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The selection of suppliers represents a pivotal aspect of supply chain management and has a considerable impact on the success and competitiveness of the organization in question. The selection of a suitable supplier is a multi-criteria decision making (MCDM) problem based on a number of qualitative, quantitative, and even conflicting criteria. The aim of this paper is to propose a novel MCDM approach dedicated to the supplier evaluation problem using an ordered fuzzy decision making system. This study uses a fuzzy inference system based on IF–THEN rules with ordered fuzzy numbers (OFNs). The approach employs the concept of OFNs to account for potential uncertainty and subjectivity in the decision making process, and it also takes into account the trends of changes in assessment values and entropy in the final supplier evaluation. This paper's principal contribution is the development of a knowledge base and the demonstration of its application in an ordered fuzzy expert system for multi-criteria supplier evaluation in a dynamic and uncertain environment. The proposed system takes into account the dynamic changes in the value of assessment parameters in the overall supplier assessment, allowing for the differentiation of suppliers based on current and historical data. The utilization of OFNs in a fuzzy model then allows for a reduction in the complexity of the knowledge base in comparison to a classical fuzzy system and makes it more accessible to users, as it requires only basic arithmetic operations in the inference process. This paper presents a comprehensive framework for the assessment of suppliers against a range of criteria, including local hiring, completeness, and defect factors. Furthermore, the potential to integrate sustainability and ESG (environmental, social, and corporate governance) criteria in the assessment process adds value to the decision making framework by adapting to current trends in supply chain management. [ABSTRACT FROM AUTHOR]

AbstractIn a multi-channel distribution environment, the selection and assessment of suppliers are pivotal to effective retailer performance management. This necessitates heightened qualifications and competence from suppliers. This study examines the relationship between the perception of supplier firms’ status, evaluation performance, and overall satisfaction of food buyers with suppliers in online/offline channels. In addition, this study investigates the moderating impacts of the distribution channel to explore the influence of the online/offline distribution channel on this relationship. For exploratory research, food buyers from 20 large retailers headquartered in Seoul, South Korea, were surveyed, and 110 valid questionnaires were used for analysis. Results of the study indicate that among suppliers’ firm factors, suppliers’ firm size and experience with the retailer were significantly and positively related to buyer satisfaction. Likewise, among evaluation factors, product competency and delivery reliability were significantly and positively related to buyer satisfaction. In addition, the results reveal that the distribution channel has moderating effects on the relationship between firm size and buyer satisfaction, as well as between experience with the retailer and buyer satisfaction. Therefore, the study verified that the distribution channel is an important factor that must be considered not only in the consumer market but also in the buying behavior research of the business-to-business market.

This research aims to aid original equipment manufacturers (OEMs) to model, analyze, evaluate, and benchmark potential design and manufacturing suppliers based on respective product engineering teams' efficiencies. The product engineering efficiency in this study is modeled in terms of product engineering-related attributes such as commercial lead time, number of parts, number of green features, number of end products developed, and so forth. Essentially, these parameters capture more complex interactions than simple traditional supplier selection criteria such as cost, quality, delivery, and flexibility. Due to the presence of information uncertainty in terms of bounds related to the suppliers' related parameters, a number of data envelopment analysis (DEA) efficiency measurement models have been deployed. The proposed decision support system is novel because it models both the self-assessment type and cross-efficiency type using DEA such that maximum discrimination can be achieved amongst suppliers in the presence of interval data. The study is demonstrated for ten different sheet-metal cabin suppliers. Comparison with some well-known, relevant methods is also carried out to illustrate the validity of the proposed method. The research can specifically help supply chain managers to align the evaluation of potential suppliers with their firm's commercial considerations in the presence of information uncertainty. [ABSTRACT FROM AUTHOR]

Increasing carbon emissions and environmental degradation have led to rapid depletion of resources. This requires circular low carbon (CLC) supply chains which extend the lifecycle of resources as much as possible. The aim of this study is to propose an integrated model for CLC supplier selection. First, economic, environmental and social responsibilities related to carbon management are identified. Then, DANP (Dematel-Analytic Network Process) and COPRAS (Complex Proportional Assessment) model with interval type-2 (IT-2) fuzzy sets are applied to evaluate the suppliers of a case energy company in Turkey. In this study, the ranking of dimensions from the most important to the least yielded the following order: environmental, social, and economic. In turn, carbon policy, carbon emission risks and low carbon supplier collaboration are found to be the most important environmental criteria. The current study has been used for the first time for a CLC supplier selection problem. Further, the study innovatively employs IT-2 fuzzy sets to better address differences and uncertainties that may come into play with a group of experts' linguistic judgments. The validity of the proposed method is determined through sensitivity and comparative analysis. [ABSTRACT FROM AUTHOR]

