Investigating Factors That Influence College Students' Online Continuous Learning Intention during COVID-19 Epidemic

This study aims to explore university students' continuous intention toward online learning during COVID-19 pandemic. A total of 120 students enrolled in online learning were surveyed to collect their perception of an extended model by adding task value to the expectation-confirmation model. Structural equation modeling was employed to verify the hypotheses proposed in this study. The results indicated that task value and technology usefulness were significant predictors of students' continuous intention toward online learning. More specifically, technology usefulness had a direct impact on students' continuous intention, while students' perceived task value played an indirect role in the prediction of their continuous intention. However, the impacts of both confirmation and satisfaction were not statistically significant on students' continuous intention. The results suggest that practitioners and researchers should pay special attention to the technological usefulness of online learning environments and task value, especially task value, in order to enhance students' retention of online learning. This study would contribute to implications to better design and implement online learning. © 2023 IEEE.

Investigating Students' Satisfaction with Online Collaborative Learning During the COVID-19 Period: An Expectation-Confirmation Model.

The recent outbreak of COVID-19 posed discontinuous disruption to traditional learning modes worldwide. In order to keep social distance, online collaborative learning has become a necessity during the pandemic. However, our understanding of students' well-being and satisfaction with online collaborative learning is limited, especially during the COVID-19 period. Leveraging expectation confirmation theory, this study focuses on the triggers and inhibitors of students' cognitive load during online collaborative learning process and their subsequent satisfaction with the learning mode during the pandemic. We used a mixed-method approach in this study. We conducted a qualitative study with interview data and a quantitative study with surveys. The results indicate several psychological and cognitive antecedents of students' cognitive load during online collaborative learning. Findings also indicate that a high level of cognitive load will decrease students' perceived usefulness of the online learning platform and expectation confirmation, thus leading to a low level of satisfaction with online collaborative learning. This study can provide theoretical and practical implications for a better understanding of online student groups' satisfaction with online collaborative learning during the COVID-19 period.

Does User Satisfaction Play a Role in the Sustainability of Contact Tracing Application Intention?

Various countries have developed contact tracing applications to prevent the spread of COVID-19 outbreaks. For example, Indonesia launched a government surveillance technology named PeduliLindungi as a contact tracing application for COVID-19. This empirical paper aims to assess the explanatory power of the Expectation-Confirmation Model (ECM) by adding three new constructs, perceived security, perceived privacy, and effort expectancy, concerning the users' continuance usage of contact tracing applications. A survey instrument was developed for PeduliLindungi application users, with survey participants (N=535) recruited from Indonesia. The study tested the model using partial least squares structural equation modeling. The results showed that effort expectancy is the most significant factor in continuance intention mediated by satisfaction. Meanwhile, perceived privacy does not affect continuance intention mediated by satisfaction. © 2022 IEEE.

Factors Influencing Students' Continuance Usage Intention with Virtual Classroom during the COVID-19 Pandemic: An Empirical Study

The constant variation of COVID-19 has intensified the spread and recurrence of the epidemic, and education continues to be hard hit in most countries. The virtual classroom has become the main platform to replace the traditional classroom in the COVID-19 pandemic context. Due to the lack of a comprehensive understanding of college students' perceptions of the platform system, it is essential to explore the factors and mechanisms that influence students' willingness to use virtual classrooms consistently to improve the learning efficiency and optimize the effect of educational communication during the epidemic. This study integrates the Delone and McLean (D&M) information systems (IS) success model, expectation–confirmation model (ECM), and instructor quality factor to construct an operational model, and it used a structural equation model to analyze the 411 valid samples received from online questionnaires. The results reveal that the determinants of college students' perceived usefulness of virtual classrooms are service quality, instructor quality, and confirmation, while system quality has no effect on perceived usefulness in the context of the COVID-19 pandemic. Secondly, system quality, service quality, and instructor quality are three critical antecedents of confirmation, and perceived usefulness and confirmation positively affect satisfaction. Finally, perceived usefulness and satisfaction directly affect college students' continuance intention. © 2023 by the authors.

