The conservation renewal of historic districts is currently not effective due to insufficient public participation. Therefore, this study takes Dongguan Street in Dalian as an example and constructs a spatial environmental evaluation model for the historical district based on user perception. The Analytic Hierarchy Analysis (AHP) was used to determine the indicator weights, and a satisfaction survey was combined with the quadrant chart model method to analyze the discrepancies between the expert weights and user satisfaction. The results show that the overall satisfaction of the district reached a score of 80.43, but the key indicators such as participation and cultural experience showed characteristics of high weighting and low satisfaction. Accordingly, strategies such as the implantation of experiential businesses and cultural revitalization were proposed, and their effectiveness was verified through return visits. This study aims to provide multi-dimensional decision-making support for the conservation and renewal of historic districts, and to enhance the universality and accuracy of historic district design.

The travel agency network is a spatial organization that connects tourist flow between cities and scenic spots. Taking Wuxi City as the research object, the kernel density and service network measurement model were used to quantitatively evaluate the spatial evolution of the travel agency service network in Wuxi in 2005, 2010, 2015, and 2020. The results reveal that the “centripetal” spatial distribution of travel agencies is still strengthening. Liangxi District has always been a hot spot for travel agencies, but the development of peripheral hot spots is also accelerating. The evolution of the trends in how travel agencies operate in the three major sectors differs markedly. The hotspot network of travel agencies in the urban and Jiangyin sectors has developed rapidly, but the hotspot network of travel agencies in the Yixing sector has begun to emerge, albeit relatively slowly. Moreover, the focus of Wuxi’s tourism service network is the connection between urban areas. Notably, the network connection between urban areas and Jiangyin continues to strengthen. The travel agency service network between Jiangyin and Yixing has not yet been established, and the integrated service network of regional tourism still needs to be strengthened. From the aspects of tourism service market construction, the results of this study can guide business support capacity improvement and travel agency service innovation, as well as corresponding countermeasures and recommendations for Wuxi travel agency service network development.

We apply a modified data envelopment analysis (DEA) model, spatial autocorrelation method, and geographic detector model to evaluate the resource conversion efficiency and its interaction mechanism in 81 red tourist attractions in Hunan Province in 2021. The results show that: (1) The overall conversion efficiency is 0.335, exhibiting high values in the east and low values in the west. (2) Next, both production and conversion efficiencies exhibit local spatial correlation, gradually decreasing from east to west. Accordingly, the efficiency types of Hunan province's red tourism resources can be divided into five types. (3) The strongest influencing factor was product innovation capability, followed by the quality of human capital, tourism market scale, policy support, traffic network conditions, and economic development level. Product innovation ability, human capital quality, and tourism market scale were three endogenous factors. Finally, we identified three interaction types of internal and external factors interaction type drove the spatial differentiation in conversion efficiency.

Studying residency satisfaction is essential for designing optimal social spaces in ethnic villages, with villagers as the primary focus. This study analyzed data from 941 villagers across 21 typical ethnic villages in the Xiangxi Region to identify key factors influencing their satisfaction with their living environment. Using eight machine learning techniques—Logistic Regression (OneVsOne), SVM, AdaBoost, Random Forest, XGBoost, CatBoost, LightGBM, and Stacking—we sequentially develop prediction models for three dimensions of socio-spatial satisfaction categorization (Material bears, Behavioral activities, Institutional beliefs) in multi-category villages (Agriculture-leading, Historical and cultural, Leisure tourism). These models are then combined with SHAP for global interpretation analysis. Among these techniques, the Stacking model proved to be the most effective in predicting villagers’ satisfaction with their living conditions. Additionally, the study revealed a strong correlation between residents’ contentment and the specific socio-spatial attributes of their homes. This study offers a theoretical framework for designing efficient social spaces in ethnic villages in western Hunan and similar regions.

