An empirical investigation on big data analytics (BDA) and innovation performance

Nowadays, big data analytics (BDA) have widely used in our business environment as an undeniable function for firms to not only survive in turbulence but also have the opportunity to be ahead of their major competitors. One of the promising aspects of BDA relates to its influence on innovation performance. In line, the present study proposed a conceptual model in order to investigate the relationship between BDA use and innovation performance by considering the role of dynamic capability (DC) theory. In this research, we consider firm agility in terms of DC theory and decompose it into three main factors contacting sensing agility, decision making agility, and acting agility. The research model and required data were analyzed using Partial Least Squares (PLS)/Structured Equation Modelling (SEM). The outcome of this study indicates that firms would be able to increase their innovation performance from a DC theory. This study also shows that BDA use has a positive influence on sensing agility of firms.