Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. KMITL
  3. Publication
  4. An AI-integrated framework for sustainable conflict mitigation and policy innovation
Loading...
Thumbnail Image

An AI-integrated framework for sustainable conflict mitigation and policy innovation

Author(s)
Tissamana, Apinya
Ajayi, Babatunde Oluwaseun
Bamisaye, Mayowa Emmanuel
Katerenchuk, Wendell
Aziz, Tamoor
Ajayi, Olawande Emmanuel
Sereewatthanawut, Issara
Date Issued
September 1, 2026
Type
Article
DOI
10.1016/j.indic.2026.101395
Abstract
Conflict in Thailand's peripheral regions remains a persistent challenge, particularly in provinces such as Ubon Ratchathani, where inequalities, cultural marginalization, and resource pressures intersect to shape local tensions. Despite growing attention to conflict analysis, existing approaches often struggle to combine contextual understanding with predictive capability, limiting their usefulness for timely and effective policy intervention. To address this gap, this research introduces a hybrid framework integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with the Random Forest (RF) algorithm. Using primary data from 400 respondents across urban and rural communities in Ubon Ratchathani, the framework combines stakeholder-informed causal mapping with data-driven prediction. DEMATEL identifies and structures relationships among key conflict dimensions, while RF evaluates and predicts these relationships using empirical data. The findings reveal that cultural and identity issues are the primary drivers of conflict, shaping political and economic marginalization, whereas resource-related conflicts emerge as downstream effects. The RF model demonstrates excellent predictive performance (MSE = 0.0120; RMSE = 0.1097), indicating that these relationships can be reliably translated into predictive insights. This enables policymakers to move beyond reactive responses toward early identification of conflict risks and more targeted interventions. Effective interventions, however, must be coordinated across sectors and tailored to local contexts to achieve lasting impacts. By linking causal understanding with predictive capability, the proposed framework offers a practical tool for conflict monitoring and more inclusive governance aligned with the Sustainable Development Goals (SDGs). While promising, the framework should be tested in other regions to assess its broader applicability.
Citation
Environmental and Sustainability Indicators, 31, 2026
Subjects

AI

Conflict

Conflict mapping

DEMATEL

Governance

Peace

Policy

SDG

Metrics
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your Institution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback