Supplier Selection Practices Research Articles

Sourcing for high technology innovation: Engaging to absorb knowledge pre-contract

This study investigates how firms can identify, access, and capitalize on viable innovation in the high technology supply market during the pre-contractual phase of relationships. The industrial landscape is changing rapidly due to technological advancements like automation and electrification, leading traditional industries to explore new avenues for knowledge and partner selection. However, identifying, assessing, and trusting suppliers with whom firms can enter a relationship is a complex task. Therefore, the study adopts the absorptive capacity perspective for conceptualizing the supplier selection process, focusing on the pre-contractual phase. Based on two in-depth case studies in the automotive industry, we find that supplier selection can be assisted with higher levels of engagement, coordination, and alignment internally with different firm stakeholders and externally with the larger supply market. This study illustrates that new actors bring disruptive innovation into the automotive industry, and the knowledge is absorbed during supplier selection, facilitated by fostering higher levels of engagement, coordination, and alignment both internally among various stakeholders within the firm and externally within the broader supply market. This study significantly advances the understanding of supplier selection practices in the context of high technology innovation. The theoretical contributions made through our empirical investigations enhance the knowledge base on sourcing strategies, shed light on the complexities of supplier selection, and offer practical implications for firms aiming to navigate the rapidly changing landscape of technological advancements.

The Nexus between Supplier Selection Practices and Procurement Function Performance: A Kenyan Public Universities Perspective

Purpose: This study aimed to unveil how supplier assessment and governance influenced procurement function performance.
 Methodology: The study employed a post-positivist research philosophy and a causal-comparative design. The study used multi-stage sampling to arrive at the sample of respondents of 93 procurement officers. Quantitative data was collected through self-designed structured questionnaires and analyzed using Statistical Packages for Social Sciences (SPSS version 27). Demographically, the study included predominantly experienced, educated male and female professionals.
 Findings: The findings of the study revealed that supplier selection significantly and positively impacted procurement function performance. Specifically, supplier assessment exhibited a noteworthy positive effect on procurement function performance (β = .517, p < .001), underlining the critical role of due diligence, evaluations, and appraisals among suppliers. Similarly, supplier governance demonstrated a substantial positive effect on procurement function performance (β = .310, p = .001), highlighting the significant roles of supplier selection transparency and conflict resolution mechanisms in procurement processes.
 Unique Contribution to Theory, Practice and Policy: This study unveiled how supplier assessment and governance influenced procurement function performance anchored in the Resource Dependence Theory (RDT), The study's results confirmed that robust supplier selection practices, grounded in supplier assessment and governance, significantly improved procurement function performance in Kenyan public universities. Strengthening supplier assessment protocols and governance mechanisms emerged as imperative for optimizing outcomes in procurement functions.

Sustainable Supplier Selection using Neutrosophic Multi-Criteria Decision Making Methodology

Sustainable supplier selection is an important part of supply chain management since it encourages ethical and eco-friendly procedures. This study examines the most important criteria and factors for judging the sustainability performance of suppliers and presents a thorough overview of sustainable supplier selection. A decision-making framework for sustainable supplier selection is created via a review of relevant research, case studies, and best practices. Key factors for assessing suppliers include environmental performance, social responsibility, and economic viability, all of which are included in the framework. The results stress the need to take into account suppliers' energy efficiency, waste management, and social responsibility initiatives including fair labor practices and community involvement. Other essential considerations for long-term sustainability include economic viability and supply chain resilience. Organizations may improve their environmental impact, reduce supply chain risks, and boost overall performance by using sustainable supplier selection practices. This study used the TOPSIS method to rank sustainable suppliers. The TOPSIS method is employed with the single-valued neutrosophic set to deal with vague information. A case study in a food company is conducted to show the best supplier

A supply risk perspective integrated sustainable supplier selection model in the intuitionistic fuzzy environment.

With the recent focus on supply risk management in sustainable supply chains, it is more important than ever to evaluate and select the right sustainable suppliers from a supply risk perspective. However, few existing studies consider supply risks from the perspective of all three triple-bottom-line dimensions at the same time. To bridge this research gap, this research constructs a supply risk perspective integrated sustainable supplier selection model in the intuitionistic fuzzy environment. First of all, the weights of decision-makers in the decision-making group are obtained by intuitionistic fuzzy set. Secondly, after obtaining the aggregated intuitionistic fuzzy decision matrix considering the weight of decision-makers, the fuzzy entropy weight method is used to calculate criteria weight, objectively. Then, an improved failure mode and effects analysis is used to undertake risk assessments and to identify high-risk suppliers. Last but not least, the extended alternative queuing method is adopted to rank the eligible sustainable suppliers in the intuitionistic fuzzy environment. The proposed model not only reduces the uncertainty of decision-making in sustainable supplier selection, but also enables focal companies to reduce supply risk in their sustainable supplier selection practices and prevent the failure modes that relate to supply risk. The practicality and effectiveness of the proposed model are verified through an empirical illustration in a leading electrical appliance manufacturer in China.

