A Systematic Risk Management Model for Social Innovation Projects

Due to limited and diverse resources, risk management has become a critical issue in social innovation projects. The prioritization of risks in such projects involves multiple and often conflicting criteria. Multi-Criteria Decision Making (MCDM) methods are suitable for explicitly evaluating these criteria in decision-making and prioritization processes. In complex problems like risk management, decision-makers tend to rely on imprecise rather than precise information. Fuzzy set theory effectively addresses the inherent uncertainty and imprecision in such contexts. In particular, hesitant fuzzy sets offer an enhanced ability to represent uncertain and ambiguous expert judgments. In this study, we propose a risk management framework for social innovation projects. First, a comprehensive literature review is conducted to identify relevant risks. Then, a fuzzy MCDM approach based on the Analytic Hierarchy Process (AHP) and extended using hesitant fuzzy sets is employed to prioritize these risks. From a managerial perspective, the proposed model provides a systematic tool to evaluate and classify social innovation projects across a risk spectrum, thereby supporting more informed and effective risk assessment and prioritization.