Cognitive modeling of reinsurance flows on the global reinsurance market
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DOIhttps://doi.org/10.21511/gg.01(1).2017.01
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Article InfoVolume 1 2017, Issue #1, pp. 5-11
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The article studies one of the areas of the world globalization processes – formation, interaction and regulation of financial flows of world reinsurers. Mathematical formalization of the relationships of countries’ reinsurance flows is proposed to be built on the basis of cognitive maps and correlation analysis. Identification of relevant areas of global reinsurers’ development is conducted on the basis of indicators of consonances of mutual influence, interaction and centralization.
- Keywords
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JEL Classification (Paper profile tab)G22
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References13
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Tables4
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Figures1
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- Fig. 1. The scheme of relationships of reinsurance operations of insurance (reinsurance) companies around the world
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- Table 1. Coefficients of pair correlation between reinsurance flows of countries
- Table 2. Matrix of the mechanism of regulation of reinsurance between countries
- Table 3. Matrix of quantitativeassessment of interaction between the concepts of the mechanism for reinsurance regulation according to areas (countries)
- Table 4. Results of analysis of the processes regulating the mechanism of reinsurance according to areas (countries)
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Selection of parameters for multifactor model in the knowledge economy marketing (country level)
Maxim Polyakov
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Vladimir Bilozubenko ,
Maxim Korneyev ,
Gennadiy Shevchenko
doi: http://dx.doi.org/10.21511/im.15(1).2019.08
Modern economy is characterized by rapid qualitative and quantitative changes that significantly affect the nature of economic, socio-economic and social relations. Innovative processes and trends are very specific manifestations, which are reflected in the economic and marketing theory. A greater place in science and practice is occupied by the concepts of new economy, knowledge economy, knowledge society. Therefore, the study of knowledge economy marketing becomes more and more relevant.
The paper is aimed to develop a technique for selection of the key parameters for building the model of national knowledge economy marketing.
For this purpose, it is proposed to conduct a cluster analysis based on aggregated data. Classification of differences between clusters is given. As a result of classification, the authors have identified a group of indicators, which make all clusters distinctive and, first and foremost, determine positions of countries in the global landscape. These indicators are interpreted as key factors of the knowledge economy.
Based on the suggested mathematical functions, the authors assessed the value of every key factor within the selected group. It became the second step in selecting the parameters to build a multifactor model of knowledge economy marketing at the national level. The paper also justifies that it is reasonable to use cognitive approach to address challenges in the sphere under consideration. This approach is able to become a sound basis for building the model of national knowledge economy marketing in the form of cognitive map.
