Improving Natural Resource Management through AI: Quantitative Analysis using SmartPLS

Authors

  • Juan Carlos Rodr ́ıgue Ilearning Incorporation
  • John van der Merwe Ilearning Incorporation
  • Syahrul Muarif Wahid Alfabet Inkubator Indonesia
  • Galih Putra Cesna University of Raharja
  • Dimas Aditiya Prabowo Alfabet Inkubator Indonesia

DOI:

https://doi.org/10.33050/italic.v2i2.548

Keywords:

Artificial Intelligence, Natural Resource Management, SmartPLS, Technological Competence, Quantitative Analysis

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.

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Published

2024-06-21