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The purpose of this paper is to explore the key antecedents of organizational users’ continuance intention of cloud enterprise resource planning (ERP) by the integration of constructs from the expectation–confirmation model (ECM), technology acceptance model (TAM), theory of planned behavior (TPB), task-technology fit and TAM2.

Sample data for this study were collected from end users of cloud ERP working in companies in Taiwan. A total of 560 questionnaires were distributed in the 56 sample companies, and 395 (70.5 percent) usable questionnaires were analyzed using structural equation modeling in this study.

Findings show that while compatibility and output quality are key antecedents of confirmation of expectations toward cloud ERP, compatibility still reveals overwhelming and more indirect impacts on users’ continuance intention of cloud ERP than output quality because output quality has significant but evidently lesser effects on perceived usefulness and perceived ease of use than compatibility.

First, this study contributes to the identification of compatibility and output quality that may reveal deep insights to the task-related factors in understanding users’ cloud ERP continuance greatly driven by their confirmation of expectations toward cloud ERP. Next, the empirical evidence on capturing the ECM, TAM and TPB for completely explaining the antecedents of users’ continued cloud ERP usage intention is well documented. Hence, this study’s findings have significantly shed light on the possible formulation of a richer post-adoption model.

The purpose of this study is to propose an integrated model based on expectation-confirmation model (ECM) and technology acceptance model (TAM) to examine whether environmental, human, organizational and technology factors as the antecedents to physicians’ beliefs can affect their satisfaction and continuance intention of the cloud-based hospital information system (HIS).

Sample data for this study were collected from physicians at six hospitals in Taiwan. A total of 600 questionnaires were distributed, and 471 (78.5 per cent) usable questionnaires were analyzed using structural equation modeling in this study.

This study proposes a solid research model that is based on ECM and TAM, four types of factors, environmental factor, human factor, organizational factors and technology factors, as antecedents to physicians’ continuance intention of the cloud-based HIS have been examined. This study’s results strongly support the research model with all hypothesized links being significant, and control variables have no confounding effects on physicians’ continuance intention of the cloud-based HIS.

This study contributes to physicians’ continuance intention toward the cloud-based HIS based on ECM, TAM, technology-organization-environment framework and human-organization-technology fit framework, and reveals deep insights into the evaluation of determinants in the field of physicians’ continuance intention of the cloud-based HIS. Accordingly, it is particularly worth mentioning that IS and non-IS determinants are simultaneously evaluated and taken into consideration in this study’s theoretical development of physicians’ continuance intention of the cloud-based HIS to acquire a more comprehensive and robust analysis.

The purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.

Sample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.

Synthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.

Particularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into consideration in this study's theoretical development of medical professionals' cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

This study's purpose is to propose an integrated model based on expectation-confirmation model (ECM), task-technology fit (TTF) model, and updated DeLone and McLean information system (IS) success model to examine whether quality factors and TTF as antecedents to physician beliefs can affect physicians' continuance intention of the cloud-based hospital information system (HIS) and performance impact.

Sample data for this study were collected from physicians at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 305 (61.0 percent) usable questionnaires were analyzed using structural equation modeling in this study.

This study verified that physicians' perceived information quality, system quality, general technical support service quality, and cloud storage service quality all positively caused their PU, confirmation, and perceived TTF in the cloud-based HIS, which together explained their satisfaction with the system, and subsequently led to their continuance intention of the system and performance impact.

First, IS-related and cloud-related quality factors are simultaneously taken into consideration within this study's research model, and empirical results reveal deep insights into quality evaluation in the field of physicians' cloud-based HIS continuance intention. Next, this study contributes to an understanding of TTF in explaining physicians' cloud-based HIS continuance intention that is difficult to explain with only their utilitarian perception of the system, and places emphasis upon physicians' perception of performance impact greatly driven by their perceived TTF and continuance intention of the system, thus the results can shed light on antecedents and outcome of physicians' cloud-based HIS continuance intention.

Although many studies have sought to address the topic of continuance intention among Fintech customers, the reported findings are fragmented. Therefore, the present study proposes a research model that integrates the main constructs involved in Fintech continuance intention.

