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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.

This study aims to investigate the determinants of successful implementation of cloud computing and, further, examines how cloud computing success influences firm performance.

The authors developed a conceptual framework based on the integration of several strands of literature in business studies and information systems. To test the proposed model, data were collected from 300 Chinese firms which have adopted cloud computing. To analyze the data, partial least squares structural equation modeling (PLS-SEM) was used. An importance-performance map analysis (IPMA) was also conducted to identify the critical factors that exhibit high importance but low performance.

The results of the study revealed that end-user satisfaction, information quality, system quality, managerial information technology (IT) capability and technical IT capability significantly affect cloud computing success. Additionally, cloud computing success has a strong and positive impact on firm performance. IPMA further confirms that managers need to concentrate more on system quality, information quality, user satisfaction and technical IT capability.

This paper is one of the few attempts to integrate several theoretical frameworks (i.e. IT capabilities and resource-based view, expectation-confirmation theory, and information system success theory) to develop a comprehensive model for understanding the key determinants of cloud computing success and its impact on firm performance. This study makes a useful contribution to the conventional information systems (IS) literature and IT management practice.

This study aims to discover the factors which influence user satisfaction levels and their continuous use intention (CUI) of academic library social media, and then considers how to promote and improve further work on library social media to reduce user churn and increase user satisfaction.

An updated DeLone and McLean information systems success (D&M ISS) model and the expectation confirmation model for information systems continuance (ECM-ISC) with new variables of emotions are used to examine the factors which influence user satisfaction levels and CUI of academic library social media through 445 questionnaires. Partial least squares structural equation modelling was used to analyse the data and presented in tables.

The results show that information quality, system quality and emotions affect user satisfaction and CUI, and reveal that emotions can affect that most obviously.

The WeChat public platform is mainly used in China, so the study only focuses on Chinese academic libraries. There are still limitations on the settings of observed variables which cannot cover all the causes of users’ positive and negative emotions. In addition, although the respondents of this questionnaire can represent academic library users, 445 samples are still fairly low in contrast to the great number of academic library WeChat public platform users.

This study integrates ECM-ISC and D&M ISS models, adds positive and negative emotions as new variables, to broaden the application scope of these models, and demonstrates the applicability of these two models in the fields of researching academic library social media, expanding and deepening related theories above. This also provides practical reference for academic libraries on how to improve user satisfaction and CUI of academic library social media and academic library WeChat public platforms, promoting the development of academic library social media.

The purpose of this study is to clarify theory and identify factors that could explain the level of fintech continuance intentions with an expectation confirmation model that integrates self-efficacy theory.

With data collected from 753 fintech users, this study applies partial least square structural equation modeling to compare and select the research model with the most predictive power.

The results show that financial self-efficacy, technological self-efficacy and confirmation positively affect perceived usefulness. Among these factors, financial self-efficacy and technological self-efficacy have both direct and indirect effects through confirmation on perceived usefulness. Perceived usefulness and confirmation are positively related to satisfaction. Finally, perceived usefulness and satisfaction positively influence fintech continuance intentions.

To the best of our knowledge, this is one of the earliest studies that investigates the effect of domain-specific self-efficacy on fintech continuance intentions, which enriches the existing research on fintech and deepens our understanding of users' fintech continuance intentions. We distinguish between financial self-efficacy and technological self-efficacy and specify the relationship between self-efficacy and continuance intentions. Moreover, this study highlights the importance of assessing a model's predictive power using the PLSpredict technique and provides a reference for model selection.

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.

The purpose of this paper is to propose a hybrid model based on expectation-confirmation model (ECM), technology acceptance model (TAM), and updated DeLone and McLean information system (IS) success model to examine whether quality factors as the antecedents to user beliefs affected users’ continuance intention of the digital library.

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 library, and 525 (87.5 percent) usable questionnaires were analyzed using structural equation modeling (SEM) in this study.

Findings show that the proposed research model integrating ECM, TAM, and updated DeLone and McLean IS success model has good explanatory power for quality antecedents of users’ continuance intention of the digital library. Information relevance, system accessibility, and technical support play key roles in explaining users’ continuance intention of the digital library via their beliefs.

This study’s empirical evidence on capturing ECM, TAM, and updated DeLone and McLean IS success model reveals deep insights into quality evaluation for users’ continuance intention of the digital library. Especially, this study additionally contributes to the identification of interface features that may lead to users’ continuance intention of the digital library.

The purpose of this study is to propose a research model based on expectation-confirmation model (ECM) to examine whether interactivity and course quality factors (i.e. course content quality, course design quality) as antecedents to student beliefs can influence students' satisfaction and continuance intention of the cloud-based electronic learning (e-learning) system within the educational institution.

