Spatial analysis of large food industries in Babylon Governorate and the role of artificial intelligence technologies in improving their spatial efficiency

Abstract

This research examines the spatial analysis of large food industries in Babylon Governorate, focusing on studying their geographical distribution patterns and spatial efficiency levels in light of rapid digital transformations and the growing applications of artificial intelligence. The research aims to identify spatial imbalances in industrial location. The geographical and economic factors affecting it, as well as exploring the role of artificial intelligence technologies in improving the spatial distribution efficiency of industry and suggesting more suitable locations for industrial activity.

The research adopted a descriptive-analytical approach, supported by spatial analysis tools and geographic information systems, as well as employing some artificial intelligence models in industrial concentration analysis and predictive modeling. The research concluded that there is a clear spatial variation in the efficiency of food industries within Babylon Governorate. The cluster analysis results showed that the governorate's districts are not organized within a single level of industrial performance, but are distributed across three main clusters (high, medium, and low efficiency). The results of artificial intelligence also showed that optimal industrial expansion is not necessarily achieved in the most efficient areas, but rather in the intermediate areas that have existing capabilities that can be improved at the lowest planning cost. The integration of artificial intelligence technologies contributes to enhancing the efficiency of spatial analysis and supporting industrial decision-making. The research concludes with a set of recommendations aimed at promoting smart industrial planning and achieving balanced spatial development.