This study aims to develop an expectation-tree-based Cost Benefit Analysis (CBA) model as a more accurate evaluation approach for policies operating under uncertainty. Traditional CBA often fails to capture variations in risky policy outcomes due to its deterministic nature, whereas the expectation tree allows various scenarios to be mapped through probabilities and expected values. Through a systematic literature review, this research integrates CBA principles with expectation tree structures to produce an evaluation model capable of calculating the expected net benefits of a policy. The findings indicate that this approach not only enhances the efficiency of benefit–cost assessment but also strengthens rationality and risk-resilience in public decision-making. Thus, the expectation-tree-based CBA model serves as a relevant and adaptive alternative for evaluating high-risk policies across different sectors.
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