Investigating medical professionals' continuance intention of the cloud-based e-learning system: an extension of expectation–confirmation model with flow theory

Which quality determinants cause MOOCs continuance intention? A hybrid extending the expectation-confirmation model with learning engagement and information systems success

Purpose

The purpose of this study is to propose the research model integrating the expectation-confirmation model with the views of learning engagement (LE) and extending DeLone and McLean information systems (IS) success model to examine whether quality determinants as antecedents to students' beliefs can influence students' continuance intention of massive open online courses (MOOCs).

Design/methodology/approach

Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed, and 363 (60.5%) useable questionnaires were analyzed using structural equation modeling in this study.

Findings

This study proved that students' perceived knowledge quality, system quality, interface design quality, learner–instructor interaction quality, and collaboration quality all positively caused students' perceived usefulness, confirmation and LE in MOOCs, which jointly explained students' satisfaction with MOOCs and subsequently resulted in students' continuance intention of MOOCs.

Originality/value

This study fully evaluates IS-related and interaction-related quality determinants via an understanding of students' state of LE in explaining students' continuance intention of MOOCs that is difficult to expound with only their utilitarian perception of MOOCs. Hence, this study contributes to deep insights into an all-round quality evaluation in the field of MOOCs continuance intention and takes extrinsic and intrinsic motivators into account in the theoretical development of MOOCs continuance intention to acquire a more comprehensive and robust analysis.

Antecedents of students’ e-learning continuance intention during COVID-19: An empirical study

This study aims at exploring the underlying determinants influencing students' continuance intention to use an e-Learning platform during the COVID-19 pandemic. Based on the technology acceptance model and expectation-confirmation model, the study investigated the role of contextual (i.e., social isolation), psychological (academic year loss and cyberchondria), and student support-related (government and institutional supports) determinants on students' continuance intention to use an e-Learning platform during the pandemic. The study collected data from 440 respondents and analyzed those with Structural Equation Modeling. The findings showed that an e-Learning continuance intention during the pandemic is affected by usefulness, ease of use, attitudes, and intention to use the e-Learning platform; while the behavioral intention is influenced by usefulness, ease of use, attitudes, contextual, psychological, and student support-related determinants; and attitudes are impacted by usefulness and ease of use. Moreover, usefulness is predicted by confirmation of expectation; e-satisfaction is forecasted by usefulness and confirmation of expectation; whereas, cyberchondria is influenced by social isolation; fear of academic year loss is influenced by cyberchondria. Finally, intention to use mediated the impact of usefulness, ease of use, attitudes, contextual, psychological, and student support-related determinants on continuance intention. The study contributes to e-Learning literature incorporating contextual, psychological, and student support-related determinants into the technology acceptance model and expectation-confirmation model, which guide policymakers to understand how all levels of students can be brought into the e-Learning platforms that eventually help to eliminate digital discrimination barrier in the academia during any emergency. The policymakers must be careful in designing eLearning platforms since students' e-learning continuance intention may vary due to unprecedented crises, such as COVID-19.

How can robo-advisors retain end-users? Identifying the formation of an integrated post-adoption model

Purpose

This study's purpose is to propose an integrated post-adoption model based on expectation-confirmation model (ECM) and cognitive absorption (CA) theory to examine whether network factors, gamification factor, and quality factors as antecedents to end-users' beliefs can affect their continuance intention of the robo-advisor.

Design/methodology/approach

A total of 600 questionnaires were distributed in three sample banks in Taiwan, and sample data for this study were collected from these three banks' customers who had experience in using these banks' own robo-advisor to make their investment decisions. Consequently, 381 useable questionnaires were analyzed using structural equation modeling in this study, with a useable response rate of 63.5%.

Findings

This study proposes a solid research model that based on ECM and CA theory, three types of factors, network factors, gamification factor, and quality factors, as antecedents to end-users’ continuance intention of the robo-advisor have been examined, and this study's results strongly support the research model with all hypothesized links being significant.

Originality/value

This study contributes to end-users' continuance intention of the robo-advisor based on ECM, CA theory, theory of network externalities, gamification, and updated DeLone and McLean IS success model, and reveals deep insights into the evaluation of determinants in the field of end-users' continuance intention of the robo-advisor. Hence, it is especially worth mentioning that three types of determinants (i.e. network factors, gamification factor, and quality factors) are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into account in this study's research model development of end-users' continuance intention of the robo-advisor to acquire a more all-round and robust analysis.

Understanding Agri-Food Traceability System User Intention in Respond to COVID-19 Pandemic: The Comparisons of Three Models

Scientists believed the outbreak of COVID-19 could be linked to the consumption of wild animals, so food safety and hygiene have become the top concerns of the public. An agri-food traceability system becomes very important in this context because it can help the government to trace back the entire production and delivery process in case of food safety concerns. The traceability system is a complicated digitalized system because it integrates information and logistics systems. Previous studies used the technology acceptance model (TAM), information systems (IS) success model, expectation confirmation model (ECM), or extended model to explain the continuance intention of traceability system users. Very little literature can be found integrating two different models to explain user intention, not to mention comparing three models in one research context. This study proposed the technology acceptance model (TAM), technology acceptance model-information systems (TAM-IS) success, and technology acceptance model-expectation confirmation model (TAM-ECM) integrated models to evaluate the most appropriate model to explain agri-food traceability system during the COVID-19 pandemic. A questionnaire was designed based on a literature review, and 197 agri-food traceability system users were sampled. The collected data were analyzed by partial least square (PLS) to understand the explanatory power and the differences between the three models. The results showed that: (1) the TAM model has a fair explanatory power of continuance intention (62.2%), but was recommended for its’ simplicity; (2) the TAM-IS success integrated model had the best predictive power of 78.3%; and (3) the system providers should raise users’ confirmation level, so their continuance intention could be reinforced through mediators, perceived value, and satisfaction. The above findings help to understand agri-food traceability system user intention, and provide theoretical and practical implications for system providers to refine their system design.