The selection of suppliers represents a pivotal aspect of supply chain management and has a considerable impact on the success and competitiveness of the organization in question. The selection of a suitable supplier is a multi-criteria decision making (MCDM) problem based on a number of qualitative, quantitative, and even conflicting criteria. The aim of this paper is to propose a novel MCDM approach dedicated to the supplier evaluation problem using an ordered fuzzy decision making system. This study uses a fuzzy inference system based on IF–THEN rules with ordered fuzzy numbers (OFNs). The approach employs the concept of OFNs to account for potential uncertainty and subjectivity in the decision making process, and it also takes into account the trends of changes in assessment values and entropy in the final supplier evaluation. This paper’s principal contribution is the development of a knowledge base and the demonstration of its application in an ordered fuzzy expert system for multi-criteria supplier evaluation in a dynamic and uncertain environment. The proposed system takes into account the dynamic changes in the value of assessment parameters in the overall supplier assessment, allowing for the differentiation of suppliers based on current and historical data. The utilization of OFNs in a fuzzy model then allows for a reduction in the complexity of the knowledge base in comparison to a classical fuzzy system and makes it more accessible to users, as it requires only basic arithmetic operations in the inference process. This paper presents a comprehensive framework for the assessment of suppliers against a range of criteria, including local hiring, completeness, and defect factors. Furthermore, the potential to integrate sustainability and ESG (environmental, social, and corporate governance) criteria in the assessment process adds value to the decision making framework by adapting to current trends in supply chain management.

The purpose of this research is to present an adaptive and integrated reference model for the Supplier Selection Process (SSP) to integrate it into the Product Development Process (PDP) or the serialized component supply. The research methodology adopted a broad literature review on indexed databases and a logical deductive analysis of the identified constructs and factors. The two main results obtained were: compilation and categorization (moderating factors, connecting factors) of critical SSP success factors; and proposal of a reference model so that the SSP can serve the PDP and the serialized component supply. Regarding originality we can mention: (a) this reference model covers all the critical SSP success factors; (b) it makes a clear distinction between moderating and connecting factors (c) while addressing both the PDP and the serialized component supply. The considerable number of factors identified in this research suggests that the vast majority of models proposed in the literature are based on an incomplete set of variables, restricting the conceptual view of the SSP. Finally, the results contribute to reducing the risk of the SSP not adding value to the Original Equipment Manufacturers' (OEMs) strategic purpose or causing losses. Additionally, the proposed model can be adapted according to the company's business strategy. [ABSTRACT FROM AUTHOR]

In a service exchange setting, the supply management literature generally assumes, with notable exceptions, the availability of complete information regarding supplier reliability. Highlighting the information asymmetry in supplier evaluation and using signaling theory, we argue that for a focal buyer, a supplier's downstream ego‐network instability, that is, other buyers' turnover in a supplier's network from one period to the next, acts as a signal of supplier unreliability, thereby reducing the price that the buyer pays to the supplier in a service exchange. Furthermore, we suggest that focal buyer–supplier relationship strength and structural equivalence weaken the negative effect of instability because the buyer has a more direct and positive experience with the supplier. Using a dataset of 3263 unique dyads formed by 260 buyers (shipoperators) and 493 suppliers (shipowners) during the 2000–2018 period in the container shipping charter market, we find support for our hypotheses, except for the contingent effect of structural equivalence. Our study contributes to signaling literature and network research by developing a supplier's downstream ego‐network instability as a salient heuristic for a focal buyer's pricing decisions. These findings equip buyer managers who may not accurately foresee supplier service quality in the charter market with a new supplier evaluation tool: a supplier's downstream ego‐network instability. Highlights: For shipoperator buyer managers making pricing decisions in the container shipping charter market, turnover (instability) in the supplier's network of direct buyer relations acts as a relevant supplier evaluation tool.A shipowner supplier whose downstream network exhibits instability may signal unreliability of service quality, and in this regard switching buyers can backfire for suppliers in terms of potential buyers' evaluations and pricing decisions.The relational embeddedness of buyer‐supplier relationships helps mitigate the effects of negative external signals about supplier reliability originating elsewhere in the supplier network, suggesting the relevance for shipowner supplier managers of nurturing and strengthening one‐to‐one existing relationships with buyers. [ABSTRACT FROM AUTHOR]

Traditional mathematical models for supplier evaluation and selection have primarily focused on cost-oriented perspectives, neglecting non-cost factors such as strategic and relational measures. However, such models have often compromised the optimality of solutions. Additionally, the use of genetic algorithms in these models has resulted in similar objective function outputs with minimal differences, making it challenging to differentiate between potential suppliers. To address these limitations, this study proposes a novel approach that employs multi-criteria decision-making (MCDM) techniques to evaluate suppliers without sacrificing optimality or imposing additional constraints. The proposed model utilizes hybrid algorithms and incorporates the weighted criteria obtained through the Best–Worst Method and the ranking and selection of alternatives using the Technique for Order of Preference by Similarity to Ideal Solution. By applying MCDM methods in the post-evaluation phase, this research introduces a unique approach that preserves solution optimality. The findings highlight that while the objective function outputs from the genetic algorithm implementations may be nearly identical, they can vary significantly across other criteria. This study demonstrates the strength of multi-criteria evaluation in overcoming the limitations of genetic algorithms without compromising solution optimality. [ABSTRACT FROM AUTHOR]