Aligning Corporate Strategy With Supplier Selection

This article aims to demonstrate if corporate strategy is deployed to purchasing function practices, specifically to select suppliers, considering purchasing categories. The article has a qualitative empirical approach, and it is characterized as descriptive in the specific context of a multinational life science company. Our findings indicate an alignment between corporate strategy and purchasing strategy regarding the elements of corporate strategy, such as innovation, quality, sustainability, delivery, flexibility, and costs. However, the hierarchical cascading of these elements for supplier selection practices does not always occur as in the literature. The results suggest that purchasing categories are determining factors in the strategy alignment. The main contribution of this article is to point out that there is an alignment between corporate strategy and purchasing strategy regarding the main elements of corporate strategy. However, the hierarchical cascading of such criteria for supplier selection practices does not always occur as previously described in the literature, as there are variables that influence this process. This article indicates that purchasing categories are key determinants of strategy alignment, as in each category a combination of criteria has been more relevant and not necessarily aligned with corporate or purchasing strategy.

Supplier-Selection Practices for Robust Global Supply Chain Networks: A Simulation Of The Global Auto Industry

How can companies develop and maintain global supply chain networks that are robust—that is, capable of maintaining an uninterrupted flow of goods and materials—when confronted with a geographically spreading disruption that could cause the shutdown of multiple suppliers at once? To answer this question, this article combines an empirical analysis of supply chain networks of three global automotive manufacturers with computational experiments. The results reveal that even when a small fraction of buyers adopt regionalizing supplier-selection practices—those in which a buyer chooses geographically proximate suppliers, whether to the buyer or its current suppliers—the supply chain network becomes more robust.

Antecedent Factors of Procurement Performance in the Public Health Sector in the Gauteng Province

Public procurement occupies a key role in government departments and public entities. Supplier selection, a sub-function of procurement, has become one of the elementary roles of procurement managers since it virtually affects any industry’s competitiveness. Therefore, selecting suitable suppliers brings substantial benefits to enterprises and increases customer satisfaction. The purpose of this study was to investigate the relationship between supplier selection practices, supplier risk management, supplier commitment, and procurement performance in the public health industry in Gauteng province. The survey material was designed in a structured questionnaire to measure the study constructs. The collected quantitative data were analysed using the SMART-PLS 3 structural equation modelling procedure. The study results showed positive and significant relationships amongst all variables except for one. Supplier risk management had a weak and insignificant connection with procurement performance. The results are essential to the existing literature on procurement performance within public health industries in developing countries such as South Africa. The study concludes by suggesting recommendations for limiting the impact of the identified challenges on procurement performance.

Supplier Selection Practices and Procurement Performance: A Critical Analysis

As market globalization quickens, things to consider when selecting suppliers and the potential suppliers increases. There is a serious concern from the practitioners, government agencies and other stakeholders to what should be done to curb supplier related procurement issues. Evaluation of suppliers is one of the ways an organizations can reduce supplier related inefficiencies. Supplier selection yields positive influence to procurement performance when conducted well. However, what puzzles is the relation hasn’t been the case as different scholars give mixed findings. The objective of the study was to establish the influence of supplier selection on procurement performance in county governments. The study was anchored on stakeholder theory and adopted the multiple case studies design. Units of analysis were 14 LREB county governments, target population 196 staff: chief officers, procurement officers and procurement committee members. Primary data were collected. Pilot results (n=20) reveal 20 item instrument reliability (α=0.9563). The study finding (n=181 92.3%) results in two retained attitudes (positive and negative) comprising 7 items with a good fit (p<.005). Bivariate ordered probit regression analysis reveals supplier selection adoption are significantly associated with procurement performance and multivariate ordered probit regression analysis show supplier certification

The impact of sustainable supplier selection to supplier performance in mining industry: ethical culture as moderating variable

Sustainable supplier selection during tender is one of the critical factors in the supply chain management to maintain sustainable procurement in an organisation. Many factors contribute to the success of sustainable supplier selection practices, and ethical culture is one of the factors because it would influence supplier selection. This study aims to determine the effect of implementing sustainable supplier selection on supplier performance by moderating the effect of ethical culture in the mining industry. This type of research is explanatory research with hypothesis testing of 104 respondents by distributing questionnaires. The data analysis is conducted by Structural Equation Model (SEM). The research shows that the construct of sustainable supplier selection with economic, social, and environmental aspects as dimensions has a direct and significant impact on supplier performance in the mining industry. This research also shows that ethical culture has a significant moderating effect in the relationship between sustainable supplier selection and supplier performance. The managerial implication of this research is providing guideline for decision-makers to implement sustainable supplier selection by considering economic, social, and environmental aspects while maintaining an ethical culture as a part of work professionalism to maintain sustainable performance in the mining industry.