Urban-rural integration is a significant driving force in promoting regional balance, optimizing the allocation of social resources, and achieving high-quality economic development. The study investigates the spatial-temporal evolution and influencing factors of urban-rural integration in Zhejiang from 2003 to 2022 based on four dimensions of “economy-society-space-ecology”. The research has found that: Firstly, the overall level of urban-rural integration in Zhejiang is on the rise with certain disparities. Secondly, the integration of urban and rural areas in Zhejiang exhibits a clear clustering phenomenon, presenting a spatial characteristic of “higher in the northeast and lower in the southwest”. Subsequently, per capita GDP, the advancement of the digital economy, the adjustment of industrial structure as well as the proportion of financial support dedicated to agriculture and urban-rural community affairs have played positive roles in promoting the process of urban-rural integration by influencing the flow of resources and factors between urban and rural areas. Accordingly, to further promote urban-rural integration, it is imperative to fully utilize leading cities to drive regional development, bolster the revitalization of mountainous regions and islands, accelerate the adjustment and upgrading of industrial structures, promote the growth of the digital economy, as well as refine the structure of government financial expenditures. This integrated approach will ultimately create a new paradigm of urban-rural integration.

In 2018, the Chinese government unveiled a comprehensive set of policies outlining the blueprint for rural revitalization, promoting the idea of “boosting rural revitalization through green development”. Using provincial panel data from 2011 to 2021, this study explores the impact of green development on rural revitalization, and the spatiotemporal and network evolution characteristics of this influence. Each region’s green development and rural revitalization levels are measured using the composite weighting method. Next, it explores the spatial characteristics of green development’s influence on rural revitalization by using spatial Durbin model. It further explores the heterogeneity of the spatial spillover effect of green development on rural revitalization using a two-regime spatial Durbin model. Lastly, it combines the complex network correlation method to identify important provinces.

Unbalanced regional development remains a major obstacle to sustainable development. In recent years, China has experienced slower GDP growth, shifting population trends, rural revitalization, and nationwide poverty reduction. It is unclear if China’s core pattern of uneven regional development has changed as a result. This study analyzes county-level data from 2010 to 2020 using five regional categories: poverty-stricken vs. non-poverty- stricken counties, urban-dominant vs. rural-dominant areas, population growth vs. population decline, GDP growth vs. decline, and Eastern, Central, Western, and Northeast China regions. Using the Sustainable Development Index and Theil Index, we calculated 21 county-level sustainability indicators to measure regional gaps across economy, environment, and social services. Results show that as of 2020, the overall sustainable development in China steadily improved. While the disparity between poverty- and non-poverty-stricken counties has largely narrowed, disparities between urban-rural-dominant areas and between Eastern and Western China remain the main challenges. Differences linked to population or GDP changes were not significant. However, many Northeast China regions pose sustainability concerns due to simultaneous population and GDP decline.

Under small-scale farming operations, cultivated land protection behaviors (CLPBs) are a feasible path to achieve food security, ecological security, and sustainable agricultural development in China. However, farmers may face operational difficulties because of their lack of motivation or “freeriding” behavior. This study uses survey data from 265 micro farmers in Xingning City, Guangdong Province, to examine the theoretical framework of the impact of social capital and policy cognition on CLPBs. This study uses a partial least squares model to explore the path relationship between the three factors and verify the intermediary mechanism. Results show that (1) social networks, social norms, and social trust have a significant direct impact on CLPBs, with social trust as the leading factor, followed by social norms; (2) different types of social capital will have varying influence on the CLPBs of the farmers; and (3) the influence path of social capital on CLPBs is through the indirect positive influence of policy cognition. Moreover, social networks are the social capital most affected by policy cognition. Therefore, the promotion of the CLPBs of farmers should start from two aspects, that is, the increase of farmers’ social capital and the enhancement of their policy cognition, to improve the pertinence of cultivated land protection policy formulation.

