Big Data Analytics as an Enabler of Process Innovation Capabilities: A Configurational Approach
Journal article, Peer reviewed
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Original versionLecture Notes in Computer Science. 2018, LNCS 11080 426-441. 10.1007/978-3-319-98648-7_25
A central question for information systems (IS) researchers and practitioners is if, and how, big data can help attain a competitive advantage. Anecdotal claims suggest that big data can enhance a firm’s incremental and radical process innovation capabilities; yet, there is a lack of theoretically grounded empirical research to support such assertions. To address this question, this study builds on the Resource-Based View and examines the fit between big data analytics resources and organizational contextual factors in driving a firm’s process innovation capabilities. Survey data from 202 chief information officers and IT managers working in Norwegian firms is analyzed by means of fuzzy set qualitative comparative analysis (fsQCA). Results demonstrate that under different patterns of contextual factors the significance of big data analytics resources varies, with specific combinations leading to high levels of incremental and radical process innovation capabilities. These findings suggest that IS researchers and practitioners should look beyond direct effects, and rather, identify key combinations of factors that lead to enhanced process innovation capabilities.