Purpose The purpose of this paper is to explore the impact of information technology (IT) on supply chain performance in the automotive industry. Prior studies that analyzed the impact of IT on supply chain performance report results representing the situation of the “average industry.” This research focuses on the automotive industry because of its major importance in many national economies and due to the fact that automotive supply chains do not represent the supply chain of the average industry.Design/methodology/approach A research model is proposed to examine the relationships between IT capabilities, supply chain capabilities, and supplier performance. The model divides IT capabilities into functional and data capabilities, and supply chain capabilities into internal process excellence and information sharing. Data have been collected from 343 automotive first-tier suppliers. Structural equation modeling with partial least squares is used to analyze the data.Findings The results suggest that functional capabilities have the greatest impact on internal process excellence, which in turn enhances supplier performance. However, frequent and adequate information sharing also contributes significantly to supplier performance. Data capabilities enable supply chain capabilities through their positive impact on functional capabilities.Practical implications The findings will help managers to understand the effect of IT implementation on company performance and to decide whether to invest in the expansion of IT capacities.Originality/value This research reports the impact of IT on supply chain performance in one of the most important industries in many industrialized countries, and it provides a new perspective on evaluating the contribution of IT on firm performance.

Additional Metadata
Persistent URL dx.doi.org/10.1108/JEIM-03-2017-0038, hdl.handle.net/1765/112657
Journal Journal of Enterprise Information Management
Fuchs, C, Beck, D., Lienland, B., & Kellner, F. (2018). The role of IT in automotive supplier supply chains. Journal of Enterprise Information Management, 31(1), 64–88. doi:10.1108/JEIM-03-2017-0038