With the intensification of global competition and the increasing awareness of reducing energy consumption, sustainable supplier selection is crucial for establishing a solid cooperative relationship in sustainable supply chain management. This paper proposes a new framework that considers both the effective expression of uncertain information and the objective weights of decision makers to select sustainable suppliers. We first apply an interval-valued intuitionistic fuzzy set to express the information of decision makers. Moreover, this paper applies a plant growth simulation algorithm to aggregate decision makers' information. Next, we adopt the similarity measure method to derive the target weight of each decision maker. Then, we apply the score function to rank the candidate sustainable suppliers. Finally, two practical cases are presented to verify the effectiveness of the proposed framework. The outcomes and comparative discussion show that the developed framework is efficient for sustainable supplier selection. Therefore, the proposed framework can be used to establish a solid cooperative relationship in the process of sustainable supply chain management. [ABSTRACT FROM AUTHOR]

When confronted with underperforming suppliers, the need to evaluate and improve supplier performance becomes apparent. However, the inherent inaccuracies in information introduce complexity, especially when subjective human judgment is involved in the supplier evaluation process. Associated with such problem, this study presents a novel methodology for supplier performance evaluation in the crumb rubber industry, integrating the Taguchi Loss Function (TLF), fuzzy Best-Worst Method (BWM), and VIKOR technique in group decision-making environment. Aimed at addressing the challenges in industries with variable supplier quality and performance, such as the crumb rubber industry in Indonesia, the methodology was empirically tested to demonstrate its practical utility. The process involved identifying evaluation criteria through literature review tailored to the needs of decision makers (DMs), applying TLF to quantify losses from supplier performance deviations, using fuzzy BWM to determine criteria weights based on the DMs judgment, and employing the VIKOR technique for comprehensive supplier ranking. The findings underscore the methodology's effectiveness in enhancing decision-making, offering a unified metric that accommodates diverse criteria and balances precise data with subjective assessments. This approach simplifies the evaluation process, particularly in situations with conflicting interests among decision-makers. Demonstrating its practical application in the crumb rubber industry, the study highlights the methodology's potential for broader industrial applicability. Future research could explore comparative analyses with other analytical methods, further establishing the methodology's robustness and adaptability in different management contexts.

AbstractSupplier selection plays a crucial role in enhancing the competitiveness and operational efficiency of manufacturing industries. In the Indonesian manufacturing sector, where market conditions are dynamic and complex, the need for an effective supplier selection methodology is particularly critical. The suggested method converts conventional DEA (Data Envelopment Analysis) models into fuzzy events through the application of credibility measures. Additionally, the relative closeness (RC) index is employed to enhance the differentiating capability of traditional DEA. This article incorporates three input criteria and five output criteria. The findings suggest that higher values of the RC Index correspond to superior performance by the supplier. Furthermore, the study’s outcomes reveal that the credibility index influences the RC index. Imposing stricter credibility constraints can diminish the value of the RC index.

In the past decade, sustainable supply chain management has received much attention from practitioners and academics due to the heightened emphasis on environmental, economic, and social sustainability by customers, for-profit and non-profit institutions, community organizations, legislation, and government oversight. Evaluating and selecting a suitable supplier is considered a critical choice, crucial in supply chain management. Social sustainability in the supplier selection process is an important factor that has not received sufficient attention from academicians. Social and societal challenges are increasingly impacting supply chains. To tackle this challenge in the agricultural section of nations with emerging economies, this study proposed a new methodology using Grey FUCOM (Full Consistency Method) and Gray PROMTHEE (Preference Ranking Organization Method for Enrichment Evaluation) methods for evaluating the social sustainability of wheat and barley seed production companies. This study assists seed users in identifying the most significant supplier selection criteria and one of the most effective suppliers for ecological sustainability throughout the supply chain while maintaining market competitiveness. The results demonstrated a consistent and dependable rating behavior about the weight coefficients of the criteria. Improving the procedures used to evaluate wheat and barley seed suppliers results in a healthier society. So, the proposed model can efficiently evaluate a critical component of the food supply chain in the early stages. [ABSTRACT FROM AUTHOR]

