This analysis integrates the “technology acceptance model (TAM)” with the “use of gratifications theory (U&G)” to develop an embedded model that predicts the use and satisfaction of emotional icons called stickers through WhatsApp. The explanation for combining these two theories is that U&G offers accurate information and a thorough knowledge of use, while TAM theory has been firmly established in several technical implementations. A newly developed hybrid analysis procedure has been applied within this research. Using an artificial neural network (ANN), and the structural equation model (SEM) have been combined. The research also uses the importance-performance map analysis (IPMA) to present each factor’s performance as well as importance. The ANN and IPMA research have both indicated that for sticker use intention, a highly essential predictor is Socialization. An online questionnaire survey was developed to assess the recommended model. The intention to use stickers was significantly affected by “Socialization, Self Presentation, Enjoyment, Novelty, Unique Function, Perceived Ease of Use, and Perceived Usefulness”. The research's main achievement is the convergence of two separate theories into a single conceptualization to accurately calculate the TAM components when it comes to the usage of stickers in WhatsApp. Theoretically, the recommended model provides enough insight for aspects which affect the intention to use stickers with relevance to the socialization’s factors considering interpersonal aspects. Practically, the higher education decision-makers along with professionals would extract variables that are important as compared to others and policies would be developed accordingly. The deep ANN model competence has been analyzed within the research to decide upon the non-linear associations between variables of the theoretical model, methodologically.

This paper presents a numerical investigation on the flexural performance of a novel cementitious reinforced GEM-TECH material using finite element method. A discrete nonlinear FE model using the commercial software ANSYS was employed to model a steel-reinforced GEM-TECH beam. Element SOLID65 was used to model the cementitious material while LINK180 element was used to model the reinforcing bars and stirrups. For model validation, FEA results and crack plots were compared to those obtained from the experimental results of five reinforced GEM-TECH beams: three beams designed with target density of 1810 kg/m3 and two beams with target density of 1600 kg/m3. Both load-deflection plots and the failure mode crack plots predicted by the FE model were in good agreement with the experimental results.

The purpose of the current paper is to identify influential aspects of published literature and future research questions to set forth future research agenda based on comprehensive literature review using bibliometric and content analysis. The study analyzed 1225 documents from the international Scopus database using bibliometric analysis and content analysis. VOSviewer software is used for bibliometric analysis. The analysis revealed that most of the information was derived from the Finance Research Letters. Moreover, the United Kingdom is the most cited country, while Tianjin University in China has the highest publications affiliations. Furthermore, the analysis shows that the keyword analysis of cryptocurrency literature had four classes of research streams in cryptocurrency, namely, cryptocurrency, Blockchain, Fintech, and currency, representing the most upcoming trends. The present study makes a significant contribution to the literature by providing a framework for future research. The framework provides opportunities to future researchers to explore the web of relations among some identified research streams as future research agenda.

There are various reasons why vaccine fear has resulted in public rejection. Students have raised concerns about vaccine effectiveness, leading to hesitation when it comes to vaccination. Vaccination apprehension impacts students' perceptions, which has an impact on the acceptability of an e-learning platform. As a result, the goal of this study is to look at the post-acceptance of an e-learning platform using a conceptual model with several factors. Every variable makes a unique contribution to the e-learning platform's post-acceptance. In the current study, TAM variables were combined with additional external factors such as fear of vaccination, perceived routine use, perceived enjoyment, perceived critical mass, and self- efficacy, all of which are directly associated with post-acceptance of an e-learning platform. Here, a hybrid conceptual model was used to evaluate the newly widespread use of e-learning platforms in this area in this study in the UAE. In the past, empirical investigations primarily used Structural Equation Modeling (SEM) analysis; however, this study used a developing hybrid analysis approach that combines SEM with deep learning–based Artificial Neural Networks (ANN). This study also employed the Importance–Performance Map Analysis (IPMA) to determine the significance and performance of each element. Through the findings, it was found that fear of vaccination, perceived ease of use, perceived usefulness, perceived routine use, perceived enjoyment, perceived critical mass, and self-efficiency all had a significant impact on students' behavioral intention to use the e-learning platform for educational purposes. It was also shown in the analysis of ANN as well as IPMA that the perceived ease of use of the e-learning platform is the most important indicator of post-acceptance. The proposed model, in theory, provides appropriate explanations for the elements that influence post-acceptance of the e-learning platform in terms of internet service factors at the individual level. In the practical sense, these findings will help decision-makers and practitioners in higher education institutions identify the factors that should be given extra care and plan their policies accordingly. The ability of the deep ANN architecture to identify the non-linear relationships between the factors involved in the theoretical model has been determined in this research. The implication offers extensive information about taking effective steps to decrease the fear of vaccination among people and increase vaccination confidence among teachers and educators and students, consequently impacting society.

Corporate Social Responsibility (CSR) policy, digital marketing and green marketing are considered as some of the most emerging topics. However, the major problem is associated with the lack of CSR policies, development and adaptation of green marketing in the companies operating in manufacturing companies in the UK. In this manner, this study aimed to determine the role of digital marketing, CSR policies and green marketing in brand development. Concerning this, the case of UK’s manufacturing companies was considered which can help the manufacturing companies operating in the UK to make the development of brand more effective, as the consumers would perceive the brand which complies with the environmental laws. To attain the aim, the researchers utilized a quantitative method of data collection where a close-ended survey questionnaire was utilized. The data was collected from the concerned participants working in the manufacturing sector of the UK and the sample size considered for the analysis was based on 404 participants. The analysis was conducted using Structural Equation Modeling (SEM) on Smart PLS. The analysis revealed that the overall impact of green marketing, CSR policy and digital marketing was statistically significant on the brand development of UK’s manufacturing companies. Considering this, it has been recommended to the manufacturing companies in the UK to focus on environmental disclosure, green innovation, green alliance and promotional activity for the purpose of ensuring brand development. However, this study is limited to the geographical bounds of the UK; therefore, it has a certain room for future research.

