The effect of IoT capability on supply chain integration and firm performance: An Empirical study in the UK Retail industry.

Résumé Fr

Purpose- The purpose of this study is to use empirical data to examine the hierarchical impact of the Internet of Things capability on supply chain integration, supply chain capability and firm performance in the UK retail industry.Design/Methodology/approach-A deductive approach was employed to carry out this research. Structural Equation modelling (SEM) was performed using the Partial Least Square method (SmartPLS 3.3.3) to test theoretical predictions which underlie the relationships among IoTC, SCI, SCC, and firm performance. Data is collected using an online survey completed by senior executives of 66 large, medium, and small firms within the UK retail industry.Findings- The empirical results of this research reveal that IoTC has a significant positive effect on the UK retail industry firm performance through the mediating role of supply chain integration and supply chain capability.Practical Implications- The research results from this study provide useful management insights for firms within the retail industry into the development of effective strategies for integrating their supply chain alongside the adoption of IoTC into supply chain integration, consequently leading to improvements in firm performance.Originality/value- Although previous studies have explored the impact of IoT on firm performance through the sequential mediating role of SCI and SCC, few have explored the impact of the IoT capability on firm performance through sequential mediators, i.e., SCI and SCC. This study examines the relationship between IoT capability, SCI, SCC and FP in the UK retail industry supply chain to address this knowledge gap. Moreover, this study examines the effects ofIoT capability on firm performance by applying PLS-SEM techniques. Testing the sequential mediating role of SCI and SCI is undertaken, and analysing the relationships among IoT-enabled SCI and SCC to improve firm performance. The robustness check's result through PLSpredict analysis also confirms the power of the model proposed in this study.