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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.

The long-term development of a mobile gaming application (app) depends on its continued use by its users. The expectation–confirmation model of IS continuance was used as the basic framework, to which bi-dimensional consumption emotions were added to help better explain satisfaction judgment and continuance intention in the context of mobile gaming app use. The paper aims to discuss this issue.

The data were analyzed using structural equation models. The effects of positive consumption emotions and negative consumption emotions were examined, respectively, in Models 1 and 2. Competing models (Models 3 and 4) were also examined in order to compare the proposed model.

Both PE and NE have an effect on the satisfaction of mobile gaming app users and their continued usage intention, a finding that represents an important contribution to the extension of technology continuance theory. Comparison with the IS continuance model shows that the new model can explain significantly more variance in continuance intention.

Mobile gaming firms should pay attention to users’ consumption emotions, especially negative emotions. Some specific emotions involved in mobile gaming app use were identified, which could guide firms’ understanding of users’ emotions.

This study offers insight into the role of consumption emotions in forming continuance intentions toward mobile gaming app use in China, a topic that has not previously been investigated.

Open government data (OGD) is a comparatively new field in e-government and the factors influencing its continuance use by citizens have not been extensively explored. A better understanding of these factors can help the government to articulate strategies and policies that can advance the acceptance and use of OGD technologies. Thus, this paper aims to empirically determine the predictors influencing the continuance usage intention of OGD technologies.

Following an empirical investigation among 370 respondents in Bangladesh, a developing country, the paper applied path analysis using the structural equation modeling approach. The unified theory of acceptance and use of the technology model is integrated with the information system continuance model to investigate the continuance usage intention of OGD technologies.

The outcomes of this study reveal that performance expectancy, effort expectancy, social influence and facilitating conditions (FC) directly affect users’ satisfaction (SAT). In addition, SAT and FC were found statistically significant toward continuance usage intention of OGD technologies.

The findings of this study suggest policymaker and OGD providers to formulate or modify their strategies to retain the existing OGD users and stimulate persistence usage.

Facilitating long-term use by citizens would increase their engagement and they might derive value from the OGD platforms. Concurrently, the government’s objective of ensuring increased future use of OGD technologies would be better realized.

The novelty of this study lies in the fact that it addresses a previously overlooked area of open data research, namely, the acceptance and use of open data technologies and ways to stimulate it. This study has contributed to the existing but limited literature on continuance usage intention of OGD technologies in the context of a developing country.

The advancement in Internet technology has played a significant role in revolutionizing the Internet banking services. Therefore, little is discussed about factors that motivate technology user to continue the use of Internet banking services. The current study investigates Internet banking user continuance behavior toward the use of Internet banking services with the integration of two-well known information system (IS) theories namely task technology fit (TTF) and technology continuance theory (TCT).

The research design of this study is based on positivist paradigm and followed quantitative research approach. Data were collected from 360 Internet banking users of commercial banks across Pakistan. The research model was tested with structural equation modeling (SEM).

The research model had explained 53.9% variance in Internet banking user continuance intention. Next to this, the predictive relevance of the research model was tested with Stone-Geisser's Q² values using blindfolding procedure. Results revealed that the newly developed integrated technology continuance research model has substantial power to predict Internet banking user continuance intention. Moreover, the effect size analysis revealed that factors like satisfaction and user expectation were the most important factors in determining Internet banking user continuance intention.

For practical implications importance performance matrix analysis (IPMA) has used to see the importance and performance of the underpinned factors. Findings indicate that managers and policy makers should focus on user satisfaction, perceived usefulness and expectation confirmation in order to enhance the Internet banking user continuance intention toward the use of Internet banking services. Some of the ways banks can do this is to develop esthetic Internet banking website with charm of novelty, relevant information and smooth flows with less complex redirects.

Unlike prior studies that focus on Internet banking user pre-adoption issues, the current study examines post-adoption issue of Internet banking users and investigates Internet banking user continuance intention. This study is significant as it integrates two-well known theories namely TCT and TTF in Internet banking user continuance intention and augments the IS literature by developing an integrated technology continuance model (TCM).

Sustainable success of group-buying web sites implies that consumers not only accept them initially but also use them continuously. Most group-buying web sites, however, are unable to achieve such sustainable success. Drawing on expectation-confirmation model (ECM), the purpose of this paper is to examine the factors that influence group-buying web sites continuance.

In total, 605 valid responses were collected via a survey of a leading group-buying web site in China. Structural equation modeling was used to test the research model. This study also compared the three competing models of continued use behavior, namely, ECM, the research model and the integrated model.

The results show that perceived web site quality, perceived price advantage and confirmation are important determinants of consumer satisfaction, while perceived web site quality, perceived reputation, satisfaction and perceived critical mass significantly influence consumers’ continuance intention. The research model accounts for more variance in satisfaction and continuance intention than ECM and is the best-fitting model among the competing models.