The current study uses a meta-analytic-based correlation analysis of effect sizes, meta-regression analysis and meta-analytic structural equation modeling, with 247 effect sizes in 69 studies involving 26,140 respondents.

The results reveal continuance intention is driven by satisfaction and trust, with ease of use and usefulness being antecedents of satisfaction and trust. The authors also found evidence to show satisfaction partially mediates the relationship between ease of use and continuance intention and that trust fully mediates the relationship between ease of use and continuance intention and partially mediates the relationship between usefulness and continuance intention. In addition, the authors found that in Western countries, with higher Human Development Index levels and greater of use of electronic payment, satisfaction has more impact on continuance intention.

From a theoretical standpoint, this meta-analytic study has implications for the literature on Fintech by offering an empirical generalization on the strength of the antecedents of Fintech continuance intentions and by testing possible moderators in a wide range of countries and studies. In other words, this study’s goal is to broaden the scope of the research. Regarding managerial implications, it is important to listen to user opinions regarding the positive and negative points of their experience with these technologies and take them into consideration when planning improvements. Additionally, the analysis shows the importance of using data from user interaction with technology, obtained, for example, through big data analytics, whereby companies can see how users behave, how much time they spend accessing certain functions and which technological features they use most, and thus seek to improve whatever is needed.

This meta-analytic study advances the understanding of Fintech continuance intentions. Using the proposed approach, it is possible to generate accurate estimates of the effect size of each analyzed antecedent as the meta-analytic method jointly evaluates the results produced by a wide variety of studies performed in different contexts, allowing more accurate conclusions to be drawn.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether media richness and social interaction as environmental feature antecedents to nurses’ learning engagement (LE) can affect their continuance intention of massive open online courses (MOOCs) and task performance.

Sample data for this study were collected from nurses at five university-/medical university-affiliated hospitals in Taiwan. A total of 500 questionnaires were distributed, and 303 (60.6%) usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that nurses’ perceived media richness and social interaction in MOOCs positively influenced their behavioral LE and psychological LE elicited by MOOCs, which jointly caused their continuance intention of MOOCs and, in turn, enhance their task performance. The results support all proposed hypotheses and the research model, respectively, explains 84.3% and 63.7% of the variance in nurses’ continuance intention of MOOCs and task performance.

This study uses the S-O-R model as a theoretical base to frame nurses’ continuance intention of MOOCs and task performance as a series of the internal process, which is affected by environmental stimuli (i.e. media richness and social interaction) and organismic states. Noteworthily, while the S-O-R model has been extensively used in prior literature, little research uses this paradigm to expound nurses’ continuance intention of MOOCs in the work settings. Besides, there is a dearth of evidence on the antecedents of nurses’ task performance in the context of MOOCs. Hence, this study’s empirical evidence contributes significantly to the existing literature on bridging the gap of limited evaluation for the research on the impact of nurses’ MOOCs learning on their task performance in the work settings, which is very scarce in the S-O-R view.

The demand for over-the-top (OTT) video streaming services has grown manifold in the last few years. With increasing competition in the OTT market, it is vitally important for businesses to understand OTT retail consumers' continuance intentions. This study aims to understand the antecedents of the continuance intention of OTT platforms and distinguish the most essential and best-performing predictor variables of continuance intention.

The study employs an integrated research model based on the theory of planned behavior (TPB), flow theory and habit. Data collected from OTT retail consumers (n = 383) using the online survey method are analyzed using partial least squares structural equation modeling.

The results elucidated which TPB antecedents and dimensions of flow experience affect OTT platforms' continuance intention. The most important factors affecting continuance intention were habit, attitude and perceived behavioral control, while the best-performing factors were perceived behavioral control, perceived enjoyment and attitude.

The study is unique in harmoniously integrating conscious cognitive intention, intrinsic motivation and habit of performing an activity to explain OTT platforms' continuance intention.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to test whether network externality, gamification and media richness as environmental feature antecedents to learners' learning engagement (LE) can affect their continuance intention of massive open online courses (MOOCs).

Sample data for this study were collected from learners who had experience in taking the gamified MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 315 usable questionnaires were analyzed using structural equation modeling in this study.

