Technological and human factors for supporting big data analytics in Saudi Arabian higher education

Aseeri, M; Kang, K

Technological and human factors for supporting big data analytics in Saudi Arabian higher education

Aseeri, M Kang, K

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Publication Type:: Conference Proceeding
Citation:: 26th Americas Conference on Information Systems, AMCIS 2020, 2020
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Aseeri, M
dc.contributor.author	Kang, K https://orcid.org/0000-0003-4252-9802
dc.date.accessioned	2021-02-23T01:03:06Z
dc.date.available	2021-02-23T01:03:06Z
dc.date.issued	2020-01-01
dc.identifier.citation	26th Americas Conference on Information Systems, AMCIS 2020, 2020
dc.identifier.isbn	9781733632546
dc.identifier.uri	http://hdl.handle.net/10453/146300
dc.description.abstract	© 2020 26th Americas Conference on Information Systems, AMCIS 2020. All rights reserved. Big data analytics is an emerging technology that is widely utilized across industries and is increasingly discussed among researchers. This study investigates the effects of Technological and Human Factors for Big Data Analytics (THFFBDA) on technological improvements of big data analytics (BDA) towards improved decision making by top management in Saudis' Higher Education. This paper seeks to enhance our understanding of how these components impact on the implementation of big data analytics to improve decision making by top management in Saudi Arabian Higher Institutions. This study draws on the Sociotechnical theory to define and investigate THFFBDA, and the Delone & McLean Information System success model to highlight the technological improvements in BDA. This research paper concludes with propositions on the potential effects of THFFBDA on decision making among universities' top management and proposes a mixed-methods approach to study the above phenomenon.
dc.language	en
dc.relation.ispartof	26th Americas Conference on Information Systems, AMCIS 2020
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Technological and human factors for supporting big data analytics in Saudi Arabian higher education
dc.type	Conference Proceeding
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - HCTD - Human Centred Technology Design
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Professional Practice and Leadership
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
dc.date.updated	2021-02-23T01:03:04Z
pubs.publication-status	Published

Abstract:

© 2020 26th Americas Conference on Information Systems, AMCIS 2020. All rights reserved. Big data analytics is an emerging technology that is widely utilized across industries and is increasingly discussed among researchers. This study investigates the effects of Technological and Human Factors for Big Data Analytics (THFFBDA) on technological improvements of big data analytics (BDA) towards improved decision making by top management in Saudis' Higher Education. This paper seeks to enhance our understanding of how these components impact on the implementation of big data analytics to improve decision making by top management in Saudi Arabian Higher Institutions. This study draws on the Sociotechnical theory to define and investigate THFFBDA, and the Delone & McLean Information System success model to highlight the technological improvements in BDA. This research paper concludes with propositions on the potential effects of THFFBDA on decision making among universities' top management and proposes a mixed-methods approach to study the above phenomenon.

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http://hdl.handle.net/10453/146300