Are digital technologies killing future innovation? The curvilinear relationship between digital technologies and firm's intellectual property

Abstract

PurposeThe study aims to investigate the interplay among digital technologies, intellectual capital and innovation. Thus far, there have been scant research on such intricate bundle of interactions. Also, the findings of previous studies were rather inconclusive, because conflicting results emerged over time. Building on the existence of heterogeneous evidences, this study solved the detected criticism by suggesting a curvilinear relationship among digital technologies, digital skills of human capital and intellectual property. Specifically, we argue that the relationship between digital technologies and intellectual property is inverted u-shaped.Design/methodology/approachHypotheses are tested by applying a generalized linear model (GLM) regression analysis and a quadratic model for non-linear regression. The study analysed a large-scale sample of micro-data drawn from Eurostat. Such sample embraces the population of firms operating in all European member states.FindingsOverall, the results of the study confirm that digital technologies are curvilinearly related to intellectual property. Precisely, the curve is inverted u-shaped. Notably, results show that digital skills only matter when employees have very demanding duties to accomplish. In all other cases, digital skills do not affect intellectual property significantly.Research limitations/implicationsThe research is solely focused on firms' operating in the European Union. Future studies should extend the analysis to other geographies.Practical implicationsAt a real impact level, the study suggests that intellectual property is only partially fostered by digital skills and digital technologies. In this sense, digital skills might be overrated.Originality/valueDifferently from prior research, this study originally detangles the impact of digital technologies on firm's intellectual capital by suggesting the existence of an inverse u-shaped relationship between variables.