Artan rekabet koşulları ile birlikte işletmelerin tedarikçilerine olan bağımlılığı her geçen gün artarak devam etmektedir. Tedarikçiler ile yapılan iş birliği sadece ürün bazında kalmamakla birlikte üretilen ürünlerin dağıtımı, pazarlanması, dış yaptırımı ya da hizmet alımı şeklinde de olabilir. Bu sebeple tedarikçi seçimi sadece özel sektörde faaliyet gösteren işletmeler için değil, kamu işletmeleri için de büyük önem arz etmeye başlamıştır. Bu çalışmada, demiryolu sektöründe faaliyet gösteren bir kamu kurumu için tedarikçiler Çok Kriterli Karar Verme Yöntemleri (ÇKKV) kullanılarak değerlendirilmiştir. Bu yöntemlerden Analitik Hiyerarşi Prosesi (AHP), Bulanık Analitik Hiyerarşi Prosesi (BAHP) ve Düzey Temelli Ağırlık Değerlendirmesi (LBWA) yöntemleri ile kriterler ağırlıklandırılmış ve Karmaşık Oransal Değerlendirme (COPRAS) yöntemi ile de alternatifler sıralanmıştır. Uygulamada 61 tedarikçi, 4 ana kriter ve 9 alt kriter üzerinden değerlendirilmiştir. AHP yöntemi, kriter ağırlıklandırmada etkin çözümler vermesi ve diğer yöntemler ile birlikte kullanılabilir olması sebebi ile tercih edilmiştir. Çalışmada öznel kriterlerin sayısının fazla olması sebebi ile BAHP yöntemi kullanılarak belirsizliklerin giderilmesi amaçlanmıştır. LBWA yöntemi, literatürde yeni kullanılmaya başlanmış bir yöntem olması ve geniş kullanım alanına sahip olmaması sebebi ile çalışmaya dahil edilmiştir. Bu şekilde üç farklı yöntem kullanılarak, farklı kriter ağırlıklandırma yöntemlerinin sıralama üzerindeki etkisi ve literatürde yeni bir yöntem olan LBWA yönteminin tedarikçi seçimi problemine uygulanabilirliği ve problem üzerindeki etkinliği araştırılmıştır. COPRAS yöntemi ile gerçekleştirilen sıralama sonucu en iyi yedi tedarikçi belirlenmiş ve bu tedarikçilerin her üç ağırlıklandırma yöntemi için de (AHP, BAHP ve LBWA) benzer şekilde sıralandığı görülmüştür.

