Influence of artificial intelligence on warehouse performance: The case study of the Colombo area, Sri Lanka

Abstract

This study is focused on the influence that artificial intelligence can bring on warehouse performance. A sample of 329 workers from selected warehouses was used for this study, and a self-administered questionnaire was used to collect data. An index was constructed using the Principal Component Analysis (PCA) method to measure the influence on warehouse performance. Mann Whitney U test and Kruskal-Wallis H test were used to determine the effect of demographic factors on warehouse performance. The association among the variables was identified by employing correlation analysis. A regression analysis was performed to determine the relationship between the identified factors and warehouse performance. When the study tests for the association among the variables, it depicts a positive correlation. Finally, based on the analysis, it illustrates the influence of machine learning, robotics, the Internet of things (IoT), and fuzzy logic on warehouse performance. The warehouse performance was mentioned in three categories: time, inventory, and cost.