Hierarchical and Spatial Effects in the Development of Municipalities

Yusupov, Kasim; Timiryanova, Venera; Toktamysheva, Iuliia; Popov, Denis

doi:10.15838/esc.2018.5.59.9

Cited by 1 publication

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“…This method was originally introduced to study group and intergroup differences in human behavior (Goldstein 2010;Garson 2013;Raudenbush et al 2011). Over time, however, the ability to identifying group effects has been used to analyze production (Lee 2018;Yusupov et al 2018), consumption (Chen 2012), and firm reaction speed (Lawson et al 2019) within the supply chain.…”

Section: Methodsmentioning

confidence: 99%

Spatial Patterns of Production-Distribution-Consumption Cycle: The Specifics of Developing Russia

2020

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The existing body of academic literature reveals that production, distribution, and consumption might be both consistently connected and geographically scattered. This requires assessing the spatial order of production–distribution–consumption cycle, within which exploring of spatial relationship would be based on mutual dependence on each other’s of production, distribution and consumption. Hierarchical and spatial nesting of production, distribution, and consumption data allows us to apply hierarchical spatial autoregressive models (HSAR). The study was conducted on data from 2132 municipalities within 84 regions of the Russian Federation in 2018. The created models enabled distinguishing intraregional and interregional effects and highlighted the positive effect of spatial interactions in production volume. The calculations showed that population income, which determine the demand for goods are positively associated with production volume while relationship between manufacturing and wholesale is negative, resulting in revision of relations between wholesale and manufacturing enterprises and boosting ways of improvement the competitiveness of manufactured goods. The results allow us not only to enhance understanding of the spatial pattern of production–distribution–consumption cycle, but also to reveal new opportunities in the development of supply chain location policy.

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