Author
Listed:
- MARYAM AL KAMZARI
(Faculty of Business and Law, The British University in Dubai (BUiD), Dubai, United Arab Emirates)
- FARZANA ASAD MIR
(Faculty of Business and Law, The British University in Dubai (BUiD), Dubai, United Arab Emirates)
- ABUBAKR SULIMAN
(Faculty of Business and Law, The British University in Dubai (BUiD), Dubai, United Arab Emirates)
Abstract
Big data governance, along with big data analytic capabilities (BDACs) and organisational agility, is expected to increase the organisation’s innovation performance. Drawing on the resource-based view, the dynamic capabilities view, and the literature on big data governance and BDACs, this study examines the relationship between big data governance and innovation performance, while focussing on the mediating roles of BDACs and organisational agility. Using a partial least square- structural equation modelling (PLS-SEM) approach, questionnaire responses from 152 enterprises from various industries in the Gulf Cooperation Council (GCC) countries were analysed to test the hypotheses presented in the study’s conceptual framework. The study’s main findings are that BDACs fully mediate the big data governance relationships with innovation performance and organisational agility. The study also found significant serial mediation by BDACs and organisational agility between big data governance and innovation performance. This study highlights that the ability of management to develop and deploy an appropriate combination of essential resources depends on their resources and capabilities (big data governance, BDACs, and organisational agility), leading toward the improvement of firm innovation performance.
Suggested Citation
Maryam Al Kamzari & Farzana Asad Mir & Abubakr Suliman, 2024.
"Big Data Governance And Innovation Performance: The Mediating Role Of Big Data Analytic Capabilities And Organisational Agility,"
International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 28(01n02), pages 1-28, February.
Handle:
RePEc:wsi:ijimxx:v:28:y:2024:i:01n02:n:s1363919624500038
DOI: 10.1142/S1363919624500038
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