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The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere physical activity tracking. While these modern wearables have empowered users with real-time data and personalized health insights, their environmental implications remain relatively unexplored despite a growing emphasis on sustainability. To bridge this gap, this study extends the UTAUT2 model with smartwatch features (mobility and availability) and perceived security to understand the drivers of smartwatch usage and its consequent impact on environmental sustainability.

The proposed theoretical model is evaluated based on data collected from 303 smartwatch users using a hybrid structural equation modeling–artificial neural network (SEM-ANN) approach.

The PLS-SEM results supported smartwatch features’ effect on performance and effort expectancy. The results also supported the role of performance expectancy, social influence, price value, habit and perceived security in smartwatch usage. The use of smartwatches was found to influence environmental sustainability significantly. However, the results did not support the association between effort expectancy, facilitating conditions and hedonic motivation with smartwatch use. The ANN results further complement these outcomes by showing that habit with a normalized importance of 100% is the most significant factor influencing smartwatch use.

Theoretically, this research broadens the UTAUT2 by introducing smartwatch features as external variables and environmental sustainability as a new outcome of technology use. On a practical level, the study offers insights for various stakeholders interested in smartwatch use and their environmental implications.

Despite the increased use of wearables in education, little attention has been paid to why some students are more likely to adopt smartwatches than others. The question of what impacts the adoption of smartwatches in educational activities is still neglected. In addition, the question of how security determinants can affect the adoption of smartwatches by students has not been addressed yet. Hence, this study aims to develop a theoretical model by integrating the technology acceptance model (TAM) and protection motivation theory (PMT) to study students' adoption of smartwatches for educational purposes.

Questionnaires were distributed to university students in Malaysia. A total of 679 valid responses were collected. The collected data were analyzed using partial least squares-structural equation modeling (PLS-SEM).

The results of data analysis provide support for the proposed model. Furthermore, the findings indicated that perceived vulnerability, self-efficacy, response efficacy, response cost, ease of use and perceived usefulness have significant effects on students' behavioral intention to use smartwatches for educational purposes. In addition, perceived ease of use of smartwatches for educational purposes helps students to realize the benefits of this technology.

This is an original study that develops a new holistic theoretical model by combining the PMT and TAM to study the effects of ease of use, usefulness and security-related factors on the adoption of smartwatches for educational purposes. The study offers practical implications for universities and higher education institutions to improve students' learning experiences to ensure their sustainability using new and innovative ways by exploiting new technologies such as smartwatches.

While there is an abundant amount of literature studies on mobile payment adoption, there is a scarce of knowledge concerning the sustainable use of mobile payment contactless technologies. As those technologies are mainly concerned with security and users' trust, the question of how security factors and trust can influence the sustainable use of those technologies within and beyond the COVID-19 pandemic is still unanswered. This research thus develops a theoretical model based on integrating the protection motivation theory (PMT) and the expectation-confirmation model (ECM), extended with perceived trust (PT) to explore the sustainable use of mobile payment contactless technologies.

The developed model is evaluated based on data collected through a web-based survey from 523 users who used contactless payment technologies. Unlike the existing literature, the collected data were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) technique.

The data analysis results reinforced all the proposed relationships in the developed model. The sensitivity analysis results showed that PT has the largest impact on the sustainable use of mobile payment contactless technologies with 97.2% normalized importance, followed by self-efficacy (SE) (77%), satisfaction (72.1%), perceived vulnerability (PV) (48.9%), perceived usefulness (PU) (48.2%), perceived severity (PS) (40.7%), response efficacy (RE) (28.7%) and response costs (RCs) (24.1%).

The originality of this research lies behind the development of an integrated model based on PMT and ECM to understand the sustainable use of mobile payment contactless technologies. The study provides several managerial implications for decision-makers, policy-makers and service providers to ensure the sustainability of those contactless technologies within and beyond the COVID-19 pandemic.

This systematic review aims to comprehensively explore the existing literature on the use of corporate communication within the realm of social media.

A total of 136 peer-reviewed journal articles are explored and analysed using both performance and bibliometric analysis.

This review identifies five main findings: (1) trends in corporate social media research that highlight the growth trajectory of research on social media use for corporate disclosure, (2) geographical coverage of studies indicating the concentration of research in certain regions, such as the USA, followed by China and the UK, with notable gaps in others, such as developing countries, (3) theoretical frameworks employed demonstrate that various theoretical frameworks are utilized, although a significant portion of the studies do not specify any theoretical underpinning, (4) social media platforms studied, confirming Twitter to be the most studied channel followed by Facebook and (5) thematic analysis of articles on disclosure type that categorized the articles using bibliometric analysis into five themes of disclosure: general disclosure, corporate social responsibility-related information, financial information, CEO announcements and strategic news communication. A subsequent cross-theme analysis classifies disclosure determinants and consequences of corporate social media usage.

Through a comprehensive and systematic analysis of existing research, this review offers novel insights into the current state of corporate communication on social media. It consolidates current knowledge, highlights under-explored areas in the existing literature and proposes new directions and potential avenues for future research.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

This chapter reviews Internet of Things (IoT) as a concept with bibliometric analysis using data selected from the Scopus database. The cited references included two clusters. Also, co-occurrence keyword analysis found four groups. The first cluster shows IoT adoption in agriculture, manufacturing, logistics, and supply chain management. The second cluster includes behavioral models of IoT technology acceptance. The third cluster refers to the adoption of IoT and automation technology in intelligent buildings, smart homes, smart cities, and health care. Finally, the fourth cluster contains information management.

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's aim was to investigate the stimulators of fashion e-consumers within e-commerce environments. The study proposed a framework utilizing stimulus–organism–response (S-O-R) theory to suggest that fashion involvement and opinion-seeking would act as sociopsychological stimuli, while product variety as an objective stimulus. Perceived quality is proposed as an organism, moderated by perceived price. Consumer buying behavior within e-commerce environments presents the framework's response. The study looked at variables with deeper insights into Malaysian fashion consumers.

A quantitative method was used to assess the significance of relationships within the proposed model. Partial least squares structural equation modeling technique was implemented to assess the framework's relationships with a sample size of 374.

Results indicate that fashion involvement is significantly associated as a sociopsychological stimulus, with product variety being an objective stimulus for Malaysian fashion e-consumers. Perceived quality is significantly represented as an organism through the framework, and buying behavior is the latent response. Price would significantly moderate the relationship between fashion involvement and quality. Opinion-seeking was found not to be a significant stimulus for Malaysian e-consumers.

Contribution of this study goes to the existing literature by providing a deeper understanding of Malaysian e-consumer behavior by applying S-O-R theory. Malaysian fashion e-consumerism was suggested to be influenced by product involvement, quality, price, opinion-seeking and product range offered; therefore, a proposed framework was demonstrated and tested.

ChatGPT is a cutting-edge chatbot powered by artificial intelligence that could revolutionise and advance the teaching and learning process. Drawing on the technology acceptance model (TAM) and information system (IS) success model, this study aims to investigate determinants of students’ intention to use ChatGPT for education purposes.

The partial least squares technique was used to analyse 406 usable data collected from university students in Malaysia.

The results confirmed the relationships between perceived usefulness (PU), perceived ease of use (PEU), attitude and intention to use proposed by TAM. PU and PEU are influenced by system quality. Surprisingly, trust in information moderates negatively the influences of PEU and PU on attitude.

The findings provide insight for higher education institutions, unit instructors and ChatGPT developers on what may promote the use of ChatGPT in higher education.

The study contributes to the literature by exploring the determinants of ChatGPT adoption, extending the TAM model by incorporating IS success factors and assessing the moderating effect of trust in information.