Analytics, Innovativeness, and Innovation Performance

Steffen Wölfl, Alexander Leischnig, Björn Ivens, Daniel Hein (2017)

Based on organizational information processing theory, this paper develops and tests a research model to deepen the understanding about the conditions under which the use of data analytics contributes to innovation performance. This paper suggests that firm innovativeness, as an organization cultural concept, should moderate the relationship between data analytics use and innovation performance. The results of a moderation analysis based on data from cross-sectional survey support this account. The findings indicate a significant inversely U-shaped effect of innovativeness on the relationship between data analytics use and innovation performance. The effect of data analytics use on innovation performance is strongest under medium levels of innovativeness but comparatively weaker when firms have a low or a high level of innovativeness. These insights contribute to the IS literature by clarifying the important role of firm cultural factors in shaping information needs and deployment of information processing capabilities.

Published in ICIS 2017 Proceedings

http://aisel.aisnet.org/icis2017/Strategy/Presentations/18/

Open Access Link

Innovation