What “V” of the big data influence SMEs' open innovation breadth and depth? An empirical analysis

Abstract

The open innovation (OI) paradigm has garnered relevant attention in recent years. Against this backdrop, this study explores the impact of a relatively recent phenomenon, such as Big Data, in terms of Volume, Velocity, and Variety, on small and medium enterprises' (SMEs') OI search. In fact, while issues related to Big Data have been often examined in the context of high-tech firms, the effects on SMEs' OI search strategies have not been extensively studied. This paper addresses this gap by developing a quantitative analysis on a sample of 123 Italian SMEs. The findings reveal that Big Data significantly influences SMEs' OI breadth, leading to increased external collaborations. In parallel, they do not affect SMEs' OI depth. Moreover, the impact varies among the different “3Vs” of Big Data, suggesting that some characteristics have a more pronounced effect on SMEs' OI strategies. Drawing on these insights, this study contributes to the understanding of the interplay between Big Data characteristics and SMEs' OI, offering hopefully valuable implications for both OI and Big Data literature and proposing avenues for further research and practice.