دانلود رایگان مقاله انگلیسی داده های بزرگ - سودهای کلان؟ ارتباط بین تحلیل کلان داده و نوآوری - تیلور و فرانسیس 2018

ABSTRACT

This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance in terms of product innovations. Since big data technologies provide new data information practices, they create novel decision-making possibilities, which are widely believed to support firms’ innovation process. Applying German firm-level data within a knowledge production function framework we find suggestive evidence that big data analytics is a relevant determinant for the likelihood of a firm becoming a product innovator as well as for the market success of product innovations. These results hold for the manufacturing as well as for the service sector but are contingent on firms’ investment in IT-specific skills. Overall, the results support the view that big data analytics have the potential to enable innovation.

7. Conclusions

This paper investigates the relationship between the use of big data analytics and firms’ innovative performance. As big data and associated technologies are changing the way information is generated and made relevant, they are widely expected to affect established ways of decision-making within the firm. Better informed decision-making based on novel data practices can be particularly advantageous for business processes involving high uncertainty and risk. Therefore, big data analytics has raised expectations of being particularly beneficial for the firms’ innovation process. In addition to improving the innovation process through new and higher quality information, big data technologies can furthermore be at the core of the innovation itself and generate new innovative digital products and services.

We provide large-scale empirical evidence on this widely discussed relation between big data analytics and innovation. Our empirical analysis exploits survey data on 2706 manufacturing and service firms in Germany within a classical knowledge production function framework. Our results show that the use of big data analytics is associated with a higher propensity to innovate, as well as a higher innovation intensity, which we measure by the sales share resulting from new products or services and which constitutes a measure of the market success of the firms’ innovations. Importantly, this relation holds when we control for the use of mature software systems and data technologies, such as Enterprise Resource Planning Software, which lack more sophisticated features encompassed by big data analytics.