Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

Vietnam’s garment industry is facing many challenges, including domestic competition and the global market. The free trade agreement, which Vietnam signed, includes environmental barriers, sustainable development, and green development. The agreement further requires businesses to make efforts to improve not only product quality but also the production process. In cases when enterprises cause environmental pollution in the production process and do not apply solutions to reduce waste, save energy, and natural resources, there is a risk of no longer receiving orders or orders being rejected, especially orders from the world’s major branded garment companies. In this research, the authors propose a multicriteria decision-making model (MCDM) for optimizing the supplier evaluation and selection process for the garment industry using sustainability considerations. In the first stage of this research, all criteria affecting supplier selection are determined by a triple bottom line (TBL) model (economic, environmental, and social aspects) and literature reviews; in addition, the fuzzy analytic hierarchy process (FAHP) method was utilized to identify the weight of all criteria in the second stage. The technique for order preference by similarity to an ideal solution (TOPSIS) is a multicriteria decision analysis method, which is used for ranking potential suppliers in the final stage. As a result, decision-making unit 10 (DMU/10) is found to be the best supplier for the garment industry. The contribution of this research includes modeling the supplier selection decision problem based on the TBL concept. The proposed model also addresses different complex problems in supplier selection, is a flexible design model for considering the evaluation criteria, and is applicable to supplier selection in other industries.

Selecting suppliers plays an important role in improving efficiency of supply chains. In the field of extraction of vegetable oil, one of the main submaterials is hexane solvent. Choosing a supplier of hexane solvent is a multicriteria decision-making task that decision-makers must have an understanding of the quantitative and qualitative elements for assessing the symmetrical impact of the criteria to reach the most accurate result. In this paper, the authors suggest a multicriteria decision-making (MCDM) model for N-hexane solvent (C6H14) supplier evaluation and selection for vegetable oil production. All criteria affecting to the hexane solvent supplier evaluation and selection process are defined by experts. Then, a fuzzy analytic hierarchy process (FAHP) multicriteria comparative analysis method has been applied for determining the weight of all criteria. Finally, the technique for order of preference by similarity to ideal solution (TOPSIS) was applied to select the optimal hexane solvent supplier. As a result, decision making unit 003 (DMU3) is the optimal supplier. The contribution of this research is to propose an MCDM model for hexane solvent supplier selection in the food industry. The work also proposed a useful guideline for supplier evaluation and selection processes in other industries.

Purpose The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods. Design/methodology/approach In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach. Findings Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes. Originality/value The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

Watershed prioritization using morphometric analysis by MCDM approaches

Suppliers are extremely important in business operations. The supplier ensures the supply of materials, raw materials, commodities, etc. in sufficient quantity, quality, stability, and accuracy to meet the requirements of production and business with low costs and on-time deliveries. Therefore, selecting and managing good suppliers is a prerequisite for organizing the production of quality products as desired, according to the schedule, and with reasonable prices and competitiveness in the market. It is also important to gain the support of suppliers in order to continue to improve and achieve more as a business. The evaluation and selection of a supplier is a Multi-Criteria Decision-Making (MCDM) issue, in which the decision-maker is faced with both qualitative and quantitative factors. In this research, the authors propose an MCDM model using a hybrid of Supply Chain Operations Reference metrics (SCOR metrics), the Analytic Hierarchy Process (AHP) model, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach for supplier evaluation and selection in the gas and oil industry. Using literature reviews on SCOR metrics, all criteria that impact supplier selection are defined in the first stage, the AHP model is applied to determine the weight of each factor in the second stage, and the optimal supplier is presented in final stage using the TOPSIS model. As a result, Decision-Making Unit 5 (DMU-05) is found to be the best supplier for the gas and oil industry in this research. The contribution of this work is to propose a new hybrid MCDM model for supplier selection in the gas and oil industry. This research also introduces a useful tool for supplier selection in other industries.

Supplier selection problem has a major regard in terms of the performance of supply chain of an organization. Several various approaches were proposed, including the analytic hierarchy process, fuzzy analytic hierarchy process, and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS). However, no comparative researches of these three approaches related to the supplier selection problem have been carried out. Therefore, this article proposes a methodology to evaluate the selected approaches. The evaluation was conducted based on the following factors: agility during the decision process, computational complexity, number of criteria and alternative suppliers, and adequacy in supporting a group decision. The methodology is implemented in X company. The results show that each approach is convenient to the supplier evaluation and selection problem, particularly toward the support of group decision-making and uncertainty modeling. In terms of computational complexity, analytic hierarchy process performs better than fuzzy TOPSIS and fuzzy analytic hierarchy process. Moreover, the fuzzy TOPSIS approach is better suited to the supplier evaluation and selection in terms of agility during the decision process, the number of criteria and alternative suppliers, and the adequacy in supporting a group decision.

