|Title||Cluster analysis of development of alternative finance models depending on the regional affiliation of countries|
Rubanov, Pavlo Mykolaiovych
Vasylieva, Tetiana Anatoliivna
Lieonov, Serhii Viacheslavovych
Pokhylko, Svitlana Vasylivna
|Date of Issue||2019|
|Publisher||Business and Economic Horizons|
|License||In Copyright - Educational Use Permitted|
|Citation||Cluster analysis of development of alternative finance models depending on the regional affiliation of countries [Текст] /P. Rubanov, T. Vasylieva, S. Lyeonov, S. Pokhylko // Business and Economic Horizons. - 2019. Vol. 15, No. 1. - P. 90-106. - DOI: 10.15208/beh.2019.6|
The article examines the hypothesis about the existence of regional peculiarities in the development of alternative financing models (such as p2p consumer lending, p2p business lending, p2p real estate lending, balance sheet business lending, balance sheet consumer lending, equity-based crowdfunding, reward-based crowdfunding, real estate crowdfunding, profit sharing crowdfunding, donation-based crowdfunding, invoice trading, debt-based securities). According to an alternative hypothesis, due to the high integration of international financial markets, there are no regional peculiarities of the development of alternative financing models. The cluster analysis tools allow verifying these hypotheses. The cluster analysis methods used, such as tree clustering, k-means clustering, and two-way joining, demonstrate the lack of links between the country's regional affiliation and the degree of development of certain types of alternative financing in it. The key factors affecting the formation of clusters are volumes of peer-to-peer consumer lending and business lending, as well as the volume of invoice trading. According to the results of the research, the authors conclude that it is necessary to find other factors, apart from the regional features, which influence the ratio in the development of certain types of alternative financing in different countries.
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Наукові видання (ННІ ФЕМ)
|Vasilyeva_cluster_analysis_CEEOL.pdf||1,29 MB||Adobe PDF||6662|
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