AbstractIn today's global competition, choosing suppliers, increasing relationships with suppliers, and developing collaborative and sustainable relationships with them to reduce costs and increase flexibility against market changes is necessary and difficult. The present study aims to design a model for ranking suppliers and allocating the optimal number of purchases of sugar beet from the suppliers. The statistical population of the research is experts and specialists in the field of supplier selection at Torbat-e Heydarieh Sugar Company whose number is about 10 people based on proficiency, authority, and skills. The research method of this study is quantitative based on nature, and applicable based on purpose. In this research, to identify the basic criteria for the selection of suppliers, theoretical literature and experts' opinions have been used, and the method of the Analytic Hierarchy Process has been used to rank suppliers. In addition, to allocate the optimal order amount to each of the suppliers, the integration of the Goal Programming model with the Analytic Hierarchy Process has been used. The results of this research show that how Torbat-e Heydarieh Sugar Company can allocate optimal order amount to any of the suppliers by prioritizing them and also by examining the different parameters, according to the capacity of suppliers, and determine how the studied companies purchase their desired raw materials from suppliers to achieve the desired relative and strategic advantage.ExtendedIntroductionThe issue of supplier evaluation and achieving sustainability in the supply chain is one of the important components of supply chain management because suppliers play an important role in creating sustainability in the supply chain, which means achieving social, environmental, and economic goals and ultimately the success of the company. As much as the selection of suitable suppliers is effective in reducing costs and increasing the competitiveness of companies, the selection of inappropriate suppliers can also degrade the financial and operational position of companies (Baroto et al., 2022; Soheilifar and Falah Lajimi, 2019). The process of selecting suppliers is the most important factor in the effective management of the modern supply chain network because it helps in achieving high-quality products and customer satisfaction. Also, the performance of the supplier plays a key role in price, quality, delivery, and service in achieving the goals of the chain (Mohammed et al., 2021; Tavakolian et al., 2020).Currently, the way to supply raw materials and evaluate suppliers in the supply chain is one of the challenges that organizations face for more profitability. Because of the ever-increasing number of suppliers due to the creation of competitive conditions, organizations need to develop a suitable methodology for evaluating and selecting suppliers as well as evaluating their performance to successfully reduce costs and increase the quality of services and products (Rashidi Komijan and Masoudifar, 2021).On the other hand; if the supplier cannot deliver the orders on time and with the required quality and reliability, issues and problems will arise in meeting the demand of the seller's customers and ultimately lead to customer dissatisfaction (Ha & Krishnan, 2008). A supplier that fails to deliver a guaranteed and sufficient product to the seller on time will result in customer loss (Gupta & Barua, 2017). Therefore, choosing a supplier is of considerable importance. During the process of choosing a supplier, especially in a competitive environment, it is very important to buy from a supplier who can meet the most criteria such as material quality, on-time delivery, etc. The current research aims to provide a multi-stage and consistent approach for selecting and ranking effective factors and providing a model for the best purchasing situation using the Goal Programming method, which initially identifies the effective criteria for the evaluation and selection of suppliers and the desired criteria using the hierarchical analysis method, then the important suppliers of Tarbat-e Haidarieh Sugar Company have been ranked and finally, the optimal amount of purchase from suppliers has been allocated using the AHP-GP mixed model.Theoretical frameworkRashidi Komijan and Masoudifar (2021) in a research titled "Mathematical model for evaluating suppliers and purchasing spare parts" showed that determining the group for each part according to the two dimensions of supply risk and criticality of the part is a suitable management tool for equipment supply management, and the use of the zero and one planning model is a suitable method for allocating orders in the field of spare parts, and the structure and components of the objective function and restrictions can be changed according to the type of organization.Firouzi & Jadidi (2021), in research entitled "Multi-objective model for supplier selection and order allocation problem through fuzzy parameters", presented a fuzzy multi-objective model for the supplier selection problem and have created a weight additive function to convert the fuzzy multi-objective model into a single objective fuzzy model that can effectively consider the preferences of decision-makers. Then, a separation method was used to solve the single-objective model with fuzzy parameters (Firouzi & Jadidi ,2021).Naqvi & Hassanzadeh Amin (2021) have written an article titled "Supplier selection and order allocation: a literature review." In this research, the articles conducted in the field of supplier selection have been reviewed, and the scope of the problem has been examined in three subcategories, including literature models, deterministic optimization models, and uncertain optimization models.MethodologyThis research is applied based on the purpose, and descriptive-survey based on the nature and method of research. Data collection has been done through interviews and distribution of questionnaires among senior and middle managers and experts involved in the purchase of beet sugar of Torbat-Haidarieh sugar factory. Also, through library studies and the use of references and sources related to the topic, the materials and topics related to the discussion have been extracted and used in the present research. The aim of this study is to provide a multi-stage and consistent approach to select the effective factors, rank them, and then provide a model for the best purchase situation using the Goal Programming method. This methodology can be divided into two main phases: the first phase includes the determination of quantitative and qualitative criteria and the use of an Analytic Hierarchy Process to weigh the criteria and options, and the second phase includes the identification of goal and systemic limitations and combining the results of the first phase with the Goal Programming method to allocate the optimal order amount to each supplier. The softwares used in this research were Expert Choice and Lindo 6.01.Discussion and ResultsThe purpose of this research is to provide a framework for the analysis and selection of suppliers of raw materials for Torbat-Haidaryeh Sugar Joint Stock Company. Therefore, this research provides a framework that determines the optimal combination of suppliers according to multiple quantitative and qualitative goals and takes into account system limitations so that the maximum possible value is achieved according to the opinions of experts and specialists of the company. One of the features of this research and the combined model is the possibility of considering the weight of decision-makers. This is important because the decision-making committee may include different members, each of whom has different positions in the organization. By accepting the assumption that different positions are the result of knowledge, experience, work records, etc., the executive director as the person in charge of the decision-making committee can compare the members of the committee in pairs, and finally, the weight of the decision-makers is obtained by calculating the special vector of the matrix. Then the next calculations will be influenced by the weight of the decision-makers. In this study, the factors influencing the selection of suppliers were first identified using literature and experts' opinions. Then these criteria and sub-criteria were prioritized using the AHP method. After that, each of the suppliers was rated for each criterion and also for all sub-criteria. In the next step, using the Goal Programming method, the optimal amount of order allocation to each supplier was determined, and according to the results of the research, the largest amount of purchase allocation should be made from Razavi Agricultural Company; Islamabad and Khezri Agricultural Company in the second place, and Marghzar Farmers’ Cooperative Company were ranked third according to the number of orders. Among the other advantages of this model, it can be mentioned that this model includes multiple criteria (quantitative and qualitative) such as grade, quality, timely delivery, etc. in the evaluation and selection of suppliers so that the optimal value according to the Goal limitations is allocated to selected suppliers.ConclusionAccording to the results of this research, at first, the effective components on the evaluation of suppliers were extracted based on the opinion of experts and theoretical foundations. After that, these components were prioritized. After prioritizing these components, all suppliers were evaluated based on these components. Finally, after prioritizing the suppliers based on these components, the optimal allocation of orders from suppliers was determined for each supplier. Among the evaluation components, shipping cost is one of the factors influencing the order (Gergi̇n et al., 2021; Jiang et al., 2018; Adalı & Işık, 2017) and most companies are formed near raw materials to bear the least excess cost. (Khan et al., 2016). Also, companies are generally looking for suppliers who can be more compatible with these companies in terms of conditions (Hadian et al., 2020; Gergi̇n et al., 2021), but in some situations, such as the lack of primary goods and the presence of strong competitors, the supplier gets a higher bargaining power and in this situation, the company has to adapt reluctantly to the supplier's conditions (Mohammed et al., 2021). In this situation, companies may have financial requests in the implementation of the contract (Öztürk & Paksoy, 2020). The more financially powerful the suppliers are and the more they can supply, the more they can change the conditions in their favor. On the other hand, the fewer competing companies in the market, the more companies can choose their suppliers with better conditions (Taherdoost and Brard, 2019). Governments can push companies to buy more products from suppliers by giving subsidies. However, companies tend to buy from suppliers with higher quality products (Rezaei et al., 2014; Adalı & Işık, 2017).The higher the quality of the products, the more companies look for the products of these suppliers (Fei et al., 2019). On the other hand, one of the most important factors for sugar beet companies is the grade of this product, and the companies have understood very well that products with higher grades lead to more profit for these companies; therefore, they are looking for buying quality products with suitable quality. Reassuring factors are among the factors that are of great importance in the process of supplier evaluation and selection. Suppliers whose delivery is fast and on time are more important for companies (Jain et al., 2018; Arabsheybani et al., 2018); because if the delivery time is inappropriate, it may cause problems for the company's production. In addition, suppliers who have stable delivery guarantee the future of the company's production (Hadian et al., 2020), and these suppliers are considered strategic partners of the company and are generally much easier adapt with the Companies' conditions to conclude a contract (Szmelter-Jarosz, 2020).The company should support its loyal suppliers and not leave them alone in critical situations, and the contract between the two should be designed in such a way that the risk is shared between the supplier and the company to create confidence on both sides of the transaction (kabgani & shahbandarzadeh, 2019; Junior et al., 2014). Due to the fact that in this research, the mentioned cases have been investigated, therefore, this research is in accordance with the research conducted in terms of using the mentioned variables. In this section, according to the results of the research and in line with expanding the scope of the dynamic problem of supplier selection and order amount allocation, it is suggested that from now on, using the results of this research, the selection of suppliers in this company to be done every year by systematically and scientifically collecting the information required by the models, and establish a marketing strategy related to the suppliers who have obtained high ranks in this research. Also, considering that the conclusion of the initial contract is the responsibility of the company's inspectors; a list of factors affecting the selection of suppliers based on the set priorities has been provided to each of the inspectors to identify the suppliers based on it and proceed to the final negotiations. After the ranking, it was found that the sugar beet quality criterion has a very important priority among the factors. Therefore, it is suggested that sugar production companies use the quality determination device (Betalyzer) to determine the quality of beet sugar.

