A MULTI-LEVEL SYSTEM OF STATISTICAL INDICATORS FOR REGIONAL TRANSPORT INFRASTRUCTURE ASSESSMENT: METHODOLOGY AND APPROBATION

A MULTI-LEVEL SYSTEM OF STATISTICAL INDICATORS FOR REGIONAL TRANSPORT INFRASTRUCTURE ASSESSMENT: METHODOLOGY AND APPROBATION

Authors

  • Keunimzhaev Mukhamedali Kuanysbaevich

DOI:

https://doi.org/10.5281/zenodo.19540610

Keywords:

transport infrastructure; statistical indicators; integrated index; transport provision; Republic of Karakalpakstan; regional statistics; road network.

Abstract

This article presents the methodology and approbation results of an original multi-level system of statistical
indicators for assessing regional transport infrastructure. The study addresses the limitations of existing one-dimensional
approaches that fail to simultaneously account for road surface quality, demographic characteristics, and spatial features
of territories. The research object is the transport infrastructure of the Republic of Karakalpakstan — the largest region of
the Republic of Uzbekistan by area (166,600 sq. km). The proposed system comprises five indicator blocks: quantitative,
qualitative, demographic, spatial, and economic. Based on these blocks, an integrated Infrastructure Transport Index
(ITI) is calculated, enabling inter-district comparisons. The system was tested using data for 2000–2025 across 16
administrative units of the republic. The ITI values range from 0.14 (Qo‘ng‘irot district) to 0.95 (Takhiatash district),
indicating significant intra-regional disparities in transport provision. The results can be applied by government authorities
in developing regional transport programmes.

Author Biography

Keunimzhaev Mukhamedali Kuanysbaevich

Lecturer, Department of Higher and Applied Mathematics
Tashkent State University of Economics
Tashkent, Republic of Uzbekistan

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Published

2026-04-01

How to Cite

Keunimzhaev , M. (2026). A MULTI-LEVEL SYSTEM OF STATISTICAL INDICATORS FOR REGIONAL TRANSPORT INFRASTRUCTURE ASSESSMENT: METHODOLOGY AND APPROBATION. Innovation Science and Technology, 2(4). https://doi.org/10.5281/zenodo.19540610
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