The methods of AHP and Fuzzy AHP provide supports for decision making process, go through normalization procedure, produce different values for decision criteria weights and finally determine decision result. Interestingly both the method produces same decision result in various cases. The model for supplier selection showed by Foriborz Jolai (2011) based on AHP with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a matter of modification replacing by Fuzzy AHP and Modified Fuzzy TOPSIS methods in order to introduce ‘Fuzzification’ and ‘Defuzzification’ which is not available in existing model. The proposed model is verified with an illustrative example and comparing the results generated by both the existing and proposed model in consensus decision making. Keywords: AHP, Fuzzy, MCDM, TOPSIS, Supplier Selection DOI: 10.7176/JIEA/10-4-07 Publication date: October 30 th 2020

Supplier selection is one of the key activities of purchase management in supply chain. Supplier selection is a multifaceted problem relating qualitative and quantitative multi-criteria. This paper deals with a supplier selection problem in an Indian automobile company. The work presents selection of headlamp supplier using integrated fuzzy multi-criteria decision-making approaches: analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). The selection process starts with identifying the criteria based on literature review and interviewing industry experts. Weights to criteria are assigned using AHP, and suppliers are ranked using AHP and TOPSIS. Consistency tests are carried out to check the quality of expert's inputs. Also, sensitivity analysis is done to check the robustness of the approach. The results address that fuzzy approaches could be effective and more accurate than the existing approaches for supplier selection problems.

Sustainable supplier selection for smart supply chain considering internal and external uncertainty: An integrated rough-fuzzy approach

A key factor in the success of dairy industry enterprises is the supplier selection procedure. With a focus on obtaining high-quality raw materials and ensuring a reliable supply chain, dairy companies must carefully evaluate and choose their suppliers. The supplier selection process involves assessing various factors, including the supplier's reputation, product quality, pricing, delivery capabilities, and compliance with industry standards. Additionally, considerations such as sustainability practices, food safety certifications, and proximity to production facilities are vital. A well-executed supplier selection process in the dairy industry ensures that companies can maintain consistent product quality, meet customer demands, and uphold industry regulations. The dairy industry's supplier selection procedure has the ability to increase operational effectiveness, product quality, and overall competitiveness, which makes it important for research. By carefully examining and comprehending the elements that affect supplier selection choices, this research can provide valuable insights for dairy companies. It can help them optimize their supply chain, minimize risks, and strengthen relationships with reliable suppliers. Additionally, the research can contribute to the development of best practices and guidelines for supplier evaluation and selection, leading to improved industry standards and enhanced consumer trust. Ultimately, an effective supplier selection process can positively impact the entire dairy industry by ensuring a sustainable and reliable source of high-quality raw materials. A combination of qualitative and quantitative methods will be used in the methodology for the research of the dairy industry's supplier selection process. Firstly, a comprehensive literature review will be conducted to gather insights into the existing supplier selection criteria and methodologies used in the industry. This will be followed by qualitative interviews and surveys with key stakeholders such as dairy company managers, procurement professionals, and suppliers to gather their perspectives on the supplier selection process. To find recurring themes and patterns, the obtained data will be examined utilizing qualitative data analysis approaches. Additionally, using statistical techniques and models like the Analytic Hierarchy Process (AHP) and TOPSIS, quantitative analysis will be done to assess the significance and effectiveness of various supplier selection criteria. To provide a comprehensive understanding of the supplier selection procedure in the dairy business, the results from both qualitative and quantitative assessments will be merged. Alternative parameters: Price, Product, On-time delivery, supply capacity, and track record of performance. Price, Product, Delivery on time, supply capacity, and performance history. Both the Alternative and Evaluation Parameters are Same. By using the DEMATEL for Supplier Selection Process in Dairy Industry in Price is on 1st Rank, Product is on 2nd Rank, Performance History is on 3rd Rank, Capacity of Supply is on 4th Rank and on time delivery is on 5th Rank.

