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Does data-driven culture impact innovation and performance of a firm? An empirical examination

Author

Listed:
  • Sheshadri Chatterjee

    (Indian Institute of Technology Kharagpur)

  • Ranjan Chaudhuri

    (National Institute of Industrial Engineering (NITIE))

  • Demetris Vrontis

    (University of Nicosia)

Abstract

Data-driven culture is considered to bring business-oriented cultural transformation to a firm. It is considered to provide substantial dividends to the firms’ product and process innovations. Recently, several firms have been using different advanced technology-embedded business analytics (BA) tools to improve their business performance. Again, advancement of information and communication technology has helped firms to explore the option to use BA tools with artificial intelligence. This has brought radical change in the business-oriented cultural landscape of the firms to arrive at accurate decision-making to improve their innovation and performance. In this perspective, the aim of this study is to show how a firm’s data-driven culture impacts its product and process innovation, which in turn improves its performance and provides better competitive advantage in the current business environment. With the help of background study, a resource-based view model and different theories, a conceptual model has been developed. The conceptual model has been validated with 456 usable responses from the employees of different firms using different business analytics tools. The study highlights that data-driven culture highly influences both product and process innovation, making the firm more competitive in the industry. In this study, leadership support and data-driven culture have been taken as moderators, whereas firm size, firm age and industry type have been taken as control variables.

Suggested Citation

  • Sheshadri Chatterjee & Ranjan Chaudhuri & Demetris Vrontis, 2024. "Does data-driven culture impact innovation and performance of a firm? An empirical examination," Annals of Operations Research, Springer, vol. 333(2), pages 601-626, February.
    • Handle: RePEc:spr:annopr:v:333:y:2024:i:2:d:10.1007_s10479-020-03887-z
    DOI: 10.1007/s10479-020-03887-z
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