Cropland plays a crucial role in agricultural production, significantly impacting crop yield, quality, and the sustainable development of agricultural ecosystems. This study establishes an evaluation index system to assess cropland quality using panel data from 30 Chinese provinces. The research employs the entropy method to quantify cropland quality, the Dagum Gini coefficient to investigate the sources of disparities in cropland quality and the development quality of its subsystems, and various analytical techniques including Kernel density estimation, Markov chains, and spatial convergence to examine the distribution dynamics and evolutionary trends of cropland quality. The findings reveal a consistent upward trend in overall cropland quality in China over the years, with a relatively low Gini coefficient, indicating minor quality fluctuations. Notably, the inter-regional Gini coefficient is highest between China’s eastern and western regions and lowest between the western and northeastern regions. Moreover, the Gini coefficients show an increasing trend among the eastern-central, eastern-western, eastern- northeastern, and central-western regions. Regarding distribution dynamics, the absolute disparities in cropland quality among the eastern, central, and northeastern regions are decreasing but widening in the western region, suggesting a polarization effect among the four major regions, albeit with a tendency towards reduction. The findings from the Markov chain analysis indicate that cropland quality in China tends to be stable, making leapfrog development challenging. From a spatial convergence perspective, the σ coefficient is relatively high for the entire country; however, the western region exhibits a lower σ coefficient. The consistently significant negative β value indicates the presence of absolute β convergence, conditional β convergence, spatial absolute β convergence, and spatial conditional β convergence in the cropland quality index across China and its two major regions, with variations in convergence rates and cycles observed at both national and regional levels.

Landscape pattern is considered a powerful concept for identifying environmental changes, whereas landscape ecological risk serves as a negative indicator of urban ecosystem health. However, few studies have systematically explored the relationship between the two aspects. This study utilizes Nanjing as a case study, analyzing the spatiotemporal changes in landscape patterns and LER from 2012 to 2022, and geographically and temporally weighted regression is employed to investigate the impact of landscape pattern on the spatial changes of LER. The results indicate the following: (1) From 2012 to 2022, the study area was primarily composed of cultivated land, followed by forest land and construction land, a distribution closely constrained by topographic conditions. (2) Most landscape pattern indices reached extreme values in the first gradient zone of the city center and the third gradient zone on the edge of the main urban area, while fluctuating across several urban subcenters. (3) The overall pattern of LER presented a clear center-periphery polarization structure, with high-risk areas distributed in the southwestern zone and along the Yangtze River. Over time, the area gradually expanded and transitioned from a scattered to a clustered spatial pattern. Low and sub-low risk areas were concentrated in the city center and urban subcenters, exhibiting a continuous decline in areal extent. (4) A significant negative correlation was observed between landscape pattern indices and LER, indicating that enhanced landscape diversity and richness can partially mitigate ecological risk. (5) Regarding degradation from unregulated development, Nanjing can proactively reduce LER by refining local landscape configurations. This entails linking fragmented ecological patches in the northern and southern prime farmland belts, or softening the edges of high-intensity built-up areas to ease impacts on peripheral biodiversity.

This study takes the ecological resilience of coal cities as the research theme, constructs an index system including 41 constraint factors from the three dimensions of social economy, resources and the environment, and takes Xuzhou as a typical case study with data from 2002 to 2023 as the original data. The GM-Markov time series prediction model and ARIMA model are used to fit the developmental prospect of ecological resilience in 2024-2040, with the aim of accurately predicting the future development trend. The results show that Xuzhou will reach the “ideal state” of ecological resilience in 2031 at the earliest and 2032 at the latest. In that state, the case city can better coordinate the contradictory relationship between the “limitation” and “need” of ecological resilience, and realize positive development of the socio-economic, resource and environmental subsystems. Then, the understanding of this research topic is deepened and the following coping strategies are proposed based on the research results: improve the collaborative digital governance co-construction model and lay a solid foundation for ecological resilience, optimize the collaborative digital co-governance mechanism to enhance the efficiency of ecological governance, adhere to the fundamental spirit of shared development and release the dividends of ecological governance.

