Awareness and Adoption of Big Data Technology in Public Sector Auditing in Tanzania: Mediation Effect of Knowledge Management Practices.

Authors

DOI:

https://doi.org/10.63158/IJAIS.v3i1.60

Keywords:

Awareness, Big data technology adoption, Knowledge Management Theory, Diffusion of Innovation, Public sector auditing

Abstract

Big data technology enables auditors to identify patterns and anomalies across extensive datasets, supporting improved audit quality. However, its adoption in Tanzania’s public sector auditing remains limited. This study examines the mediating role of knowledge management practices in the relationship between awareness and readiness to adopt big data technology. Drawing on Diffusion of Innovation (DOI) theory and Knowledge Management Theory (KMT), it proposes that awareness provides the foundation for adoption readiness, while knowledge creation, sharing and application translate awareness into practical capabilities. Data were collected from 221 randomly selected respondents and analysed using descriptive statistics and binary logistic regression. The findings indicate that knowledge management practices mediate the relationship between awareness and adoption readiness, highlighting their role in developing skills for technological adoption. Descriptive results reveal high operational awareness but low technical awareness among auditors, indicating a technical skills gap. These findings suggest that awareness alone is insufficient without mechanisms for acquiring, sharing and applying relevant knowledge. Public sector auditing institutions in Tanzania should strengthen knowledge management through targeted training programmes and knowledge sharing platforms. The study contributes an integrated DOI–KMT perspective explaining how awareness and knowledge management jointly support readiness for big data adoption in public sector auditing.

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Published

2026-03-20

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How to Cite

Awareness and Adoption of Big Data Technology in Public Sector Auditing in Tanzania: Mediation Effect of Knowledge Management Practices. (2026). International Journal of Artificial Intelligence and Science, 3(1), 39-62. https://doi.org/10.63158/IJAIS.v3i1.60