@article{Dymchenko_Smachylo_Rudachenko_Dril_2022, title={MODELING OF PROCESSES OF FORMATION OF STARTUP ECOSYSTEMS ON THE BASIS OF CLUSTER ANALYSIS: ENTREPRENEURIAL ASPECT}, volume={2}, url={https://khg.kname.edu.ua/index.php/khg/article/view/5937}, DOI={10.33042/2522-1809-2022-2-169-71-78}, abstractNote={<p><em>The aim of the article is to model the processes of formation of startup ecosystems on the basis of cluster analysis as a basis for developing strategies for their development. The development of startup ecosystems is due to various support systems that are implemented at different levels: international, national, regional, local.</em></p> <p><em>The article considers the peculiarities of starting a startup ecosystem in Ukraine and abroad. It is proved that the topic of startups is quite popular in Ukrainian business, as startups are the largest number of innovative and innovative products or services, which is a significant prospect for attracting domestic and foreign investment in the economy.</em></p> <p><em>The main approaches to the definition of "startup" and "ecosystem" are analyzed. In a startup ecosystem, all actors involved are connected. Entrepreneurs come together to share ideas and interact with universities to attract future employees, and investors learn to understand which types of entrepreneurs, teams and startups are most likely to succeed and exit, investing in startups to raise new capital.</em></p> <p><em>Models of cluster analysis of processes of formation of startup ecosystems are constructed, which gave the chance to generalize ratings of ecosystems of the countries on 5 clusters. The purpose of cluster analysis is the formation of relatively homogeneous groups (clusters) in the space of variables based on a set of models and methods of aggregation of rows of the data matrix. The use of cluster analysis has a certain sequence of actions and involves the use of several methods. The grouping included 96 countries (4 countries that were included in the ranking for the first time were excluded automatically), which created 5 clusters that differ from each other, but have common characteristics within the selected groups. Each cluster is characterized by features. This division into clusters allowed to highlight the features of the development of startup ecosystems, provide characteristics of each group of countries and in the future will be the basis for developing recommendations and formulating strategies for the development of startup ecosystems.</em></p>}, number={169}, journal={Municipal economy of cities}, author={Dymchenko, O. and Smachylo, V. and Rudachenko, O. and Dril, N.}, year={2022}, month={Mar.}, pages={71–78} }