Data-Driven Customer Assessments for Biodiversity Conservation
Abstract:
This study centers on addressing the critical challenge posed by illegal wildlife and plant trade to biodiversity, aiming to propose a client evaluation model designed for conservation efforts. Operative within a rigorous assessment framework that integrates sophisticated statistical tools, including McKinsey's Logic Tree Analysis, Analytic Hierarchy Process (AHP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the model conducts evaluations spanning both non-governmental organizations and government institutions. Following meticulous analysis, the United States government is identified as the optimal partner. The rationale behind this selection is multifaceted, examining the ecological, social, and economic dimensions to comprehensively scrutinize the validity and necessity of collaborating with the U.S. government in tackling the pressing issue of illegal wildlife and plant trade.
Keywords:
Illegal Wildlife Trade, 5-year Project, AHP, EWM, Topsis method.
APA Citation:
Tongji Cui, Yiyi Li (2024). Data-Driven Customer Assessments for Biodiversity Conservation. Transactions on Computer Science and Intelligent Systems Research, 8(1), 44-53. https://doi.org/10.62051/wxq5zr38
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