Infrastructure Coverage of the Ural Federal District Regions: Assessment Methodology and Diagnostics Results
Abstract
The article examines the infrastructure as one of the essential elements in the economic system. The authors consider the development stages of this concept in the scientific community and provide the opinions of a number of researchers as to the role and place of the infrastructure in the economic system. The article provides a brief genesis of approaches to describing the infrastructure and conferring its functions on individual branches. The authors emphasize the higher importance of infrastructure coverage with the economy transition to machine production. Two key methodological approaches are identified to describe the substance and content of the infrastructure: industrial and functional.
The authors offer their methodology of assessing the infrastructure coverage of regional-level territories. The methodology is based on identifying a combination of specific indicators the values of which can be used to evaluate the development level of individual infrastructure elements. The indicative analysis being the basis of the methodological apparatus helps make a judgment of any phenomenon by comparing the current observed values with the previously adopted threshold levels. Such comparison makes it possible to classify the observations by the «norm—pre-crisis—crisis» scale. An essential advantage of this method is the possibility of standardizing the indicators, or, in other words, bringing them to one comparable conditional value. Thus, you can get estimates for individual blocks of indicators and a complex assessment for the whole set in general. The authors have identified four main infrastructure elements: transport, communications, public utility services and healthcare. The methodology includes 21 indicators all together.
The test estimates based on the authors’ methodology revealed the defects in the development of the Ural regions` infrastructure. The article provides a brief analysis of the obtained data with identifying individual indicators and areas.
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DOI: https://doi.org/10.15826/recon.2015.3.004
Copyright (c) 2018 Pavel A. Pykhov, Tatyana O. Kashina
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