Digital Transformation of the Indonesian Public Sector: A Systematic Review of Governance, Audit, and Service Innovation
This dataset supports the systematic review article "Digital Transformation of the Indonesian Public Sector: A Systematic Review of Governance, Audit, and Service Innovation" , which synthesises evidence from ten (10) empirical studies examining how digital technologies influence financial oversight, service innovation, and institutional governance in the Indonesian public sector. The review covers multiple digital technologies including computer-assisted audit techniques (CAATs), big data analytics, artificial intelligence, electronic evidence, e-government platforms, ICT-based performance systems, generative AI, IT governance frameworks, an
Resource information
- Data purpose
- Research dataset
- Format
- tiff, xlsx
- Original repository
- 21850858
- DOI
- 10.5281/zenodo.21850858
- Credit basis
- Creators in Zenodo record metadata
- Access
- Open files available from the original Zenodo deposit
- Last checked
- Nov 5, 2026
- License
- cc-zero
- Last record update
- Nov 5, 2026
About this resource
This dataset supports the systematic review article "Digital Transformation of the Indonesian Public Sector: A Systematic Review of Governance, Audit, and Service Innovation" , which synthesises evidence from ten (10) empirical studies examining how digital technologies influence financial oversight, service innovation, and institutional governance in the Indonesian public sector. The review covers multiple digital technologies including computer-assisted audit techniques (CAATs), big data analytics, artificial intelligence, electronic evidence, e-government platforms, ICT-based performance systems, generative AI, IT governance frameworks, and village financial systems (SISKEUDES) across institutional contexts including central government agencies (Ministry of Finance, Indonesian Audit Board/BPK), local governments (Palembang City, Sarbagita region in Bali), and village administrations. The dataset includes Figure 1 (PRISMA 2020 Flow Diagram illustrating the study selection process from 9,211 initial records to 10 included studies), Supplementary Document 1 (PRISMA 2020 Checklist with 27 items completed for the systematic review), Supplementary Document 2 (Risk of Bias Assessment Criteria detailing the quality appraisal tool and scoring system adapted for diverse study designs), Supplementary Document 3 (Full Data Extraction Form containing standardised data from all ten included studies including author(s), year, objective, study design, population, technology, outcome focus, and key findings), and Supplementary Document 4 (Complete Search Strings and Retrieval Results from the Scopus database including Boolean operators, filters applied, and retrieval numbers by screening stage). All files are available under a Creative Commons Zero (CC0 1.0) license.