Drawing on ECM, this research proposes a model by incorporating three online group-buying characteristics (perceived price advantage, perceived reputation and perceived web site quality) and two social influence factors (subjective norm and perceived critical mass). Specially, this study uses these three online group-buying characteristics to represent perceived usefulness in ECM. These constructs are found to influence consumer satisfaction and continuance intention. This study extends ECM and provides a better explanation of consumers’ post-purchase behavior in the online group-buying context.

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 purpose of this study is to propose a synthetic post-adoption model based on the expectation-confirmation model (ECM) and flow theory to examine whether the fit factor, network factors and psychological factors as antecedents to end-users’ beliefs can affect their continuance intention of the robo-advisor.

This study used the research model based on ECM and flow theory to examine the effects of the fit factor, network factors and psychological factors on end-users’ beliefs and continuance intention of the robo-advisor. Sample data were collected from end-users at three financial services companies in Taiwan. A total of 450 questionnaires were distributed and 360 (80.0%) usable questionnaires were analyzed using structural equation modeling.

This study proposes a solid research model that based on ECM and flow theory, three types of factors, namely, fit factor, network factors and psychological 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.

It is particularly worth mentioning that a synthetic post-adoption model can be proposed in this study by introducing the fit factor extracted from task-technology fit model, network factors originated from the theory of network externalities and psychological factors derived from uses and gratifications theory as antecedents to perceived usefulness, confirmation, satisfaction and continuance intention referred in ECM and flow experience derived from flow theory. Thus, this study’s research model and findings can reveal deep insights into the evaluation of determinants in the field of end-users’ continuance intention of the robo-advisor.

The purpose of this paper is to understand blog continuance. Specifically, this paper aims to compare two theoretical models and an integrated model to identify which theoretical models best predicts blog continuance intention.

An empirical study was conducted through an online survey. Data collected from six famous blogs in Taiwan (n=361) were analyzed using structural equation modeling and pairwise nested F‐tests.

Results show that the ECT‐IS model and the integrated model have greater explanatory power of blog continuance intention than the technology acceptance model (TAM). The results of pairwise nested F‐tests show that the ECT‐IS model exhibits statistically significant R² improvement compared to TAM. However, the R² improvement in the integrated model is not statistically different from that in the ECT‐IS model. The ECT‐IS model is also more parsimonious than the integrated model. Thus, the ECT‐IS is a preferable model. Confirmation and satisfaction are salient factors influencing this intention.

The results of this study provide useful information for blogging service providers (BSPs) to enhance and develop useful blog functions for user satisfaction. By revealing the differences and comparisons among these three models, this study can help BSPs promote the benefits of their blogs to strengthen the continuance intentions of their customers.

This paper is one of the first studies to examine of influence change of variables and compare the relative ability of two competing theories, ECT‐IS and TAM, and an integrated model in explaining blog continuance intention. The results confirm that the ECT‐IS is a better model than the other two for explaining blog continuance intention.

This study's purpose is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether gamification and social interaction as environmental stimulus antecedents to learners' perceptions of presence 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 gamified MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 353 usable questionnaires were analyzed using structural equation modeling (SEM).

This study demonstrated that learners' perceived gamification, learner–instructor interaction and learner–learner interaction in MOOCs positively affected their cognitive presence, teaching presence and social presence elicited by MOOCs, which jointly expounded their continuance intention of MOOCs. The results support all proposed hypotheses, and the research model accounts for 72.6% of the variance in learners' MOOCs continuance intention.

This study employs the S-O-R model as a theoretical umbrella to frame learners' MOOCs continuance intention as a series of the internal process, which is influenced by gamification and social interaction. Noteworthily, three psychological constructs of the community of inquiry model (i.e. cognitive presence, teaching presence and social presence) are adopted to represent learners' internal experiences of MOOCs usage. To date, hedonic/utilitarian concepts are more commonly adopted as organisms in prior studies based on the S-O-R model, whereas psychological constructs have received lesser attention. Hence, this study enriches the S-O-R model into an invaluable context.

The purpose of this paper is to apply expectation-confirmation theory (ECT) and the unified theory of acceptance and use of technology (UTAUT) to identify potential determinants of library patrons’ intention to continue using (continuance) self-issue and return systems for borrowing and returning books. The role of continuance is specifically interesting and is well-established in the literature of information systems (ISs) and marketing because continuance is considered to be the central element for the survival of ISs and of self-service technology (SST). However, the role of continuance has been neglected by researchers studying library SST adoption.

A research model integrating the expectation-confirmation model of IS continuance with UTAUT was developed and empirically validated using data obtained from a field survey involving 128 active users of a self-issue and return system at a public library in Taiwan.

Library patrons’ continuance intention was affected by their post-adoption expectation of perceived performance, effort performance and facilitating conditions as well as their satisfaction when using self-issue and return systems. Moreover, a patron satisfaction level was influenced by performance expectancy and confirmation of initial expectations, whereas confirmation had a positive effect on all post-adoption expectations.

This study broadens perspectives on SST adoption behavior in the library context by identifying some factors that influence library patrons’ continuance decisions. Furthermore, the authors verified the applicability and predictability of the theoretical integration of ECT with UTAUT in a diverse setting because the authors sought survey participants outside of the college population.