Earthquakes can alter the structure of ecosystems rapidly. This study aimed to assess the impact of earthquakes on plateau ecosystems using the 2021 Maduo 7.4-magnitude earthquake as a case study. A plateau ecosystem assessment index (PEAI) was proposed based on the 3S-Integrated Valuation of Ecosystem Services and Trade-offs model (3S-InVEST) and the analytic hierarchy process (AHP). It was constructed using information on land cover, vegetation coverage, landscape pattern, habitat quality, and ecosystem service value to comprehensively evaluate the impact on plateau ecosystems. The findings revealed that: (1) After the earthquake, the overall PEAI decreased from 5.47 to 5.09, which was a decline of 6.94%. The value of ecosystem services decreased by RMB 5.5814 billion, and the degree of impact displayed a spatial gradient pattern that diminished with seismic intensity. (2) The area with intensity level X was the most affected and that with intensity level VII was the least affected, with a decline of 40.76% and 1.64% in PEAI, respectively. The spatial heterogeneity analysis revealed that land cover changes were the most drastic in Ngoring Lake, Gyaring Lake, and the river area in the north of the VII seismic intensity zone. (3) A big change in land cover was witnessed after the earthquake, whose direction was from lake wetland to sandy land, marshy wetland, and grassland, and from riverine wetland to marshy wetland and grassland. Among the various types of wetlands, marshy wetlands experienced the most significant decrease, followed by lake wetlands and riverine wetlands, with a reduction of 286.28 km², 61.66 km², and 30.82 km², respectively. (4) The vegetation coverage showed structural degradation, with medium- and high-coverage areas decreasing by 6.03% and 3.16%, respectively. However, the ecosystem service value of grasslands increased against the trend, revealing their ecological resilience. The study identified land cover change, degradation of ecosystem service value, and vegetation decline as the core driving factors behind a decrease in PEAI. This assessment system provides a quantitative basis for prioritizing post-earthquake ecological restoration efforts on the plateau.

This study examines the optimization of land use patterns to address the dual challenges of urban expansion and ecological conservation, while promoting agricultural sustainability within the context of enhanced environmental protection and sustainable socio-economic development. Utilizing the PLUS model, which incorporates strategic planning principles and industrial policy requirements, we developed a targeted planning scenario to project land use in the Ningxia Hui Autonomous Region for the year 2030. This research aims to establish a balance between socio-economic growth and ecological conservation. The findings demonstrate that: (1) The model employed is both effective and reliable; (2) Under the targeted planning scenario, as opposed to a natural evolution scenario, there is a notable expansion in the areas dedicated to croplands, woodlands, and scrublands, while building lands are developed responsibly with a controlled expansion rate of 1.3, thus moderating development intensity; (3) The planning approach significantly enhances the value of ecosystem services compared to natural trajectories, thereby improving service capacities; (4) The ecosystem service values associated with land use under the 2030 scenario exhibit significant spatial concentration, with distinct zones of high and low concentration providing valuable spatial insights for future land use optimization and regulatory adjustments.

This study focuses on Siguniang Town, a mountain tourism destination, to explore the subjective well-being (SWB) of non-standard workers and its influencing mechanisms with the aim of promoting sustainable destination management. Employing Grounded Theory, the research identifies the key factors affecting the SWB of non-standard workers, which are categorized into two dimensions namely life satisfaction and value identification and highlights that health perception is a critical determinant of SWB. Further analysis using fuzzy-set Qualitative Comparative Analysis (fsQCA) reveals that the well-being of non-standard workers is shaped by both internal factors such as self-actualization and external factors including occupational characteristics, religious beliefs and social structures based on kinship and locality. The results indicate that even without professional enthusiasm or social recognition, a sense of self-fulfillment remains essential to their well-being, emphasizing the need for a more comprehensive understanding of the complex interactions among these factors and their collective role in shaping the well-being of non-standard workers in mountain tourism destinations. This research contributes to the theoretical framework for the sustainable management of non-standard employment in tourism and provides empirical insights for promoting long-term regional development in destinations such as Siguniang Town.

