Supplier Selection Research Articles

Combining permissioned blockchain and Bayesian best-worst method for transparent supplier selection in supply chain management

Combining permissioned blockchain and Bayesian best-worst method for transparent supplier selection in supply chain management

Selection of Small and Diverse Suppliers and Contractual Performance: Do Set-Asides Pay Off?

Selection of Small and Diverse Suppliers and Contractual Performance: Do Set-Asides Pay Off?

A dual-level consensus model for large-scale group decision-making driven by trust relationships in social networks

In large-scale group decision-making, obtaining reasonable and reliable decision results is the research focus. To this end, a dual-level consensus model for large-scale group decision-making is constructed. In the model, we first presented a method for measuring the two-dimensional similarity between decision-makers. The method considered the opinion similarity at evaluation scales and ranking results level, which provided a more comprehensive measure of the opinion differences between decision-makers. A hierarchical clustering algorithm based on the two-dimensional similarity-trust matrix is proposed. By considering the two-dimensional similarity and trust relationships among decision-makers, the method contributed to the formation of subgroups with excellent cooperative and communicative atmospheres. Furthermore, we introduced a dual-level consensus measures method to comprehensively and accurately assess the group consensus level. To increase the efficiency of decision-making and the satisfaction of decision-makers, we proposed a personalized feedback adjustment mechanism for decision-makers. Additionally, for the subgroups that have not reached consensus, a social networks DeGroot model is constructed to adjust the opinion of subgroups. Finally, a case study of low-carbon supplier selection verified the feasibility and applicability of the model. The effectiveness and superiority of the model are demonstrated by comparative and simulation analysis. The analysis results show that the model is conducive to promoting cooperation and coordination among decision-makers and obtaining highly acceptable and quality decision results.

Challenges and Strategies for Green Transformation in Logistics Procurement Business: Case Study of SF Express

This study explores the challenges and coping strategies logistics enterprises face in green transformation in procurement management operations. By analyzing the current situation of logistics enterprises, it is found that there are many problems in the traditional procurement model, such as focusing on profit and price while neglecting product quality and long-term partnership. At the same time, the cognitive level of logistics enterprises in green logistics procurement is low, and green supplier selection is influenced by price and profit. This study proposes strategies for establishing and improving green procurement management systems and policies, developing green procurement standards, and setting up evaluation mechanisms to facilitate logistics enterprises' transition towards green. Through case analyses, it is found that some enterprises have begun implementing green procurement and achieved positive results. Finally, this study emphasizes that the government has strengthened its policy support and supervision of green logistics procurement to promote logistics enterprises to make greater progress in green transformation.

The Effect of Suppliers’ Green and Traditional Selection Criteria in Supply Chain Management on Purchasing Firms’ Performance

In recent years, procurement managers have introduced environmental considerations into supplier selection and evaluation as a response to strict environmental regulations implemented by governments. Although previous research investigated the selection of eco-friendly suppliers, little research has been conducted on the significance of the wide range of selection criteria used by industrial customers. The aim of this study was to address this gap and examine the difference in the perceived importance of the selection criteria versus the performance achieved using the selection criteria, in addition to the difference in the business performance and the total supply performance. By investigating the selection criteria of manufacturers in the market environment, this study aimed to demonstrate how their business performance was affected by the performance of suppliers in relation to such criteria. To accomplish this task, this study conducted an empirical analysis based on the questionnaire responses of 72 purchasing managers working in the electrical/electronic and heavy chemical industries. Based on previous research, the following six supplier selection factors were identified: eco-friendliness, quality, relationship, flexibility, delivery, and price/finance. By using statistical analyses, including sample t-tests and multiple regression analysis, this study identified a correlation between supplier and manufacturer performance. The findings show that some factors, such as eco-friendliness, flexibility, price, and delivery, were statistically relevant to the performance of manufacturers, which added value to the decision-making strategy employed in supplier selection.

Selection of Official and Unofficial Lemon Raw Material Suppliers (Case Study of Tasikmalaya City Branch Mixue)

Mixue is one of the most popular contemporary drink brands in Indonesia. One of the important raw materials for Mixue is lemon. In Indonesia, there are two types of lemon raw material suppliers, namely imported suppliers and local suppliers. This research aims to examine and compare the use of lemon raw materials from official suppliers of PT. Zhisheng Pacific Trading (MIXUE) imports raw materials from local suppliers in the context of use by Mixue retail stores operating in the food and beverage sector. This research uses mixed methods between qualitative methods and quantitative methods. Data collection techniques in this research were observation, interviews and questionnaires. Mixue is one of the most popular contemporary drink brands in Indonesia. Based on the results of this research, it can be concluded that local suppliers are superior to most of the factors considered than official suppliers. There is positive interest from experts involved in research regarding the use of lemon raw materials from local suppliers. From this research, recommendations and suggestions were obtained to consider updating policies related to regulations on the use of raw materials from third parties by considering all the advantages possessed by local suppliers in various factors. The results of this research state that local suppliers are superior in price and logistics efficiency. Official suppliers offer stable and reliable product quality.

