Data Science Professionals’ Innovation with Big Data Analytics: The Essential Role of Commitment and Organizational Context

Abstract

Implementing Big Data Analytics (BDA) has been widely known as a major source of competitiveness and innovation. While previous research suggests several process models and identifies critical factors for the successful implementation of BDA, there is a lack of understanding of how this organizational process is realized by its primary recipients, that is, Data Science Professionals (DSPs) whose innovation with BDA technologies stands at the core of big data-driven innovation. In particular, far less understood are the motivational and contextual factors that derive DSPs’ innovation with BDA technologies. This study proposes that commitment is the force that can attach DSPs to the BDA implementation process and motivate them to engage in innovative behaviors. It also introduces two organizational mechanisms, namely, BDA communication reciprocity and BDA leader theme-specific reputation, that can be employed to develop this constructive force in DSPs. Inspired by this, a theoretical model was developed based on the assertions of Commitment in Workplace Theory and the literature on creativity in organizations to assess the impact of DSPs’ commitment to BDA implementation and organizational context on their innovation with BDA technologies. This study theorizes that communication reciprocity and leader theme-specific reputation influence the three components of DSPs’ commitment (affective, continuance, and normative) to BDA implementation through their perceived participation in organizational decision-making and positive uncertainty, which, in turn, derive DSP’s innovation with BDA technologies. To further enrich the theorization, the moderating role of DSPs’ competency on the effect of DSPs’ components of commitment on their innovation with BDA technologies is investigated. Predictions were tested following an experimental vignette methodology with 240 subjects where the two organizational mechanisms were manipulated. Results indicate that organizational mechanisms provoke mediating psychological perceptions, though with varying strengths. In addition, results suggest that DSPs’ innovation with BDA technologies is primarily rooted in their affective and continuance commitments, and DSPs’ competency interacts with DSPs’ affective commitment to affect their innovation with BDA technologies. This research enhances the theoretical understanding of the role of commitment and organizational context in fostering DSPs’ innovation with BDA technologies. The results of this study also offer suggestions for information systems implementation practitioners on the effectiveness of organizational mechanisms that facilitate big data-driven innovation.