Tourism often burdens destination environments, making the promotion of “green consumption”—that is, environmentally responsible consumer behavior—crucial for sustainable tourism. Travel photography, an emerging tourism service wherein visitors don local traditional attire for professional photo shoots, prioritizes experiential value over material consumption and consumes relatively few direct resources. This study investigates whether and how travel photography serves as a pathway to green consumption at tourism destinations. Using a mixed-methods approach, including a survey of 203 travel photography participants and 14 in-depth interviews with producers in Shangri-La, Yunnan, China, we aim to identify the mechanisms through which travel photography encourages green consumption and the factors influencing this process. The results show that travel photography satisfies tourists’ desire for immersive cultural experiences while reducing reliance on resource-intensive activities. Thus, strong policy support is needed for sustainable emerging tourism sector development.

Ecotourism in national parks represents an important pathway for synergistically advancing ecological conservation and sustainable development. Based on a review of domestic practices in national park ecotourism development and focusing on core attractions, this paper systematically proposes four representative development models: the “Forest Wellness+” model, the “Flagship Species-Centered” model, the “Eco-Cultural Tourism” model, and the “Nature Quest” model. This study examines case studies from national parks such as Tangwanghe, Giant Panda, Zoige, and the Yellow River Estuary, and the core characteristics and limitations of each model. The main findings are as follows: (1) All four models are grounded in high-quality ecological resources and generate economic benefits for local communities through tourism activities, thereby achieving multiple objectives, including ecological conservation, tourism development, and community revitalization. (2) The models differ significantly in terms of target visitor groups, resource dependence, and seasonal adaptability, and each faces distinct challenges, such as market homogenization, human-wildlife conflict, insufficient cultural interpretation, and climatic constraints. (3) To promote model optimization and long-term sustainability, it is essential to adapt and innovate development models according to local conditions, enhance technology-enabled smart management, and transcend administrative boundaries to establish regional collaborative networks. This study provides an in-depth exploration of the underlying operational logic of ecotourism models in China’s national parks. It offers precise, replicable development paradigms for different park types, thereby contributing to the standardization and sustainability of ecotourism within China’s national park system.

Volunteer activities based on national parks represent a crucial pathway for public participation in the construction of ecological civilization, as well as an important means for national parks to achieve public welfare goals. Hainan National Park science popularization and education volunteers were invited to participate in a questionnaire survey, yielding 437 valid responses. PLS-SEM was employed to test the conceptual model of “learning outcomes-meaningfulness/environmental passion-daily pro-environmental behavior”. The findings indicate that learning outcomes (knowledge accumulation, skill cultivation, changes in environmental attitude, and self-reflection) positively influence both meaningfulness and environmental passion; meaningfulness positively influences environmental passion; and both meaningfulness and environmental passion positively affect daily pro-environmental behavior. Specifically, meaningfulness mediates the relationships between knowledge accumulation, changes in environmental attitude, self-reflection, and daily pro-environmental behavior, while environmental passion mediates the relationships between knowledge accumulation, skill cultivation, changes in environmental attitude, self-reflection, and daily pro-environmental behavior. This study clarifies the connotations and dimensions of learning outcomes from national park science popularization and education volunteer activities and enriches research on the mechanisms promoting pro-environmental behavior. Moreover, it provides valuable practical implications for national parks.

Guided by the “means-ends” chain and grounded theories, this study first constructed a perceived value system for tourists in ice and snow tourism destinations, including 18 main and 39 corresponding categories at three levels—attributes, consequences, and values—and used a social network analysis to generate a clear network system map for the perceived value of tourists. Second, this map deconstructs the relationships among the attributes, consequences, and values in tourists’ perceived value systems. Analyzing the eight most dominant perceived value chains reveals that happiness, sense of accomplishment, and sense of belonging are the most critical perceived values of ice and snow tourists. Further, the related consequences of enriching experiences, restoration, and emotional reactions as well as the attributes of tourism resources, infrastructure, and tourism activities are important factors that trigger tourists’ key perceived values. This study presents the perceived value of tourists in ice and snow tourism destinations, provides a new method and perspective for studying their perceived value, and analyzes the effectiveness of improving the supply of ice and snow tourism destinations based on this perceived value.