Examining students' continuous use of online learning in the post-COVID-19 era: an application of the process virtualization theory

Purpose

This study investigated the impact of the virtualization requirements of the learning process on students' satisfaction and their intention to continue using online learning.

Design/methodology/approach

A research model was developed using the process virtualization theory (PVT); it was validated empirically using data obtained from an online questionnaire-based survey of 489 undergraduate students.

Findings

The main results support the role of representation for sensory requirements, sensory requirements, reach, representation for relationship requirements and relationship requirements on shaping students' satisfaction, which all also have a significant influence on students' intention to continue using online learning. Relevance factors are responsible for 61.6% of the variance in students' satisfaction and 83.6% of the variance in their intention to continue using online learning. However, neither the synchronism requirements nor the identification and control requirements had a significant effect on students' satisfaction or on their intention to continue using online learning.

Originality/value

The present research focused on PVT in an online learning context; consequently, a new set of factors that influenced students' satisfaction with and intentions to continue using online learning was empirically tested for the first time. This research contributes to the literature on information systems because it advances the generalizability and applicability of the PVT in a new context and new cultural setting. Moreover, the research apprises researchers and practitioners of new factors, which should be understood and fulfilled to make virtual learning equivalent to the face-to-face learning experience.

Students' satisfaction and continued intention toward e-learning: a theory-based study

Coronavirus disease (COVID-19) has forced the urgent lockdown of schools and colleges worldwide. To ensure the continuity of education a shift from traditional teaching to e-learning was required. This study aims to identify factors that affect students' satisfaction and continued intention towards e-learning. A questionnaire was distributed to medical and dental students (second to sixth year) from different universities in Saudi Arabia. The study synthesizes the expectation-confirmation theory (ECT) and the theory of planned behavior (TPB) to predict students' satisfaction and intention to continue using e-learning using a validated self-administered questionnaire. We used the structural equation model to analyze the results and assess the study's hypotheses. A total of 870 completed questionnaires were received (67% response rate). The results showed that students were at a moderate level of satisfaction (median = 3.5). According to the ECT, both perceived usefulness and confirmation significantly influenced students' satisfaction (β = -.69 and β = .82, respectively). Satisfaction was the strongest predictor of students' continued intention (β = 1.95). Among the TPB constructs, perceived behavioral control (β = .51), attitudes (β = .39), and subjective norms (β = .36) had a significant positive influence on their intention to use e-learning. The results suggest efforts to increase students' satisfaction and intention with e-learning should be directed to adopting easy and useful e-learning platforms. In addition, training and motivating students to continue e-learning and increasing their confidence to ensure the effective and efficient use of such teaching modalities.

A comprehensive study of the role of cloud computing on the information technology infrastructure library (ITIL) processes

Purpose

Information technology infrastructure library (ITIL) is a commonly utilized IT service management execution technique that helps IT services to be planned, designed, selected, operated and continuously improved. ITIL procedures are utilized to measure the efficiency of IT service management procedures and their association with the accelerated system development of cloud systems. The challenges faced in IT deployment and maintenance management significantly restrict cloud computing services' reliability. Therefore, this article aims to review a comprehensive study of the role of cloud computing on the ITIL processes.

Design/methodology/approach

Each enterprise strives to stay competitive in the market and offers the services its consumers are looking for, all in line with cost-effectiveness and client needs. The ITIL framework provides best practice guidance for IT service management that includes a collection of ample publications supplying detailed guidelines on the management of IT functions, processes, responsibilities and roles associated with IT service management. On the other hand, the way companies employ IT services with an effect on the role of enterprise infrastructure is altered by cloud computing. Hence, the investigation makes utilization of a systematic literature review (SLR) detailing crucial success factors of cloud computing execution in ITIL. The authors have recognized 35 valuable contributions, providing a comprehensive view of study in this field, of which 22 papers were found according to some filters that have been analyzed in this article. Selected articles are presented in two groups, including cloud service and cloud service providers.

Findings

Owing to the overall expense of execution and problems with combining the ITIL approach with the existing organizational IT strategic strategy, ITIL adoption has begun to wane over the last few years. An established methodology for ITIL deployment that will assure long-term success for those wanting to use private cloud procurement will be the most important inference that can be taken from this article. ITIL offers a perfect platform to execute and support cloud applications effectively. IT will prevent cloud sprawl and instability, reduce the likelihood of service interruption and optimize customer loyalty by merging humans, procedures and technologies into hybrid environments.

Research limitations/implications

This survey is more aimed at specialists such as IT experts; so, further evaluations must also be carried out in order to understand the company's views on the risks and advantages of adopting ITIL. In addition, non-English articles are not discussed in this article.

Practical implications

The study outcomes would help suppliers of cloud computing services assess their service quality and ensure customer satisfaction with the quality of cloud computing services. The outcomes will also supply a reference for cloud infrastructure customers to assess and choose various kinds of cloud computing services.

Originality/value

An SLR with perspectives from ITIL professionals and business studies is the benefit of this report. By offering a more thorough framework that helps companies achieve efficiency, effectiveness and creativity in ITIL execution, this article would be useful for ITIL clients, decision-makers and developers.