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The potential growth in cryptocurrencies has raised serious ethical and religious issues leading to a new investment rethinking. This paper aims to identify the influence of religiosity on cryptocurrency acceptance through an extended technology acceptance model (TAM) model.

In the first phase, this research develops a conceptual model that extends the theory of the TAM by integrating the religiosity component. In the second phase, the proposed model is tested using search volume queries in daily frequencies from 01/01/2018 to 31/12/2022 and structural equation modeling (SEM).

The empirical results demonstrate a significant positive effect of religiosity on the intention to use cryptocurrency, the users' perceived usefulness (PU) and ease of use (PEOU). Besides, the authors note that PEOU positively influences the intention. Furthermore, religiosity indirectly affects the intention through the PEOU and positively impacts the intention through the PU. In the same way, PEOU has a considerable indirect effect on the intention through PU.

This study has practical and theoretical contributions by providing insights into the cryptocurrency acceptance factors. In other words, it contributes to the literature by extending TAM models. Practically, it helps managers determine factors affecting the intention to use cryptocurrencies. Therefore, they can adjust their industry according to the suitable characteristics for creating successful projects.

Identifying the effect of religiosity on cryptocurrency users' choices and decisions has a social added value as it provides an understanding of the evolution of psychological variants.

The findings emphasize the importance of integrating big data to analyze users' attitudes. Besides, most studies on cryptocurrency acceptance are investigated based on one kind of religion, such as Christianity or Islam. Nevertheless, this paper integrates the effect of five types of faith on the users' intentions.

Providing quality education with the help of technologies in order to create global competitiveness among the students is the current trend in the education field. This research attempts to investigate following objectives: (1) the effect of students' perceived benefits and adoption intention of technology-enhanced learning (TEL) on their satisfaction; (2) the effect of students' perceived benefits of TEL on their adoption intention of TEL; (3) the mediating and moderating effect of students' perceived benefits of TEL in the link between students' adoption intention and satisfaction to TEL.

The primary data were collected from 600 undergraduate and postgraduate students, particularly those who are using TEL for at least one year. The authors used purposive sampling technique with “criterion variable”.

Results indicated that students' perceived benefits and adoption intention of TEL have significant and positive influence on their satisfaction. Direct effect was also found between perceived benefits and adoption intention of students. Authors also concluded that mediating and moderating effect of students' perceived benefits of TEL in the link between students' adoption intention and satisfaction for TEL was found significant and positive.

There is a huge lack of empirical studies available in the knowledge domain explaining the significance and implication of TEL in higher education in the state of Chhattisgarh, India.

Students' perception towards learning technologies in the disruptive times like coronavirus disease (2019) COVID-19 is what the educational institutes are striving to know so that the educational institutes could provide the best learning experiences to students. The present study attempts to identify the technology-enhanced learning (TEL) factors (i.e. informational quality, compatibility, resource availability, self-efficacy, subjective norms, subject interest and informational quality) with the mediation effect of perceived benefits on student satisfaction to TEL amongst non-technical students of different college/universities at Chhattisgarh state.

Purposive sampling technique with “criterion variable” was applied to collect responses from 600 participants. Students, who are enrolled in non-technical courses at different colleges/universities, were participated in the present study. The data collection process was completed during April–November 2019.

The results revealed that perceived benefits to TEL were significantly and positively mediated between all the TEL factors (i.e. information quality, compatibility, resource availability, self-efficacy, subjective norms, subject interest and institutional branding) and student satisfaction to TEL.

The present study itself is a novel study by taking TEL factors such as informational quality, compatibility, resource availability, self-efficacy, subjective norms, subject interest and institutional branding by considering perceived benefits as mediator to examine the influence on student satisfaction to TEL.

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.

In the era of artificial intelligence, natural language processing (NLP) models are revolutionizing numerous sectors. This research aims to explore the perceived value of them among university students. In particular, it aims to investigate how gender may influence students’ intention to use these models in educational contexts, highlighting potentially significant differences that could inform the implementation and adoption of educational technologies.

This study investigates the relationship between perceived value and students' intention to adopt NLP models, considering gender as a moderator. The research involves 562 students from the University of Salerno, in Italy, and uses confirmatory factor analysis to evaluate the reliability and validity of the measurement scales. A regression model with robust errors is used to explore the moderating role of gender on the relationship between perceived value and intentions of use of NLP models.

The results reveal a significant positive association between perceived value and intention to use NLP models, confirming that students with higher perceived value are more likely to adopt these technologies. Furthermore, gender moderates this relationship, indicating that females are less prone to use NLP models than male counterparts.

Research takes on a significant role in the academic field, underlining the importance of adapting teaching practices to the increasingly widespread digitalization. The inclusion of NLP models in university programs emerges as a possible improvement of the learning experience, ensuring cutting-edge education in tune with the needs of the digital society.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.