With the increasing popularity of ski tourism, issues related to tourism service quality have become prominent. As the core venue for ski tourism, it is particularly important to establish a standardized service quality evaluation index system for ski resorts. As consumers, experiencers, and participants in tourism activities, tourists play a crucial role in the establishment of the service quality evaluation index system. This study evaluated the service quality of ski resorts from the perspective of ski tourists, focusing on six ski resorts (Zhangjiakou Taiwu Ski Resort, Jilin Songhua Lake Ski Resort, Altay Jiangjunshan Ski Resort, Harbin Yabuli Ski Resort, Guangzhou Sunac Snow Park, and Beijing Nanshan Ski Resort). Grounded theory was used to analyze online texts from the Ctrip website and interview data of tourists. The service quality evaluation system for ski resorts in China primarily included 4 main dimensions (Site Quality, Supporting Facilities, Operations Management, and Staff Service) and 18 specific indicators. These dimensions were interrelated and jointly determined tourists’ ski tourism experience and satisfaction.

Investigating the behavioral characteristics and influencing factors of ski resort tourists’ decision-making in southern China holds significant practical value for the development of winter sports tourism markets in the region. Grounded in push-pull theory, this study employs an integrated methodological approach that combines text analysis, genetic algorithm-based fuzzy comprehensive evaluation, and fuzzy-set qualitative comparative analysis (fsQCA) to examine the determinants and patterns underlying ski tourism decisions in resorts across southern China.The findings reveal that the pursuit of novel experiences, enriching life experiences, promotional recommendations, cost-effectiveness, facilities and services, and travel constraints constitute the six core factors influencing decision-making among ski tourists in southern China. Genetic algorithm-based fuzzy comprehensive evaluation demonstrates that “enriching life experiences” and “the pursuit of novel experiences” have the highest weight coefficients, indicating that tourists predominantly focus on the value-added life experiences and novelty derived from skiing activities. Through configuration analysis, six condition combinations were identified and categorized into three typical decision-making patterns: experience-driven, promotion-guided and price-sensitive, and trade-off decision-making. These findings provide practical insights for improving marketing management and service optimization in ski resorts across southern China while also contributing to the expansion of tourist behavior decision-making research.

Ski tourism has become a hotspot in the tourism industry due to its high revisit rate. Accurate assessment of its experience quality is crucial for enhancing tourists’ revisit intentions and promoting the high-quality development of the ski industry. Based on the expectation-disconfirmation theory, this study comprehensively applies the LDA model, Text-CNN model, and Importance-Performance Analysis (IPA) to examine 103503 online reviews from 55 ski resorts across nearly 10 ski seasons (2015/2016-2024/2025) in China. It constructs evaluation indicators for ski tourism experience quality and conducts an evaluation and comparison of the experience quality in the four major ski tourism areas: Northeast, North, Northwest, and East of China. The results indicate: (1) 16 influencing factors on ski tourism experience quality were identified, including the newly recognized factors of Ski Instructor Quality and Peer Interaction; (2) In terms of the evolutionary characteristics of experience quality, Established ski regions (Northeast and Northwest) show slow experience improvements, while emerging regions (North and East China) exhibit rapid progress; (3) Overall, North China leads in experience quality, followed by Northeast, Northwest, and East of China; (4) In comparing influencing factors, Natural Scenery, Emotional Perception, and Peer Interaction are common advantages across the four ski tourism areas, while Price Perception is a shared disadvantage. This study systematically evaluated the spatiotemporal heterogeneity of experience quality in major ski tourism areas of China, providing theoretical basis and practical insights for precise improvement of tourism experiences in various regions.

