 Will machine learning resolve the issues in container management in ports and logistics industries?S. Mohanbabu and R. Vettriselvan International Journal of Process Management and Benchmarking, 2025, vol. 20, issue 4, 559-575 Abstract: In this digital era, data is driving the world, and machine learning is part of it. This research study has been carried out by various logistics companies that deal with port authorities across Indian regions. The data was collected through a structured questionnaire and put across 163 respondents, with 150 responses received from various industries working closely with the logistics industry. Factual analysis was done through their response and analysis of variance, and simple linear regression analysis was deployed for interpreting the results. Regression equation: = 5.2892 + 0.6907X Machine learning improves logistic operation efficiency, and machine learning solves logistics issues. The relationship R-squared (R2) equals 0.6289. This means that 62.9% of the variability of machine learning improving logistics operation efficiency is explained by machine learning solving logistics issues. The results reveal that there is a strong direct relationship between machine learning solving logistics issues and improving logistics operation efficiency. Keywords: container management; machine learning; logistics industry. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpmbe:v:20:y:2025:i:4:p:559-575 Access Statistics for this article More articles in International Journal of Process Management and Benchmarking from Inderscience Enterprises Ltd |
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