Multi Criteria Decision Making Under Single-Valued Neutrosophic Set Environment for Supplier Selection

Multi Criteria Decision Making Under Single-Valued Neutrosophic Set Environment for Supplier Selection

Healthcare procurement in the race to net-zero: Practical steps for healthcare leadership.

Although it is challenging to assess the greenhouse gas emission footprint associated with individual products and services, health leaders can play a pivotal role in emissions reduction by understanding and utilizing available tools and certifications that measure suppliers' operational environmental performance. Integrating environmental standards into procurement and supplier selection has the potential to greatly impact emissions production across the healthcare landscape as it will pressure suppliers to improve their operations in order to be selected. The purpose of this article is to emphasize the importance of the supply chain in addressing healthcare-related greenhouse gas emissions. We provide an overview of the types of tools available that can be used to evaluate the carbon footprints of individual companies and rate their performances, as well as certifications that formally recognize companies' sustainability practices and commitments.

Selection of Packaging Supplier Manufacturing Industry PT. ABC in East Java with An Analytical Hierarcy Process (AHP) Approach

This research was conducted to study and analyze problems related to supplier selection in manufacturing companies. Data collection was carried out by means of interviews, observation and literature study. Data processing uses the AHP approach. The results of data processing using the AHP method can be obtained from several alternative suppliers, namely "GA", "BS", "PO", while the criteria include quality, price and service. Then, using AHP, the results of Suppliers that are recommended to be prioritized by taking into account the three criteria are found in the first order, namely Supplier GA with a priority weight of (0.657), then the second priority order is Supplier BS with a weight of (0.237) and the third priority is Supplier PO with a weight of (0.104).

Relationship between civil construction companies and suppliers: comparative analysis with companies in other sectors

Strategic supplier management establishes criteria for the selection, evaluation, and development of suppliers, in addition to the administration of contracts and supplies. This type of management aims to organize all processes involving suppliers, defining criteria to support decision-making in selecting the best partners, considering those who meet pre-established requirements. Furthermore, efficient management provides closer proximity to suppliers, facilitating relationships, fostering collaborative innovation, improving product costs, and increasing the company's competitiveness. The objective of this work is to analyze the relationship of suppliers in the construction industry and compare it with companies from other sectors. To achieve this objective, an applied, quantitative, and exploratory research was developed through field research. Questionnaires were applied to employees of construction companies and companies from other sectors, such as service providers and large industrial sectors, addressing issues related to organizational characteristics and specific axes that determine the relationship, such as trust, long-term relationship, and information sharing between client and supplier. The collected data were subjected to descriptive and exploratory analyses to observe the divergent and similar characteristics between the two groups. The results indicate that construction companies have gaps in the axes of trust, information sharing, and especially in the sphere of long-term relationships compared to companies in other sectors. This indicates the need for improvements in supplier management practices in the construction industry to achieve a competitive performance more aligned with other industrial sectors. The implementation of more robust strategies and the adoption of better practices in supplier management can help overcome these gaps, resulting in a more efficient and collaborative business environment, with mutual benefits for construction companies and their suppliers.

Enhancing Supplier Selection for Sustainable Raw Materials: A Comprehensive Analysis Using Analytical Network Process (ANP) and TOPSIS Methods

Enhancing Supplier Selection for Sustainable Raw Materials: A Comprehensive Analysis Using Analytical Network Process (ANP) and TOPSIS Methods

Optimizing construction supplier selection in conflict-affected regions: a hybrid multi-criteria framework

AbstractConflicts and wars profoundly impact infrastructure, exacerbating the adversity already caused by natural disasters. Therefore, it is imperative that the reconstruction process be both effective and efficient to expedite a return to normalcy. This study aims to enhance the efficacy of reconstruction efforts through improved construction supplier evaluation and selection. It introduces an innovative hybrid multi-objective decision-making model that integrates a broad spectrum of economic, technical, and humanitarian criteria. The model is designed to optimally select and assign construction suppliers in regions affected by human and natural conflicts and crises. Fifteen criteria have been incorporated into the evaluation process to validate its effectiveness and maximize its contribution to local communities. This methodology streamlines decision-making and enhances transparency in conflict zones, aligning with the interests of all stakeholders. The study incorporates advanced methodologies, including Fuzzy Goal Programming (F-GP), Geographic Information System (GIS)-based Risk Assessment, and Fuzzy Analytic Hierarchy Process (F-AHP), leveraging real-world data and a case study. Additionally, a sensitivity analysis examines the impact of varying inputs on the model's output. The findings attest to the model's utility in conflict-affected regions and its potential applicability in stable settings.

