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.
To avoid the spread of the COVID-19 crisis, many countries worldwide have temporarily shut down their academic organizations. National and international closures affect over 91% of the education community of the world. E-learning is the only effective manner for educational institutions to coordinate the learning process during the global lockdown and quarantine period. Many educational institutions have instructed their students through remote learning technologies to face the effect of local closures and promote the continuity of the education process. This study examines the expected benefits of e-learning during the COVID-19 pandemic by providing a new model to investigate this issue using a survey collected from the students at Imam Abdulrahman Bin Faisal University. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed on 179 useable responses. This study applied Push-Pull-Mooring theory and examined how push, pull, and mooring variables impact learners to switch to virtual and remote educational laboratories. The Protection Motivation theory was employed to explain how the potential health risk and environmental threat can influence the expected benefits from e-learning services. The findings revealed that the push factor (environmental threat) is significantly related to perceived benefits. The pull factors (e-learning motivation, perceived information sharing, and social distancing) significantly impact learners' benefits. The mooring factor, namely perceived security, significantly impacts learners' benefits.
The evolution of Artificial Intelligence (AI) has revolutionized many aspects of human life, including healthcare. Amidst the Covid-19 pandemic, AI-enabled smartwatches are being used to help users to self-monitor and self-manage their health. Using a framework based on Stimulus-Organism-Response (S-O-R) theory, this present study aimed to explore the use of AI-enabled smartwatches for health purposes, in particular the effects of product quality, service quality, perceived convenience, and perceived ease of use on user experience, trust and user satisfaction. Based on a purposive survey sample of 486 smartphone users in Bangladesh, data collected was analyzed using SPSS software for elementary analyses and PLS-SEM for hypotheses testing. The findings showed that the predictors, namely product quality, service quality, perceived convenience, and perceived ease of use, significantly affected user experience and trust. Similarly, user experience and trust were influential on user satisfaction and played partial mediating roles between predictors and user satisfaction. Besides, gender and age moderate the relationships of experience and trust with customer satisfaction. These findings support the S-O-R theoretical framework and have practical implications for brand and marketing managers of smartwatches in developing product features and understanding users' attitudes and behaviours.
This study investigates the underlying motives for online fake news sharing during the COVID-19 pandemic, an unprecedented time that witnessed a spike in the spread of false content. Motives were identified based on a fake news sharing model developed using the SocioCultural-Psychological-Technology (SCulPT) model, Uses and Gratification (U&G) theory and Self-Determination Theory (SDT), and further extended using fake news predictors/gratifications from past studies. A self-administered survey resulted in 869 online Malaysian respondents aged between 18 and 59 years old (Mean = 22.6, Standard deviation = 6.13). Structured equation modelling revealed the fake news sharing model to collectively account for 49.2 % of the variance, with Altruism (β = 0.333; p
Higher education (HE) serves to produce well trained and job-ready graduates. Despite this belief, whether HE produces certificates/qualifications or job-ready graduates-this debate remains unsettled. To date, the current COVID-19 pandemic which erupted in late 2019 continues to create much economic, social and political dislocation throughout the world. Consequently, one outcome for HE during this crisis is the much greater dependence on online/digital technology to deliver courses and programs. Although it is not considered to be a complete substitute, critics argue that education delivered through online technology has expended the 'diploma disease' crisis and subsequently may pose a threat to the viability of producing HE graduates. It has been suggested that this can result in significant long-term problems that may be impossible to recover from. This study was based on a 'empirical survey' where the sample incorporated 240 people in two groups (before and during COVID-19, for a total of 120 in each), and the objective was to examine academic and job-readiness of graduates in greater depth. Findings demonstrate that pre-pandemic students scored poorly academically compared to their post-pandemic classmates. Pre-pandemic graduates, on the other hand, had higher work readiness scores in terms of both aptitude and practical aspects. Furthermore, both groups outperformed their job-readiness scores in terms of learning performance. This raises the question: is it the job of higher education to promote sustainable production of graduates or deliver certificates and degrees? COVID-19 appears to have been utilised by the HE system as an excuse to exacerbate the "diploma disease crisis," a scenario that must be resolved by developing a proper policy framework that allows HE to play the necessary role in an emergency. Meaningful measures should be taken so that online technology is employed properly in this situation.
Online reviews have been used effectively to understand customers' satisfaction and preferences. COVID-19 crisis has significantly impacted customers' satisfaction in several sectors such as tourism and hospitality. Although several research studies have been carried out to analyze consumers' satisfaction using survey-based methodologies, consumers' satisfaction has not been well explored in the event of the COVID-19 crisis, especially using available data in social network sites. In this research, we aim to explore consumers' satisfaction and preferences of restaurants' services during the COVID-19 crisis. Furthermore, we investigate the moderating impact of COVID-19 safety precautions on restaurants' quality dimensions and satisfaction. We applied a new approach to achieve the objectives of this research. We first developed a hybrid approach using clustering, supervised learning, and text mining techniques. Learning Vector Quantization (LVQ) was used to cluster customers' preferences. To predict travelers' preferences, decision trees were applied to each segment of LVQ. We used a text mining technique; Latent Dirichlet Allocation (LDA), for textual data analysis to discover the satisfaction criteria from online customers' reviews. After analyzing the data using machine learning techniques, a theoretical model was developed to inspect the relationships between the restaurants' quality factors and customers' satisfaction. In this stage, Partial Least Squares (PLS) technique was employed. We evaluated the proposed approach using a dataset collected from the TripAdvisor platform. The outcomes of the two-stage methodology were discussed and future research directions were suggested according to the limitations of this study.