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An empirical investigation on big data analytics (BDA) and innovation performance

Published:12 September 2019Publication History

ABSTRACT

Nowadays, big data analytics (BDA) have widely used in our business environment as an undeniable function for firms to not only survive in turbulence but also have the opportunity to be ahead of their major competitors. One of the promising aspects of BDA relates to its influence on innovation performance. In line, the present study proposed a conceptual model in order to investigate the relationship between BDA use and innovation performance by considering the role of dynamic capability (DC) theory. In this research, we consider firm agility in terms of DC theory and decompose it into three main factors contacting sensing agility, decision making agility, and acting agility. The research model and required data were analyzed using Partial Least Squares (PLS)/Structured Equation Modelling (SEM). The outcome of this study indicates that firms would be able to increase their innovation performance from a DC theory. This study also shows that BDA use has a positive influence on sensing agility of firms.

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      cover image ACM Other conferences
      ICBIM '19: Proceedings of the 3rd International Conference on Business and Information Management
      September 2019
      205 pages
      ISBN:9781450372329
      DOI:10.1145/3361785

      Copyright © 2019 ACM

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      Publication History

      • Published: 12 September 2019

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