valued Intuitionistic Fuzzy AHP method. Then, sustainability performances of selected suppliers from the focal company’s portfolio were ranked by using Fuzzy EDAS, Fuzzy CODAS and Fuzzy MOORA methods. The results show that sustainable supplier monitoring & evaluation criteria involve a mix of external criteria (rules and regulations) and internal criteria (suppliers’ values). This finding helps us understand how we can have a more relaxed criteria set involving basic external criteria while selecting suppliers to have access to a more innovative and diverse supplier space and then have more challenging internal and external criteria to monitor & evaluate those suppliers toward true sustainability.

A Novel Perspective to Sustainable Supplier Performance Evaluation Problem: A Case Study Based on Determining the Optimum Number of Clusters

In this study, it is aimed to contribute to the development of companies in order to reach the desired values utilizing the cluster features of the suppliers in a sustainable supplier evaluation process and to guide the supplier in this regard. The clustering features acquired at the end of the study will guide the determination of sustainable supplier criteria and potential new suppliers according to the sector and business line in future studies. The first step of the three-stage model is to apply the best–worst method to determine the weights of the criteria. At the second stage, suppliers are clustered together by the k-means algorithm and silhouette index method. At the third stage, suppliers are divided into categories, and suggestion policies for each supplier category are included. Then, sensitivity analysis has been performed to analyze the effects of variations of criteria weights on the result of the proposed model. Finally, to express the integrated method, a real-life sustainable supplier selection problem is solved and suppliers are categorized according to their similarities. Following evaluation, it was seen that the environmental management system and waste management criteria were the most critical criteria in the categorization of suppliers. When its reasons are investigated, sectoral characteristics come into prominence. The results indicate that the proposed model fits well as a multicriteria decision-making tool for sustainable supplier selection and evaluation decisions. Finally, it is predicted that this model will evaluate new suppliers or new products/services to be procured and selected from the set of features.

Consistent and Sustainable Supplier Evaluation and Order Allocation: Evaluation Score based Model and Multiple Objective Linear Programming Model

Consistent and Sustainable Supplier Evaluation and Order Allocation: Evaluation Score based Model and Multiple Objective Linear Programming Model

An integrated framework for sustainable supplier development through supplier evaluation based on sustainability indicators

The chemical industry has growing importance in sustainability because of the potential adverse effects on the environment. Also, stakeholders emphasize many social issues besides environmental protection for the chemical industry. Relying on a solid supplier base has become the main prerequisite for chemical manufacturers to achieve environmental targets and fulfill stakeholders' expectations while remaining competitive. This study develops the Integrated Sustainable Supplier Evaluation & Development Framework (ISSED-F) to support chemical manufacturers with managing supplier relationships according to the economic, environmental, and social facets of sustainability. Although the literature is rife with evaluation models aiming to fulfill the supplier selection tasks, these models mostly ignore the developmental role of supplier evaluation. To remedy this gap, ISSED-F adopts a deductive and holistic approach from setting the criteria to setting the measurement structure, evaluating the suppliers, and developing the suppliers. Materiality analysis, Analytic Network Process (ANP), Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), and cluster analysis are the fundamental methods that constitute the ISSED-F structure. A case study presents the use of the ISSED-F in a transnational chemical manufacturer's supplier relationship management (SRM) process. The case company evaluates 69 suppliers and assigns development strategies to the relevant performance segments within the implementation. The successful implementation of ISSED-F shows that it can be a roadmap for chemical manufacturers to adopt sustainability practices and ensure continuous development in their supply chains.