Enhancing Supply Chain Safety and Security: A Novel AI-Assisted Supplier Selection Method

The "Make or Buy” decision and the supplier selection are critical steps for the efficient operation of companies' supply chains. Safety and security are paramount considerations, especially in industries like logistics, where supply chains are vulnerable to external threats and disruptions. In this scientific article, we present a novel Artificial Intelligence (AI)-assisted supplier selection method that significantly enhances the safety and security of suppliers. During our research project, we have created an expert system and a corresponding knowledge base with the relevant rules to support supply chain decision-makers in selecting logistics service providers for warehousing services. The foundation of the AI-assisted supplier selection method is advanced data analytics and the application of expert systems, enabling companies to evaluate potential suppliers in detail from a safety and security perspective. The applied expert systems can identify potential risks and make predictions about supplier performance in the future. In the turbulent environment of the global supply chain, selecting long-term partners like warehousing services providers is critical for the success of the organization. A wrong supplier selection can hardly be reversed in warehousing services, as the cost of change is usually high. The article demonstrates the practical application of the expert system-assisted supplier selection method in a real-world supply chain environment and thoroughly analyzes the achieved results and advantages. The results show that the expert system-assisted method not only increases supplier safety and security but also contributes to improving the efficiency and sustainability of the supply chain. This article provides valuable guidance and solutions for companies looking to enhance their supplier selection using expert system technologies, thereby increasing the safety and security of their supply chains.

Revolutionizing procurement processes in LNG operations: A synthesis of agile supply chain management using credit card facilities

Revolutionizing procurement processes in LNG operations is essential for ensuring efficient and cost-effective supply chain management. This paper presents a synthesis of agile supply chain management (SCM) principles using credit card facilities to streamline procurement processes in LNG operations. The integration of credit card facilities offers a flexible and efficient alternative to traditional procurement methods, enabling LNG companies to adapt quickly to changing market conditions and customer demands. The paper begins by discussing the challenges faced by LNG operations in traditional procurement processes, including lengthy approval processes, limited supplier options, and lack of transparency. It then introduces the concept of agile SCM and its principles, highlighting its potential to address these challenges and improve procurement efficiency. The synthesis of agile SCM principles with credit card facilities is explored in detail, focusing on how this approach can transform procurement processes in LNG operations. By utilizing credit card facilities, LNG companies can simplify the procurement process, reduce paperwork, and improve transaction speed. This approach also offers greater flexibility in supplier selection, allowing companies to quickly onboard new suppliers and respond to market changes. The paper also discusses the benefits of this approach, including cost savings, improved supplier relationships, and enhanced operational efficiency. Case studies and examples are provided to illustrate the application of agile SCM using credit card facilities in LNG operations. In conclusion, the synthesis of agile SCM principles with credit card facilities offers a transformative approach to procurement in LNG operations. By adopting this approach, LNG companies can enhance their competitive advantage, improve procurement efficiency, and drive overall operational excellence in the LNG industry. Keywords: Revolutionizing, Procurement Processes, LNG Operations, Credit Cards Facilities, Agile Supply Chain Management.

Integrated model to optimize supplier selection and investments for cyber resilience in digital supply chains

Digitalization has revolutionized the supply chain networks but also introduces vulnerabilities to the cyber threats. Notably, in past two years, the cyber-attacks on different organizations worldwide have increased at an alarming rate resulting in significant financial loss to supply chains, intellectual property breaches and supply disruptions. As a result, companies are making significant investments in their cybersecurity. However, many incidents were reported where threat actors attacked a company using the shared digital systems with its suppliers. Therefore, it is important that suppliers are selected based on their cyber resilience. This paper identifies the cyber resilience criteria and proposed a multi criteria decision making based framework to evaluate the cyber resilience of a supply chain partner. It has been also realized that investment in organizational cybersecurity alone is not sufficient to protect supply chains. Companies are now investing in increasing their supply chain cyber capabilities. In this direction, paper also proposes a mixed integer linear program (MILP) to jointly optimize supplier selection and cyber investment decisions in a supply chain based on the supplier's current cyber resilience and potential return on the cyber investments made in selected suppliers. Computational experiments are conducted to study the tradeoffs and impact of sourcing strategy, supplier capacity, cyber security investment decisions on supply chain cyber resilience. The findings underscore that an integrated decision making of supplier selection and cyber investments maximizes the supply chain cyber resilience.

