Cluster analysis of charitable organizations of Ukraine using K-means technology

The work is devoted to the issue of segmentation of charitable organizations for structuring the sector of non-profit organizations of Ukraine using cluster analysis tools using software R for automated data processing. The four-cluster and five-cluster models were constructed using the K-means method, the suitability for clustering of which was checked using the Hopkins’ Index (H statistics). The developed four-cluster model demonstrated a significant level of validity in terms of correspondence between data and the stability of their structure. The basic indicators of financial and economic activity of charitable organizations were used as criteria for clustering: the number of staff, charitable assistance received and funds spent on the maintenance of the organization in the reporting period. It was found that the clusters of charitable organizations of Ukraine differ in the scale of activity, the number of funds raised, the number of costs for their own maintenance and the relationship between these indicators. The study demonstrated the existence in Ukraine of the most influential cluster of local charities that address social issues exclusively at the regional level, due to the small financial resources involved to support their activities. Such organizations are system-creating for the entire nonprofit sector in Ukraine, their importance is manifested in the most rapid response to the needs of recipients through the implementation of small charitable projects.