The study investigates the underlying motives facilitating users’ continuance intention for digital content in academic settings. Extending the expectation confirmation model of IS continuance (ECM-ISC), the study proposes a conceptual model by incorporating personal and technological antecedents of users’ continuance intention for digital content. In addition, users’ environmental concerns and price value are considered as potential moderators in the relationship between their satisfaction and continuance intention for digital content. An online survey was used to collect data from 311 digital content users of a large public university in Saudi Arabia. Structural equation modeling was used to test the relationships in the conceptual model. The results obtained from SmartPLS 3.2 confirm that compatibility, convenience, self-efficacy, and facilitating conditions are the predictors of confirmation and usefulness of digital content. The confirmation of expectations and perceived usefulness result in greater satisfaction with the digital content, which in turn leads to users’ continuance intention. In addition, the article provides empirical evidence for the impact of environmental concerns on the satisfaction–continuance intention relationship, thus opening a novel research debate. The study is expected to offer new insights both for academicians and managers of digital content.

In order to fight against the COVID-19 pandemic the government of Saudi Arabia launched three mobile applications namely Tetamman, Tabaud & Tawakkalna to keep the public aware about the corona virus and ensure monitoring of the suspected cases. The objective of this study is to curb the spread of COVID-19 by enhancing social measures and investigate the role of mobile applications in achievement of this objective. Comprehensive review of the role of mobile applications was made and a survey approach was used to evaluate the effectiveness of these applications. Findings of the study indicate that the users perceive that the applications are successful in achievement of the objectives for which these applications were launched. The key performance indicators (KPIs) included in the survey were efficiency, ease of use, satisfaction of users, fulfilment of purpose, usefulness and helpfulness etc. The average number of respondents, who agreed that these applications are performing according to the mentioned KPIs, is 86.6% for Tetamman, 80.5% for Tabaud and 90% for Tawakkalna. More awareness campaigns are needed so that more people adopt the use of these applications, which could significantly help in identification of new casesand enhance telehealth and teleconsultations. Moreover, the applications should be upgraded for self-triage.

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COVID-19 is a serious epidemic that has an unmistakable impact on all aspects of our lives, including the educational process. Most of the world has adopted Virtual Classes (VCs) to sustain teaching and learning. While prior research about such e-learning technologies has been focusing on the initial adoption, this research investigates the factors influencing the students’ desire and intention to continue using VCs, especially after the crisis subsides. This study extends the literature by developing a model that integrates pre-and post-adoption constructs and incorporates technological characteristics, namely, task technology fit, convenience, and compatibility into the Expectation Confirmation Model (ECM) to study the post-adoption Continuance Intention (CI) of VCs. The model is empirically validated using the partial least squares–structural equation modelling method and proved to have a reasonable description power (R2=62%) in terms of students’ CI. The survey empirical data is also supported by interviews with some students. The results support all the hypothesized relationships and confirm that the integration of technical characteristics in the ECM provides an appropriate framework to explain students’ intention to continue using VCs, which forms a good base for practitioners to consider a wide range of technological features for preparing applications. Yet, the model still requires to be extended with other stakeholders, including teachers, and other constructs like personal, psychological, social, and environmental factors.

Smart wearable (SW) devices have attracted the users’ attention and their utility has been increasingly employed in different arenas of life. Of late, it is expected that wearable payments will be the norm of mobile payments soon. Recognizing the SW payments as an emerging innovation, this study investigates the consumers’ adoption of SW payments. A survey method was used to collect data from SW devices users in Saudi Arabia. For this purpose, online questionnaires were distributed and a total of 269 responses were received within that 243 operational cases were used for data analysis. Partial least squares structural equation modeling (PLS-SEM) technique was employed to analyze the data. The statistical tools employed for data analysis are SmartPLS 3.0 and SPSS23. The findings show that all hypothesized relationships were supported except the compatibility and perceived ease of use relationship which was found insignificant. Additionally, the moderating role of personal innovativeness on behavioral intention and actual use relationship was also confirmed. Although TAM is an established robust model of technology adoption, however, the integration of technological features like (perceived esthetics, compatibility, and convenience) make it a more vigorous model for adoption of the smart wearable device.

Advances in information technology have included the development of smart wearable healthcare (SWH) devices that have potential benefits for consumer health. The adoption of SWH devices is limited, however, compared with other established digital technologies. This study examines the determinants of consumers’ adoption of SWH devices. A conceptual model is proposed that incorporates health (health beliefs and health information accuracy), and technology (compatibility and functional congruence) attributes into the technology acceptance model framework. The proposed model was tested in two steps. Structural equation modelling (SEM) was performed with 473 usable responses to test the hypothesized relationships. The artificial neural network (ANN) approach was then applied to validate the outcomes of Step 1. The SEM analysis indicates that all the hypothesized relationships are supported. The ANN analysis further validates the outcomes of the SEM. The findings of this study and the dual-stage SEM-ANN methodology will have a strong impact on the existing literature regarding SWH devices.

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Electronic commerce has provided opportunities to businesses to enhance their