Determinants Of Big Data Analytics Adoption Intention In Local Government Internal Audit(Empirical Study on Local Government in Indonesia)
Keywords:
Big Data Analytics, Internal Audit, TOE, Local Government, Adoption Intention, Fraud Risk Detection, Top Management SupportAbstract
The use of Big Data Analytics (BDA) in local government internal audits has been introduced as a form of innovation in public financial oversight. However, its implementation still faces various challenges, such as infrastructure readiness, human resources, and suboptimal organizational support. This study aims to statistically test the influence of Relative Advantage, Compatibility, Complexity, Fraud Risk Detection, and Top Management Support on the intention to adopt BDA in internal audit practices in Local Government Inspectorates in Indonesia. This study uses the Technology-Organization-Environment (TOE) framework as its theoretical basis. This research uses a quantitative approach with primary data obtained through questionnaires distributed to respondents who are auditors at local government inspectorates in Indonesia. The sampling technique used purposive sampling and convenience sampling. The minimum sample is 92 inspectorates in Indonesia.Hypothesis testing was conducted using Structural Equation Modeling Partial Least Square (SEM-PLS) analysis through SmartPLS software version 4.0. This study contributes theoretically by strengthening the application of the Technology-Organization-Environment (TOE) framework in the context of the public sector, particularly in local government internal audits in Indonesia. In addition, this study adds to the literature on factors that influence the intention to adopt Big Data Analytics (BDA) by Regional Inspectorate auditors in Indonesia, thereby broadening the understanding of the dynamics of adopting big data analysis-based audit technology in the government environment.
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