Multi-layered hinterland classification of Indian ports of containerized cargoes using GIS visualization and decision tree analysis

Abstract

In this study, we develop a multi-layered hinterland classification of major Indian ports for containerized shipments using a novel approach that integrates geographic information system visualizations and data mining methods. Strong export-oriented business sectors and growing industrial diversity have been prompting developing economies like India to move towards the containerization of maritime transport. We recognize the dearth of systematic research on Indian ports’ hinterlands and therefore seek to understand how the hinterland of container shipping markets in India has evolved in recent years, within the context of ongoing privatization and modernization efforts in this sector. Using disaggregate shipping data of exports from India to the United States, we conduct origin-destination analysis to describe the patterns of container traffic flows from major Indian ports. Furthermore, we develop a decision tree model of hinterland structure and overlap that explains the nature of inter-port competition from three dimensions: space, commodity types and shipment values. This article also attempts to assess the competition posed by private ports like Mundra and Pipavav on major Government ports, for which data have largely been unavailable. The results demonstrate the utility of this data mining method in conceptualizing the port hinterland as a dynamic spatial object and in unravelling multidimensional relationships.