A framework for technology-based factors for knowledge management in supply chain of auto industry

Abstract

Purpose – The main aim of this study is to provide a framework for technology-based factors for knowledge management in supply chain. Design/methodology/approach – This is an applied research and has been done as a survey in Iran Khodro and Saipa Company as the largest companies in automotive industry of Iran. In this study, 206 experts participated. Reliability methods were Cronbach’s alfa, and validity tests were content and construction analyses. In response to one main question and three sub-questions in this research, first and second confirmative factor analysis were used. Findings – In this research, after a literature review, a comprehensive framework with three factors is presented. These factors are information technology (IT) tools, information systems integration and information security management. The findings indicate that the first framework in supply chain of the automotive industry has a good fitness and perfect validity. Second, in this framework, factors have also been considered based on importance. The technique of factor analysis was given the highest importance to the information systems integration. Then, IT tools and, ultimately, information security management are considered. In addition, findings indicate that information systems integration has the highest correlation with IT tools. Originality/value – The main innovation aspect of the research is to present a comprehensive framework for technology-based factors and indices for knowledge management in supply chain. In this paper, in addition to presenting a grouping for IT tools for knowledge management processes in supply chain, key indices for information systems integration and information security management are also referred.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 13 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.