The COVID-19 pandemic has brought life changing conditions to families that require coping strategies in order to survive and achieve family well-being. This study aims to analyze differences between single earner and dual earner families during the COVID-19 pandemic and to analyze the factors that influence subjective family well-being. The research design used was a cross sectional study with sample collection through non-probability sampling. Data collection was carried out by filling out questionnaires online. The number of respondents involved in the study was 2084 intact families with children residing in DKI Jakarta, West Java, and Banten Provinces. Reliability and validity tests were conducted. The results of the independent t-test showed that dual-earner families experienced better life changes and a higher level of subjective family well-being than single-earner families and had lower economic pressure and lower economic coping than single earner families. The SEM analysis found that life changes affected economic coping negatively and subjective family well-being positively. Family income influenced economic coping negatively and subjective family well-being positively. Finally, it was found that economic coping had no effect on subjective family well-being.

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.

This study investigates the public’s perceptions of digital innovations in pharmacy, with a focus on health informatics and medication management. Despite the rapid development of these technologies, a comprehensive understanding of how various demographics perceive and interact with them is lacking hence, this research aims to bridge this gap by offering insights into public attitudes and the factors influencing the adoption of digital tools in pharmacy practice, as KSA population and healthcare professionals after Covid-19 has observed the significant potential of digital health. A cross-sectional survey involving 1132 participants was conducted, employing SPSS for data analysis to ensure precise and reliable results. The findings indicate general optimism about the potential of digital innovations to enhance healthcare outcomes but concerns about data privacy and usability significantly affect user acceptance. The researchers recommended tailored educational programs and user-centered design to facilitate the adoption of digital pharmacy innovations. Key contributions include the identification of ‘Ease of Use’ and ‘Data Security and Privacy’ as predominant factors in the adoption of digital health tools.

The concept of sustainable urban mobility has gained increasing attention in recent years due to the challenges posed by rapid urbanization and environmental degradation. The objective of this study is to explore the role of on-demand transportation in promoting sustainable urban mobility, incorporating insights from customer interests and demands through survey analysis. To fulfill this objective, a mixed-methods approach was employed, combining a systematic literature review with survey analysis of customer interests and demands regarding on-demand transportation services. This study combines a systematic literature review and a targeted survey to provide a comprehensive analysis of sustainable urban mobility, addressing gaps in understanding customer preferences alongside technological and financial considerations. The literature review encompassed various aspects including technological advancements, regulatory frameworks, user preferences, and environmental impacts. The survey analysis involved collecting data on customer preferences, satisfaction levels, and suggestions for improving on-demand transportation services. The findings of the study revealed significant insights into customer interests and demands regarding on-demand transportation services. Analysis of survey data indicated that factors such as convenience, affordability, reliability, and environmental sustainability were key considerations for customers when choosing on-demand transportation options. Additionally, the survey identified specific areas for improvement, including service coverage, accessibility, and integration with existing transportation networks. By providing flexible, efficient, and environmentally friendly transportation options, on-demand services have the potential to reduce congestions, improve air quality, and enhance overall urban livability.

The consensus is that price stability promotes sustainable economic growth while excessive inflation harms growth. This study assesses the linkage between inflation and economic growth in South Africa to determine the optimal inflation rate threshold for the sustainable growth of the economy. Quarterly data from 1995 to 2022 was analysed through the ARDL and threshold regressions. The ARDL and threshold regressions estimate established a relationship between inflation and economic growth and computed the optimal inflation rate threshold for economic growth at 6 percent. The results also established that both the repo rate (repurchase rate) and real effective exchange rate have a negative relationship with economic growth. The Toda-Yamamoto causality test result indicated a unidirectional causality runs from inflation to economic growth. These results are crucial for the South African Reserve Bank to discharge its monetary policy functions to attain and maintain price stability. Therefore, this study offers the Bank a roadmap for targeting an inflation rate that aligns with the nation’s long-term objectives for sustainable economic growth.

The paper demonstrates the importance of subnational data on housing to be systematically reported and added to country typologies. We asked which national and local level characteristics of housing regimes can serve as benchmarks for reasonable country groupings. The aim of this paper is to (1) develop a methodological tool enabling the comparison of conditions for housing policy implementation on national and subnational levels and (2) identify the group of countries where conditions for housing policy implementation on national and subnational levels tend to be comparable. This country classification can be used as a practical instrument for comparative analyses and policy learning. As a conceptual framework, we used the international comparative Housing research 2.0 launched by Hoekstra in 2020. For our analysis, we selected 15 basic factors that were tested in 24 European countries. We have identified three key factors having an impact on housing policy implementation: decentralisation level in housing, local budget housing expenditure and the information on which governance level has core competencies within housing. The numeric database has been run through a k-means cluster analysis. Five distinct types of countries with similarities in conditions for housing policy implementation on national and subnational level have been identified and described.