Structural equation modeling of E-supplier selection criteria in mechanical manufacturing industries

• Published in: Journal of cleaner production Vol. 311; p. 127597
• Main Author: Garg, Ramesh Kumar
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.08.2021
• Subjects: antagonists; decision making; e-supplier selection; e-supply chain; equations; globalization; infrastructure; Mechanical manufacturing industries; regression analysis; Structural equation modeling; Supplier criteria; e-supplier selection; Structural equation modeling; e-supply chain; Supplier criteria; Mechanical manufacturing industries
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2021.127597

In today's world of globalization and intense technical competence, the relationship between the mechanical manufacturers and the e-suppliers has turned from antagonist to cooperative. The key factor that maintains such relationships depends on the selection criteria that the manufacturers adopt. This present study selects mechanical manufacturing industries as research subjects to explore the critical e-supplier selection criteria and relationships among these criteria with previous studies' aid. The study will apply Structural equation modeling (SEM) to verify the critical criteria derived and evaluate each key factor's impact based on the modeling results. The study also provides a systematic appraisal of the published literature in Web of Science (WoS)/Scopus databases for the period 1995–2020 for selection criteria and 2005–2020 for selection criteria methods. The analyses extract 52 selection criteria and four significant categories of selection methods. The goodness-of-fit indices validate structural equation model consisting of forty-four criteria divided into eight factors representing the overall e-supplier selection problem to the extent of 94%. Finally, Regression analysis provides the ranks and priority weights of selection criteria. The cost (23.2%) has emerged as the most significant criterion, followed by quality (14.1%) and delivery (12.5%), whereas infrastructure and environment concern (4.5%) ranks at the lowest, followed by management systems (7%). The results of the hypotheses testing uncovered that 14 hypotheses support the model. The research findings may help organizations gain a thorough and better understanding of the selection criterion concepts to enhance their effectiveness, triumph, and competitiveness. The results show that applying a structured decision-making technique is vital, especially under complex conditions that include qualitative and quantitative criteria. •A novel method is proposed to evaluate and rank e-supplier selection criteria.•The systematic appraisal of 724 articles covers three decades (1995–2020).•Interrelationship degree among e-supplier selection criteria analyzed using SEM.•Cost, quality and delivery are the most dominating e-supplier selection criteria.•The paper concludes with limitations and future scope for the use of SEM + MCDM.