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2019 | vol. 15, iss. 1 | 90--106
Tytuł artykułu

Cluster Analysis of Development of Alternative Finance Models Depending on the Regional Affiliation of Countries

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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. (original abstract)
Rocznik
Strony
90--106
Opis fizyczny
Twórcy
  • Sumy State University, Ukraine
  • Sumy State University, Ukraine
  • Sumy State University, Ukraine
  • Sumy State University, Ukraine
Bibliografia
  • Aldenderfer, M. S., & Blashfield, R. K. (1984). Cluster analysis. Beverly Hills: SAGE Publications.
  • Alshubiri, F. (2015). The impact of financial position on risk asset ratios: Empirical study of banking sector listed in Muscat Security Market. Economics and Sociology, 8(2), 95-107.
  • Barnes, S. (2015). Peer-to-peer lending - Disruption for the banking sector? International Banker. Retrieved September 21, 2018, from https://internationalbanker.com/
  • Belas, J., Vojtovich, S., & Kljuchnikov, A. (2016). Microenterprises and significant risk factors in loan process. Economics and Sociology, 9(1), 43-59.
  • Berger, S. C., & Gleisner, F. (2009). Emergence of financial intermediaries in electronic markets: The case of online P2P lending. BuR - Business Research, 2(1), 39-65.
  • Bruton, G., Khavul, S., Siegel, D., & Wright, M. (2015). New financial alternatives in seeding entrepreneurship: Microfinance, crowdfunding, and peer-to-peer innovations. Entrepreneurship Theory and Practice, 39(1), 9-26.
  • Cebula, J., & Pimonenko, T. (2015). Comparison financing conditions of the development biogas sector in Poland and Ukraine. International Journal of Ecology and Development, 30(2), 20-30.
  • Chow, W. W., & Fung, M. K. (2013). Financial development and growth: A clustering and causality analysis. The Journal of International Trade and Economic Development, 22(3), 430-453.
  • Christopoulos, D. K., & Tsionas, E. G. (2004). Financial development and economic growth: Evidence from panel unit root and cointegration tests. Journal of Development Economics, 73, 55-74.
  • Dhand, H. Mehn, G., Dickens, D., Patel, A., Lakra, D., & McGrath, A. (2008). Internet based social lending. Communications of the IBIMA, 2, 109-114.
  • Djalilov, K., Lyeonov, S., & Buriak, A. (2015). Comparative studies of risk, concentration and efficiency in transition economies. Risk Governance and Control: Financial Markets and Institutions, 5, 179-198.
  • Duran, B. S., & Odell, P. L. (1974). Cluster analysis: A survey. Berlin: Springer-Verlag.
  • Everett, C. R. (2010). Group membership, relationship banking and loan default risk: The case of online social lending. Banking and Finance Review, 7(2). Retrieved September 21, 2018, from SSRN website: https://ssrn.com/abstract=1114428
  • Everitt, B., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (5th ed.) Chichester: Wiley.
  • Greiner, M., & Wang, H. (2010). Building consumer-to-consumer trust in e-finance marketplaces: An empirical analysis. International Journal of Electronic Commerce, 15(2), 105-136.
  • Gerber, E. M., Hui, J. S., & Kuo, P. Y. (2012). Crowdfunding: Why people are motivated to post and fund projects on crowdfunding platforms. Proceedings of the International Workshop on Design, influence, and social technologies: Techniques, impacts and ethics (Vol. 2, No. 11). New York, NY: ACM.
  • Greenberg, M. D., Hui, J., & Gerber, E. (2013). Crowdfunding: a resource exchange perspective. In CHI'13 Extended Abstracts on Human Factors in Computing Systems. Conference proceedings of the ACM SIGCHI (pp.883-888). April 27-May 02, 2013. Paris, France.
  • Hulme, M. K., & Wright, C. (2006). Internet based social lending: past, present and future. Social Futures Observatory. Retrieved September 21, 2018, from http://citeseerx.ist.psu.edu/
  • Karaev, A., Melnichuk, M., Guev, T., & Mentel, G. (2017). Stability analysis of the banking system: A complex systems approach. Journal of International Studies, 10(3), 273-284.
  • King, R. S. (2015). Cluster analysis and data mining: An introduction. Herndon, VA: Mercury Learning and Information.
  • Kirichenko, L., Radivilova, T., & Carlsson, A. (2017). Detecting cyber threats through social network analysis: Short survey. SocioEconomic Challenges, 1(1), 20-34.
  • Klafft, M. (2008). Online peer-to-peer lending: A lenders' perspective. Paper presented at the International conference on E-Learning, E-Business, Enterprise Information Systems, and E-Government, Las Vegas, USA. Retrieved September 21, 2018, from https://ssrn.com/abstract=1352352
