The purpose of the study was to examine the role of personalization in motivating senior citizens to use AI driven fitness apps. Vroom’s expectancy theory of motivation was applied to examine the motivation of senior citizens. The responses from participants were collected through structured interviews. The participants belonged to South Asian origin belonging to India, Bangladesh, Nepal and Bhutan. The authors adopted a content analysis approach where the gathered interview responses were coded in the context of elements of Vroom’s theory. The findings of the study indicated that a highly personalized approach in the context of motivation, expectancy, instrumentality and valence will motivate senior citizens to use AI based fitness apps. The study contributes to the personalization of AI fitness apps for senior citizens.

In the fast-paced modern society, enhancing employees’ professional qualities through training has become crucial for enterprise development. However, training satisfaction remains under-studied, particularly in specialized sectors such as the coal industry. Purpose: This study aims to investigate the impact of personal characteristics, organizational characteristics, and training design on training satisfaction, utilizing Baldwin and Ford’s transfer of training model as the theoretical framework. The study identifies how these factors influence training satisfaction and provides actionable insights for improving training effectiveness in China’s coal industry. Design/Methodology/Approach: A cross-sectional design that allowed the study to capture data at one point in time from a large sample of employees was employed to conduct an online survey involving 251 employees from the Huaibei Mining Group in Anhui Province, China. The survey was administered over three months, capturing a diverse sample with nearly equal gender distribution (51% male, 49% female) and a majority aged between 21 and 40. The participants represented various educational backgrounds, with 52.19% holding an undergraduate degree and most occupying entry-level positions (74.9%), providing a broad workforce representation. Findings: The research indicated that personal traits were the chief predictor of training satisfaction, showing a beta coefficient of 0.585 (95% CI: [0.423, 0.747]). Linear regression modeling indicates that training satisfaction is strongly related to organizational attributes (β = 0.276 with a confidence interval of 95% [0.109, 0.443]). In contrast, training design did not appear to be a strong predictor (β = 0.094, 95% CI: [−0.012, 0.200]). Employee training satisfaction was the principal outcome measure, measured with a 5-point Likert scale. The independent variables covered personal characteristics, organizational characteristics, and training design, all measured through validated items taken from former research. The consistency of the questionnaire from the inside was strong, as Cronbach’s alpha values stood between 0.891 and 0.936. We completed statistical testing using SPSS 27.0, complemented by multiple linear regression, to study the interactions between the variables. Practical implications: This research contributes to the literature by emphasizing the necessity for context-specific training approaches within the coal industry. It highlights the importance of considering personal and organizational characteristics when designing training programs to enhance employee satisfaction. The study suggests further exploration of the multifaceted factors influencing training satisfaction, reinforcing the relevance of Baldwin and Ford’s theoretical model in understanding training effectiveness. Ultimately, the findings provide valuable insights for organizations seeking to improve training outcomes and foster a more engaged workforce. Conclusion: The study concluded that personal and organizational characteristics significantly impact employee training satisfaction in the coal industry, with personal characteristics being the strongest predictor. The beta coefficient for personal characteristics was 0.585, indicating a strong positive relationship. Organizational characteristics also had a positive effect, with a beta coefficient of 0.276. However, training design did not show a significant impact on training satisfaction. These findings highlight the need for coal companies to focus on personal and organizational factors when designing training programs to enhance satisfaction and improve training outcomes.

Mediating role of artificial intelligence in the relationship between higher education quality and scientific research ethics among faculty members: A Study in carrying out the study, specific research objectives were derived, and based on the derived objectives, null hypotheses were formulated and tested for the study. This study, thus, employed survey research design. This study’s population comprised postgraduate students from Middle Eastern University, Jordan, with 1200 students. Using the population, a sample size of 291 respondents was selected based on Krecie and Morgan The students in the sample completed Google Forms questionnaires. The data were statistically processed, and the analysis’s most significant level was 0.25. The research questions were analyzed using descriptive statistics, and the null hypothesis was tested using Pearson Product Moment Correlational Analysis (PPMC). Also, the study showed a significant relationship between artificial intelligence and the quality of higher education and the relationship of significance between artificial intelligence and ethics in scientific research. The researcher suggested a need for ongoing education, cross-discipline cooperation, and the development of solid ethical frameworks for the integration ethics of AI academia.

This study examines the microeconomic determinants influencing remittance flows to Vietnam, considering factors such as gender (SEX), age (AGE), marital status (MS), income level (INC), educational level (EDU), financial status (FS), migration expenses (EXP), and foreign language proficiency (LAN). The study analyzes the impact of these factors on both the volume (REM_VL) and frequency of remittance flows (REM_FR), employing ordered logistic regression on survey data collected from Vietnamese migrants residing in Asia, Europe, the Americas, and Oceania. The estimations reveal that migrants’ income, age, educational level, and migration costs significantly positively influence remittance flows to Vietnam. Conversely, the financial status of migrants’ families in the home country negatively impacts these flows. Gender and migration costs primarily influence the frequency of remittance transfers, but they do not have a significant effect on the volume of remittances. Although foreign language proficiency was introduced as a novel variable of the models, it does not demonstrate any significant impact in this study. Furthermore, the survey data and regression estimates suggest that two primary motivations drive remittances to Vietnam: altruistic motives and implicit loan agreements. This research contributes to a deeper understanding of remittance e behavior, particularly in the context of Vietnam’s status as a major labor exporter. The findings provide valuable insights for policymakers and researchers seeking to optimize remittance flows and their impact on the Vietnamese economy. By understanding the complex interplay of factors influencing remittance behavior, policymakers can design effective strategies to support migrants and encourage increased remittance inflows, ultimately contributing to economic development and poverty reduction.

This study explores how demographic factors shape perceptions of celebrity and influencer marketing in the context of promoting cryptocurrencies, particularly in the tourism sector. It evaluates whether such marketing strategies effectively promote cryptocurrencies and how their impact varies across demographic groups. By analyzing responses from a sample of 161 predominantly young and educated respondents, the study uses statistical methods to identify differences in perceived marketing effectiveness based on age, gender, and other demographics. Findings reveal no significant demographic differences in effectiveness; instead, the study underscores the importance of universal marketing qualities, such as authenticity, credibility, and relevance. These results suggest the need for inclusive marketing strategies that foster trust and transparency. Additionally, the study highlights avenues for future research, including cultural and ethical considerations, to refine marketing approaches and develop innovative campaigns that drive cryptocurrency adoption and trust in the tourism industry.