Suppliers significantly affect the effectiveness of sustainable supply chain management. Hence, it is extremely important to evaluate and select suppliers scientifically and objectively. Based on the theory of triple bottom line (economic, social, and environmental dimension) and a balanced scorecard, a measureable supplier evaluation framework in a sustainable supply chain is first formulated. Second, to reduce the defects of the single weight method, the subjective and objective weights of evaluation indicators are determined by combining the fuzzy best-worst method (BWM) and the entropy method, and then the combination weights are obtained through linear weighting. Third, the grey relational technique for order performance by similarity to ideal solution (TOPSIS) method is further adopted to evaluate and rank the suppliers. Finally, a case study illustrates and demonstrates the availability of the proposed supplier evaluation index system and evaluation method. Subsequently, some suggestions are proposed according to the results. [ABSTRACT FROM AUTHOR]

Evaluation and selection of a third-party reverse logistics provider (3PRLP) is an important tool for enterprises to improve the level of reverse logistics management. The identification of critical indicators plays a crucial role in the evaluation process. Firstly, on the basis of fully considering the characteristics of 3PRLP evaluation and selection, we summarized 27 evaluation indicators from 5 dimensions—overall operation level, management service level, information technology level, social and ecological benefits, and strategic alliance. Secondly, we adopted the Delphi method to determine the formal evaluation index system, and the best–worst method (BWM) to calculate the weight of each indicator. We determined the critical evaluation indicators on the basis of the weights. Finally, based on our results, corresponding countermeasures and implications regarding the process of 3PRLP evaluation were put forward. The research results show that the critical indicators include transportation allocation capacity, network coverage, service price level, service response speed, recovery efficiency, and service flexibility level. [ABSTRACT FROM AUTHOR]

Healthcare supply chains are complex systems facing challenges in delivering high-quality care while maintaining cost-effectiveness. Research on inventory management and control, the heart of the healthcare supply system, has demonstrated that these targets can be reached by managing inventories efficiently while aiming at desired service levels. Although this can be enabled by adopting various supply chain management practices, the healthcare sector appears to lag compared to other industries. Seeking to investigate these aspects, this study draws on operations management literature, identifies and categorizes technology-driven supply chain management practices that are applied in hospital operations, develops a holistic conceptual framework delineating the key factors influencing their adoption in healthcare facilities, and examines their aggregated impact on financial performance. The research model is tested using structural equation modeling with survey data collected from Greek public hospitals. The study results indicate that technological readiness, organizational readiness, perceived benefits, and hospital size significantly influence the adoption of these practices in hospital supply chains. Moreover, they show a statistically significant association between the supply chain management practices applied and improved hospital cost performance, suggesting greater urgency for hospitals to exploit them fully. Theoretical and practical implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

