The sustainability of the creative industry through creative-based tourism in the Laweyan Tourism Village requires the support of a sustainable and inclusive development model for local communities. This research aims to present the design of a tourist village development model that applies the eco-cultural city concept as a Surakarta City Perspective through creative-based tourism towards creative industries. This research uses a qualitative approach with a descriptive exploratory method. Data collection techniques use interviews with key informants. Empirical observation using cultural mapping as identification of physical mapping of spatial layout, build ings and environment, as well as cultural landscapes for tangible and intangible cultural assets of the community in the local landscape in the Laweyan tourist village. Content analysis is applied as a research data analysis method. The research results provide an overview of the design of the creative-based tourism village development model towards a sustainable creative industry including aspects attraction, accessibility, amenities, and ancillary, and green tourism. Model design requires commitment and participation from the government and private sector in collaborating with sustainable tourist village development forums.

China is currently at a critical juncture in implementing the rural revitalization strategy, with urbanization and tourism development as crucial components. This study investigates 41 counties (cities) in the Wuling Mountain area of central China, constructing an evaluation system for the coordinated development of these two sectors. The coupling coordination degree is calculated using a combination weighting method and the coupling coordination degree model. Spatio-temporal evolution characteristics are analyzed through spatial autocorrelation, while the geographic detector explores the driving factors of spatial variation. The findings reveal a significant increase in coupling coordination between urbanization and tourism, transitioning towards a coordinated phase. Spatially, urbanization and tourism exhibit positive correlations, with high-value clusters in the southeast and northwest and low-value clusters in the south. The geographical detector identifies industrial factors as the most critical drivers of spatial variation. This study offers novel insights into the dynamics of urbanization and tourism, contributing to the broader literature by providing practical implications for regional planning and sustainable development. The results are relevant to the Wuling Mountain area and serve as a reference for similar regions globally. However, the study has certain limitations, such as regional specificity and data availability, which should be considered in the context of this research.

This study explores benefits, barriers and willingness to pay for bike-sharing service in tourism context. Based on a sample of 800 individuals who visited Da Nang, Vietnam between July and August 2023, trends in the barriers and benefits related to bike-sharing service from tourists’ point-of-view were explored. The results show that bike-sharing is appreciated for many reasons, notably for its fun/relaxing, cost saving, ease of city exploration, and promotion of better physical and mental health. However, bike-sharing services are considerably less likely to be viewed as options for faster transportation to a destination or reducing traffic hazards. Notably, eighty-six percent of non-riders indicated contentment with their existing transportation options and a lack of interest in bike-sharing services, a proportion significantly higher than any other group. Predictably, barriers related to the availability of bike-sharing and infrastructure, such as lack of sufficient number of shared bikes, far destination, and poor road conditions were notably more likely to be selected by one-time riders. The results are also evident that a significant portion of tourists is willing to pay to enhance their tourist experience with a bike-sharing service. On average, tourists were willing to pay $0.92 per hour (with a standard deviation of $0.24). This amount reflects the tourists’ recognition of the value added to their mode experience. These findings suggest that bike-sharing service play a significant role in fulfilling an essential transportation niche and have the potential to contribute to enhance tourists’ experience. Efforts aimed at addressing barriers associated with bike-sharing usage could further enhance their contribution to improve tourist satisfaction and boost attraction demand.

This study investigates how digital transformation influences visitor satisfaction at 12 World Heritage Sites (WHS) across eight coastal provinces in Eastern and Southern China. Utilizing 402 valid survey responses, it explores the impact of demographic factors—education, age, and income—on visitors’ perceptions of digital services, particularly focusing on usability, quality, and overall experience. The findings reveal that younger, higher-income, and STEM-educated visitors express significantly higher satisfaction with digital services, while older, lower-income visitors report lower levels of engagement and satisfaction. This research highlights the need for tailored digital strategies that cater to diverse demographic groups, ensuring the balance between technological innovation and the preservation of cultural authenticity at heritage sites. The originality of this study lies in its focus on non-Western contexts, particularly China’s rapidly developing coastal regions, which have been largely overlooked in the global discourse on digital tourism. By applying established theoretical frameworks—such as the Technology Acceptance Model (TAM) and Expectation-Confirmation Theory (ECT)—to a non-Western setting, this research fills a crucial gap in the literature. The insights provided offer actionable recommendations for heritage site managers to enhance visitor engagement, adapt digital services to demographic variations, and promote sustainable tourism development.

The article aims to evaluate the participation of below-poverty-line local community in tourism-related business activity in Himalayan state of Uttarakhand. Further, this article addressed for those who work in the tourism sector. The study employs a mix of methods, including survey data from 500 respondents with a random sampling approach, using Analysis of variance (ANOVA) statistical tools for analysis, other methods were interviews and observations at six tourism sites in Garhwal and four sites in Kumaun. Our findings showed that there has declined in community participation in tourism development, due to the lack of economic benefits obtained in the tourism sector, many believe that the tourism sector does not provide much income growth for them and does not make a significant contribution to the development of their region. Moreover, lack of understanding is considered the basis for community’s inability to play an active role, and lack of stakeholders’ involvement in encouraging them to improve their economy and culture through the tourism sector. Ultimately, this research also underlines the existence of some efforts by tourism travel to encourage public trust, which can help reduce poverty and increase community trust in tourism development in their region.

Introduction: With the adoption of the rural rehabilitation strategy in recent years, China’s rural tourist industry has entered a golden age of growth. Due to the lack of management and decision-support systems, many rural tourist attractions in China experience a “tourist overload” problem during minor holidays or Golden Week, an extended vacation of seven or more consecutive days in mainland China formed by transferring holidays during a specific holiday period. This poses a severe challenge to tourist attractions and relevant management departments. Objective: This study aims to summarize the elements influencing passenger flow by examining the features of rural tourist attractions outside China’s largest cities. Additionally, the study will investigate the variations in the flow of tourists. Method: Grey Model (1,1) is a first-order, single-variable differential equation model used for forecasting trends in data with exponential growth or decline, particularly when dealing with small and incomplete datasets. Four prediction algorithms—the conventional GM(1,1) model, residual time series GM(1,1) model, single-element input BP neural network model, and multi-element input BP network model—were used to anticipate and assess the passenger flow of scenic sites. Result: The multi-input BP neural network model and residual time series GM(1,1) model have significantly higher prediction accuracy than the conventional GM(1,1) model and unit-input BP neural network model. A multi-input BP neural network model and the residual time series GM(1,1) model were used in tandem to develop a short-term passenger flow warning model for rural tourism in China’s outskirts. Conclusion: This model can guide tourists to staggered trips and alleviate the problem of uneven allocation of tourism resources.