As more consumers adopt virtual try-on apps, shops can offer their goods at any time. Optimizing the online presence of e-tailers is based on technological advances, especially in mobile networks and augmented reality (AR) and virtual reality (VR) apps. This paper examines the factors influencing consumers’ experience and satisfaction using AR apps in makeup e-shopping. We employed constructs from models based on the stimulus–organism–response (SOR) paradigm as a starting point for our research. We added fit confidence, social value, and innovativeness, used in similar research on AR apps, to the continued usage intention, perceived utilitarian value, immersion, and perceived hedonistic value. Our research used the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach from SmartPLS 4 for an online questionnaire. We obtained that all parameters impact consumers’ intention to utilize AR applications. Considering the total effect (direct and indirect), the order of influence is as follows: fit confidence, innovativeness, immersion, social value, perceived hedonistic value, and perceived utilitarian value. This paper’s key findings demonstrate that social value, fit assurance, perceived utilitarian value, and immersion are the most significant direct influences on customer behavior using AR apps in makeup e-shopping.

During the pandemic years, universities worldwide adopted online teaching on a large scale. Besides desktop systems or laptops, many students also use smartphones for online learning. In our paper, we propose a hybrid theoretical model to analyze the continuance intention to use mobile learning in higher education. The scientific demarche is carried out from different perspectives opened by the models and theories integrated in a unitary approach. In addition to the main constructs taken from the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the research model was enriched with new capabilities by considering the Motivational Model (MM), Flow Theory (FT) and the Social Cognitive Theory (SCT). The research model was applied to the Romanian higher education environment and proved that perceived usefulness (PU), habit (HB), perceived skill (PS), and self-efficacy (SE) directly influence the continuance intention to use (CU) smartphones in higher education. Further, performance expectancy (PFE), intrinsic motivation (IM), perceived ease of use (PEOU), and perceived enjoyment (PE) indirectly influence the continuance intention to use (CU). We presented our results according to top studies on the critical challenges and factors influencing smart mobile learning success usage during the COVID-19 pandemic. Thus, we found that Romanian universities provide excellent IT infrastructure and top management support and that creating habits of using m-learning in the context of university classes will strengthen the university culture. The conclusions of the undertaken research represent a starting point in the diversification and flexibility of educational processes in Romanian universities.

This paper focuses on the importance of online questionnaires, used in employee recruitment activities. It presents the theoretical frame of this study, as well as some existing software and hardware tools which can be used in order to implement online questionnaires. The article also highlights several observations on the type of questions which can be used in the online environment and, in the end, it presents algorithms which can be used for questionnaire data analysis

This paper examines students’ perceptions of factors influencing normative support for the integration of AI Chatbots in universities, providing an empirical basis for developing institutional policies and implementation strategies in higher education. Framed within the sustainability perspective, the study examines how ethical, cognitive, and perceptual factors shape the long-term adoption of AI technologies in academic environments. Our study employs a structural model comprising 10 constructs, 46 items, and 9 hypotheses, tested on a sample of 408 economics students from Timisoara. The research identifies AI literacy as the most influential factor in the formal integration of these technologies in universities. The following factors have a direct impact: teacher perception, student perception, and cognitive risks (reliance on AI Chatbots and avoidance of intellectual effort). Use for personalized learning is a factor with a significant direct effect on positive perceptions and intentions to use AI Chatbots among students. Academic integrity risks, as well as limitations on accuracy and reliability, have no significant impact. AI Chatbots represent an essential opportunity to transform higher education. However, their positive impact is realized only through responsible formal integration, grounded in ethical policies, adequate digital education, and the adaptation of pedagogical practices. Universities must regard AI as a strategic ally for teachers and students, while keeping human interaction, critical thinking, and academic integrity at the centre of the educational process. The study argues that students’ perceptions are that universities must approach AI Integration as a strategic component of sustainable educational ecosystems, aligning innovation with long-term academic integrity and the objectives of sustainable development, particularly Sustainable Development Goal 4 (Quality Education).

For the travel industry, technology, digitalization, and connectivity are factors of significant importance. We proposed a city guide app (CGA) model in this research. The general city tourist information is enormous, but it is essential to know the information of interest for travelers and useful for mobile applications. We used an online survey to detect this kind of information. The interviewees were young people aged 20 to 24 from Romania who used at least a CGA while travelling in different cities, especially abroad. We kept forty questions for the proposed model—sixteen from the previous research on app quality, user habits, travel agency app usage, behavioral intention, twenty-four questions on touristic information proposed by us. We used the partial least squares structural equation modelling (PLS-SEM) method. We concluded which touristic information influences mobile app quality and behavioral intention. Given the age and location of our interviewees, this information could be different, considering the respondent age, location, and habits. Whether we are talking about passionate information technology (IT) developers, city halls, or travel agencies, this study is helpful for those who want to develop a CGA.