The effect of a hotel's star-rating-based expectations of safety from the pandemic on during-stay experiences

As a result of the COVID-19 pandemic, safety is one of the top priorities for travellers when choosing a hotel. This work examines the effect of customers' pre-stay expectations of a hotel about its safety-focused services, shaped through its official star-rating, on the during-stay confirmation of those expectations, satisfaction, and revisit intentions. A cross-sectional research design is used spanning temporally from the pre-stay to the during-stay phases. The pre-stay phase was the peak COVID-19 period in India (June–July 2021) to stimulate the safety concerns in the travellers planning their travel, while the during-stay phase was when the planned travel was undertaken with the traveller staying at the planned hotel (October 2021–January 2022). Data were collected from 452 customers and the results supported the proposed model. Further, the star-rating, as a signal for safety-focused services, was found to have a serial effect on revisit intentions, through the pre-stay expectations of safety services, and the during-stay confirmation of expectations and satisfaction. © 2022 Elsevier Ltd

Understanding e-satisfaction, continuance intention, and e-loyalty toward mobile payment application during COVID-19: an investigation using the electronic technology continuance model

This research examined the determinants of e-satisfaction, continuance intention, and e-loyalty regarding the use of mobile payment applications (MPAs). It developed and validated the electronic technology continuance model (e-TCM) integrating a psychological factor (perceived threats), e-satisfaction, circumstantial factor (perceived anxiety), and the dimensions of quality. Using a questionnaire, data was collected from 455 respondents and analyzed using structural equation modeling. The influences of information quality, service quality, system quality, perceived usefulness, and confirmation on both e-satisfaction and continuance intention are found positive. However, perceived threats and perceived anxiety do not influence e-satisfaction but influence continuance intention. Moreover, e-satisfaction positively impacts continuance intention and e-loyalty;and continuance intention positively impacts e-loyalty. This research evidences the roles of perceived threat, e-satisfaction, perceived anxiety, and the dimensions of quality on customers' e-satisfaction, continuance intention and e-loyalty, using the integrated framework comprising the health belief model, expectation–confirmation model, and information systems success model. The findings of this research can guide MPA services providers, online businesses, industry analysts, suburban consumers, and respective government authorities when MPA usage is concerned during any unprecedented crisis such as the COVID-19 pandemic. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

The Determinants of Continuance Intention toward Activity-Based Events Using a Virtual Experience Platform (VEP)

The COVID-19 pandemic compelled traditional in-person events to begin transforming into more innovative and safer experiences by utilizing various virtual experience platforms (VEP). This study explores the salient determinants affecting the self-paced hiking or race event attendees' intention to continue attending the event through the use of VEP based on two robust theories: the expectation–confirmation model (ECM) and the unified theory of acceptance and use of technology (UTAUT2) model. Data were collected from 243 event attendees of a self-paced hiking event in South Korea and analyzed using a PLS-SEM approach. The results of this study demonstrate that performance expectancy had the most significant effect on the event attendees' continuance intention to use VEP, followed by satisfaction, hedonic motivation, and price value. The implications of these findings for event firms and organizations utilizing VEP are discussed. [ FROM AUTHOR]

Determinants of Continuance Intention to Use Mutual Fund Investment Apps: The Changing of User Behavior during the Pandemic Crisis

