Impact of big data analytics & machine learning on innovation of manufacturing companies

Abstract

Developments in Business Analytics in the era of Big Data have furnished unprecedented possibilities for businesses to innovate. With insights gained from Business Analytics, businesses are in a position to cultivate new or even enhanced products/services. Nevertheless, not many scientific studies have examined the mechanism whereby Business Analytics plays a role in a firm 's innovation results. This particular analysis aims to deal with this gap by empirically and theoretically checking out the connection between Business Analytics as well as innovation. In order to do this aim, absorptive capability principle is employed as a theoretical lens to understand the improvement of a research version. Absorptive capacity theory describes a firm 's potential to understand the importance of fresh, external info, assimilate it and put it on to commercial ends. The study model covers the usage of Business Analytics, innovation, data-driven culture, environmental scanning, along with competitive advantage. The study design is examined by way of a questionnaire survey of 228 USA companies. The results suggest that Business Analytics specifically increases green scanning which helps you to improve a company 's development. Business Analytics also specifically enhances data driven culture which in turn impacts on green scanning. Data-driven culture plays another essential function by moderating the impact of green scanning on new product meaningfulness. The findings show the beneficial effect of company analytics on development and the pivotal roles of green scanning as well as data driven culture. Organizations wishing to realize the possibility of Business Analytics thus require changes in both their internal and external focus.