A flexible combinatorial auction bidding language for supplier selection and order allocation in a supply chain with price sensitive demand

This study addresses the multi-item multi-sourcing supplier selection and order allocation problem in a Combinatorial Auction (CA) framework. First, we propose a new flexible procurement CA bidding language, then prove that it can convey the same information as existing bidding languages while allowing more efficient auction outcomes and reduced computational complexity. Suppliers submit combinatorial bids to a single manufacturer. Each bid carries information about the supplier’s cost structure and potential discounts. The manufacturer purchases the items and assembles one or more product types that experience price-sensitive demand rates by end consumers. We use the realistic logit function to represent the price-sensitive demand rates of finished products. A Mixed Integer Non-Linear Programming (MINLP) model is developed to help the manufacturer make optimal supplier selection, order allocation, and pricing decisions under the proposed bidding language. The MINLP model considers purchasing, transportation, ordering, administrative, holding, and manufacturing costs. These considerations make the results of this study realistic with the potential to be used in practical applications. Also, we derive a set of necessary conditions that must exist in at least one optimal solution to the problem. These conditions can be utilized to design efficient solution mechanisms for this difficult problem in the future. Finally, an extensive numerical analysis is performed to illustrate the bidding language and the key results.

A proposed framework for supplier selection and order allocation using machine learning clustering and optimization techniques

A proposed framework for supplier selection and order allocation using machine learning clustering and optimization techniques

Smart TOPSIS: A Neural Network-Driven TOPSIS with Neutrosophic Triplets for Green Supplier Selection in Sustainable Manufacturing

Decision-making in complex environments requires advanced methodologies to manage uncertainty and indeterminacy effectively. This research introduces a novel decision-making framework that integrates the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with Neutrosophic Triplets (NTs) to address the limitations of decision-making methods in handling indeterminate information. By incorporating a frequency analysis-based ranking strategy and leveraging neural network-driven machine learning, the proposed method significantly enhances the accuracy and computational efficiency of the decision-making process. The necessity of this research stems from the growing complexity of multi-attribute decision-making (MADM) scenarios where traditional methods fall short in accurately ranking alternatives under uncertainty. The novelty lies in integrating NTs with a machine-learning approach, providing a more flexible and robust framework for MADM. The proposed method’s contributions are demonstrated through its application in green supplier selection, a critical area in sustainable supply chain management. The results reveal that the smart TOPSIS method improves decision accuracy and reduces computational complexity, making it a viable tool for broader applications. Although the proposed methodology is primarily applied to green supplier selection management, it can also be extended to real-world scenarios in various research fields.

Effect of supplier environmental damage on environmental concern and green purchase dynamic capabilities

Objective: Given the importance of sustainability in the supply chain, this study aims to analyze the effect of supplier environmental damage on managers' perception of the need to develop Green Purchasing Dynamic Capabilities (GPDC) and whether this effect is mediated by environmental concern. Method: A full-factorial vignette-based experiment was employed, involving 267 US professionals with management experience. Hypotheses were tested through multiple regression analysis. Results: The responsibility for supplier selection did not have a direct effect on the need to develop GPDC. Controllability of environmental damage did not moderate the effect of responsibility on GPDC development. However, environmental concern mediated the effect of responsibility on the need for GPDC development. Conclusions: This study provides novel insights into the role of management in decision-making related to GPDC and highlights the significant mediating role of environmental concern. These findings elucidate how external and internal company aspects regarding supplier environmental damages interact within the framework of Green Purchasing Dynamic Capabilities.

The predicting role of sustainable supplier selection on lead-time performance in public procurement: relational capability as a moderator

PurposeWith increasing concerns regarding the performance of public procurement, especially concerning timely delivery, this study aims to investigate the predictive role of sustainable supplier selection (SSS) in enhancing lead-time performance in public procurement, while also examining the moderating effect of relational capability.Design/methodology/approachThe study collected primary data from 179 accredited public organizations in Tanzania through structured questionnaires and used partial least squares structural equation modeling for data analysis.FindingsThe results reveal that SSS and relational capability influence lead-time performance in public procurement. Regarding the moderating effect of relational capability, the study establishes that relational capability strengthens the influence of SSS on lead-time performance. Therefore, based on the collected data from surveyed public organizations, relational capability positively moderates the relationship between SSS and lead-time performance in public procurement.Social implicationsThe study offer valuable implications for public procurement practitioners, academics and other stakeholders. Public organizations should consider contemplate integrating sustainability aspects into supplier selection processes. Furthermore, the study contributes to advancing efforts toward achieving sustainable development goals (i.e. SDG12) within Tanzania, particularly by advocating for sustainable public procurement practices aligned with national policies and priorities.Originality/valueThis study not only enhances the understanding of public procurement performance by investigating lead-time improvement, incorporating considerations of SSS and relational capability, but it also offers empirical evidence of the moderating role of relational capability within the unexplored Tanzanian context.