The COVID-19 pandemic and the implementation of large-scale social restrictions have caused economic and social disruptions globally, including in Indonesia. These difficult situations have shifted the financial attitudes, especially among the working-age group in Indonesia, to be more focused on saving and investing. One of the popular options among new investors is mutual fund investment because it requires a lower cost than other options, offers diversified holdings, and supports a variety of risk profiles. New investors primarily use an investment app, such as a mutual fund investment application, to manage their investment portfolios safely and seamlessly. In line with the rapid growth of mutual fund investors, the number of mutual fund investment apps in Indonesia has increased to more than 80 providers in 2022, resulting in fiercer competition between service providers. Therefore, retaining and increasing the apps' investment usage is crucial to providers' business success. This study investigates factors affecting the investor's continuance intention to use mutual fund investment apps by adapting the expectation-confirmation model (ECM) with other key constructs, i.e., perceived security, trust, and self-efficacy. The collected data from 384 participants were analyzed using Structural Equation Modelling. The results indicate that perceived usefulness, trust, and user satisfaction positively affect the continuance use of mutual fund investment apps. Based on findings, this study proposes practical strategies to retain the application usage, such as implementing security measures, personalized investment courses and advisories based on the user's profile risks and preferences, and recommendations on achieving the user's investment goals based on machine learning solutions. Digital solutions, such as financial and investment apps, may contribute to expanding access to banking, financial services, and financial inclusion in the Indonesian population. © 2022 IEEE.

A Multi-Dimensional Nomological Network of Mobile Payment Continuance

Despite the high utilization of mobile payment during the COVID-19 pandemic, this situation may change in the post-pandemic era. Therefore, great value can be derived from determining the significant antecedents of mobile payment continuance intention. This study looks to do so by introducing a Multi-Dimensional Nomological Network of Mobile Payment Continuance. A two-stage Partial Least Square-Structural Equation Modeling and Artificial Neural Network was utilized for the data analysis. The results provided empirical support to establish the overall nomological network. In addition, more than 70% of the variance in continuance intention was captured. Overall, this study provides practitioners with detailed insights to develop strategies for sustainable utilization and academics with a dynamic framework to look into users' mobile payment continuance intention.

Factors influencing vocational college students' creativity in online learning during the COVID-19 pandemic: The group comparison between male and female.

The COVID-19 pandemic has forced higher education institutions to shift their teaching activities from traditional face-to-face to online learning. This brings a great challenge to the creativity training of vocational college students, who not only learn theoretical knowledge but also cultivate technical skills. Therefore, it is very important to explore the influencing factors of online learning on students' creativity during the epidemic. By relying on the related literature review, an extensive model is developed by integrating the expectation confirmation model (ECM), technology task fit model (TTF), and the technology acceptance model (TAM) to illustrate key factors that influence creativity. Based on the proposed model, theory-based hypotheses are tested through structural equation modeling employing empirical data gathered through a survey questionnaire of 229 students from different vocational colleges in China. In addition, to extend the analysis results, this paper performs a comparative analysis based on gender. The findings demonstrate that perceived ease of use and perceived usefulness significantly influence knowledge sharing; knowledge sharing significantly affects creativity. However, there is no substantial relationship between perceived usefulness and attitude, and no relationship between attitude and knowledge sharing. Moreover, a multi-group comparison shows that there is a significant gender difference between perceived ease of use and attitude. Based on the findings, theoretical and practical implications are discussed.

Examining key factors of beginner's continuance intention in blended learning in higher education.

With the outbreak of the COVID-19 pandemic, blended learning became exceptionally widespread, especially in higher education. As a result, many college students became beginners in this learning method. To identify key factors that impact beginners' continuance intention in blended learning, this study surveyed 1845 first-year college students at a university in central China in the falls of 2020 and 2021 who used blended learning for the first time. Structural equation modeling was employed to verify a model that integrates intrinsic motivation and academic self-efficacy in the Expectation-Confirmation Model of Information System Continuance. The results show that performance expectancy, intrinsic motivation, and satisfaction significantly impact beginners' continuance intention in blended learning. Moreover, performance expectancy, intrinsic motivation, and confirmation significantly impact beginners' continuance intention through mediating variable satisfaction. Academic self-efficacy does not directly impact college students' continuance intention but indirectly impacts their continuance intention through intrinsic motivation. Finally, this study provides suggestions for educators to improve beginners' blended learning experience thus promoting their continuance intention in blended learning.

Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach

Purpose>While there is an abundant amount of literature studies on mobile payment adoption, there is a scarce of knowledge concerning the sustainable use of mobile payment contactless technologies. As those technologies are mainly concerned with security and users' trust, the question of how security factors and trust can influence the sustainable use of those technologies within and beyond the COVID-19 pandemic is still unanswered. This research thus develops a theoretical model based on integrating the protection motivation theory (PMT) and the expectation-confirmation model (ECM), extended with perceived trust (PT) to explore the sustainable use of mobile payment contactless technologies.Design/methodology/approach>The developed model is evaluated based on data collected through a web-based survey from 523 users who used contactless payment technologies. Unlike the existing literature, the collected data were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) technique.Findings>The data analysis results reinforced all the proposed relationships in the developed model. The sensitivity analysis results showed that PT has the largest impact on the sustainable use of mobile payment contactless technologies with 97.2% normalized importance, followed by self-efficacy (SE) (77%), satisfaction (72.1%), perceived vulnerability (PV) (48.9%), perceived usefulness (PU) (48.2%), perceived severity (PS) (40.7%), response efficacy (RE) (28.7%) and response costs (RCs) (24.1%).Originality/value>The originality of this research lies behind the development of an integrated model based on PMT and ECM to understand the sustainable use of mobile payment contactless technologies. The study provides several managerial implications for decision-makers, policy-makers and service providers to ensure the sustainability of those contactless technologies within and beyond the COVID-19 pandemic.

A Study on Student's Satisfaction of using E-learning System During the COVID-19 Pandemic

The e-learning system, is usually defined as a teaching and learning activities that is done with a computer, which evolves alongside with the evolution of the web. During the COVID-19 Pandemic, schools are forced to make a switch to the distance learning methods. With some previous research on studies about satisfaction using TAM, ECM and ISS, a conceptual framework was created to create a further study on Satisfaction. A total of seven hypotheses were created on this research that connects six variables from TAM, ECM, and ISS. As the survey was conducted to 400 high school students in Indonesia who uses the e-learning, the data was processed and calculated using SmartPLS using the PLS and Bootstrapping calculation. After the convergent and discriminant validity and the path analysis were conducted, it was found out that all of the hypotheses were accepted. However, there are some limitations in this study, which include sample and variable limitations. © 2022 IEEE.

Cross-national differences in mobile learning adoption during COVID-19

Purpose The COVID-19 pandemic has resulted in social isolation;nevertheless, universities will proceed throughout this trying period with the assistance of technology. As such, this paper seeks to develop a conceptual framework to investigate the continued intentions of students to use mobile learning during COVID-19 under different cultural contexts expanding upon the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Expectation-Confirmation Model (ECM) under different cultural contexts. Design/methodology/approach The suggested model is empirically tested with 1,206 students from different universities in three societies (i.e. Saudi Arabia, Egypt and the UK) using SEM/PLS. Findings Performance expectancy, satisfaction, social influence, facilitating conditions and instructors' competencies positively influence students' continued intentions to use mobile learning. In addition, the findings of the current research indicate that student's isolation negatively impact the continuous usage behavior. Furthermore, the findings indicated that a "one-size-fits-all" approach is insufficient in capturing the heterogeneity of students' intentions to use mobile learning across countries. Originality/value To the best of the authors' knowledge, this is the first study that has been conducted to understand the main determinants of students' continued intentions to use mobile learning under different cultural contexts.