With the focus of many industries being on supply chain efficiency and Inventory effectiveness, there are various factors that play a major role in affecting the outcome for the organization, prioritizing Inventory control, statistically they are bound to be one of the most variate networks in any supply chain of an organization. The reasoning effectively funnels towards the vast network of suppliers involved merged with the staggering market conditions of unique SKU's that establish unmatched demand with supply Furthermore, the effect on ineffectiveness of inventory has a crucial cascade, seeping into the financial structure of the organization burning through potential profits that have turned into ashes to be able to never recover. We plan to establish criteria for an objective evaluation of all suppliers which shall directly/indirectly influence in the organization - quality of the final product, effective usage of inventory, improved inbound/outbound inventory SKU's and not restricted to improved profit margins induced by the above. Adding further, we also establish assignment of penalties or rewards for the potential low-rated or high-rated suppliers, and to be able incorporate direct audits and improvements with one segment of suppliers whilst terminating relationship with the counter segment of suppliers. [ABSTRACT FROM AUTHOR]

Organisations need to develop long-term strategies to ensure they incorporate innovation for environmental sustainability (IES) to remain competitive in the market. This can be challenging given the high level of uncertainty regarding the future (e.g., following the COVID pandemic). Supplier selection is an important decision that organisations make and can be designed to support IES. While the literature provides various criteria in the field of IES strategies, it does not identify the criteria which can be utilised to assist organisations in their supplier selection decisions. Moreover, the literature in this field does not consider uncertainty related to the occurrence of possible future events which may influence the importance of these criteria. To address this gap, this paper develops a novel criteria decision framework to assist supplier evaluation in organisations, taking into consideration different events that may occur in the future. The framework that combines three decision-making methods: the stratified multi-criteria decision-making method, best worst method, and technique for order of preference by similarity to ideal solution. The framework, proposed in this paper, can also be adopted to enable effective and sustainable decision making under uncertainty in various fields. [ABSTRACT FROM AUTHOR]

The primary activities of any organization rely on the procurement of the required goods and services at the shortest time and highest quality possible. On this basis, the problem of supplier evaluation, ranking, and selection is considered critically important. Data envelopment analysis is a well-known and successful approach in this field. In this study, we propose a robust-stochastic data envelopment analysis model to measure the efficiency of decision-making units under uncertainty. We measure efficiency through a standard and an inverted model in terms of resilience and agility. In order to demonstrate the practical potential of the proposed model, we apply the model to a case study of the Iranian telecom industry with 90 decision-making units. Numerical results reveal that human resources and cash assets are the most important input criteria. Also, the output indicators, including adaptability, reliability, visibility, and coordination, have high importance in measuring the efficiency of decision-making units. It should be noted that employing the robust-stochastic optimization approach leads to controlling the fluctuations of uncertain parameters and maintaining a desirable optimal level of efficiency for decision-making units under different scenarios. The results suggest that the model is sufficiently valid and reliable for evaluating the performance of suppliers in the telecom industry, may be employed under uncertain conditions, and can incorporate decision-makers' varying preferences. The managerial insights derived from this research indicate that, in the short term, uncertainty throughout the evaluation process of suppliers often leads to reduced efficiency among the decision-making units. However, operating under uncertainty is associated with several advantages in the long term, such as increased decision-making consistency and improved vital ability to cope with uncertainty. [ABSTRACT FROM AUTHOR]

Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other criteria except for price, like the production process, the features of parts and reliability of supply have long term effects on the performance of supply chains. In this research a general closed loop supply chain network including production centres, disassembly, refurbishing, and disposal sites is considered. An integrated two-phase model is given so that in the first phase, the proposed fuzzy-MOORA-reference point method is applied to suppliers’ assessment and the results from this phase is used in the second phase. In the second phase, a three-objective mixed integer linear programming model is proposed in order to determine the eligible suppliers, the locations of refurbishing sites and the material flows between the supply chain members. The objective functions are maximizing profit, suppliers’ evaluation and resiliency scores. Unsatisfied demand of customers is lost. The numerical results show the validity of the model and the role of stockout option in reaching better solutions based on the LP-Metric method.