Traditional culture is a crucial pillar for the sustainable development of the tourism industry. This study aims to uncover the intrinsic value of traditional ice and snow cultural elements and examine their role in empowering the sustainable development of ice and snow sports tourism, thereby supporting the goal of building a leading ice and snow sports nation. By applying documentary research and logical analysis, this study systematically elucidates the connotative characteristics through which traditional ice and snow cultural elements contribute to sustainable tourism development, identifies key practical challenges constraining this sector, and proposes targeted and actionable development pathways. The findings indicate that traditional ice and snow cultural elements have evolved primarily through two historical stages—ancient and modern—characterized by continuity, regional specificity, and cultural richness. These elements empower ice and snow sports tourism by providing diverse cultural resources and a sustained historical narrative. However, current development faces several challenges, including superficial cultural exploration, homogenized development models, low participation in traditional cultural activities, and the distortion or alienation of cultural elements in some tourism projects. Accordingly, this study proposes four development pathways: (1) Constructing a deep cultural narrative system to transform tourist experiences from “landscape presentation” to “cultural immersion”; (2) Promoting the creative transformation of traditional techniques and activities to build a distinctive cultural IP product system; (3) Strengthening regional cultural identifiers by implementing a differentiated “one region, one product” strategy that integrates culture, sports, and tourism; and (4) systematically organizing and revitalizing the history of modern Sino-Western exchange in ice and snow culture to enhance cultural depth and international dialogue capabilities. Collectively, these measures aim to promote the substantive, high-quality, and sustainable development of ice and snow sports tourism.

This study examines the ice and snow intangible cultural heritage resources in Northeast China as the research object. From the perspective of activation and utilization entities (primarily cultural and tourism integrated development and operation enterprises, hereinafter referred to as development and operation enterprises), it analyzes the typological characteristics and spatial distribution patterns of these resources. Using “ice and snow intangible cultural heritage tourism” as the keyword, mainstream media news reports were collected, and text analysis methods were applied for data processing. Through manual close reading and analysis of the sample news reports, development models such as festival exhibitions, folk art performances, and skill-based experiences were summarized. The Grounded Theory research method was used to code the raw news reports under each model, thereby extracting the implementation paths of the festival exhibition, folk art performance, and skill experience modes.

The successful 2022 Winter Olympics in Beijing and the th Asian Winter Games in Harbin in 2025 have accelerated the growth of ski tourism in China. However, this rapid expansion has also led to a trend of homogenisation among ski tourism destinations. As a result, identifying unique attributes and establishing differentiated positioning have become critical challenges for these destinations. Prior literature shows that the destination image and features play important roles in market positioning. However, due to the new changes in the tourism market, the effectiveness of destination positioning has been adversely affected by the lack of identifying market segments and matching differentiated strategies. This study examines four ski tourism destinations in the Chengdu region of Sichuan Province, China, using destination positioning and value co-creation theory. First, the unique attributes of the destinations are identified using the word frequency-inverse document frequency (TF-IDF) and correspondence analysis (Study 1). Second, the ski tourism market is segmented based on tourists’ demand through factor analysis, cluster analysis, and other methods(Study 2). Third, the study matches demand-side preferences (tourists) with the supply-side advantages of the destinations to develop differentiated strategies. The findings demonstrate that differentiated competitive positioning is appropriate and effective, offering practical marketing strategies to help ski tourism destinations overcome the homogenisation dilemma and enhance their appeal and competitiveness. In addition, the study introduces a new theoretical analysis framework for destination positioning, contributing to the further improvement of the marketing system.

