The influence of big data analytics technological capabilities and strategic agility on performance of private higher education institutions

Khaw, Tze Yin; Teoh, Ai Ping

doi:10.1108/jarhe-07-2022-0220

Cited by 8 publications

(7 citation statements)

References 55 publications

(100 reference statements)

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“…Despite criticism regarding its ability to address dynamic environments, many researchers still support the applicability of RBV in various contexts, enabling firms to leverage their internal resources (Iqbal et al, 2023b;Iqbal et al, 2023cIqbal et al, , 2023dKhaw and Teoh, 2023;Yaakub and Mohamed, 2020). On the other hand, DCT theory has been applied to improve the static characteristics of RBV, DCT continuously leverages organizational resources, enabling firms to achieve sustained business success and competitive advantage (Khaw and Teoh, 2023). In light of RBV and DCT theories, this study considers TFL and TNL as valuable resources, while QC is viewed as a university's strategic dynamic capability for fostering continuous improvement and managing the prevailing uncertain environment.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

“…The RBV theory emphasizes the use of valuable, scarce, inimitable and irreplaceable internal resources to achieve a competitive advantage (Barney, 1991). Despite criticism regarding its ability to address dynamic environments, many researchers still support the applicability of RBV in various contexts, enabling firms to leverage their internal resources (Iqbal et al, 2023b;Iqbal et al, 2023cIqbal et al, , 2023dKhaw and Teoh, 2023;Yaakub and Mohamed, 2020). On the other hand, DCT theory has been applied to improve the static characteristics of RBV, DCT continuously leverages organizational resources, enabling firms to achieve sustained business success and competitive advantage (Khaw and Teoh, 2023).…”

Section: Conceptual Frameworkmentioning

confidence: 99%

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The nexus between leadership styles and organizational performance: the mediating role of quality culture

Iqbal

Taib

Razalli

2023

QAE

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Purpose This study aims to investigate the mediating role of quality culture (QC) between transformational leadership (TFL), transactional leadership (TNL) and organizational performance (OP) in higher education institutions. Design/methodology/approach The study collects data through a nationwide survey of administrators representing public and private universities in Pakistan using stratified random sampling techniques, while partial least squares structural equation modeling (PLS-SEM) is used for data analysis. Findings The results show that both TFL and TNL directly influence QC and that QC directly influences OP. Additionally, the study reveals significant indirect effects of TFL and TNL on OP through QC. However, the direct effects of TFL and TNL on OP are not empirically supported. Research limitations/implications This study contributes theoretically to the understanding of OP in universities by examining valuable resources (TFL, TNL) and dynamic capability (QC) as predictors while also introducing QC as a mediator to explain the underlying mechanism between TFL, TNL and OP. However, limitations include a cross-sectional design, a small sample size and reliance on administrators' perceptions as the sole respondents. Practical implications This study provides interesting insights for leaders, policymakers and quality managers to integrate valuable, dynamic resources and foster QC by increasing quality awareness at all departmental levels, thereby improving university performance. Originality/value The novelty of this study is the introduction of QC as a mediator of TFL, TNL and OP in a university setting.

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Section: Conceptual Frameworkmentioning

confidence: 99%

Section: Conceptual Frameworkmentioning

confidence: 99%

The nexus between leadership styles and organizational performance: the mediating role of quality culture

Iqbal

Taib

Razalli

2023

QAE

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“…The RBV theory underscores the leverage of internal resources that are esteemed for their rarity, distinctiveness, and irreplaceability, aimed at securing a competitive edge (Barney, 1991). The broad acknowledgment of RBV's applicability across diverse sectors, including HE, empowers organizations to harness their internal resources (Iqbal et al, 2023a, b, c, d;Khaw and Teoh, 2023;Muangmee et al, 2021). Within this RBV framework, the present study regards management support, quality infrastructure, and staff training as invaluable assets within universities, augmenting the effectiveness of QECs.…”

Section: Research Frameworkmentioning

confidence: 99%

“…The broad acknowledgment of RBV's applicability across diverse sectors, including HE, empowers organizations to harness their internal resources (Iqbal et al. , 2023a, b, c, d; Khaw and Teoh, 2023; Muangmee et al. , 2021).…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

