MODELLING TERRITORIAL LOGISTICS BASED ON ECONOMIC DISTANCE
Journal Title: Journal of Economic Research & Business Administration - Year 2025, Vol 151, Issue 1
Abstract
This article examines methods for modeling territorial logistics using the concept of economic distance. Logistics plays a key role in the socio-economic development of Kazakhstan by facilitating the efficient movement of goods and integrating the country into international transport corridors. The study explores the principles of modeling transport flows by applying models that assess the impact of transport accessibility and infrastructure capacity on the effectiveness of logistics processes. A comparative analysis was carried out on the Huff Model, the Rayleigh Distribution, and the Modified Gravity Model across six parameters. Based on a hypothetical example using the Huff and Rayleigh models, a practical study was conducted for three regions of Kazakhstan’s transport network. As an example, the transport network of Kazakhstan, including logistics hubs in the cities of Astana, Almaty, and Karaganda, was examined. The calculations demonstrated that the distribution of cargo turnover is determined not only by the volume of freight flows but also by economic distance, which reflects the logistics attractiveness of hubs in regional development. The practical analysis of Kazakhstan’s transport network shows that hubs with high cargo turnover located in close proximity to consumer regions possess enhanced logistical attractiveness. This enhances the significance of economic distance, which combines physical distance and the economic costs of transport. Optimizing the territorial logistics infrastructure helps reduce transport costs, improve the efficiency of freight transport, and facilitate the integration of regions into national and international transport corridors. The models and methods presented in the article can be employed for strategic planning of logistics processes and the development of effective cargo distribution schemes.
Authors and Affiliations
Mussa K. A. , Akhmetkaliyeva S. K. , Muratbekova A. А. , Jeevan J.
Keywords
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- EP ID EP765537
- DOI 10.26577/be2025151110
- Views 12
- Downloads 0
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