Abstract
Big data analytics is a prominent tool of value, capable of developing competitive advantage and better company efficiency. This paper presents the first empirical exploration of the theoretical design, since the mediating consequences of four value development mechanisms on the connection between big data analytics abilities and four benefit targets. The four value development mechanisms investigated are proactive adaptation, discovery, access, and transparency, while the four benefit goals are business efficiency, business process improvement, consumer experience as well as industry enhancement, and product as well as service innovation. The proposed empirical validation design uses an econometric analysis of information gathered by a survey involving 129 business development center (BDC) professionals in France. The results show that transparency mediates the connection for all value targets, while entry and practical adaptation mediate just in case of some worth targets, and discovery doesn’t have some mediating outcome. Practical and theoretical implications are discussed in the conclusion of the paper.
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