Information systems success in libraries: a meta-analysis of ISSM and future direction

Ali, Irfan; Warraich, Nosheen Fatima

doi:10.1108/el-06-2023-0163

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…The findings revealed that system factors and content factors have a significant impact on students' satisfaction with YouTube, which further influences their intention to use the platform for learning purposes. Ali and Warraich (2024) examined information systems success in libraries. The results show that information quality, system quality and service quality positively influence satisfaction with library systems.…”

Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

Recommended information adoption by university students in their study/research

Zha,

Lu,

Yan

2024

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Purpose For undergraduate and graduate students in universities, social media are playing an important role in their study/research because a large amount of academic information has been accumulated on social media. Indeed, social media are complementing university libraries. Given that intelligent recommender systems have been widely implemented on social media, this paper aims to examine the adoption mechanism of intelligently recommended information by university students in their study/research. Design/methodology/approach Building upon the updated information system success model and herding theory, this study developed a research model to examine the determinants of recommended information adoption in mobile applications for social media. Data were collected through an online questionnaire and analyzed with partial least squares structural equation modelling. Findings The results suggest that herding belief is a valid second-order construct, comprising two first-order dimensions of imitating others and discounting their own information. Information quality, system quality and service quality directly impact satisfaction with the intelligent recommender system. Furthermore, satisfaction with the intelligent recommender system and herding belief directly impact recommended information adoption by university students in their study/research. Originality/value This study draws on the updated information system success model and incorporates herding belief as an extended component to investigate recommended information adoption, providing a new lens for understanding recommended information adoption by university students in their study/research.

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Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

Recommended information adoption by university students in their study/research

Zha,

Lu,

Yan

2024

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Acceptance and use of artificial intelligence and AI-based applications in education: A meta-analysis and future direction

Ali,

Warraich,

Butt

2024

Information Development

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The aim of present study was to measure the relationship of UTAUT (Unified Theory of Acceptance and Use of Technology) and TAM (Technology Acceptance Model) variables regarding AI technology and AI-based applications acceptance in education sector. Research was carried out by using PRISMA (Preferred reporting items for systematic review and meta-analysis) guidelines. The relevant studies were searched from major databases that included a) Scopus, and b) Web of Science. Initial search retrieved 309 titles, and 30 relevant articles and conference papers were selected following the search process. Data was analysed using CMA (Comprehensive Meta-analysis) and Meta-Essential software. Findings exhibit that the relationship between UTAUT variables and BI to accept AI and AI-based applications in education was high (PE → BI), medium (EE → BI, SI → BI), and low (FC → BI). The magnitude of the relationship of TAM constructs remained high for all paths (PU → AT, PEOU → AT, PU → BI, and PEOU → BI). Theoretically, this meta-analysis provided a panoramic picture of two leading technology acceptance models regarding the acceptance/adoption of AI and AI-based technology in education sector. This meta-analysis provided a way forward for researchers to extend research on AI-based applications including ChatGPT, intelligent tutoring, AI-based robots, AI-based Chatbots, and AI-based voice assistants. Practically, findings are useful for IT companies, and decision makers of educational institutes in designing and implementing AI and AI-based applications.

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Navigating Digital Transformation in Zimbabwe's Higher and Tertiary Education Post the COVID-19 Pandemic

Tsverukayi,

Poshai

2024

Advances in Higher Education and Professional Development

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Higher and tertiary education sectors in different parts of the world have experienced substantial digital transformations since the emergence of the Coronavirus (COVID-19) pandemic, which forced many higher education institutions (HEIs) to adopt remote teaching and learning systems using relevant technologies. The purpose of this chapter is to examine the scope of digital transformation in HEIs in Zimbabwe, post the COVID-19 pandemic. The study employed a qualitative methodology where purposive sampling was used in selecting students, lecturers and university administrators from whom data was collected through semi-structured interviews and focus group discussions. The study revealed that HEIs in Zimbabwe have committed to embracing digital transformation, but they are financially incapacitated to procure supporting technologies for use by staff, administrators and students. The study recommends that amongst other measures, partnerships with the donor community can help leverage the financial resources to support the digital transformation of HEIs in Zimbabwe.

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Information systems success in libraries: a meta-analysis of ISSM and future direction

Cited by 3 publications

References 30 publications

Recommended information adoption by university students in their study/research

Recommended information adoption by university students in their study/research

Acceptance and use of artificial intelligence and AI-based applications in education: A meta-analysis and future direction

Navigating Digital Transformation in Zimbabwe's Higher and Tertiary Education Post the COVID-19 Pandemic

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