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.

This study investigates the impact of tourism and institutional quality on environmental preservation, utilizing principal component analysis to generate three composite indices of environmental sustainability for 134 countries from 2002 to 2020. The results reveal that environmental sustainability indices have generally improved in lower- and middle-income nations but have declined in certain high-income countries. The findings also underscore the critical role of institutional quality—particularly regulatory standards, government effectiveness, anti-corruption efforts, and adherence to legal frameworks—in promoting environmental sustainability. However, the study shows that both domestic and international tourism expenditures can have adverse effects on environmental sustainability. Notably, these negative effects are exacerbated in countries with well-developed institutions, which is an unexpected outcome. This highlights the need for careful, thoughtful policymaking to ensure that the tourism sector supports sustainable development, rather than undermining environmental objectives.

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.

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.

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.