This study verified that learners' perceived network externality, gamification and media richness in MOOCs positively influenced their behavioral LE, emotional LE and social LE elicited by MOOCs, which collectively caused their continuance intention of MOOCs. The results support all proposed hypotheses, and the research model accounts for 75.6% of the variance in learners' continuance intention of MOOCs.

This study uses the S-O-R model as a theoretical groundwork to construct learners' continuance intention of MOOCs as a series of the internal process, which is influenced by network externality, gamification and media richness. Noteworthily, three psychological constructs, behavioral LE, emotional LE and social LE, are employed to represent learners' organisms of MOOCs usage. To date, the concepts of network externality, gamification and media richness are rarely together adopted as environmental stimuli, and psychological constructs as organisms have received lesser attention in prior MOOCs studies using the S-O-R model. Hence, this study's contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners' continuance intention of MOOCs is well documented.

Mobile social apps permeate every facet of daily life through the pervasive use of smartphones. Customer retention with mobile social apps has become extremely important for app-related companies. The purpose of this paper is to explore why experienced users in mobile social apps (e.g. WeChat) are likely to continue using the app.

This study proposed a conceptual model to identify key determinants of continuance intention of WeChat users and highlight the effects of individual experience. Data were collected from WeChat users, which is one of the most popular mobile social apps in China. The study employed partial least squares regression to test the research model based on a survey of 295 valid responses.

Results showed that trust, which was driven by user satisfaction and perceived critical mass, played a critical role in influencing the continuance intention of WeChat users. Moreover, tie strength exerted a negative moderating effect on the relationship between trust and continuance intention. Specifically, tie strength and perceived critical mass had strong impacts on the continuance intention of low-experience users. In addition, the effect of frequency was closely associated with the continuance intention of high-experience users.

This study addressed the issue of mobile social app continuance intention by providing an innovative means to explore the key antecedents of user continuance intention from the experience perspective. The findings not only prove that trust plays a central role in influencing the continuance intention of experienced users but also reveal that the determinants of continuance intention vary among users with different experience. The results provide insights into the key antecedents of experienced WeChat user continuance intention and contribute to the literature on mobile social apps and individual differences.

The results provide suggestions for mobile social app practitioners to effectively plan mobile social app retention practices and to set up appropriate incentive mechanisms for retaining users with different experiences.

Although abundant studies have focused on the adoption of media users, few studies have investigated the post-adoption behavior of experienced users in the context of mobile social apps. This study revealed the key determinants of the continuance intention of WeChat users and pinpointed the different impacts of these antecedents on users with different levels of experience. It also provides useful guidelines for practitioners to effectively retain users with different levels of experience.

Consumers in India are increasingly using mobile payment systems (MPSs) to make online and offline payments. Digital payment applications are gradually being used as surrogates for cash, checks and plastic money. The motive behind this research is to analyze the different antecedents that impact the users' willingness to continue using the MPS in India.

An extensive study of the literature review supports the creation of a framework that describes the continuance intention of using MPS. Data from a survey of 612 respondents from India were collected to assess the research model. The study used partial least squares (PLS)–structural equation modeling (SEM) technique to empirically validate the framework developed.

The outcomes of the research suggest that service quality, attitude, effort expectancy and perceived risk act as influencing antecedents of continuance intention to use MPS. Determinants like perceived trust, convenience and social value have no influence on users' continuance intention. SEM analysis has verified the proposed model, which explains 50.7% of the variance of the users' continuance intention of using MPSs.

The research is built upon cross-sectional data carried out in India. Hence, the outcomes of the study are limited to this region only.

Engaging with the consumers for a long time and enabling their continuance usage are extremely important for firms offering mobile payment services. The managerial implications provide insights into the different ways to capture new business opportunities to the firms rendering mobile payment services in the wake of changing consumer behavior.

This research tries to analyze users' continuance intention to use MPS in India. Although many research studies have investigated the willingness of the individuals to adopt novel technology in different frameworks, there are hardly any empirical studies carried out to analyze the antecedents of users' continuance intention to use MPSs.