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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.

Social networking services/systems (SNSs) have grown in popularity in the past decade. However, while some have been abandoned by their once loyal users, others have grown in popularity. Literature provides diverse and often conflicting justifications for this phenomenon. Seeking a credible explanation, this study aims to examine the roles of system-like trust and habit in SNS use continuance.

This study conducted a comprehensive review of related literature to formulate an extended model of information technology (IT) continuance. A cross-sectional field survey was used to collect data from 401 university-student Facebook users. The research model was evaluated using structural equation modeling.

The results indicate that trust in technology and hedonic motivation are important direct influences on end-user continuance intention (CI), while habit is not. Interestingly, the most salient (indirect) predictor of CI is confirmation of (user) expectations.

The study suggests a set of practical steps that managers and practitioners can undertake to support users’ decisions to continue using the systems.

This paper advances IT continuance research by theorizing that trust in technology along with habit and hedonic motivation positively influence CI. In addition, the study enhances the concept of perceived usefulness by modeling this unitary measure as a multidimensional construct.

This research set out to investigate the quality service and self-determination theory (SDT) that contributes to the continuance usage of m-banking.

A valid of 310 respondents who experienced and intensified using the m-banking is collected. The proposed research model is empirically tested using structural equation modelling.

The result informs that the service quality can not only be significantly mediated by the SDT, but it also has a direct effect to the satisfaction. It also informs that the satisfaction and the perceived usefulness indeed have a significant effect to the continuance usage intention of the m-banking. In addition, it also demonstrates that the perceived competence and perceived relatedness of the SDT significantly influence satisfaction and perceived usefulness towards the continuance usage intention of the m-banking.

Practically, the results inform the bank management the factors to be taken into account to increase the motivation of the existing customers for them to continue using the m-banking.

Theoretically, these results contribute to the existing literatures of the m-banking by introducing the SDT that determines the continuance usage intention of it.

The purpose of this study is to propose an integrated post-adoption model based on expectation-confirmation model (ECM) and flow theory to examine whether gamification and interface design aesthetics as antecedents to students' beliefs can affect their continuance intention of massive open online courses (MOOCs) and perceived impact on learning.

Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed in the campus, and 318 (53.0%) useable questionnaires were analyzed using structural equation modeling in this study.

This study's results verified that students' perceived gamification and interface design aesthetics of MOOCs positively affected their perceived usefulness, confirmation and flow experience elicited by MOOCs, and these in turn directly or indirectly led to their satisfaction, continuance intention of MOOCs and perceived impact on learning. Essentially, the results strongly support the research model with all hypothesized links being significant.

It should be particularly noticed that this study contributes to the application of capturing both ECM and flow experience (i.e. an intrinsic motivator) for completely explaining students' perceived gamification and interface design aesthetics as external variables to their continuance intention of MOOCs and perceived impact on learning, and this study's empirical evidence can further shed light on the possible formulation of MOOCs success.

This study's purpose is to propose a hybrid model based on expectation-confirmation model (ECM) and technology acceptance model (TAM) to examine whether organizational users' perceived task-technology fit (TTF) in cloud enterprise resource planning (ERP) as an antecedent to user beliefs can directly and indirectly affect their continuance intention of cloud ERP and individual performance.

Sample data for this study were collected from end users of cloud ERP working in companies in Taiwan. A total of 500 questionnaires were distributed in the 50 sample companies, and 355 (71.0%) usable questionnaires were analyzed using structural equation modeling in this study.

This study showed that organizational users' perceived TTF contributed positively to their perceived usefulness, confirmation and perceived ease of use of cloud ERP, which in turn directly and indirectly led to their satisfaction with cloud ERP, continuance intention of cloud ERP and individual performance; that is, this study's findings strongly supported the research model integrating ECM, TAM and TTF model with all hypothesized links being significant.

This study contributes to an understanding of the TTF model in explaining organizational users' cloud ERP continuance intention that is difficult to explain with only their utilitarian perceptions of cloud ERP. Further, it is especially worth mentioning that this study places considerably more emphasis upon organizational users' individual performance greatly driven by their perceived TTF in cloud ERP and continuance intention of cloud ERP. Thus, this study's empirical evidence on incorporating ECM, TAM and TTF model can significantly enhance better understanding of the outcomes for cloud ERP continuance intention and shed light on the possible formulation of a richer post-adoption model.

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.

This study aims to examine the relationship between emotional attachment (EA) and intelligent personal assistant (IPA) continuance intention. While existing theories emphasize purely rational and goal-oriented factors in terms of information technology (IT) continuance intention, this research examines how users' EA toward technology impacts their continuance intention in the absence of cognitive and habitual factors.

This study contextualizes attachment theory from the social psychology/consumer psychology literature to an IT application and formulates and tests a new model that is proposed in the context of IPA continuance. Five research hypotheses developed from contextualization and application of the theory were posited in a structural model and empirically validated using survey results from IPA users.

The results show that users' EA to IPA use significantly influences their IPA continuance intention, along with emotional trust and interaction quality with the IPA.

This study contextualizes attachment theory developed in the social psychology/consumer psychology literature to formulate and test a new model in the context of IPA continuance. This work contributes to the theoretical understanding by investigating IPA continuance intention in the absence of cognitive or habitual factors and fills a critical research gap in IT post-adoption literature. IPA is just one example of technologies to which individuals can form attachments and this research provides an important foundation for future research by positing and testing the value of EA in IT post-adoption behavior. This research also contributes to practical knowledge by inferring that IPA manufacturers, managers and vendors could extend their revenue streams by integrating product features that capture emotion.

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.

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.