Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment
Tóm tắt
With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.
Từ khóa
Tài liệu tham khảo
Antonakis J., 2014, Causality and endogeneity: problems and solutions, Oxford Handbook of Leadership and Organizations, 1, 93
Aspect(2013). ‘Southwest Airlines heads to the cloud with Aspect software to provide best‐in‐class customer experience [Press release]’. Available athttp://www.aspect.com/company/news/press-releases/southwest-airlines-heads-to-the-cloud-with-aspect-software-to-provide-best-in-class-customer-experience[accessed 15 June 2018].
Brinkhues R., 2014, Proceedings of the 20th Americas Conference on Information Systems (AMCIS)
Chin W. W., 1998, The partial least squares approach to structural equation modeling, Modern Methods for Business Research, 295, 295
Davenport T. H., 2012, Data scientist: the sexiest job of the 21st century, Harvard Business Review, 90, 70
Delta(2016). ‘Delta introduces innovative baggage tracking process’. Available athttp://news.delta.com/delta-introduces-innovative-baggage-tracking-process-0[accessed 15 June 2018].
Hair J. F., 2016, A Primer on Partial Least Squares Structural Equation Modeling (PLS‐SEM)
Intel(2016). ‘Accelerating business growth through IT’. Available athttps://www.intel.com/content/dam/www/public/us/en/documents/best-practices/using-big-data-in-manufacturing-at-intels-smart-factories-paper.pdf[accessed 15 June 2018].
Kiron D., 2017, Lessons from becoming a data‐driven organization, MIT Sloan Management Review, 58, 1
LaValle S., 2011, Big data, analytics and the path from insights to value, MIT Sloan Management Review, 52, 21
Liu Y., 2014, Big data and predictive business analytics, Journal of Business Forecasting, 33, 40
Manyika J. M.Chui B.Brown J.Bughin R.Dobbs C.RoxburghandA. H.Byers(2011). ‘Big data: the next frontier for innovation competition and productivity’. Technical Report McKinsey Global Institute.
McAfee A., 2012, Big data: the management revolution, Harvard Business Review, 90, 60
Mikalef P. V. A.Framnes F.Danielsen J.KrogstieandD. H.Olsen(2017a 2018). ‘Big data analytics capability: antecedents and business value’. Paper presented at the Pacific Asia Conference on Information Systems Langkawi Malaysia.
Nunnally J., 1978, Psychometric Methods
Ransbotham S., 2017, Analytics as a source of business innovation, MIT Sloan Management Review, 58, 1
Ransbotham S., 2015, Minding the analytics gap, MIT Sloan Management Review, 56, 63
Ransbotham S., 2016, Beyond the hype: the hard work behind analytics success, MIT Sloan Management Review, 57, 3
Ringle C. M. S.WendeandJ.‐M.Becker(2015).SmartPLS 3. Boenningstedt: SmartPLS GmbH. Available athttp://www.smartpls.com[accessed 12 November 2017].
Ross J. W., 2013, You may not need big data after all, Harvard Business Review, 91, 90
Sagiroglu S.andD.Sinanc(2013). ‘Big data: a review’. Paper presented at the Collaboration Technologies and Systems (CTS) International Conference.
Tushman M. L., 1995, Research in Organizational Behavior, 171