The trickle-down effect of big data use to predict organization innovation: the roles of business strategy alignment and information sharing

Purpose: In this age of digitalization, organizations are generating large data from the organizations' manufacturing processes that are valuable for capturing a competitive edge. Chinese small and medium enterprises (SMEs) can bring organizations radical innovation by investing in innovation projects (i.e. big data use; BDU) using the SMEs' scarce resources. Thus, the authors' research aims to predict Chinese SMEs' radical innovation (RI) through BDU using the theoretical lenses of the resource-based view. Moreover, the authors' study also pursues to realize the undermining mediating process of business strategy alignment (BSA) and the buffering role of information sharing in BDU–RI linkage. Design/methodology/approach: In total, 297 Chinese SMEs entrepreneurs and managers were recruited from the Yangtze River Economic Belt, China using a survey approach. In Mplus 7.4, the authors tested the proposed hypotheses. Findings: The sample of 297 shows that BDU is directly and indirectly (via BSA) related to RI. Further, information sharing moderates the linkage between BDU and BSA and BSA and RI. The association between BSA and RI is only significant and stronger when information sharing is high. Practical implications: This research is beneficial for SME entrepreneurs/managers to enhance the understanding of BDU, eliminate challenges of BSA via BDU and align business strategies to bring RI to Chinese SMEs. Originality/value: SMEs always search for new ways to enhance SMEs' productivity using scarce resources. This is the first research that advances big data and innovation literature by predicting firm RI through BDU using a resource-based view. Moreover, this study is novel because the study investigates the mediation role of BSA and the moderating role of information sharing in the linkage between BDU and firm RI in Chinese SMEs.