Big Data Capabilities and the Transformation of Management Accounting Practices in Emerging Economies: Empirical Evidence from Cameroon

Abstract : Purpose – This study examines how the four canonical dimensions of big data capabilities—volume, variety, velocity, and veracity—influence the transformation of management accounting practices within Cameroon economy. Despite the proliferation of digital analytics in developed markets, empirical evidence regarding their differential effects in resource-constrained institutional contexts remains fragmented. Design/methodology/approach – Anchored in the Resource-Based View, Decision Usefulness Theory, and Dynamic Capabilities Theory, the study employs an ex-post facto cross-sectional design. Primary data were collected via structured questionnaires from 87 management accountants employed in firms operating digital data infrastructures across Douala and Yaoundé, Cameroon’s principal commercial and industrial centres. Multiple regression analysis, supplemented by diagnostic tests for multicollinearity, heteroscedasticity, and normality, was used to test the hypothesised relationships. Findings – The findings reveal that data velocity (β = 0.336, p < 0.001) and veracity (β = 0.291, p = 0.003) exert the strongest positive influence on management accounting transformation, followed by variety (β = 0.278, p = 0.005) and volume (β = 0.214, p = 0.019). The model explains 64.1% of the variance in management accounting practices (Adjusted R² = 0.598; F = 14.782, p < 0.001), suggesting that real-time processing capability and data reliability are more consequential than data magnitude per se in emerging economy settings. Originality/value – The study contributes to the digital accounting literature by providing rare quantitative evidence from a Sub-Saharan African context, where infrastructural deficits, institutional voids, and capability constraints shape technology adoption trajectories differently than in developed economies. The findings challenge the assumption that greater data volume automatically yields superior accounting outcomes, highlighting instead the primacy of processing speed and information integrity.