Sample data were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed in the campus, and 515 (85.8%) useable questionnaires were analyzed using structural equation modeling.

Findings showed that students' perceptions of interactivity, course content quality and course design quality positively significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, which in turn directly or indirectly led to their continuance intention of the system. Thus, the results strongly supported the research model based on ECM via positioning key constructs as the drivers with all hypothesized links being significant.

This study identifies three factors (i.e. interactivity, course content quality, course design quality) as drivers from the learner perspective within the cloud-based e-learning environment, and links these factors to students' satisfaction and continuance intention of the cloud-based e-learning system based on ECM. It is particularly worth mentioning that the three drivers can serve as precursors for recognizing the determinants that are crucial to understand students' satisfaction and continuance intention of the cloud-based e-learning system. Hence, this study may provide new insights in nourishing the cloud-based e-learning continuance literature in the future.

The sharing economy is changing the way people use products and services, and the success of sharing-based apps like bicycle and automobile sharing has drawn a lot of interest across the world. The purpose of this research is to investigate the factors affecting the consumer's adoption of ride-sharing services.

With this aim, the current study integrates the Technology Acceptance Model (TAM) and Expectancy Confirmation Model (ECM) with a further extension of consumer trust and social norms. Using a survey-based research design, data were collected from 558 respondents using multi-stage convenience sampling on 5 point Likert scale. Confirmatory factor analysis is conducted followed by structural equation modelling using IBM AMOS-22.

The findings of the study report crucial determinants for the consumer's continuance intention and actual use of these services. Perceived usefulness, consumer satisfaction, trust and subjective norms were found positively associated with the continuous intention to use ride-sharing services, whereas perceived ease of use was found to be insignificant. This study also highlights antecedents for the consumer's trust towards these services and found reputation, propensity to trust as a significant contributor whereas structural assurance was found insignificant to establish the trust among the users.

The research on consumer adoption towards ride-sharing services are meagre and this study adds the value to the field by integrating TAM and ECM model with further extension of consumer trust and social norms and empirically test the proposed model.

Demonetization and pandemic-related restrictions in India propelled the usage of mobile payments (M-payments). The culture of online smartphone transactions is expected to rise over the coming years, even after things return to normal. This study aims to unveil the factors that escalate the satisfaction levels of M-payment users and eventually stimulate them to continue using M-payments for their daily activities.

This study evaluated the intention to continue using M-payments for 710 users utilizing structural equation modeling and augmenting the technology acceptance model (TAM) as well as the expectation confirmation model (ECM). Mediation and moderation analysis examined the proposed model's direct and indirect relationships.

The findings unveil that perceived value co-creation participation, service quality and cognitive processing magnify user satisfaction, significantly escalating M-payment continuance usage intention. Perceived value co-creation participation and user satisfaction with M-payment partially mediate the linkage among the constructs. Furthermore, perceived usefulness strengthens the link, while perceived severity of security threats weakens the linkage between user satisfaction with M-payment and continuance usage intention.

The study's findings could benefit M-payment service providers, users, policymakers and the telecom industry to strengthen India's digital payment framework.

The perceived value co-creation participation and cognitive processing domain have not garnered much attention in the M-payment literature. The study strives to comprehend these constructs by widening the purview of TAM and ECM models. It also measures the moderating role of perceived severity of security threats and perceived usefulness to unfurl potential linkages between the identified constructs.

This study aims to understand the factors affecting the continuance usage intention (CUI) of mHealth among the rural elderly.

An integrated model was proposed with the constructs derived from multiple models such as the unified theory of acceptance and use of technology, information system success model and expectation confirmation model. Data were collected from 400 participants who had prior experiences with mHealth services in Bangladesh. The research model was tested using the partial least squares method based upon structural equation modelling.

The findings indicated that system quality, performance expectancy, facilitating conditions and social influence were significant to the degree of confirmation and ultimately affect satisfaction and CUI. Surprisingly, service quality and information quality were insignificant.

This study has added in the field of knowledge by contributing some new thoughts and interpretations of continuance usage modelling for mHealth services. The findings may become beneficial for the government agencies, policymakers, mHealth systems developers and service providers.

As limited research was found on CUI of mHealth in the integrated view of rural elderly’s value, this research contributes to the extant literature by categorizing key factors that might support to proliferate the continuance usage of this service. Moreover, the contextualization of the related variables and integration of the existing model is theoretically original. Furthermore, because of a generic approach, the findings could be easily modified to assist other developing countries in the planning and up-take of mHealth.