A Study on Strategies to Reduce Illegal Wildlife Trade Based on the Analytic Hierarchy Process and Grey Prediction Method

Illegal wildlife trade is a major challenge in global environmental protection, severely threatening biodiversity and ecological balance. This paper first employs the Analytic Hierarchy Process (AHP) to conduct a multi-level and comprehensive evaluation of several international organizations in terms of their potential to reduce illegal wildlife trade. The results indicate that the United Nations Environment Programme (UNEP) possesses significant advantages in authority, resources, and international cooperation, making it the recommended best choice. A grey prediction model was further applied to forecast future trends in illegal wildlife trade, revealing that despite the current policies and measures achieving some success, the volume of illegal trade continues to show an upward trend. Additionally, the measurable factor impact assessment model developed in this paper considers the degree of project implementation, investment costs, and stakeholder influence, revealing these factors' actual effects and interrelationships in reducing illegal trade. Through data analysis and model simulation, this study provides a scientific basis for formulating effective strategies and policies, emphasizing the importance of integrated measures and multi-party collaboration in combating illegal wildlife trade.