Background: In an increasingly globalized world, public health is a challenge in the future of health systems. Nursing is a fundamental profession in health systems and the purpose of the study is to quantify the scientific production in global public health carried out by nursing to demonstrate its competence, capacity and specialization in this subject. Methods: A bibliometric study was carried out to understand the scientific production of public health nursing in WoS. A total of 17,545 documents were analyzed using Bibliometrix software in version 4.0.5. Results: A notable increase in production is observed over time, a sign of specialization and capacity. The theme focuses on three stages: hygiene and sanitation, infectious diseases and quality, prevention and non-communicable diseases coinciding with the real social needs of each moment. Most of the production is in English and produced by countries with developed economies. Nursing is aligned with current public health needs. Conclusions: Bibliometrics is a good method to quantify scientific production. The results show extensive scientific production in public health nursing, which translates into extensive knowledge of public health by nursing. There is a growth in production in accordance with time as well as an adaptation to the most current themes in accordance with population needs. Public health is an area of concern to countries and nursing can actively participate in studies, planning and leadership of health systems. Public health nursing should not be considered relegated to medicine but independent and of crucial importance to the “Onehealth” concept. Public, private and educational administrations must promote and support nursing research in public health, and it is not advisable to reduce the teaching load of global public health in nursing studies, in favor of the family and community environment.

In Industry 4.0, the business model innovation plays a crucial role in enabling organizations to stay competitive and capitalize on the opportunities presented by digital transformation. Industry 4.0 is driven by digitalization and characterized by integrating various emerging technologies. These technologies can potentially change traditional business models and create new value propositions for customers. This paper aims to analyze and review the research papers through a bibliometric approach scientifically. The data were extracted from reputable Clarivate Web of Science (WoS) Core Collection sources from 2010 to 2023 (June). However, the publication started in 2018 for the research fields. The results show that scientific publications on research domains have increased significantly from 2020. VOSviewer, R Language, and Microsoft Excel were utilized for analysis. Bibliometric and Scientometric approaches conducted to determine and explore the publication patterns with significant keywords, topical trends, and content clustering better discussions of the publication period. The visualization of the data set related to research trends of Industry 4.0 in relation to Business Model Innovation resulted in several co-occurrence clusters namely: 1) Business Model Innovation; 2) Industry 4.0; 3) Digital transformation; and 4) Technology implementation and analysis. The study results would identify worldwide research trends related to the research domains and recommendations for future research areas.

Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.

Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.

This study examines the impact of emotional intelligence (EI) and employee motivation on employee performance within the telecommunication industry in the Sultanate of Oman. The target population consisted of 4344 non-managerial employees across nine telecommunication companies, including Omantel, Ooredoo, Vodafone, Oman Broadband Company, Awasr Oman & Co, TEO, Oman Tower Company L.L.C, Helios Tower, and Connect Arabia International. Employing a deductive research approach, finally data were collected via an online survey from 354 respondents. The hypotheses were tested using multiple regression analysis. The results indicate that all dimensions of EI self-awareness, self-regulation, empathy, and social skills positively and significantly influence employee performance, with social skills having the strongest effect. Furthermore, both intrinsic motivation factors, such as work itself and career development, and extrinsic motivation factors, including wages, rewards, working environment, and co-worker relationships, significantly enhance employee performance. The interaction between EI and employee motivation was found to amplify these positive effects. Among control variables, age and education level showed significant impacts, while gender did not. These findings underscore the critical role of both emotional intelligence and motivation in driving employee performance. The study suggests that managers and policymakers should adopt integrated strategies that develop EI competencies and enhance motivational factors to optimize employee performance, thereby contributing to the success of organizations in the telecommunication sector.

In recent years, China’s economy has undergone rapid development. Increased disposable income and the rapid expansion of Internet-based financial services have positioned China as the largest market for luxury goods. Gen Z, the youngest demographic within emerging markets, is expected to play a pivotal role as the primary driver of the luxury market. However, while China’s luxury market continues to exhibit a high growth rate, this growth has gradually decelerated in comparison to the previous two years according to researchers. This presents a significant challenge for the luxury industry, as maintaining and enhancing the global growth trend has become a pressing concern where consumer behavior is concerned. The second key issue addressed in this study revolves around the concepts of compulsive buying and brand addiction, which can lead individuals, particularly Gen Z, to develop an addiction to luxury consumption. This study is based on an integrated model of conspicuous consumption, social comparison, and impression management theory. The key variables are materialism, brand consciousness, status-seeking, peer pressure, and collectivism to predict the luxury consumption model with debt attitude introduced as a moderating variable to study consumer behaviour in this age group. A non-probability sampling method and 480 people were selected as research samples. Quantitative analysis was used in this study, and SPSS and Smart PLS were used as data analysis tools. Structural equation model (SEM) using partial least squares method was used to determine the relationship of the variables and the moderating effect of debt attitude. The results showed that brand consciousness, status seeking, debt attitude and materialism had the strongest relationship with luxury consumption. Debt attitude as a moderating factor has a significant impact on the hypothesized relationship of the model. This paper provides empirical evidence for research on Gen Z’s luxury consumption, which has practical implications to marketers, luxury companies, local luxury brands and credit institutions.