Multi-Criteria Decision-Making Algorithm based on HyperSoft Set for Civil Litigation Efficiency Evaluation in the Context of Artificial Intelligence

Artificial Intelligence (AI) is increasingly being integrated into civil litigation to enhance efficiency, reduce costs, and improve decision-making accuracy. This study evaluates the effectiveness of AI-driven tools in civil litigation efficiency using a multi-criteria decision-making (MCDM) framework. Key evaluation criteria include case processing speed, judicial decision accuracy, cost reduction, transparency, accessibility, and AI adoption rates. Two MCDM methods are used in this study such as LMAW to compute the criteria weights and the CoCoSo method to rank the alternatives. We use the concept of the HyperSoft set to deal with various criteria and sub criteria in the evaluation problem. We conducted a case study with eight criteria and ten alternatives to show the validation of the proposed approach. The sensitivity analysis is conducted to show the stability of the proposed approach.