Sustainable Technology Supplier Selection in the Banking Sector

Supplier evaluation is a relevant task of supply chain management where multicriteria methods make great contributions to manufacturing industries. This is not the case in food distribution companies, which have a key role in providing safe and affordable food to society. The purpose of this research is to measure the sustainability of products and suppliers in food distribution companies through a multiple criteria approach. Firstly, the system proposed provides indicators to qualify products and assess the food quality, using the compensatory Multi-Attribute Utility Theory (MAUT) model. Secondly, these indicators are included in supplier evaluation, which takes economic, environmental, and social criteria into account. MAUT and Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE), a non-compensatory method, are used for supplier evaluation. This approach has been validated for fresh food in a supermarket chain, mainly using historical data. Partial indicators, such as food safety scores, together with global indicators of suppliers, inform the most appropriate decisions and the most appropriate relations between companies and providers. Poor performance in food safety can lead to the disqualification of some suppliers. MAUT is good for qualifying products and is easy to apply at the operational level in logistic platforms, while PROMETHEE is more suitable for supplier segmentation, as it helps to identify supplier strengths and weaknesses.

Supplier selection an important problem in supply chain management (SCM), since the performances of suppliers determine the competitiveness of the SCM. It is practical for the purchasing company to procure multiple products simultaneously. Synergy effect may exist between products in multi-product supplier selection process, and affect the final choice of suppliers. It is advantageous for the purchasing company to take into account the synergy effect between products to reduce cost and improve efficiency. On the other hand, suppliers need to consider the synergy effect between products to increase the chance of winning bids. Nevertheless, supplier selection involves complex decision making processes regarding supplier evaluation, selection and order fulfillment, it is difficult to fully incorporate the synergy effect between products in the case of multi-product supplier selection. Most of existing research only deal with supplier selection involving the acquisition of one product, or they assume that the multiple required products are independent. They are not sufficient to incorporate the synergy effect between products for multi-product supplier selection. This paper presents a product bundle determination model which can determine the synergy effect between products, group products based on the synergy effect between products, and determine the preferred product bundles of the purchasing company. This model can help the decision maker to make right decision in multi-product supplier selection process. Illustrative examples are conducted to demonstrate the functioning of the proposed product bundle determination model and its application in multi-product supplier selection process.

Selecting suitable suppliers is a critical decision for organizations, and multi-criteria group decision-making (MCGDM) has been proven as an effective technique in selecting the most appropriate supplier. However, most existing supplier selection methods do not fully explore the trust relationships among decision-makers (DMs), fail to effectively tackle complex and uncertain information, and neglect the interdependencies among criteria. To overcome these obstacles, we develop a social trust network (STN) based hybrid supplier selection approach that adopts the best-worst method (BWM) and the preference ranking organization method for enrichment evaluation (PROMETHEE) under interval-valued Pythagorean fuzzy (IVPF) environment. The main contributions are as follows: Firstly, a novel STN is constructed and extended to the IVPF setting to fully capture both direct and indirect trust relationships among DMs. Secondly, a new trust propagation operator is designed to determine DMs’ weights more objectively. Thirdly, the BWM method, known for its high consistency and efficiency, is adapted to the IVPF environment to derive optimal criterion weights and the preference relation-based PROMETHEE method is also integrated to rank the candidate suppliers. Fourthly, the IVPF weighted Hamy mean (IVPFWHM) operator is employed to aggregate DMs’ preferences and evaluations while explicitly capturing the interrelationships among criteria. The approach is practically applied to a real-world decarbonized and sustainable supplier selection case to validate the efficacy in complex and uncertain group decision-making scenarios while incorporating social trust dynamics. The sensitivity and comparison analyses are also conducted to validate the robustness and benefits of the method.

Applications of sustainable supplier selection criteria in supply chain management (SCM) remain underdeveloped compared to other evaluation methods. This study focuses on three main dimensions of sustainable supplier performance: economic, environmental, and social criteria. The research aims to identify significant criteria within each dimension that are crucial for sustainable supplier selection process. These criteria will be utilized to develop a decision support system (DSS) that integrates a fuzzy inference system. The proposed model offers a holistic approach to supplier evaluation by considering economic performance, environmental impact and social responsibility. By incorporating these dimensions, the model ensures that the selection process aligns with broader corporate and environmental goals. The approach enables companies to make informed and sustainable decisions, ultimately contributing to a more resilient and responsible SCM. Furthermore, the fuzzy inference system effectively handles the inherent uncertainty and vagueness in supplier performance data. To enhance the robustness and reliability of the decision-making process, the proposed model can be integrated with multi-objective linear programming models, making it a valuable tool for supply chain managers. The findings of this work revealed that the economic criteria of supplier selection focus on quality, flexibility, cost, lead time, relationships, and technical capability. The environmental criteria include resource consumption, eco-design, recycling, emissions, and sustainability practices. The social criteria emphasize stakeholder involvement, staff training, safety, rights, and accident prevention in supplier selection. In summary, this comprehensive framework evaluates and benchmarks supplier sustainable performance, supporting more resilient and sustainable SCM.

Evaluating freight villages and selecting one of them are complicated tasks due to the fact that various criteria or objectives must be considered in the decision making process. Also in many real world cases the criteria are not equally important for the logistic managers and government authorities. In this study, we proposed a freight village analysis model considering both Analytic Hierarchy Process (AHP) and PROMETHEE (preference ranking organization method for enrichment of evaluations) method. Subjective and objective opinions of logistic managers/experts turn into quantitative form with AHP. PROMETHEE technique is used for calculating the freight villages’ ratings. Apparently, freight village location selection is a multi-criteria problem that includes both quantitative and qualitative factors. It is necessary to make trade-off between these tangible and intangible factors while considering a suitable location. Accessibility, transport infrastructure, the value of freight villages (maritime connections, rail connections, road connections, and airport connections), distance from city center and total surface area are some of the key success factors of freight villages. The aim of this paper is to determine the appropriate freight village candidate providing the most satisfaction for the criteria identified in the supply chain management.

Supplier selection is an important decision-making problem in supply chain management. Selecting appropriate suppliers based on sustainability criteria including economic, environmental, and social criteria can help companies move toward sustainable development. Data envelopment analysis (DEA) is applied to recognize the most sustainable supplier. However, conventional DEA models can be applied only to performance measurement systems characterized by positive input–output data. However, in real world, data can be negative. We propose a new DEA model for evaluating sustainability of suppliers in presence of negative data and volume discounts. Also, we present a super-efficiency model for ranking suppliers. In addition, we prove some main properties of our proposed method. Finally, we present a case study to demonstrate applicability of proposed model.

The evaluation and selection of the best supplier is a crucial decision-making process as it can reduce the supply chain cost and increase the quality of items supplied to a company. Choosing suppliers solely based on their previous experiences may contribute to higher purchase risk. The decision-making process is usually influenced by a variety of criteria that are often in conflict. Thus, this study employs the integration of Analytic Hierarchy Process (AHP) method and Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) II to handle supplier selection issues. AHP method was adopted to evaluate the weights of criterion. PROMETHEE II is a Multi-Attribute Decision Making method that is based on a mutual comparison of each alternative pair with respect to each of the selected criterion allowing the rankings of the alternatives from the best to the worst. A real-life data about supplier selection for railways project was used to demonstrate the operation of AHP-PROMETHEE II method. The data involved four decision makers, five alternatives (SI, S2, S3, S4, S5) and eight criteria specifically; aspect of the items (C1), arrangement of time (C2), shipment accomplishment (C3), total price of the item (C4), way of payment (C5), relation with supplier (C6), scope of product (C7), and supplier’s professional ability (C8). The findings showed that C4 was the most preferred criterion among the chosen criteria. Thus, the ranking order for criteria was C4 > C8 > C1 > C2 > C5 > C7 > C6 > C3 while the ranking order for the alternatives was S2 > S1 > S4 > S3 > S5, respectively. The findings were then compared with the result from the previous research. The sensitivity analysis was conducted by reducing criteria weights to zero. In conclusion, AHP-PROMETHEE II can be used to analyse the perfect order from best to worst.

Circular supplier selection in the construction industry: A sustainability perspective for the emerging economies

Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.

The supply chain nowadays is more dynamic than before partly due to the information techniques and changes of consumer behaviors. This proposal analyzes the multiple objective optimization problems existing in the supply chain management, and the stochastic and dynamic circumstance of current supply chain. It presents a general overview of multi-objective optimization techniques, stochastic and dynamic programming. We attempt to apply these techniques to solve some optimization problems in supply chain, under changing environment. It can be a guideline of future research. There are mainly three parts of the proposal; the first is multiple objective optimization problems in the real supply chain management, and the stochastic and dynamic environment of the supply chain. The second part is the suggesting approaches dealing with multi-objective optimization problems and the stochastic, dynamic circumstance. The last part is attempting to apply these methods into a real case existing in the supply chain.

Multi-criteria decision-making techniques have been used to solve a range of real world problems in management science and specific supply chain management (SCM) problems (e.g. supply chain design and reconfiguration, purchasing, scheduling, supplier selection). The results obtained are encouraging. Nevertheless, robust approaches for solving multi-criteria supply chain problems are still in progress, and more research is needed before an effective and operational framework can be developed. The proposed approach introduces a two-phase hierarchical approach to solve a multi-criteria SCM problem integrating both strategic and tactical decisions where the supply chain is evaluated based on the supply chain operations reference model. The latter considers various metrics such as delivery reliability, flexibility, responsiveness and cost. The first phase evaluates different supply chains configurations using analytic hierarchy process. The second phase solves the network for the optimal safety stock placement using dynamic programming. The output from this two-phase process is a supply chain network configuration that has the right amount of safety stocks at the right place to absorb variability in demand.

Strategy development for supplier selection process with smart and sustainable criteria in fuzzy environment

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.

Multi Criteria Decision Making (MCDM) helps decision makers (DMs) solve highly complex problems. Accordingly, MCDM has been widely used by DMs from various fields as an effective and reliable tool for solving various problems, such as in site and supplier selection, ranking and assessment. This work presents an in-depth survey of past and recent MCDM techniques cited in the literature. These techniques are mainly categorised into pairwise comparison, outranking and distance-based approaches. Some well-known MCDM methods include the Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), Elimination et Choix Traduisant la Realité (ELECTRE), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Each of these methods is unique and has been used in a vast field of interest to support DMs in solving complex problems. For a complete survey, discussions related to previous issues and challenges and the current implementation of MCDM are also presented.

A strategic model for supply chain design with logical constraints: formulation and solution