Knowledge Geography: Human Geography Approach to Measuring Regional Divergence of Knowledge Capital

被引:0
|
作者
Mikhaylov, Andrey [1 ,2 ]
Kuznetsova, Tatyana Yu [1 ]
Peker, Irina Yu [1 ]
机构
[1] Immanuel Kant Baltic Fed Univ, Kaliningrad, Russia
[2] St Petersburg Electrotech Univ LETI, St Petersburg, Russia
关键词
knowledge geography; innovation geography; scientometrics; regional innovation system; knowledge management; intellectual capital; Russia; INNOVATION SYSTEMS; GROWTH; POLICY; COMPETITIVENESS;
D O I
10.34190/KM.19.239
中图分类号
F [经济];
学科分类号
02 ;
摘要
Major cities and agglomerations are the innovation leaders throughout the globe. High population density and migration influx, clusters of related industries, intensive inter-regional and international networking favour the development of outstanding territorial capital. By attracting talents, entrepreneurs, and capital, coupled with advanced public infrastructure and infinite labour market urban agglomerations intensify regional divergence between and within regions. Cohesion policies are designed to overcome the effects of this unequal competition by supporting industries and the social sector of the peripheral territories. The gap that largely remains irretrievable is the loss of knowledge holders - from an individual to an excellence cluster. Knowledge is the major resource of local, regional, and national competitiveness. Regional innovation systems require a constant influx of new knowledge, while the regional innovation security argues for the most critical knowledge to be generated on spot. This paper aims to present the geography of knowledge in Russia by evaluating the bibliometric data for 997 cities (and 1 rural settlement) and 83 regions across the country for a period of 2013-2017. Tacit knowledge and impalpable innovations - the competencies, know-how, expertise, are hard to trace using common statistics. The methodology based on modern scientometrics and big data analysis offers an approach to capture some of the knowledge capital available in a certain locality and analyse innovation dynamics of urban settlements. Research results suggest there is a strong path-dependency in the Russian knowledge domain that heavily relies on the Soviet legacy and geospatial factors. Often neglected or perceived as a source of input to the knowledge-generating nucleus, peripheral areas are well integrated in value co-creation within the hub-and-spoke cooperation pattern. The data acquired is highly valuable to regional planning and knowledge management.
引用
收藏
页码:738 / 745
页数:8
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