The plastics business has grown rapidly in recent years, with annual growth rates ranging from 16% to 18% each year (second only to the telecommunications and textile industries). The plastic industry is regarded as a dynamic industry in the Vietnamese economy due to its rapid development rate. Its high growth stems from a big market with significant expansion potential, since Vietnam’s plastic sector is still in its early stages in comparison to the rest of the globe and plastic goods are pushed and utilized in many aspects of life. In order to ensure sustainable development and comply with the provisions of the Law on Environment Protection, plastic manufactures and importers must ensure to fulfill two responsibilities: (1) proper product and packaging recycling—applicable to products and packaging with recyclable value; and (2) the collection and treatment of waste—applicable to products and packaging containing hazardous substances, difficult to recycle, causing difficulties for waste collection and treatment. Therefore, raw materials supplier selection in the plastic industry is a complex decision, and decision makers must consider many qualitative factors, quantitative factors and environmental attributes during the decision making. As a result, the goal of this study is to present an integrated multicriteria decision making model (MCDM) strategy for sustainable supplier selection in the plastics sector under fuzzy environment circumstances. This paper makes a contribution by proposing a hybrid fuzzy analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) approach model for raw material supplier selection in the plastics sector. This research also provided a useful guideline for supplier selection in other industries.

The plastic industry is considered one of the most dynamic industries with the highest competitive projection in the country [1]. Thanks to the advances of this industry, new products have been developed with various applications at industrial, commercial, service levels, and society’s daily lives. Plastics are highly demanded their chemical and physical properties, versatility, and low cost. However, many challenges are arising from the growth in consumption and the dynamics of the plastics industry, such as the prices of raw materials, substitute products of plastic, the demands of consumers, government, and other interested parties with the impact of plastics on the environment during the different stages of their life cycle. Concerning the life cycle of the plastic products is especially determinant the post-consumption, where plastic waste presents a low percentage of recycling and a prolonged period of degradation, being a product questioned for its negative environmental implications. In this sense, companies in the sector must implement different strategies and tools to evaluate their environmental performance, considering the product life cycle. In the world, there are various government regulations for the responsible use of plastics. International methodologies focused on sustainable environmental management in the products, processes, and organizational level have also been developed, such as the product life cycle approach, reverse logistics, and the ISO 45001 standard. However, it is necessary to create objective and analytical methodologies for evaluating environmental management and reverse logistics that provide solutions for the plastic industry, helping companies comply with applicable legal requirements and standards, and supporting decision-making processes. Concerning the decision-making is a complex process given the complexity of the sector and the multiple criteria taken into account when evaluating and establishing improvement strategies. In the literature review, we found several studies with the application of a multicriteria combined approach focused on selecting plastic recycling methods, location of plastic processing centers, eco-design of plastic products, and selection of suppliers. Despite these considerations, the research-oriented on applying integrated methodologies for evaluating performance in the environmental management and reverse logistics in the plastic industry, under multiple criteria and uncertainty, are mostly limited and with the exciting potential of development. Therefore, this document presents a hybrid methodology for evaluating the performance in the environmental management and reverse logistics in the plastic industry by applying two techniques of Multi-criteria Decision Methods (MCDM) uses in environments under uncertainly. First, the fuzzy Analytic Hierarchy Process (FAHP) is applied to estimate the initial relative weights of criteria and sub-criteria. The fuzzy set theory is incorporated to represent the uncertainty in the judgments of decision-makers. Then, the Decision-making Trial and Evaluation Laboratory (DEMATEL) was used for evaluating the interdependences between criteria and sub-criteria. FAHP and DEMATEL are later combined for calculating the final criteria and sub-criteria weights under vagueness and interdependence. Subsequently, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to rank the companies of the plastic industry. Finally, we detect improvement opportunities for the companies of the plastic sector.

An integrated methodology for the selection of sustainable suppliers and order allocation problem with quantity discounts, lost sales and varying supplier availabilities

A comparison between fuzzy AHP and fuzzy TOPSIS methods to software requirements selection

Choosing a supplier is a complex decision-making process that can reduce the total cost of production inputs and increase profits without increasing the price or sacrificing product quality. However, supplier selection processes usually involve multiple quantitative and qualitative criteria which increase the complexity of the problem and may decrease the accuracy and effectiveness of the process. Such complex decision-making problems can be supported by using multicriteria decision-making (MCDM) models. While there have been multiple MCDM models to support supplier selection processes in different industries and sectors, only a few are developed to support the supplier selection processes in the garment industry, especially under uncertain decision-making environment. This paper presents an integrated mathematical model under a fuzzy environment and applies it to the supplier selection process in the garment industry. In this research, the authors utilize the Buckley extension based fuzzy Analytical Hierarchical Process (FAHP) method in combination with linear normalization based fuzzy Grey Relational Analysis (F-GRA) method to develop a MCDM approach to the supplier selection process under a fuzzy environment. As a result, supplier 08 (SA08) is the optimal supplier. The contribution of this work is to propose an MCDM model for ranking potential suppliers in the garment industry under a fuzzy environment. The proposed approach can also be applied to support complex decision-making processes under a fuzzy environment in different industries.