Exploring the Efficiency and Accuracy of AI-Powered Predictive Analytics: A Six-Country Case Study of the Logistic Performance Index

Abstract

This research assesses the logistics performance index (LPI) scores for six different countries: Nigeria, Malaysia, Sweden, the United States, Bolivia, and Papua New Guinea. The LPI serves as an indicator of a country’s logistics efficiency, covering aspects such as infrastructure and timeliness, and is a key metric for sustainable logistics practices. Using traditional machine learning models, we compare our predicted scores with the actual results for 2023. Initial findings suggest a trend of conservative predictions, with several countries surpassing their forecasted performance, indicating progress in sustainable logistics. Interestingly, Bolivia and Papua New Guinea stand out, demonstrating unexpected progress and diverse approaches to development. While recognizing the limitations of model biases and sudden geopolitical changes, the study highlights the importance of predictive analytics in understanding global logistics and sustainability trends, providing a solid foundation for future detailed studies into balancing economic development and environmental protection.