Design of Illegal Wildlife Trade Prevention and Control System Based on AHP and Multiple Linear Regression Model--Based on the Practical Path of National Government

Abstract

As a global environmental crime, illegal wildlife trade seriously threatens ecological security and biodiversity. In order to build a systematic prevention and control system, this study innovatively integrated the analytic hierarchy method (AHP) and multiple linear regression model to design a five-year data-driven intervention program based on the national government. The AHP model assesses potential implementation subjects from five dimensions: financial resources, human resources, influence, relevance of interests and legal enforcement, and determines that the national government has the highest overall score (0.4264), and its legislative authority, resource deployment and international collaboration capacity provide the core guarantee for the program to be implemented. Further combined with the multiple linear regression model, quantitatively analyzing the impact of the expansion of nature reserve area, environmental protection financial investment and education penetration rate on the export volume of illegal trade, the model was significant (p=0.0368), predicting a significant decrease in the export volume after implementation. Sensitivity analysis shows that disposable income and education funding are key drivers of effectiveness. The study confirms that the government-led multidimensional strategy of “regulatory enhancement-technological empowerment-international cooperation” can effectively curb illegal trade networks and provide a quantitative decision-making framework for global governance.