Optimizing quality enhancement cells in higher education institutions: analyzing management support, quality infrastructure and staff training

Iqbal,

Moosa,

Taib

2024

IJQRM

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PurposeThis study aims to investigate the relationship between management support, quality infrastructure, staff training and the effectiveness of quality enhancement cells (QECs) established in higher education institutions.Design/methodology/approachData were acquired via a structured questionnaire dispatched to faculty members across 12 public and private universities, primarily situated in Punjab, Pakistan. Among the 200 questionnaires distributed, 180 were retrieved and 140 were deemed valid. The proposed relationships were examined using SPSS–25 and PLS–SEM.FindingsThe results show a positive and significant relationship between management support, quality infrastructure and staff training with QECs' effectiveness. The study also highlights that the effectiveness of QECs is “Good” in only two of the 12 universities, while in most universities it is “Barely Acceptable”. Furthermore, QECs' effectiveness is slightly better in public universities compared to private institutions.Research limitations/implicationsThe study employs convenience sampling and a cross-sectional approach, focusing on faculty members from 12 universities, primarily in Punjab, Pakistan. To enhance future research, larger samples and probability-based sampling should be considered, while involving quality managers and students for a broader perspective.Practical implicationsThe research suggests policymakers and university leaders should strengthen their support by providing resources, quality infrastructure and training for academic and administrative staff. This would enhance the effectiveness of QECs and improve the overall quality of education in both public and private universities.Originality/valueThis study contributes to the literature on quality assurance in higher education by emphasizing the significance of QECs concerning management support, quality infrastructure and staff training – areas that are often overlooked in Pakistani universities.

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“…The digital transformation age has witnessed considerable advances in data management and intelligent technologies that changed almost all business aspects such as financial, accounting, commerce, marketing, command and control. The enormous volumes of business data led firms to depend more on smart systems to assist in the analysis of big data and make the right decisions that support the firm's competitiveness (AL-Khatib and Ramayah, 2023; Khaw and Teoh, 2023). The fundamental objective of the cutting-edge technologies embedded in artificial business intelligence is to enhance new ways of collecting and analysing data that help companies improve their decision-making ethos by using data analytics (Nisar et al , 2020; Al-Khatib, 2022a).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of data analytics-oriented business intelligence technology effectiveness: an enterprise-level analysis

Al-Okaily

Teoh

Al-Okaily

2023

BPMJ

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PurposeA crucial question still remains unanswered as to whether data analytics-oriented business intelligence (hereafter, BI) technologies can bring organizational value and benefits. Thereby, several researchers called for further empirical research to extend the limited knowledge in this critical area. In an attempt to deal with this issue, we presented and tested a theoretical model to assess BI effectiveness at the organizational benefits level in this research article.Design/methodology/approachThe suggested research model expands the application of the DeLone and McLean model in BI technology success or effectiveness research from individual level to organizational level. A cross-sectional survey is developed to obtain primary quantitative data from business and technology managers who are depending on BI technologies to make operational, technical and strategic decisions in Jordanian-listed firms.FindingsEmpirical findings show that system quality, information quality and training quality are significant predictors of user satisfaction, but not of perceived benefit. Data quality was found to be a strong predictor of both perceived benefit and user satisfaction. The influence of perceived benefit on user satisfaction was significant in turn both factors positively affect organizational benefits.Originality/valueThis research paper is a pioneering effort to assess BI technology effectiveness at an organizational level outside the context of developed countries. To the best of the authors’ knowledge, no prior research has combined all dimensions used in this research in one single model.

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The influence of big data analytics technological capabilities and strategic agility on performance of private higher education institutions

Cited by 8 publications

References 55 publications

The nexus between leadership styles and organizational performance: the mediating role of quality culture

The nexus between leadership styles and organizational performance: the mediating role of quality culture

Optimizing quality enhancement cells in higher education institutions: analyzing management support, quality infrastructure and staff training

Evaluation of data analytics-oriented business intelligence technology effectiveness: an enterprise-level analysis

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