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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 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.

Despite the proliferation of service chatbots in the tourism industry, the question on its continuance intentions among customers has largely remain unanswered. Building on an integrated framework using the task–technology fit theory (TTF) and the expectation–confirmation model (ECM), the present study aims to settle this debate by investigating the factors triggering customers to continue to use chatbots in a travel planning context.

The research followed a quantitative approach in which a survey of 322 chatbot users was undertaken. The model was empirically validated using the structural equation modelling approach using AMOS.

The results reveal that users’ expectations are confirmed when they believe that the technological characteristics of chatbots satisfy their task-related characteristics. Simply, the results reveal a significant and direct effect of TTF on customers’ confirmation and perceived usefulness towards chatbots. Moreover, perceived usefulness and confirmation were found to positively impact customers’ satisfaction towards chatbots, in which the former exerts a relatively stronger impact. Not surprisingly, customers’ satisfaction with the artificial intelligence(AI)-based chatbots emerged as a predominant predictor of their continuance use.

The findings have various practical ramifications for developers who must train chatbot algorithms on massive data to increase their accuracy and to answer more exhaustive inquiries, thereby generating a task–technology fit. It is recommended that service providers give consumers hassle-free service and precise answers to their inquiries to guarantee their satisfaction.

The present work attempted to empirically construct and evaluate the combination of the TTF model and the ECM, which is unique in the AI-based chatbots available in a tourism context. This research presents an alternate method for understanding the continuance intentions concerning AI-based service chatbots.

An increasing number of companies have become aware of the considerable commercial potential of firm-hosted online communities (FOC) and initiated their own platform for different purposes. However, limited research has systematically explored oppositional loyalty and customer satisfaction in the context of FOC. By applying the expectation–confirmation model (ECM), the purpose of this paper is to investigate the determinants of oppositional loyalty and satisfaction from the perspective of social capital and e-quality.

A research model was tested by applying partial least squares technique, and data were collected from a survey of members (n=512) of two popular smartphone communities in China.

Results revealed that satisfaction, trust and shared language are the significant antecedents of oppositional loyalty. Benefits confirmation, information quality, service quality, trust and social tie exert strong effects on the formation of satisfaction.

This study is an original empirical research guided by several theories. It contributes to the information system usage literature and provides opinions regarding how users’ oppositional loyalty and satisfaction can be developed in the FOCs. This work also widens the application of ECM and provides an alternative theoretical framework for future research on oppositional brand loyalty.

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 looks to understand the opposing forces that would influence continuance intention. This is significant as users will take into account the positive and negative use experiences in determining their continuance intention. Therefore, this study looks to highlight the opposing forces of users’ continuance intention by proposing the Expectation-Confirmation-Resistance Model (ECRM).

Through an online survey, 411 responses were obtained from mobile payment users. Subsequently, a hybrid approach comprised of the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) was utilized to analyze the data.

The results revealed that all hypotheses proposed in the ECRM are supported. More precisely, the facilitating and inhibiting variables were found to significantly affect continuance intention. In addition, the ECRM was revealed to possess superior explanatory power over the original model in predicting continuance intention.

This study successfully developed and validated the ECRM which captures both facilitators and inhibitors of continuance intention. Besides, the relevance and significance of users’ innovative resistance to continuance intention have been highlighted. Following this, effective business and research strategies can be developed by taking into account the opposing forces that affect users’ continuance intention.

M-wallets have emerged as one of the most important financial innovations of the 21st century, enabling users to carry digital cash by securely storing payment methods on their mobile devices. However, the continued use of m-wallets varies among people for several reasons. This study used the technology continuation theory (TCT), gamification and trust factors to examine the variables affecting consumers' intentions to continue using mobile wallets.

The SmartPLS partial least squares software was used to analyze data from 431 m-wallet users in Vietnam using the structural equation modeling technique.

The data revealed that the research model can predict users' intentions to continue using mobile wallets. TCT constructs demonstrated strong exploratory power in explaining consumer satisfaction and attitudes towards m-wallets. Furthermore, the study confirmed the direct effect of the perceived effectiveness of gamification on perceived ease of use and attitude, as well as its indirect effect on consumers' continued use intentions of mobile wallets via attitude. In addition, the trust negatively influenced consumers' intentions to continue using m-wallets.

