Different approaches of bibliometric analysis for data analytics applications in non-profit organisations

Alsolbi, I; Wu, M; Zhang, Y; Joshi, S; Sharma, M; Tafavogh, S; Sinha, A; Prasad, M

Different approaches of bibliometric analysis for data analytics applications in non-profit organisations

Alsolbi, I Wu, M Zhang, Y Joshi, S Sharma, M Tafavogh, S Sinha, A Prasad, M

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Publisher:: OAE Publishing Inc.
Publication Type:: Journal Article
Citation:: Journal of Smart Environments and Green Computing, 2022, 2, (3), pp. 90-104
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Alsolbi, I
dc.contributor.author	Wu, M
dc.contributor.author	Zhang, Y
dc.contributor.author	Joshi, S
dc.contributor.author	Sharma, M
dc.contributor.author	Tafavogh, S
dc.contributor.author	Sinha, A
dc.contributor.author	Prasad, M
dc.date.accessioned	2022-08-16T09:31:21Z
dc.date.available	2022-08-16T09:31:21Z
dc.date.issued	2022-01-01
dc.identifier.citation	Journal of Smart Environments and Green Computing, 2022, 2, (3), pp. 90-104
dc.identifier.issn	2767-6595
dc.identifier.issn	2767-6595
dc.identifier.uri	http://hdl.handle.net/10453/160371
dc.description.abstract	<jats:p>Aim: 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. Methods: 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. Results: 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. Conclusion: The research findings can leverage future research and add value to the existing literature on the subject of data analytics.</jats:p>
dc.language	en
dc.publisher	OAE Publishing Inc.
dc.relation.ispartof	Journal of Smart Environments and Green Computing
dc.relation.isbasedon	10.20517/jsegc.2022.09
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Different approaches of bibliometric analysis for data analytics applications in non-profit organisations
dc.type	Journal Article
utslib.citation.volume	2
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access	*
dc.date.updated	2022-08-16T09:31:20Z
pubs.issue	3
pubs.publication-status	Published online
pubs.volume	2
utslib.citation.issue	3

Abstract:

Aim: 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. Methods: 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. Results: 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. Conclusion: The research findings can leverage future research and add value to the existing literature on the subject of data analytics.

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http://hdl.handle.net/10453/160371