This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.
The objective of this work was to analyze the effect of the use of ChatGPT in the teaching-learning process of scientific research in engineering. Artificial intelligence (AI) is a topic of great interest in higher education, as it combines hardware, software and programming languages to implement deep learning procedures. We focused on a specific course on scientific research in engineering, in which we measured the competencies, expressed in terms of the indicators, mastery, comprehension and synthesis capacity, in students who decided to use or not ChatGPT for the development and fulfillment of their activities. The data were processed through the statistical T-Student test and box-and-whisker plots were constructed. The results show that students’ reliance on ChatGPT limits their engagement in acquiring knowledge related to scientific research. This research presents evidence indicating that engineering science research students rely on ChatGPT to replace their academic work and consequently, they do not act dynamically in the teaching-learning process, assuming a static role.
The process of internationalization and innovation (IPI) in the urban road passenger transport (URPT) sector is driven by the need to provide cities with efficient and sustainable mobility solutions. The objective of this study is to understand the perceptions of URPT employees in relation to PII, based on a comprehensive case study. By exploring how these two concepts interrelate and influence each other, the study seeks to provide valuable information that can help improve strategic planning and policy formulation in the urban transport sector. The research, based on semi-structured interviews with 20 employees, reveals significant gaps in internal communication, with only about half of the participants aware of ongoing national and international projects. Information was often limited to those directly involved, indicating a need for improved dissemination strategies. Despite these communication issues, employees positively view the company’s presence at international events and recognize the importance of involvement in European organizations, particularly for knowledge acquisition and networking. Challenges identified include inadequate internal communication and insufficient investment in international projects. However, there was strong agreement on the value of internationalization and innovation process (IIP) for both professional development and organizational growth. To enhance the company’s international presence and return on investment (ROI), the study recommends better coordination, improved information sharing, and strategic planning. These findings emphasize the critical role of effective communication and active participation in international initiatives for the sustainable growth of the organization.
Tourism plays a crucial role in driving economic development, and there is a growing demand to integrate sustainability into the sector, particularly in the financial practices of governments. This study introduces the Quintessence Sustainable Tourism Public Finances (QSustainableTPF) model, which combines five established financial models commonly used in the tourism industry. The research aims to identify statistically significant relationships between these models and assess their impact on sustainability and financial performance in tourism. A quantitative methodology was employed, with data collected from financial reports and budget documents of both local and central governments, along with a survey of 2099 citizens and visitors conducted during the 2023–2024 period. Statistical analysis was performed using SPSS and AMOS, incorporating exploratory factor analysis (EFA), reliability testing using Cronbach’s alpha, and confirmatory factor analysis (CFA). The findings underscore the essential role of public finance in supporting tourism sustainability, particularly through transparent budgetary practices, efficient allocation of resources, and targeted investment in local tourism initiatives. The analysis reveals key insights into the benefits of financial transparency, citizen-centred budgeting, and the promotion of innovation in tourism finance. The interconnectedness of the five models highlights the importance of responsible public financial management in fostering tourism growth, enhancing investment, and ensuring long-term financial sustainability in the sector. The study offers practical implications for policymakers, advocating for the adoption of transparent and innovative financial practices to boost tourism development. It also recommends further research to broaden the scope across different regions, integrating additional public finance dimensions to strengthen sustainable tourism growth.
This study aimed to explore the indirect effects of appearance-related anxiety (ARA) on Instagram addiction (IA) through sequential mediators, namely social media activity intensity (SMAI) and Instagram feed dependency (IFD). The study also aimed to provide theoretical explanations for the observed relationships and contribute to the understanding of the complex interplay between appearance-related concerns, social media usage, and addictive behaviors in the context of IA. A sample of 306 participants was used for the analysis. The results of the sequential mediation analysis (SMA) revealed several important findings. Firstly, the mediation model demonstrated that SMAI mediated the relationship between ARA and IA. However, there was no direct relationship observed between ARA and SMAI. Secondly, the analysis showed that IFD acted as a second mediator in the relationship between ARA and IA. Both ARA and SMAI had significant direct effects on IA, indicating their individual contributions to addictive behaviors. Furthermore, the total effect model confirmed a positive relationship between ARA and IA. This finding suggests that ARA has a direct influence on the development of IA. The examination of indirect effects revealed that ARA indirectly influenced IA through the sequential mediators of SMAI, IFD, and ultimately IA itself. The completely standardized indirect effect of ARA on IA through these mediators was found to be significant. Overall, this study provides evidence for the indirect effects of ARA on IA and highlights the mediating roles of SMAI and IFD. These findings contribute to our understanding of the psychological mechanisms underlying the complex relationship between appearance-related concerns, social media usage, and the development of IA.
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