The findings of this study can help researchers, practitioners and policymakers improve m-wallet design, development and adoption, as well as advance financial technology and define the future of digital payments in terms of consumer attraction, engagement and financial inclusion.

Based on TCT theory, this study enriches m-wallet research by examining two important factors, gamification and trust, and thus provides insights into how to improve consumers’ intentions to continue using m-wallets in developing countries. This study offers timely insights into theory and practice regarding these factors. It therefore paves the way for researchers and practitioners to learn how easy, enjoyable and secure the end-user experience should be to keep users engaged with m-wallets.

The purpose of this study is to offer a conceptual model that bridges gaps in the current research by combining constructs from the health belief model (HBM) and theory of planned behaviour (TPB). Furthermore, the researchers applied the constructed model to analyse the determinants of workers’ intentions to use e-wallet payment options for business transactions rather than physical currency during the ongoing COVID-19 pandemic. Finally, the paper examines whether there are any significant variations in the usage intentions of Ghanaian workers in the formal and informal sectors.

The non-probability convenience sampling technique was used to compile the primary respondents among Ghanaian users of e-wallets. Based on constructs derived from the HBM and TPB, an online survey involving the use of a questionnaire was administered to collect quantitative data from 285 formal and informal sector workers in Ghana. Data collected was analysed using the partial least squares-structural equation modelling approach involving the measurement, structural model tests, hypothesis tests and multi-group analysis (MGA) tests.

This study reveals that workers’ attitudes, subjective norms and perceived susceptibility as the main determinants of intentions to use e-wallets, as the analysis of data lends support to hypotheses involving these constructs. Perceived behavioural control was however not supported by the data analysis as a determinant of workers’ intention. Finally, there were no significant differences between e-wallet usage intentions of formal and informal sector workers in Ghana.

Given the ongoing pandemic, the study recommends that governments of emerging economies should formulate policies that promote the use of e-wallets, to reduce the spread of COVID-19 and at the same time contribute to the quest for a cashless economy. However, the results of the study are only based on data collected from workers in Ghana. Therefore, practitioners should apply the recommendations with discretion and make modifications where necessary. The results of the study also provide evidence from the context of a developing country that can support future academic pursuits.

This study provides evidence that influences practitioners’ decisions and practices regarding the design and implementation of e-wallet services and innovations among workers in the formal and informal sectors of the economy.

This study provides useful business insights to user acquisition managers, marketing managers and business development managers during the formulation of policies, strategies and approaches for their mobile wallet subscriber base. Moreover, to the best of the authors’ knowledge, this study is one of the first to apply the constructs of the HBM (mainly applied in health research) to the study of workers’ intentions to use e-wallets. It, therefore, makes a significant contribution to the existing literature by examining the combined effects of the constructs of the HBM and the TPB on workers’ intention to use e-wallets.

In an effort to enhance the student experience and achieve complex learning outcomes the use of gamification in higher education is increasing. Using two case studies, this paper explores the efficacy of two discrete inclusions of gamification in entrepreneurial education.

In the first case study, students leveraged their taught knowledge about gamification to develop a gamified business concept. In the second case study, students played a humanitarian game and provided feedback about its design and efficacy.

The students' overall engagement with entrepreneurial education was significantly influenced by two factors: their perceived learning about gamification; and their perceived engagement with the gamification. It was observed that highly engaged students considered the gamification component of the course challenging.

This study demonstrates the potential of gamification to enhance engagement and to foster higher-order learning in the context of entrepreneurial education.

This study intends to investigate the determinants of learners' continuance intention to use massive open online courses (MOOCs) for personal or professional development.

This study employed quantitative research design. The respondents were individual learners from six selected universities in China who used MOOCs for continuous learning. A purposive sampling technique was employed to obtain 270 valid samples. Data were analyzed and analytical outputs were produced using the techniques of Partial Least Squares Structural Equation Modeling and Importance-Performance Matrix.

Expectation confirmation was found to have a positive relationship with perceived usefulness, flow experience, learning self-efficacy and satisfaction with MOOCs. Perceived usefulness, flow experience and leaning self-efficacy were also found to have a positive relationship with MOOC satisfaction. In addition, perceived usefulness, flow experience, learning self-efficacy and MOOC satisfaction had a positive impact on continuance usage intention.

The outcomes of the study can serve as a practical reference for MOOC providers and decision-makers to develop relevant strategies to increase the course completion rates.