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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.

How to improve continuance commitment for platform workers is still unclear to platforms' managers and academic scholars. This study develops a configurational framework based on the push-pull theory and proposes that continuance commitment for platform workers does not depend on a single condition but on interactions between push and pull factors.

The data from the sample of 431 full-time and 184 part-time platform workers in China were analyzed using fuzzy-set qualitative comparative analysis (FsQCA).

The results found that combining family motivation with the two kinds of pull factors (worker's reputation and algorithmic transparency) can achieve high continuance commitment for full-time platform workers; combining job alternatives with the two kinds of pull factors (worker's reputation and job autonomy) can promote high continuance commitment for part-time platform workers. Particularly, workers' reputations were found to be a core condition reinforcing continuance commitment for both part-time and full-time platform workers.

The findings suggest that platforms should avoid the “one size fits all” strategy. Emphasizing the importance of family and improving worker's reputation and algorithmic transparency are smart retention strategies for full-time platform workers, whereas for part-time platform workers it is equally important to reinforce continuance commitment by enhancing workers' reputations and doing their best to maintain and enhance their job autonomy.

This study expands the analytical context of commitment research and provides new insights for understanding the complex causality between antecedent conditions and continuance commitment for platform workers.

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.

This study aims to identify when and why receiving i-deals will result in an increase in affective commitment rather than continuance commitment. As affective commitment yields long-term benefits for organizations than continuance commitment, this work will help organizations accrue maximum benefits from granting i-deals.

This study develops a cognitive model delineating the process between i-deal receipt and the variation in i-dealers’ continuance or affective commitment.

After receiving i-deals, i-dealers’ perceived valence may change with i-dealers’ evaluations of i-deal resources under the condition of coworkers' negative reactions or organizational investment. The i-deal valence changes trigger i-dealers’ internal or external attributions of coworkers' negative reactions or organizational investment, which leads to the variation in continuance or affective commitment. The changes of affective commitment also affect the variation in continuance commitment.

Integrating expectancy theory and attribution theory, this research addresses inconsistent findings about i-deals’ effect on continuance or affective commitment by revealing the critical factors that lead to the variation in the two types of commitment. The proposed model offers new theoretical rationale for why i-dealers may not reciprocate the goodwill of i-deals to their organizations. This study suggests i-dealers will engage in attributions rather than being passive recipients of their coworkers' negative reactions, which challenges previous view that the effectiveness of i-deals is ultimately determined by coworkers' acceptance. This research also extends the i-deal dynamics literature by depicting how i-deal valence changes arise and influence continuance or affective commitment.

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 objective of this study is to examine the drivers of retail apps satisfaction and continuance intention. An integrative theoretical framework was developed based on the IS success model, E-S-QUAL and expectancy and disconfirmation model to explain retail apps users’ satisfaction and continuance intention.

A total of 359 useable data were collected from the targeted Malaysian respondents who had experience in using retail apps services. Data were analysed using the partial least squares technique.

The results indicate that system quality and e-service quality positively influence retail apps usage satisfaction and have positive direct and indirect effects through satisfaction on continuance intention. The price level has a negative effect on retail apps usage satisfaction. Even though price level has no direct effect on continuance intention to use retail apps, it has an indirect effect on continuance intention through satisfaction.

Although the success of a marketing channel mainly depends on its continuance usage rather than first-time usage, few studies have paid attention to retail apps services. This study contributes to the advancement of knowledge on retail apps by explaining the roles of system quality, e-service quality and price level on retail apps satisfaction and continuance intention. Interestingly, the findings of multi-group analysis imply that female Gen Y app users are more satisfied than males while such differences do not impact their continuance intention to use the retail apps. The findings also suggested that frequency of using apps has no relevance to retail apps user satisfaction, but highly relevant to their continuance intention to use retail Apps services.

The purpose of this study is to empirically explore the predictors of e-marketing use continuance intention in the pharmaceutical business to business (B2B) supply chain during the COVID-19 pandemic.

This study adopted survey research strategy, and data were collected from managers dealing with marketing in 127 pharmaceutical firms in Harare Zimbabwe using a self-reported questionnaire. Partial least squares structural equation modeling (PLS-SEM) was employed to test the hypotheses.

Leadership support and perceived usefulness are significant predictors of e-marketing continuance intentions. The effect of perceived susceptibility and perceived severity on e-marketing use continuance intention was not significant. Perceived usefulness is a positive moderator in the relationship among leadership support, perceived susceptibility and e-marketing use continuance intention. However, the moderating effect of perceived usefulness created a significant but negative relationship between perceived severity and e-marketing use continuance intention.

This study provides empirical evidence of the moderating role of perceived usefulness in the relationships between e-marketing continuance intention and its predictors.

Virtual communities are useful sources of travel information for tourists. To better promote the sustainable development of virtual communities and provide theoretical guidance, this study aims to explore how the cognitive load generated by tourists in the information-seeking process facilitates the formation of their continuance intention.

Built on the cognitive load theory and flow theory, this study investigates the formation mechanism of virtual community users’ continuance intention to seek travel information. A total of 328 valid questionnaires were collected and used for hypothesis testing.

The results show that perceived usefulness, perceived information consistency and prior experience positively affect continuance intention. Concentration and time distortion have significant effects on continuance intention. Moreover, concentration and time distortion mediate between prior experience and continuance intention.

This study clarifies the formation mechanism of virtual community users’ continuance intention of travel information seeking from a new perspective. The conclusions enrich the research on consumer behavior in the information search field and provide a reference for virtual communities.

The purpose of this study is to investigate the continuance intention of using e-government services in Tanzania as well as moderating effects of system interactivity.

A research model based on expectancy confirmation model was developed and empirically tested using 213 data collected from e-government services users who were selected using the judgemental sampling technique. The variance-based structural equation modelling technique was used for data analysis using SmartPLS 3.0.

The results of this study suggest that system interactivity, computer self-efficacy, management support, confirmation, satisfaction and perceived usefulness have a positive and significant influence on continuance intention to use e-government services. Moreover, the findings of this study indicate that system interactivity moderates the influence of perceived usefulness and satisfaction on continuance intention.

This study extends the expectancy confirmation model with system interactivity, management support and computer self-efficacy which are considered as important factors in continuance usage of technology. Furthermore, this study examines the moderating effect of system interactivity on the effects of perceived usefulness and satisfaction on 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.