Supplier Selection In Industry Research Articles

Building dynamic capabilities in supplier selection in industry 4.0 era: A literature review

Firms are striving to improve their operational capacities and maintain competitive advantages in light of challenges presented by globalization, evolving consumer preferences, prolonged external disruptions, and advancements in industry 4.0. Given that their suppliers have an impact on their competitive advantages, firms must ensure that the selection process for suppliers includes dynamic capabilities such as sustainability, resilience, and digitalization. This is crucial for maintaining competitiveness and effectively managing external disruptions. The objective of this article was to provide an analysis of recent literature on supplier selection through a descriptive and thematic analysis. By examining dispersed literature, this study has developed a framework for supplier selection rooted in building dynamic capabilities of whole supply chain with three important dimensions—resilience, sustainability, and digitalization. Findings of the study will assist managers to improve their supply chain performances, particularly in their supplier selection and evaluation by highlighting the crucial role of dynamic capabilities.

Decision Models for Supplier Selection in Industry 4.0 Era: A Systematic Literature Review

Industry 4.0 comprises the application of different technological solutions so that business processes throughout the production chain are integrated. The supplier’s selection, considering the industry 4.0 requirements, is essential in promoting collaborative strategies between suppliers and manufacturers. In this context, this study presents a systematic literature review about quantitative models to support supplier selection in the industry 4.0 era. Fourteen studies were reviewed and characterized in different perspectives such as modelling, application, and validation of the decision model. The results revealed that most of the decision models were developed combining multicriteria decision-making (MCDM) with Artificial Intelligence (AI). Among the criteria related to the Industry 4.0 environment, the most frequent ones were information sharing, technological capacity, digital collaboration and engagement. The gathered results can be useful to guide researchers and managers in the development of computational tools to assist decision-making processes for supplier selection in Industry 4.0 era.

Analytic Method for Decision Support of Blockchain Technology Supplier Selection in Industry 4.0 Era

Abstract The article presents the issues covering the modern methods of securing data in both manufacturing processes and companies within the concept of Industry 4.0. In this approach, research problems arose how to implement the right method of secure data sending in sales, manufacturing and distribution processes. It is a very important issue for manufacturing companies as well as how the process of sending electronic data should be safely conducted. While current researches concentrated on the method of blockchain secured electronic documents, there is almost no research concentrating on blockchain integrator selection criteria. The main purpose of this paper is to provide a decision assistance model based on multiple criteria decision analysis technique. Also, mutual relationships between parameters for the assessment of integrators are established. In the article, a Multi-Criteria Decision Analysis (MCDA) was used to assess these characteristics. The Decision Making Trial and Evaluation Laboratory (DEMATEL) technique was chosen for this assessment.

Supplier selection for industry: a fuzzy rule-based scoring approach with a focus on usability

Compared to other selection problems, supplier selection is a particularly challenging application as often there's incomplete or imprecise information about the candidates and the key factors frequently are frequently difficult to quantify. Although the literature is replete with research to support this process, supplier selection decisions remain firmly in the domain of the human expert, while sophisticated decision support methodologies go unused in industry. This paper explores the issue of usability in supplier selection literature and proposes a usability focused methodology that combines elements from fuzzy rule-based expert systems and attribute scoring approaches. The objectives are twofold: to capture the nuances of supplier evaluation to the extent that will satisfy decision makers and to accomplish this in an intuitive manner so that the methodology can find acceptance in industry. The methodology is followed by a discussion of the tests carried out with an apparel company.