Academic integrity has been at the centre of the discussion of the adoption of Chat GPT by academics in their research. This study explored how academic integrity mitigates the desire to use ChatGPT in academic tasks by EFL Pre-service teachers, in consideration of the time factor, perceived peer influence, academic self-effectiveness, and self-esteem. The study utilized web-based questionnaires to elicit data from 300 EFL Pre-service teachers across educational fields drawn from different schools across the world. Analysis was conducted using relevant statistical measures to test the projected four hypotheses. The findings provide evidence in support of Hypothesis 1, with a statistically significant path coefficient (β) of 0.442, a t-value of 3.728, and a p-value of 0.000. The hypothesis acceptance implies that when academic integrity improves, the impact of the time-saving aspect of the use of ChatGPT Across educational fields study decreases. This suggests that EFL Pre-service teachers who have a firm dedication to academic honesty are less influenced by the tempting appeal of ChatGPT’s time-saving features, highlighting the ethical factors that influence their decision-making. The data also provide support for Hypothesis 2, indicating a substantial inverse relationship with a path coefficient (β) of 0.369, a t-value of 5.629, and a p-value of 0.001. These findings indicate that stronger adherence to academic integrity is linked to a diminished effect of colleagues on the choice to use ChatGPT in Academic tasks. The results suggest that a firm dedication to academic honesty serves as a protective barrier against exogenous pressures or influences from colleagues when it comes to embracing cutting-edge technology. However, in general, these findings revealed there was a negative association between academically related factors (e.g., time factor, sense of peer pressure, language study self-confidence, and academic language competence), as well as an attitude toward adoption of ChatGPT and commitment towards academic integrity.

Previous studies support the direct relationship between outdoor physical activity and natural spaces in cities. The Active City and Nature concept explores the relationship between urban, green and active environments; it aims to demonstrate the scientific evidence for the need for action to be taken to increase participation in active living and sport, leading to healthier cities and communities. Our research seeks to analyse the city’s natural spaces as scenarios to encourage physical activity and sport, through a combined study of qualitative research techniques: the use of a digital webGIS platform, collaborative maps made by citizens, and surveys conducted with citizens and the local government. This methodology has been tested in the city of Malaga, the European City of Sport 2020. The study of the city’s main sport areas, the waterfront and natural green spaces provided data on the types of physical activity taking place in each of these areas and the physical activity needs of citizens. This research argues that it is important to know the criteria of local communities for physical activity and/or sport in natural environments, as well as the main demands expressed. This will provide valuable information to design and manage natural public spaces as a means of promoting physical activity and healthy habits.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

Through Qualitative Comparative Analysis (QCA) on destination attractiveness characteristics at the country level, this study identifies attribute configurations in the pre- and post-pandemic period to analyze the changes and differences generated by an exogenous event (COVID-19). The results suggest that the destination attractiveness attributes work together, in multidimensional configurations, to increase leisure travel volume. We found an important change in pat-terns/configurations of attractiveness between the pre- and post-pandemic scenarios. Our findings suggest that the destination attributes may change in importance and valuation or disappear for some configurations. The conclusion has implications for the stakeholders related to the destination attractiveness development, showing possible patterns of tourism attributes to guide the action to improve the resilience in the tourism sector and recover these activities in a disaster scenario.

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.

2050 building stock might be buildings that already exist today. A large percentage of these buildings fail today’s energy performance standards. Highly inefficient buildings delay progress toward a zero-carbon-building goal (SDGs 7 and 13) and can lead to investments in renewable energy infrastructure. The study aims to investigate how bioclimatic design strategies enhance energy efficiency in selected orthopaedic hospitals in Nigeria. The study objective includes Identifying the bioclimatic design strategies that improve energy efficiency in orthopaedic hospitals, assessing the energy efficiency requirements in an orthopaedic hospital in Nigeria and analysing the effects of bioclimatic design strategies in enhancing energy efficiency in an orthopaedic hospital in Nigeria. The study engaged a mixed (qualitative and quantitative) research method. The investigators used case study research as a research design and a deductive approach as the research paradigm. The research employed a questionnaire survey for quantitative data while the in-depth Interview (IDI) guide and observation schedule for qualitative data. The findings present a relationship between bioclimatic design strategies and energy conservation practices in an orthopaedic hospital building. Therefore, implementing bioclimatic design strategies might enhance energy efficiency in hospital buildings. The result of the study revealed that bioclimatic hospital designs may cost the same amount to build but can save a great deal on energy costs. Despite the challenges, healthcare designers and owners are finding new ways to integrate bioclimatic design strategies into new healthcare construction to accelerate patient and planet healing.

Creative cities as a study discipline have garnered extensive attention and research in theory and practice as a practical approach to urban revitalization and sustainable development. This study conducted a systematic review of academic research on creative cities. Utilizing the visual analysis tools Citespace and VOSviewer, a comprehensive analysis was performed on 570 relevant articles from the Web of Science database. This study analyzed the most influential publications, authors, journals, institutions, and countries within the sample. The investigation spans various disciplinary domains, including geography, environment, culture, and others. Additionally, an exploration of the structure and characteristics of co-cited references was undertaken to enhance our understanding of the theoretical foundations of creative cities research further. Among these, the focal points of the study encompass urban development, urban policies, and the challenges faced. Finally, through co-occurrence analysis of keywords and examining the evolutionary process, the study forecasted that future trends will focus on the practical application of cities to enhance the urban image and improve urban governance from multi-dimensional perspectives such as creativity-related cultural places, public art, and so forth, exploring novel models of creative cities from case to universal. The results of this study can support scholars in grasping the development trends and exploring focal points.

Analysis of the factors influencing the price of carbon emissions trading in China and its time-varying characteristics is essential for the smooth operation of the carbon trading system. We analyse the time-varying effects of public concern, degree of carbon regulation, crude oil price, international carbon price and interest rate level on China’s carbon price through SV-TVP-VAR model. Among them, the quantification of public concern and the degree of carbon emission regulation is based on microblog text and government decisions. The results show that all the factors influencing carbon price are significantly time-varying, with the shocks of each factor on carbon price rising before 2019 and turning significantly thereafter. The short-term shock effect of each factor is more significant compared to the medium- and long-term, and the effect almost disappears at a lag of six months. Thanks to public environmental awareness, low-carbon awareness and the progress of carbon market management mechanisms, public concern has had the most significant impact on carbon price since 2019. With the promulgation of relevant management measures for the carbon market, relevant regulations on carbon emission accounting, financing constraints, and carbon emission quota allocation for emission-controlled enterprises have become increasingly mature, and carbon price signals are more sensitive to market information. The above findings provide substantial empirical evidence for all stakeholders in the market, who need to recognize that the impact of non-structural factors on the price of carbon varies over time. Government intervention also serves as a key aspect of carbon emission control and requires the introduction of relevant constraints and incentives. In particular, emission-controlling firms need to focus on the policy direction of the carbon market, and focus on the impact of Internet public opinion on business production while reducing carbon allowance demand and energy dependence.