Big Data Analytics Socio-Technical Systems on Strategic Decision Making and Organisational Performance: Case of Saudi Arabian Higher Education

Aseeri, Maher Mohammed

Big Data Analytics Socio-Technical Systems on Strategic Decision Making and Organisational Performance: Case of Saudi Arabian Higher Education

Aseeri, Maher Mohammed

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Publication Type:: Thesis
Issue Date:: 2023

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Field	Value	Language
dc.contributor.author	Aseeri, Maher Mohammed
dc.date.accessioned	2024-07-28T23:15:17Z
dc.date.available	2024-07-28T23:15:17Z
dc.date.issued	2023
dc.identifier.uri	http://hdl.handle.net/10453/179855
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	Big Data Analytics (BDA) is an emerging technology that has revolutionised varied fields such as Higher Education Institutions (HEIs), healthcare, governments, and private sectors. BDA technologies allow firms to quickly access, analyse and visualise a variety of big data that could improve executives' decision-making. As a result, improving decision-making will lead to enhance overall organisational performance. Although a significant amount of research exists on BDA in higher education institutions, studies that combine socio-technical aspect that support BDA in Saudi HEIs is lacking. In particular, applying mixed methods to explore the influence of socio-technical aspects that support BDA in Saudi HEIs. Hence, this research investigates the socio-technical subsystem that supports big data analytics and its role in improving top management decisions and the overall performance of Saudi HEIs. This research applied socio-technical theory for the proposed model based on the ontological postpositive for the quantitative method and the interpretivism paradigm for the qualitative method. Considering the research gap provided above, this study applied a mixed methods approach for data collection. Besides, we applied a cross-sectional survey for the quantitative data, whereas the qualitative data applied semi-structured interviews. The sample population involved the IT staff and data scientists, representing the big data performers (BDP) and top management in the Saudi HEIs. Quantitative data was collected using validated scales of previous studies, and the hypotheses were evaluated using PLS-SEM. Consequently, qualitative data were analysed using N-Vivo 12 pro, and a thematic analysis technique was applied, which formed themes and patterns that were then combined with the outcomes of the "quantitative results". In light of the findings, the PLS-SEM analysis conducted to test the hypotheses highlighted the significance of BDP on Big Data Systems (BDS), i.e., security, privacy, and quality. However, the results revealed the insignificance of organisational culture in big data systems (BDS), although having a positive value. Nonetheless, the organisational culture significantly impacted BDP, implying the influence of a data-driven culture and supportive top management on the workforce's attitude towards BDA-related change and skill development. Besides, the social and technical subsystems of the BDA— the BDS and BDP— are significantly correlated, along with their correlation with strategic decision-making. The study's implications comprised insights guiding the managers and policymakers to acknowledge the importance of organisational culture (hierarchical, adhocratic, market, and clan) while strategising the implementation of BDA and its systems and developing training modules for its BDP accordingly.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/179855/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2023 Maher Mohammed Aseeri
dc.rights	au.edu.uts.lib/cph
dc.title	Big Data Analytics Socio-Technical Systems on Strategic Decision Making and Organisational Performance: Case of Saudi Arabian Higher Education	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

Big Data Analytics (BDA) is an emerging technology that has revolutionised varied fields such as Higher Education Institutions (HEIs), healthcare, governments, and private sectors. BDA technologies allow firms to quickly access, analyse and visualise a variety of big data that could improve executives' decision-making. As a result, improving decision-making will lead to enhance overall organisational performance. Although a significant amount of research exists on BDA in higher education institutions, studies that combine socio-technical aspect that support BDA in Saudi HEIs is lacking. In particular, applying mixed methods to explore the influence of socio-technical aspects that support BDA in Saudi HEIs. Hence, this research investigates the socio-technical subsystem that supports big data analytics and its role in improving top management decisions and the overall performance of Saudi HEIs. This research applied socio-technical theory for the proposed model based on the ontological postpositive for the quantitative method and the interpretivism paradigm for the qualitative method. Considering the research gap provided above, this study applied a mixed methods approach for data collection. Besides, we applied a cross-sectional survey for the quantitative data, whereas the qualitative data applied semi-structured interviews. The sample population involved the IT staff and data scientists, representing the big data performers (BDP) and top management in the Saudi HEIs. Quantitative data was collected using validated scales of previous studies, and the hypotheses were evaluated using PLS-SEM. Consequently, qualitative data were analysed using N-Vivo 12 pro, and a thematic analysis technique was applied, which formed themes and patterns that were then combined with the outcomes of the "quantitative results". In light of the findings, the PLS-SEM analysis conducted to test the hypotheses highlighted the significance of BDP on Big Data Systems (BDS), i.e., security, privacy, and quality. However, the results revealed the insignificance of organisational culture in big data systems (BDS), although having a positive value. Nonetheless, the organisational culture significantly impacted BDP, implying the influence of a data-driven culture and supportive top management on the workforce's attitude towards BDA-related change and skill development. Besides, the social and technical subsystems of the BDA— the BDS and BDP— are significantly correlated, along with their correlation with strategic decision-making. The study's implications comprised insights guiding the managers and policymakers to acknowledge the importance of organisational culture (hierarchical, adhocratic, market, and clan) while strategising the implementation of BDA and its systems and developing training modules for its BDP accordingly.

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