INNOVATION AGAINST CORRUPTION: A DIGITAL RISK-ASSESSMENT FRAMEWORK FOR REGIONAL GOVERNMENT IN THAILAND AND THE ASIAN CONTEXT
DOI:
https://doi.org/10.14456/apsr.2025.12Keywords:
Good Governance, Corruption Risk, Digital Platform, Natural Language Processing, Public ProcurementAbstract
Corruption and misconduct remain persistent barriers to good governance in Thailand's regional government agencies, notably in procurement and licensing processes, thereby weakening fiscal discipline and public trust. This study, "Innovation Against Corruption," develops and evaluates a Natural Language Processing (NLP)-based digital risk-assessment framework to strengthen governance and reduce corruption risks. Utilizing a mixed-methods design, including online surveys of 160 officials, focus group discussions, and 24 in-depth interviews across four pilot provinces (Chiang Mai, Chainat, Ubon Ratchathani, and Trang), the research integrates NLP with a COSO-ERM-based risk matrix. Key findings reveal procurement as the highest-risk domain, reflecting structural vulnerabilities and entrenched patronage networks. The developed platform proved effective in automating risk scoring, reducing administrative burden, and enhancing transparency, with user feedback indicating high satisfaction with its usability, accuracy, and perceived benefits. This study significantly contributes to the digital governance and anti-corruption literature by linking technological innovation to the Sustainable Development Goals (SDGs) 16 (Peace, Justice, Strong Institutions), 9 (Industry, Innovation), and 11 (Sustainable Cities). It highlights the platform's pivotal role in fostering integrity, accountability, and public trust. Future research should address current limitations by expanding the geographical scope and exploring advanced technologies.
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