The aim of the study was to examine the impact of digital marketing capabilities on organizational ambidexterity by focusing on the Information Technology Sector in UAE. Data were primarily gathered through self-reported questionnaires created by Google Forms which were distributed to a purposive sample of managers at different levels via email. This study was conducted structural equation modeling (SEM) to test the hypotheses, which represents a contemporary statistical technique for testing and estimating the relationship between factors and variables. The results showed that the highest impact on organizational ambidexterity was for strategic approach and data content infrastructure, followed by integrating customers with employees, and finally the lowest impact belonged to the process of improving performance. Based on the study findings, the researcher hopes that the decision-makers and managers define all tasks, roles and work procedures in companies through digital marketing systems to improve their organizational ambidexterity and enhance their performance.

The primary aim of this research is to determine attitudes held towards autonomous vehicles (AVs) and understand their impact on intentions to use the service among ride-hailing users in the UK. Based on the Theory of Planned Behaviour model, an online, self-administered survey was used to collect data from 151 consumers (18-24-year-olds). The relationship between variables was measured using a Spearman’s Rank test in SPSS. The results of this study found all categories (overall attitude, perceived ease-of-use, perceived value, perceived safety, perceived risk, technology, environmentalism, subjective norms, perceived behavioural control) received a positive mean score. From these results, it can be concluded that this sample holds positive attitudes towards AVs and intend to use the service when they are made available. A positive score for perceived risk, however, indicated that this group thought there may be safety concerns when using this technology. The main contribution of this study is providing data to a new, and rapidly evolving field of research and thus the findings of the present study contribute to ongoing research related to consumers attitudes of AVs. Managerially, companies that focus on developing and implementing AV taxis need to focus more on the safety benefits of such vehicles.

Recently audio and video material has been used significantly in various online platforms. The audio-video materials enhance the teaching and learning process by facilitating the transformation of the data and providing a richer interactive environment, hence gaining wide intention within the educational realm. However, empirical studies have not examined the acceptance of the audio and video material depending on a conceptual model where acceptance is the key factor. The present study attempts to overcome this gap in the literature review by investigating the effects of media richness, speed and vividness, perceived concentration, perceived ease of use, perceived usefulness on the acceptance of audio-video material. What distinguishes the current study is the fact that content richness is considered as a mediator that affects all other factors in the conceptual model. The data is collected by distributing the online survey to college students. The results provide mostly insight and support for students’ intention to use audio-visual resources in a conceptual model. The technology characteristics of speed and vividness as well as TAM constructs were significant predictors of technology acceptance. However, it is concluded that the external factor of the perceived concentration has no impact on the students’ perception and intention to use audio-visual resources. In the recommendation, some theoretical and practical implications are stated along with the focus on technology designers, change managers, and users.

This study aims to establish Middle East users' perspectives on the major factors that impact their decision to adopt Augmented Reality AR smart glasses (ARSG). Thus, an online questionnaire was designed and sent directly to the respondents, and 584 valid data points were collected from individuals living in the Middle East. The data were analyzed using Pearson correlations and Exploratory Factor Analysis (EFA) techniques using SPSS. Eleven hypotheses were tested using Multiple Regression analysis, where seven independent variables out of eleven were confirmed to have a significant impact on the perceived adoption of ARSG. The results indicate that four of the independent variables including Pre-Market Knowledge, Image, Own privacy and Technology innovativeness show the significant impact on ARSG adoption at the 1% significant level. In addition, the results indicate that three of the social and technological factors include Perceived Ease of use, Perceived usefulness and Other's privacy show the significant effect on ARSG adoption at the 5% significant level. Among the 7 social and technological factors, the results suggest that technology innovation expresses the strongest effect on ARSG adoption with the highest coefficient value of 0.413 (b = 0.413, t = 12.881, ρ < 0.01). Moreover, user intention is significantly impacted by gender and place of living but not by education or age. The research also provides pre-market insights on users' personal types that represent who will most likely adopt the new smart glasses and that differentiate them based on their priorities. To the best of our knowledge, this is among the first works to investigate technology acceptance drivers of AR smart glasses in the Middle East.

5G is a revolutionary development in network technologies which is gradually becoming very common among people contributing significantly in different fields such as education, industry, agriculture, health, tourism and military. Currently, 5G is an outbreak change as opposed to the traditional service of the Internet since it offers better quality, ultra-fast connection, low-cost, reduced latency, energy saving, which makes its great impact even greater in people’s life. The present study examines various factors that have a significant impact on the Use of 5G in the Gulf area. The study extended the TAM (Technology Acceptance Model) to include factors such as Perceived Enjoyment, Perceived Resources and Perceived Skills Readiness. The present research has adopted a hybrid model that incorporates TAM determinants with other external factors which have a direct relation with 5G as internet service. Previous studies have focused on the importance of 5G in different environments and countries. However, this study focuses on the newly spread Use of 5G in the gulf area by adopting a hybrid conceptual model. The findings suggest that 5G may help in promoting the usage of internet service more effectively with its low-cost, faster data transfer and better quality. Moreover, the findings indicate a positive effect of the gender as a mediator between the variables: Perceived Skills Readiness, Perceived Ease of use, and Perceived Resources.