Sustainable supplier evaluation and selection in developing countries: an integrated fuzzy framework

Evaluation and selection of suppliers play a vital role in improving their sustainability performance. In this regard, evaluating the sustainability performance of suppliers is much more critical in developing countries. These countries are among the best destinations for supplying raw materials and workforce utilisation because of lower costs. In recent years, various multi-criteria decision aiding (MCDA) frameworks utilised to evaluate suppliers based on sustainable aspects. However, few studies analysed the evaluation and selection of suppliers' sustainability in an integrated fuzzy MCDA model regarding the supplier selection process and developing nations. This research presents a comprehensive, integrated fuzzy decision model for sustainable supplier evaluation and selection using an integrated FDelphi-FDEMATEL-FANP-FVIKOR by considering sustainability (social, economic and environmental). Also, this research provides a comprehensive analysis of MCDA techniques' literature in terms of the main steps of sustainable supplier selection (e.g., formulation of criteria, handling of criterion's interaction, weight calculation and final selection). The previous research rarely considered the evolution of suppliers' sustainability according to its steps in the literature. This framework assists supply chain managers and practitioners better understand the extraordinary role of these steps on businesses. This research's proposed framework is validated by a numerical example taken from Iran's automotive industry.

Sustainable Supplier Evaluation and Selection in Developing Countries; An Integrated Fuzzy Framework

Sustainable Supplier Evaluation and Selection in Developing Countries; An Integrated Fuzzy Framework

Sustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making

Supplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier’s performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier’s ranking and provide improving strategies for underperforming suppliers. The augmented max–min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.

An interval valued neutrosophic decision-making structure for sustainable supplier selection

Evolution of supply chain management (SCM) in recent years has transformed it beyond the simple logic of benefit and economic point of views. One of such key strategic elements in establishing a sustainable and socially responsive SCM is supplier selection and performance assessment. This study brings forward a sustainable supplier evaluation structure under multiple criteria and interval valued fuzzy neutrosophic (IVFN) model. The proposed structure uses CRiteria Importance Through Inter -criteriaCorrelation (CRITIC) and combined compromised solution (CoCoSo) under IVFN environment for evaluation and selection of suppliers for a dairy company in Iran. Alternative supplier 5 (S5) emerges as the best supplier with the highest overall score (1.168). Average Spearman rank correlation coefficient between the proposed model and other well established decision-making models methods is found as 0.9651 which establishes reliability of model outcomes. The estimated zero value of Gini Index indicates that supplier 5 has a constant ranking in all considered methods. This is a practical sustainable supplier selection platform which allows decision makers in procurement and SC industries to select the most suitable supplier in any pre-determined period.

An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics.

Green supply chain management considers the environmental effects of all activities related to the supply chain, from obtaining raw materials to the final delivery of finished goods. Selecting the right supplier is a critical decision in green supply chain management. We propose a fuzzy green supplier selection model for sustainable supply chains in reverse logistics. We define a novel hierarchical fuzzy best-worst method (HFBWM) to determine the importance weights of the green criteria and sub-criteria selected. The fuzzy extension of Shannon’s entropy, a more complex evaluation method, is also used to determine the criteria weights, providing a reference comparison benchmark. Several hybrid models integrating both weighting techniques with fuzzy versions of complex proportional assessment (COPRAS), multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA), and the technique for order of preference by similarity to ideal solution (TOPSIS) are designed to rank the suppliers based on their ability to recycle in reverse logistics. We aggregate these methods’ ranking results through a consensus ranking model and illustrate the capacity of relatively simple methods such as fuzzy COPRAS and fuzzy MOORA to provide robust rankings highly correlated with those delivered by more complex techniques such as fuzzy MULTIMOORA. We also find that the ranking results obtained by these hybrid models are more consistent when HFBWM determines the weights. A case study in the asphalt manufacturing industry is presented to demonstrate the proposed methods’ applicability and efficacy.

A hybrid decision-making model for sustainable supplier evaluation in electronics manufacturing

