A Comprehensive Two-Staged MCDM Model for Risk Assessment in Vietnam’s Fintech Crowdfunding Sector
摘要
Fintech crowdfunding has become a useful way to raise capital, but it also carries many risks. Early detection of risks can help minimize the negative impacts that a project may encounter. This study combines Spherical Fuzzy Delphi (SF Delphi) and Spherical Fuzzy Failure Mode and Effects Analysis (SF FMEA) to assess these risks. SF Delphi filters the risks and then SF FMEA assesses the risk level through severity (S), occurrence (O), detection (D), and calculating the Risk Priority Number (RPN). The results identify critical risks, with technology failures (RPN: 0.68827), poor communication (RPN: 0.49181), and failure to adapt (RPN: 0.47359) ranking among the highest, indicating their significant potential impact. These findings offer valuable insights and actionable recommendations for backers of fintech crowdfunding projects in Vietnam, facilitating informed decision-making and efficient resource allocation.