Different approaches of bibliometric analysis for data analytics applications in non-profit organisations (FULL-TEXT)

Profitable companies that used data analytics have a double gain in cost reduction, demand prediction, and decision-making. However, using data analysis in non-profit organisations (NPOs) can help understand and identify more patterns of donors, volunteers, and anticipated future cash, gifts, and grants. This article presents a bibliometric study of 2673 to discover the use of data analytics in different NPOs and understand its contribution. We characterise the associations between data analysis techniques and NPOs using, Bibliometrics R tool, a co-term analysis and scientific evolutionary pathways analysis, as well as identify the research topic changes in this field throughout time. The findings revealed three key conclusions may be drawn from the findings: (1) In the sphere of NPOs, robust and conventional statistical methods-based data analysis procedures are dominantly common at all times; (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. The research findings can leverage future research and add value to the existing literature on the subject of data analytics.

For FULL-TEXT https://doi.org/10.20517/jsegc.2022.09

Author(s): Idrees Alsolbi, Mengjia Wu, Yi Zhang, Sudhanshu Joshi, Manu Sharma, Siamak Tafavogh, Ashish Sinha, Mukesh Prasad
Organization(s): University of Technology Sydney, Commonwealth Bank Health Society
Source: Journal of Smart Environments and Green Computing
Year: 2022

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