Profitable organisations that applied data analytics have obtained a double-digit improvement in reducing costs, predicting demands, and enhancing decision-making. However, in nonprofit organisations (NPOs), applying data analysis can interpret and discover more patterns of donors, volunteers, and forecasting future funds, gifts and grants. To uncover the usage of data analytics in different NPOs and understand its contribution, this article presents a bibliometric analysis of 2673 related publications to reveal the research landscape of data analytics applied in NPOs. Through a co-term analysis and scientific evolutionary pathways analysis, we profile the associations between data analysis techniques and NPOs and additionally identify the research topic changes in this field over time. The results yield us three major insights: (1) Robust and classic statistical methods-based data analysis techniques are dominantly prevalent in the NPOs field through all the time; (2) Healthcare and public affairs are two crucial sectors that involve data analytics to support decision-making and problem-solving; (3) Artificial Intelligence (AI)-based data analytics is a recently emerging trending, especially in the healthcare-related sector; however, it is still at an immature stage, and more efforts are needed to nourish its development.
Author(s): Idrees Alsolbi, Mengjia Wu, Yi Zhang, Siamak Tafavogh, Ashish Sinha, Mukesh Prasad
Organization(s): University of Technology Sydney
Source: Pattern Recognition and Data Analysis with Applications. Lecture Notes in Electrical Engineering