The rapid development of information technology and electronic products has had a profound impact on global business activities and the quality of human life. To maintain competitiveness among enterprises, contribute to society, and protect the environment while maintaining profits, electronics manufacturers must move toward sustainable development. This paper proposes the following four dimensions for sustainable supplier evaluation and selection (SSES): economic, social, environmental, and institutional sustainability. These dimensions can be subdivided into 20 criteria, which constitute the SSES framework of electronics manufacturing. A modified indifference threshold-based attribute ratio analysis (ITARA) technique is proposed to obtain the objective weights of the criteria and the preference ranking organization method for enrichment evaluation based on aspiration level concept (PROMETHEE-AL) method is applied to integrate the performances of sustainable suppliers and determine their rankings. The modified ITARA and PROMETHEE-AL methods are integrated as a hybrid decision-making analysis model, which improves the conventional ITARA and PROMETHEE methods and introduces the concept of aspiration level to enhance their practical applicability. In addition, through model comparisons and sensitivity analysis, the robustness of the proposed model is demonstrated and more potential management information and suggestions are obtained. The study results can help decision-makers in the industry and academic researchers to better understand how systematic supplier selection can be conducted in electronics manufacturing. This study provides a complete SSES approach to support decision-makers and practitioners in easily determining the performance of alternative suppliers. For researchers, the proposed decision-making model can be used as a research basis for SSES to facilitate the development of other more forward-looking methodologies.

Improving sustainable supplier evaluation by an integrated MCDM method under pythagorean fuzzy environment

Sustainability plays a significant role in promoting competence and collaboration in supply chain management due to increased environmental awareness, tightened regulations, and government policies. The evaluation of sustainable suppliers and selecting the best one is indispensable for companies to promote sustainability. Due to multi-criteria nature of the supplier selection process, it has been considered as a multi-criteria decision making (MCDM) problem in many studies. In this study, a state-of-the-art MCDM method for sustainable supplier selection is developed by integrating AHP and TOPSIS techniques within the Pythagorean Fuzzy Sets (PFSs) linguistic setting. A Group Decision Making (GDM) environment is utilized due to superiority of group consensus over individual decisions. Finally, an apparel industry example is used to illustrate the effectiveness and feasibility of the proposed sustainable supplier selection method. A comparison with existing techniques and sensitivity analysis are done to verify and validate the given outcome.

An Integrated Spherical Fuzzy Approach for Global Supplier Selection

Political-economic liberalisation, modern communication technologies, and low-cost transportation have prompted companies to outsource an increasing amount of commercial activities to other countries. This exporting has often resulted in complex supply chain configurations. Considering that human and ecological regulation in these countries is often insufficient or poorly enforced, stakeholders place the responsibility of ensuring socially and environmentally sustainable product specifications across their supply chains on firms with a particular emphasis. This research presents a combined fuzzy spherical AHP-WASPAS method basis for environmental global procurement planning that takes subsupplier sustainability considerations into account. From the present study, standards (containing risk considerations) were devised and then improved with the assistance of experts in the field and case decision-makers in order to avoid literature bias. Next, providers and semi were evaluated collectively using the agreed sustainability criteria. In previous studies, this methodology proved unsatisfactory. The problem is rectified in two stages, as shown below. In the first phase, fuzzy AHP is used to define parameter weights for inclusive sustainable supplier evaluation, so in the second phase, fuzzy WASPAS is employed to assess supplier performance in relation to evaluation criteria. Economic factors held the highest weight among some of the five ecological sustainability (financial, health, environment, and social), whereas worldwide risk assessments carried the least. This research suggests that global threats are not yet important selection factors for suppliers. Moreover, the proposed framework may help pave the way for the creation of managerial decision-making tools to aid firms in tackling sustainability risks that occur farther downstream in their supply chains. When major organisations are under intense scrutiny from their stakeholders, these vital tools are extremely important.

Research on Sustainable Supplier Selection Based on the Rough DEMATEL and FVIKOR Methods

In competitive global markets, sustainable suppliers are critical success factors for sustainable supply chain operations. Sustainable supplier selection must be based on a complex network of numerous indicators and experts’ fuzzy linguistic terms. Considering the correlation between the evaluation criteria and the ambiguity of the criteria values, this paper proposes combining the rough DEMATEL method and the fuzzy VIKOR (FVIKOR) method to solve sustainable supplier selection problem. We determine 15 sustainable supplier evaluation criteria from economic, environmental and social dimensions. We also apply the rough DEMATEL method to determine the weight of evaluation indicators that are interrelated or even conflicting and use the FVIKOR method to determine supplier rankings by converting the fuzzy linguistic terms into precise information. The practicability of the proposed method is verified by an example of sustainable supplier selection.