  • Lee, E., & Lee, B. (2012). Herding behavior in online p2p lending: An empirical investigation. Electronic Commerce Research and Applications, 11(5), 495-503.
  • Leonov, S., Frolov, S., & Plastun, V. (2014). Potential of institutional investors and stock market development as an alternative to households' savings allocation in banks. Economic Annals-XXI(11-12), 65-68.
  • Lin, M., Prabhala, N. R., & Viswanathan, S. (2013). Judging borrowers by the company they keep: Friendship networks and information asymmetry in online peer-to-peer lending. Management Science, 59(1), 17-35.
  • Liu, Y., Nagahata, H., Uchiyama, H., & Taniguchi, M. (2017). Discriminant and cluster analysis of possibly high-dimensional time series data by a class of disparities. Communications in Statistics: Simulation and Computation, 46(10)8014-8027.
  • Logan, W., & Esmanov, O. (2017). Public financial services transparency. Business Ethics and Leadership, 1(2), 62-67.
  • Lyeonov, S. V., Vasylieva, T. A., & Lyulyov, O. V. (2018). Macroeconomic stability evaluation in countries of lower-middle income economies. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 1, 138-146.
  • Mateescu, A. (2015). Peer-to-peer lending. Data and Society Research Institute. Retrieved September 21, 2018, from https://www.datasociety.net/pubs/dcr/PeertoPeerLending.pdf
  • Bhandari, M. P. (2018). Journal article critique: The validity and reliability of cross-national surveys analysis. Business Ethics and Leadership, 2(1), 116-120.
  • Morgan Stanley. (2015). Global marketplace lending: Disruptive innovation in financials. Morgan Stanley Blue Paper. Retrieved September 21, 2018, from https://bebeez.it/
  • Myšková, R., & Hájek, P. (2017). Comprehensive assessment of firm financial performance using financial ratios and linguistic analysis of annual reports. Journal of International Studies, 10(4), 96-108.
  • Njegovanović, A. (2018). Artificial intelligence: Financial trading and neurology of decision. Financial Markets, Institutions and Risks, 2(2), 58-68. doi:10.21272/fmir.2(2).58-68.2018
  • Pimonenko, T., Prokopenko, O., & Dado, J. (2017). Net zero house: EU experience in Ukrainian conditions. International Journal of Ecological Economics and Statistics, 38(4), 46-57.
  • Raykov, Y. P, Boukouvalas, A., Baig, F., & Little, M. A. (2016). What to do when k-means clustering fails: A simple yet principled alternative algorithm. PLoS ONE, 11(9).
  • Reiff, M., & Tokar, V. (2016). Post-communist financial and economic development: Cluster analysis of selected countries. Economic Annals-XXI, 161, 12-17.
  • Tan, P.-N., Steinbach, M., & Kumar, V. (2006). Introduction to data mining. Boston: Pearson Addison-Wesley.
  • Vasylieva, T. A., & Chmutova, I. M. (2015). Empirical model of a bank life cycle. Actual Problems of Economics, 172(10), 352-361.
  • Vasilyeva, T., Sysoyeva, L. & Vysochyna, A. (2016). Formalization of factors that are affecting stability of Ukraine banking system. Risk Governance and Control: Financial Markets and Institutions, 6(4), 7-11.
  • Wardrop, R., Rosenberg, R., Zhang, B., Ziegler, T., Squire, R. et al. (2016). Breaking new ground: The Americas alternative finance benchmarking report. University of Cambridge. Retrieved September 21, 2018, from https://www.jbs.cam.ac.uk/
  • Beyi, W. A. (2018). The trilogy of a digital communication between the real man, his digital individual and the market of the digital economy. SocioEconomic Challenges, 2(2), 66-74. doi:10.21272/sec.2(2).66-74.2018
  • Zarutska, E. (2018). Structural-functional analysis of the Ukraine banking system. Financial Markets, Institutions and Risks, 2(1), 79-96.
  • Zhang, B., Colins, L., & Baeck, P. (2014). Understanding alternative finance. University of Cambridge and Nesta. Retrieved September 21, 2018, from https://www.jbs.cam.ac.uk/
  • Zhang, B., Wardrop, B., Rau, R., & Gray, M. (2015). Moving mainstream: The European alternative finance benchmarking report. University of Cambridge and EY. Retrieved September 21, 2018, from http://www.jbs.cam.ac.uk/
  • Zhang, B., Baeck, P., et al. (2016). Pushing boundaries: The UK alternative finance benchmarking report, 2015. University of Cambridge and Nesta. Retrieved September 21, 2018, from CAM website: https://www.jbs.cam.ac.uk/
  • Zhang, B., Deer, L. et al. (2016). Harnessing potential: The Asia Pacific alternative finance benchmarking report, 2016. University of Cambridge. Retrieved September 21, 2018, from CAM website: https://www.jbs.cam.ac.uk/
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171552143

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