Drivers and impact of big data analytic adoption in the retail industry: A quantitative investigation applying structural equation modeling

Abstract

Big data analytics (BDA) adoption has gained attention in both practical and theoretical circles owing to the opportunities and advantages that can be reaped from it. In theory, the majority of researchers have evidenced the benefits of BDA, although barriers to its adoption have also been mentioned. This study draws upon the technology-organisation-environment framework and resource-based view theory to propose an integrated model that examines the drivers and impact of BDA adoption in the retail industry in Jordan. The proposed single model encapsulates the aspects of BDA adoption and performance. The study makes use of an online questionnaire survey to collect the required data, and the research model is eventually validated based on 132 responses gathered from the retail industry in Jordan. The findings highlight two major observations. The first is that relative advantage, organisational readiness, top management support, government support, data variety and data velocity all have a significant influence over BDA adoption. The second observation is that a significant association exists between BDA adoption and firm performance, providing information on the way firms can enhance their BDA adoption for enhanced performance. This study contributes to literature dedicated to examining BDA in terms of its drivers and impact on performance and can be used as a reference in developing nations.