ENHANCING THE COMPETITIVENESS OF BUSINESS AND MANAGEMENT CONSULTING FIRMS THROUGH THE APPLICATION OF BIG DATA AND ANALYTICS

Babajide Oyewo and Dang Khoa Tran
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Babajide Oyewo: Department of Accounting, University of Lagos, Akoka, Lagos, Nigeria†Institute of Business Research, University of Economics Ho Chi Minh City, Vietnam, 59C Nguyen Dinh Chieu Street, Ward 6, District 3, Ho Chi Minh City, Vietnam
Dang Khoa Tran: ��Institute of Business Research, University of Economics Ho Chi Minh City, Vietnam, 59C Nguyen Dinh Chieu Street, Ward 6, District 3, Ho Chi Minh City, Vietnam

The Singapore Economic Review (SER), 2025, vol. 70, issue 02, 379-407

Abstract: This study investigates the application of big data analytics (BDA) and its impact on consulting firms’ competitiveness. Descriptive statistics, ordinary least square regression, and moderated regression analysis were used to analyze survey data obtained from 118 business and management consultants in Nigeria. The robustness of the result was evaluated using structural equation modeling. Result shows that the application level of BDA by consulting firms is generally moderate. BDA application has a significant positive impact on organizational competitiveness, although the strength of the relationship is weak. Further, data quality significantly moderates the relationship between BDA and organizational competitiveness. The study concludes that the application of BDA can enhance the competitiveness of consulting firms. However, the extent to which such benefit is realized is dependent on the quality of data applied in the analysis. The study contributes to knowledge by providing empirical evidence that the deployment of BDA can be a source of competitive advantage for consulting firms. The study adds to literature on management accounting in the digital economy and the application of big data to business and management consulting.

Keywords: Big data; big data analytics; organizational competitiveness; business consulting; management consulting; management accounting in the digital economy (search for similar items in EconPapers)
JEL-codes: M4 O32 O33 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0217590821500259

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