Given that the mobile wallet has become a disruptive innovation, especially in the Malaysian hospitality industry, this study investigates the adoption of mobile wallet in the hospitality industry among consumers. Different from the extant literature, this study extends the newly proposed mobile technology acceptance model with self-efficacy theory, critical mass theory, and flow theory to explain the behavioural intention to adopt. A self-administered questionnaire was utilised to collect data from mobile wallet users who have used a mobile wallet while dining out in restaurants and cafes. Other than technology self-efficacy and perceived critical mass, mobile usefulness, mobile ease of use, mobile self-efficacy, and perceived enjoyment were discovered to have a positive and significant association with the behavioural intention to adopt mobile wallet in the hospitality industry. The findings also suggested there were interrelationships between the constructs employed. Overall, the extended model was able to explain 61% of the variance in behavioural intention to adopt mobile wallet.
As the COVID-19 pandemic continues to spread at an unprecedented rate, many universities around the world halted physical forms of teaching and learning to stop the spread of the virus. As a result, many university students were forced to utilize online learning through channels such as mobile social media. Due to the novelty of this situation, there are many unknowns particularly with the negative influences of mobile learning via social media on university students. Thus, this study looks to examine this subject matter from the perspective of the stimulus-organism-response theory. The uniquely developed research model included four stimuli (i.e., social overload, information overload, life invasion, and privacy invasion), two organisms (i.e., technostress and exhaustion) as well as a response in terms of reduced intention to use mobile learning via social media. The responses were collected from 384 university students via an online survey and analyzed with the Partial-Least-Square-Structural-Equation-Modelling. It was found that the antecedents for both technostress and exhaustion were able to account for more than half of their respective variances. Furthermore, technostress and exhaustion were significant facilitators of the students' reduced intention to use mobile learning via social media. In addition to the practical insights for stakeholders in the education industry, this study also posited several theoretical implications for researchers.