The dynamic and variable environment of today's business has created a highly competitive atmosphere; n order for organizations to survive and succeed, they need to provide new and efficient methods in all aspects of their work. Therefore, supply chain management, as one of the effective factors in the quality of performance of the organization, has been an especial area of attention and since the quality of the final product is strongly dependent on the raw materials of the product and the efficiency of the supplier, the suppliers’ proper performance will guarantee the stability of the supply chain. One of the major challenges for managers in a dynamic and uncertain environment is identifying supplier evaluation indicators, and this article tries to provide a reliable approach to this important challenge. Therefore, the main purpose of this paper is to investigate of behavioral model of suppliers of raw materials for biological products with a system dynamics approach. Accordingly, the reliability and accuracy of the proposed model has been evaluated by several statistical tests. Finally, the performance of this model is shown in the supply chain of Razi Vaccine and Serum Research Institute. The results obtained both in the tests and in the case study, all indicate the ability, reliability and high accuracy of the model in suppliers’ evaluation.

With the intensification of global competition and the increasing awareness of reducing energy consumption, sustainable supplier selection is crucial for establishing a solid cooperative relationship in sustainable supply chain management. This paper proposes a new framework that considers both the effective expression of uncertain information and the objective weights of decision makers to select sustainable suppliers. We first apply an interval-valued intuitionistic fuzzy set to express the information of decision makers. Moreover, this paper applies a plant growth simulation algorithm to aggregate decision makers’ information. Next, we adopt the similarity measure method to derive the target weight of each decision maker. Then, we apply the score function to rank the candidate sustainable suppliers. Finally, two practical cases are presented to verify the effectiveness of the proposed framework. The outcomes and comparative discussion show that the developed framework is efficient for sustainable supplier selection. Therefore, the proposed framework can be used to establish a solid cooperative relationship in the process of sustainable supply chain management.

For any industry to improve and expand, the proper evaluation and selection of suppliers is essential. In order to establish whether a supplier is appropriate for working with a company, a system for selecting green suppliers is required. A variety of Decision-Making (DM) models have been created by researchers to address the problems associated with evaluating and choosing green suppliers. In order to address the Green Supplier Evaluation and Selection (GSES) challenge, we did a thorough investigation of ten works of literature, in order to find out which approach is the most widely used and which is more efficient. This study primarily focuses on the findings of ten reviews that examined 1098 research publications from academic journals between 1990 and 2020. 271 DM models examined that were broken down into 170 individual models and 101 combination models, our analysis only looked at the single models. The method of Analytic Hierarchy Process (AHP) is the dominant model used by 160 articles, 122 studies used Data Envelopment Analysis (DEA), and finally 101 research works that utilized the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model. In addition, we found that the biggest percentage "62%" of studied articles used multi-criteria decision-making (MCDM) models. As a result, the most widely utilized Decision Making models to address the evaluation and selection of green supplier were found to be AHP, DEA, and TOPSIS. [ABSTRACT FROM AUTHOR]

The evaluation of manufacturing component suppliers is focused on economic indicators, with insufficient emphasis on green indicators and no consideration of the correlation between indicators. Firstly, indicators related to green production are incorporated into the supplier evaluation system. Then, for the problem that attributes in decision making can be divided into different categories and there are interrelationships between attributes of the same category, a multi-attribute decision-making (MADM) method based on the partitioned Maclaurin symmetric mean operator (PMSM) is proposed. Finally, the proposed MADM method was applied to the evaluation of component suppliers considering green production. Comparing popular decision methods with the newly proposed method for validation, it was demonstrated that the proposed multi-attribute decision method is highly flexible and versatile. Furthermore, the newly proposed aggregation operator can not only handle the correlation between multiple attributes, but also be converted to other general aggregation operators through parameter adjustment. [ABSTRACT FROM AUTHOR]

Purpose: Following the banning of expanded polystyrene packaging material, the fast food restaurant industry was serendipitously plunged into green sourcing initiatives for its packaging materials leading to heightened efforts on evaluating the suitability of various suppliers of green packaging material. This study therefore sought to assess the performance of selected suppliers on supplier performance metrics of total cost of ownership, quality of sourced material and delivery performance, in Zimbabwe’s restaurant industry.

In an increasingly competitive industrial environment, every company strives to increase the quality and efficiency of its product development process. PT. Udaka Indonesia, a clothing manufacturer, is experiencing raw material shortages that disrupt the company's production process. The goal of this research is to assess and segment the company's suppliers. The Best Worst Method (BWM) is employed for weighting criteria, and Fuzzy TOPSIS is used to rank alternative providers and subsequently segment them. The dimensions of capabilities (8 criteria with 26 sub-criteria) and willingness (4 criteria with 15 sub-criteria) make up the company's supplier evaluation criteria. The evaluation results suggest that suppliers A2, B2, C2, and D2 are the best in terms of capabilities for label accessories, stickers, paper tags, and polybags, respectively, while A1, B2, C2, and D2 are the best in terms of willingness. Supplier segmentation results show that segmentation 1 includes suppliers C1, B1, B3, and D1, segmentation 2 includes supplier A3, and segmentation 4 includes suppliers A1, A2, B2, B4, C2, and D2.