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Adoption of robust business analytics for product innovation and organizational performance: the mediating role of organizational data-driven culture

Author

Listed:
  • Ranjan Chaudhuri

    (National Institute of Industrial Engineering (NITIE))

  • Sheshadri Chatterjee

    (Indian Institute of Technology Kharagpur)

  • Demetris Vrontis

    (University of Nicosia)

  • Alkis Thrassou

    (University of Nicosia)

Abstract

In the present digital environment, a data-driven organizational culture has become a vital emerging driver of organizational growth. This data-driven culture has assumed an advanced shape due to adoption of artificial intelligence (AI) integrated business analytics tools in the organization. Data-driven culture in the organization could considerably impact product innovation strategy as well as organizational process alteration. In this context, the aim of this study is to investigate how an organization’s data-driven culture impacts process performance and product innovation that led to enhanced organizational overall performance and higher business value. Methodologically, supported by relevant extant literature and inputs from the resource-based view and dynamic capability theories (organizational context), a conceptual model and a set of hypotheses are initially developed. These are subsequently statistically validated through a survey involving 513 usable responses from employees of different organizations using business analytics tools embedded with AI capability. The findings demonstrate that an organizational data-driven culture has considerable moderating impact on product innovation and process improvement, which ultimately enhance business value through improved organizational overall performance.

Suggested Citation

  • Ranjan Chaudhuri & Sheshadri Chatterjee & Demetris Vrontis & Alkis Thrassou, 2024. "Adoption of robust business analytics for product innovation and organizational performance: the mediating role of organizational data-driven culture," Annals of Operations Research, Springer, vol. 339(3), pages 1757-1791, August.
    • Handle: RePEc:spr:annopr:v:339:y:2024:i:3:d:10.1007_s10479-021-04407-3
    DOI: 10.1007/s10479-021-04407-3
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