Better understanding of technology effects in adoption of predictive supply chain business analytics among SMEs: fresh insights from developing countries

Purpose This study contributes to the supply chain management (SCM) literature differently. It offers insightful information about the use and adoption of technologies for small and medium-sized enterprises (SMEs) in developing countries. Some challenges regarding the predictive supply chain business analytics (SCBA) tools and their prediction remain unexplored and require addressing and examination in developing economies. Therefore, this study examines the substantial roles of relative advantage (RA) and compatibility (Comp.) in using technology in predictive SCBA adoption among SMEs in developing countries. Design/methodology/approach This paper performed a quantitative survey-based study to analyze the substantial role of RA and Comp. with the aim of using predictive SCBA adoption. To this end, the author conducted an online survey through which 262 SMEs from developing countries (i.e. Jordan, Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), Egypt, Turkey and Qatar) only responded by email. Findings The partial least squares structural equation modeling (PLS-SEM) clearly shows a significant relationship between RA and predictive SCBA adoption. Still, Comp. does not significantly affect the use of predictive SCBA adoption. Originality/value Such findings of this study can provide insightful implications for stakeholders and policymakers regarding the importance of using predictive SCBA adoption in SMEs in developing countries.