The Determinant and Impact of Big Data Analytics Adoption on Public Sector Audit Outcomes

Objective –This research investigates the determinants of big data analytics (BDA) adoption in public sector audit, namely system quality, and subsequent impacts on three aspects: audit performance, judgment, and quality. This study also examines the role of audit judgment and audit performance as mediating variables.Design/Methodology –This study used a questionnaire survey involving 137 government auditors in Indonesia. The Structural Equation Model-Partial Least Squares (SEM-PLS) was employed for data analysis.Results –The results reveal that BDA-based auditing adoption is positively determined by system quality. Moreover, BDA-based auditing adoption improves audit performance, judgment, and quality. Additionally, while audit judgment is a mediator between BDA-based auditing and audit quality, audit performance does not.Research limitations/implications –This study has limitations in the number of samples, which makes the generalizability of the study results less strong. It makes readers need to be careful when concluding the results of this study.Novelty/Originality –This study offers a novel approach by examining the use of BDA in public sector audit, which is not frequently discussed, particularly when evaluated through the Information Systems (IS) Success Model by DeLone and McLean (2003); Petter et al. (2008). In addition, this study also presents a novelty in the form of testing the mediation role of audit judgment and audit performance.