EFFECT OF THE SUPPLIER SELECTION ON SUPPLY CHAIN EFFICIENCY IN COUNTY GOVERNMENT OF NANDI

Purpose: The main purpose of this study was to evaluate the effect of supplier selection on the supply chain efficiencies in the county Government of Nandi. The study was guided by the following theories: transaction cost theory and the contingency theory. The study employed an explanatory survey which was cross-sectional in time dimension.
 Methodology: A proportionate stratified random sampling based on departmental section was utilized. The primary data collection procedure involved a survey where a self–administered questionnaire was used. With reference to content validity, the questionnaire was reviewed by a panel of experts before pilot testing was done. Once the data was cleaned, sorted and entered, it was analysed through the use of descriptive analysis (frequency distribution, means, standard deviation) with the data being presented in tabular and pictorial format. The inferential statistics (multiple regression), will be conducted at 95 per cent confidence level with significance levels of 0.05. The results were displayed using tables.
 Findings: The findings of the study indicated that supplier selection practices had positive and significant influence on supply chain efficiency, Kenya (β =0.114; p<0.05. The concluded that supplier selection is the predictor of supply chain efficiency of county government of Nandi. The study recommended that the county government of Nandi other organizations at large should show more commitment in SRM by having systems to monitor and appraise and evaluate performance at a strategic level.
 Unique contribution to theory, practice and policy: The study could be replicated in other industry sectors of the economy to build on the body of knowledge of supplier selection on performance of organizations.

An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection

Supplier selection is one of the most important multi-criteria decision-making (MCDM) problems for decision-makers in the competitive market. Today’s organizations are seeking new ways to reduce the negative effects they have on the environment and to achieve a greener system. Currently, the concept of green supplier selection has gained great importance for its ability to incorporate environmental or green criteria into classical supplier selection practices. Therefore, in this study, a multi-phase MCDM model based on the best-worst method (BWM) and the interval type-2 fuzzy technique for order preference by similarity to ideal solution (IT2F TOPSIS) is proposed. A case study in a plastic injection molding facility in Turkey was carried out to show the applicability of the proposed integrated methodology. The paper offers insights into decision-making, methodology, and managerial implications. Results of the case study are examined and suggestions for future research are provided.

Some generalized Pythagorean 2-tuple linguistic Bonferroni mean operators in multiple attribute decision making

Green supply chain management is a strategy which strengthens and integrates environmental consideration into whole supply chain. The green strategic supplier plays an important role in the implementation of green supply chain strategy. In the selection methodology of a strategic green supplier, some special requirements are needed which are different from the traditional supplier selection practices. In this paper, we combine the generalized weighted BM operator with Pythagorean 2-tuple linguistic numbers to propose the generalized Pythagorean 2-tuple linguistic-weighted Bonferroni mean operator, and then the multiple attribute decision-making methods are developed based on this operator. Finally, we use an example for green supplier selection to illustrate the multiple attribute decision-making process of the proposed methods.

A Novel Integrated Approach for Green Supplier Selection with Interval-Valued Intuitionistic Uncertain Linguistic Information: A Case Study in the Agri-Food Industry

With strengthening global consciousness of environmental protection, green supply chain management plays an increasingly important role in modern enterprise production operation management. A critical means to implement green supply chain management is incorporating environmental requirements into the supplier selection practices. In this paper, we put forward a novel integrated approach by using interval-valued intuitionistic uncertain linguistic sets (IVIULSs) and grey relational analysis (GRA)-technique for order preference by similarity to ideal solution (TOPSIS) method for the evaluation and selection of green suppliers. First, various qualitative assessments of alternatives provided by decision makers are described by the IVIULSs. Then, the GRA-TOPSIS method is extended and employed to prioritize the alternative suppliers. The proposed model can handle the uncertainty and fuzziness of decision makers’ subjective evaluations more easily and get a more realistic and accurate ranking of green suppliers. Finally, an illustrative example in the agri-food industry is presented to verify the proposed green supplier selection model and demonstrate its practicality and effectiveness.

Supplier selection: a proposed framework for decision making

This article presents and performs a preliminary validation of a framework for supplier selection. It makes use of, in sequence, Kraljic's supplier relationship portfolio and the multi-criteria decision tool named the analytic hierarchy process (AHP). The proposal's main objective is to provide companies with a practical and easy-to-use tool for classifying the importance and criticality of raw materials and for selecting suppliers based on a hierarchy. One result of this action-based study is the preliminary validation of the proposed model through its application in an electronics company. The application of the method suggests an improvement in the company's supplier selection practices related to one key item of one of its products.

Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

Purpose: The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM). Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS) problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model is developed to tackle this problem.Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value mesurement (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multi-objective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis.Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability.Research limitations/implications: Although the fuzzy expected value model (EVM) with fuzzy coefficients constructed in present research should be helpful for solving real world problems. A detailed comparative analysis by using other algorithms is necessary for solving similar problems of agriculture, pharmaceutical, chemicals and services sectors in future.Practical implications: It can help the decision makers for ordering to different supplier for managing supply chain performance in efficient and effective manner. From the procurement and engineering perspectives, minimizing cost, sustaining the quality level and meeting production time line is the main consideration for selecting the supplier. Empirically, this can facilitate engineers to reduce production costs and at the same time improve the product quality.Originality/value: In this paper, we developed a novel multi-objective programming model based on genetic algorithm to select sustainable strategic supplier (SSSS) under fuzzy environment. The algorithm was tested and applied to solve a real case of textile sector in Pakistan. The experimental results and comparative sensitivity analysis illustrate the effectiveness of our proposed model.

Supplier selection in small- and medium-sized firms

Purpose The purpose of this paper is to empirically examine supplier selection among small- and medium-sized firms in the US textile and apparel industry. For small- and medium-sized firms, one powerful method of improving the firm’s competitiveness in the dynamic business environment is through strategic approach of supplier selection, which emphasizes supplier’s contributions to the total product and to overall customer satisfaction. Design/methodology/approach Empirical survey-based research methodology was implemented and data were collected from small and medium firms in textile and apparel business in North Carolina, South Carolina, Georgia, California, and New York which are the major areas of the US textile and apparel industry. Findings This study demonstrates the supplier selection practices of the small- and medium-sized firms in the US textile and apparel industry and their perceptions of supply market and supplier evaluation systems. Results indicate that supplier selection criteria impact firm performance in different ways. Small- and medium-sized firms carry out supplier selection based on product quality, supplier responsiveness, and strategic consideration which positively impact overall customer service level and overall customer satisfaction. Originality/value This paper focuses on supply chain management practices, specifically the supplier selection issue in small- and medium-sized firms in the textile and apparel industry.

Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry

The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of three popular multi-criteria supplier selection methods in a fuzzy environment. The incorporation of fuzzy set theory into TOPSIS, VIKOR and GRA methods is thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the agri-food industry. Our comparative analysis for this case study indicates that the three fuzzy methods arrive at identical supplier rankings, yet fuzzy GRA requires less computational complexity to generate the same results. Additional analyses of the numerical results are completed on the normalization functions, distance metrics, and aggregation functions that can be used for each method.

English

Increasing importance of Supply Chain Management (SCM) is forcing organizations to reconsider and improvise their purchasing related matters. In lieu to that, the supplier selection process plays an important role in the purchasing activity. The supplier selection process has undergone significant changes during the past forty years. These changes have been beneficial to both the purchasing clients and the suppliers. The supplier selection decision making involves multi-criteria comprising both qualitative and quantitative criteria. Sometimes, there might be some contradictions between tangible and intangible criteria which may necessitate trade-off between the conflicting criteria. This paper provides an overall picture of research on supplier selection problems and supplier selection practices. Different selection criteria, emerging issues of supplier selection and the solutions are summarized. This review showed that the application of structured decision making technique is important especially under the complex condition that involves both the qualitative and quantitative criteria.

Strategic supplier selection: some emerging issues and challenges

Strategic sourcing plays a critical role in supply chain planning. Supplier selection represents one of the most important functions to be performed by the purchasing department that determines the long-term viability of a company. The supplier selection is a multi-criteria problem, which includes both qualitative and quantitative criteria. In order to select the best suppliers, it is necessary to make a tradeoff between tangible and intangible criteria, some of which may conflict. This paper provides an overall picture of research on Supplier Selection Process (SSP) and supplier selection practices. It deals with the 'supplier selection problem', where a state of the art is presented. We summarise the different selection criteria, the various problems of suppliers' selection and the existing methods to solve these problems. Furthermore, emerging issues and challenges resulting to scope for future works on supply chain procurement activities are identified and some clear guidelines for future research are proposed. It is aimed that the findings will lead to new research settings together with the directions for future research.

Supplier Selection Practices among Small Firms in the United States: Testing Three Models

One of the issues investigated in recent studies on small business enterprises involves the role of supply chain management. Supply chain management has become an important part of strategic planning in both large and small businesses in the 1990s as firms increasingly choose outsourcingas an externally‐driven strategic growth path. This study examines the supplier selection practices among 78 small business executives in the midwest United States by testing three models: rational/normative, external control, and strategic choice. Although the results show support for all three models, the rational/normative model emerges as the most significant model for predicting the supplier selection practices of small firms.