MFS usage intention during COVID-19 and beyond: an integration of health belief and expectation confirmation model

Purpose The usage rate of mobile financial services (MFS) has shown an uptick since the emergence of the COVID-19 pandemic in Bangladesh. This study aims to reveal the underpinning reasons for such MFS surge and its continuance by integrating health belief model (HBM) and expectation confirmation model (ECM). Design/methodology/approach The study analyzes 529 MFS users' responses during the second wave of the COVID-19 outbreak in Bangladesh using the partial least square method. Findings Satisfaction is more predictive than perceived usefulness in explaining continuance usage intention. Expectation confirmation also indirectly affects continuance intention. Among the HBM constructs, the indirect effect of perceived severity on continuance intention via perceived usefulness and satisfaction is significant. Besides, the impact of self-efficacy on continuance intention is also significant. Moreover, perceived credibility significantly affects satisfaction and indirectly affected continuance usage intention via satisfaction. Practical implications The study projects boosting customers' satisfaction is critical for the successful retention of existing MFS customers. MFS service providers should emphasize the factors that amplify satisfaction. They must evaluate preadoption factors so that customers can have positive confirmation. Especially, the service providers, the policymakers and the regulators should take an active role in improving the users' self-efficacy and the system's credibility. Undertaking the MFS literacy program, installing hotline service to provide emergency help will boost users' confidence in using the system. Originality/value The study is a unique contribution in the context of Bangladesh. To the best of the authors' knowledge, no previous MFS studies in Bangladesh explored MFS continuance usage intention during COVID-19 and beyond. Besides, the inclusion of "perceived credibility" in the framework will supplement the earlier studies conducted on this aspect.

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.

Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach

Purpose While there is an abundant amount of literature studies on mobile payment adoption, there is a scarce of knowledge concerning the sustainable use of mobile payment contactless technologies. As those technologies are mainly concerned with security and users' trust, the question of how security factors and trust can influence the sustainable use of those technologies within and beyond the COVID-19 pandemic is still unanswered. This research thus develops a theoretical model based on integrating the protection motivation theory (PMT) and the expectation-confirmation model (ECM), extended with perceived trust (PT) to explore the sustainable use of mobile payment contactless technologies. Design/methodology/approach The developed model is evaluated based on data collected through a web-based survey from 523 users who used contactless payment technologies. Unlike the existing literature, the collected data were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) technique. Findings The data analysis results reinforced all the proposed relationships in the developed model. The sensitivity analysis results showed that PT has the largest impact on the sustainable use of mobile payment contactless technologies with 97.2% normalized importance, followed by self-efficacy (SE) (77%), satisfaction (72.1%), perceived vulnerability (PV) (48.9%), perceived usefulness (PU) (48.2%), perceived severity (PS) (40.7%), response efficacy (RE) (28.7%) and response costs (RCs) (24.1%). Originality/value The originality of this research lies behind the development of an integrated model based on PMT and ECM to understand the sustainable use of mobile payment contactless technologies. The study provides several managerial implications for decision-makers, policy-makers and service providers to ensure the sustainability of those contactless technologies within and beyond the COVID-19 pandemic.

E-Learning in the Postpandemic Era: A Case Study in Taiwan

The COVID-19 pandemic is pressing educational institutions across the globe to transfer rapidly from face-to-face learning to e-learning. However, e-learning has some multifaceted problems waiting to be solved and optimized. This study uses a survey questionnaire to collect research data. By integrating two predictors and four moderators into expectation-confirmation model, this article develops a causal research model and studies the continuance intention of using e-learning after the pandemic and how we can optimize online learning systems to benefit the traditional education systems in the long term. This article fills the literature gap of studies on IS continuance intention of e-learning from a problem-driven perspective. Based on the research results, this article suggests policy-makers and educators not only develop continuous training for both instructors and students on e-learning to enhance their ability and acceptance of e-learning systems but also build a more comprehensive technical environment to accelerate the adoption as well as to increase the continuance usage intention of e-learning systems. In addition, high-quality educational designs of e-learning that contain interaction mechanisms and customizations according to students' perceptions and attitudes toward e-learning are needed. We also call on scholars from around the globe to continue investigating the critical factors of e-learning adaptation and online educational environment optimization for proposing better solutions to counter crises similar to the COVID-19 pandemic in the future.