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Cluster Model for Regional Banking Infrastructure

Abstract

This study examines cluster models for regional banking infrastructure. Aim. This study aims to develop an effective methodology for intra-regional management of the banking sector of the economy to give an impetus to the most important elements of regional banking infrastructure as well as to optimize the content of the infrastructure and its interelement relations. We define the concept of “decision making” and demonstrate key stages of the decision-making process in management using a cluster approach. Tasks. This study develops optimal mechanisms for the management and creation of an infrastructure network that would meet the requirements of the loan market. Conceptual clustering is used to build a corresponding classification structure. Results. It is determined that cluster analysis is an effective way to set up interaction in weakly structured economic formations. The use of firmly determined mathematical modeling in the analysis and examination of systems that are highly susceptible to the socalled psychological factors indicate low adequacy and are ineffective from a practical standpoint. Further, the predominant trends in the development of the banking sector in the North West region directly correlate with the current state, growth dynamics, and features of the system of infrastructure roles. Thus, this study concludes that positive changes need to be made to the operation of companies involved in the functioning of the banking sector, including their small and moderate constituents. Such companies should also be integrated in the banking business.

About the Author

Eleonora Aleksandrovna Ulyaeva
State Polar Academy
Russian Federation


References

1. Портал о корпоративных порталах: [Электронный ресурс]. Режим доступа: http://www.corportal.ru/.

2. Миркин Б. Г. Методы кластер-анализа для поддержки принятия решений: Обзор. М.: Изд. дом НИУ ВШЭ, 2011. 84 с.


Review

For citations:


Ulyaeva E.A. Cluster Model for Regional Banking Infrastructure. Economics and Management. 2016;(3):47-51. (In Russ.)

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ISSN 1998-1627 (Print)