Improving Natural Resource Management through AI: Quantitative Analysis using SmartPLS
Juan Carlos Rodr ́ıgue, John Van der Merwe, Syahrul Mu’Arif Wahid, Galih Putra Cesna, Dimas Aditiya Prabowo
Abstract
This study evaluates the role of Artificial Intelligence (AI) in enhancing the efficiency of natural resource management through a quantitative analysis using SmartPLS. Data was collected from 200 professionals with significant experience in AI and natural resource management. Descriptive statistics indicated high levels of AI usage (X1) and technological competence (X2) among respondents, with average scores of 4.2 and 4.0, respectively. Convergent and discriminant validity were confirmed, with all constructs having factor loading values above 0.7 and AVE exceeding 0.5. Structural model analysis revealed that AI usage and technological competence positively and significantly impact natural resource management efficiency (Y1), with path coefficients of 0.45 and 0.38, respectively. These findings underscore AI's critical role and the necessity of technological training to maximize its benefits. This research contributes to the literature by highlighting the importance of integrating AI in sustainable resource management practices, providing a robust framework for future studies.