Reinforcement of structural timber members with fibre reinforced polymer (FRP) rods offers merits over that of the conventional steel type. In recent times, near surface mounted (NSM) FRP reinforcement with timber has emerged as a promising alternative for reinforcing timber structures in both flexural and shear loading configurations. Previous investigations have shown that NSM FRP reinforcement technique has higher bond performance than externally bonded equivalents because it (NSM FRP technique) is able to utilise the full capacity of the FRP materials. In spite of these merits, the investigations and the use of this innovative technique are limited. In this paper, an experiment was conducted to investigate the bond characteristics and performance of NSM basalt FRP reinforcement with solid timber structures. In order to predict the performance of the reinforced beam structures, unreinforced control timber members of the same timber characteristics were tested. The results showed that the average bond capacity of the NSM FRP reinforced members was 16% higher than the corresponding unreinforced beams.

Social media influencers have become a more effective modern marketing approach used by businesses to influence consumers' intention and attitude. This study explores this influence by involving several factors of influencer’s characteristics on both consumers’ attitude and intention. Also, a moderation role of vloggers as a new emerging marketing tool is also examined in this research. To conduct this research and achieve its key objective, the study uses a quantitative research method to collect data from TikTok users which has also become a more worldwide favorable web device for short videos. PLS-SEM method is conducted in the phase of analysis and the results show a significant influence of the hypothesized research model except the influence of source relatability on consumer attitude and the moderating role of vloggers on consumer intention. The research findings provided unsurprisingly implications and supported the existing related literature in this field but contribute to cover the research knowledge gap through the integrated new model including numerous variables that have not been examined previously together in a unique framework.

In online shopping enterprises, AI technology has been widely used to provide accurate and fast personalized consumer services. This research demonstrates the use of AI technology in the e-commerce business, specifically online enterprises, to determine different effects. The study was conducted in Jordan and involved about 230 participants. The study evaluated different impacts of AI, such as e-payment and stimulating consumers' sentiments. The study used the Stimulus–Organism–Response model (SOR) empirical model, which states that the examination of human processes differs from that of the machine assessment. The model classified the AI technology experienced by the customers' when they visit online to do purchasing. Online purchasing behaviors can be influenced by insight, accuracy, and interaction experience. Also, the perceived value was used as a mediating variable from the prospects of perceived hedonic and utility value. The research integrated empirical research models such as SEM and SPSS to analyze the data on the effects of three-dimension. The results indicated that the AI technology accuracy, interactive experience, and insight significantly affected customers' perceived hedonic and utilitarian values.

Recent studies on e-feedback have answered many questions concerning the effectiveness of e-feedback in educational and non-educational sectors. They stated clearly that e-feedback is efficient and practical. From both teachers’ and students’ perspectives, e-feedback has influenced their learning and teaching environment effectively. It is a good technique to personalize the learning strategies. Based on the previous assumption, this study aims at exploring the effectiveness of e-feedback in an educational environment taking into consideration the TAM model and the external factors of trustworthiness and enjoyment. The data is collected by an online questionnaire that was distributed among a group of students. Facilitating communication among teachers and students. It helps in replacing the traditional feedback and assess the learning environment during the pandemic periods. The two constructs of perceived ease of use and perceived usefulness affect positively the intention to use the e-feedback and initiates this type of feedback as a prominent procedure to be used frequently in the learning environment. In addition, the perceived enjoyment and perceived trustworthiness increase the chance of using e-feedback. Recently, e-feedback is highly dominant among online platform users.

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.