Intensifying global climate change and the upgrading of China’s ice and snow industry in the post-Winter Olympics period place new demands on the spatial allocation of tourism resources. The Beijing-Tianjin-Hebei region functions as a national strategic demonstration zone for coordinated regional development. Optimization of the spatiotemporal distribution of ice and snow tourism resources in this region remains a key research issue. This study applies ArcGIS spatial analysis to examine the spatiotemporal evolution and influencing factors of multiple types of ice and snow tourism resources in the Beijing-Tianjin-Hebei region over four observation periods (2010, 2015, 2020, and 2025). Recent development trends are identified using the latest available statistical data. The results show that the number of ice and snow tourism resources follows a phased growth pattern characterized by “initial emergence, steady growth, and rapid expansion”. The Winter Olympics bidding and hosting stages function as key driving nodes. In spatial terms, the distribution pattern evolves from a relatively dispersed macro-scale structure to distinct local hotspot clusters centered on Chongli in Zhangjiakou and Yanqing in Beijing. The spatial pattern shows “northwest concentration and southeast dispersion”, with the centroid gradually shifting northwestward and forming contiguous clusters. Analysis of influencing factors indicates that policy orientation acts as the central driving force. Winter Olympics-related planning and regional coordination policies strongly promote resource agglomeration. Natural conditions provide the basic environmental foundation, while improvements in transportation accessibility strengthen regional connectivity. Socioeconomic development and market demand shape the intensity and scope of resource development. These findings provide a scientific basis for coordinated development and sustainable spatial planning of ice and snow tourism in the Beijing-Tianjin-Hebei region.

Promoting the high-quality growth of ice and snow tourism in China requires understanding the patterns of industrial development and anticipating the emerging trends. The developmental history and features of China’s ice and snow tourism are systematically examined in this paper, which also refines the evolutionary patterns of the industry’s growth and looks at the emerging trends. The conclusions are threefold. (1) This paper divides the developmental history of China’s ice and snow tourism into the budding exploration phase, the initial growth phase, the rapid development phase, the Winter Olympics driving phase, and the high-quality development phase. During the budding exploration phase, the initial market foundation for ice and snow tourism was established. In the initial growth phase, the ice and snow tourism industry began to take shape. The rapid development phase was characterized by ice and snow sports tourism. The foundation of the ice and snow tourist industry was established during the Winter Olympics driving phase. The high-quality development phase is now being guided by the principles of ecological civilization and the sports power strategy and the tourism powerhouse strategy. (2) The spatial layout of ice and snow tourism has changed from a localized and dispersed distribution to one of comprehensive development mainly centered in the Northeast, North China and Northwest represented by Xinjiang province. The evolution of ice and snow tourism technology presents localized, diversified, and high-end characteristics. The evolution of the industry presents vertical extension of the industrial chain, horizontally integrated development, and the comprehensive development of resorts. The evolution of the ice and snow tourism market has been characterized by the diversity of tourist demands, a northward flow of tourists from southern regions, and standardization of quality inspection. (3) There are four emerging trends in the development of China’ ice and snow tourism, including new productivity to propel the intelligent, sustainable, and localized transformation of winter sports equipment and venues; climate change to accelerate the evolution of regional ice-snow tourism landscapes; innovations in digital technology to change ice-snow tourism consumption scenarios; and innovations in consumption patterns to reshape supply-side development.

Forest ecosystem enhances environmental resilience by maintaining ecosystem stability and supporting natural processes. In Nepal, the rising temperature has exerted immense pressure on people’s livelihoods and ecosystems. In a forest, soil characteristics and tree diversity are the key components that enhance its resilience in response to various disturbances such as drought, fire, erosion, and landslides. However, the role of forest management in improving soil quality, fostering tree diversity, and building resilience is less investigated in Nepal. The present study aims to assess the role of forest management in soil quality, tree diversity, and building resilience. For this purpose, the soil quality was determined and soil quality rating (SQR) was computed across three management zones of the Panchase protected forest, using a semi-quantitative equation model. The observed tree richness was obtained from transect walk and tree counts around soil sample points. The community resilience adjoining the forest was assessed through participatory approach employing a scoring method. The results showed that SQR was higher in the Protected Zone (0.82) followed by the Intensive Management Zone (0.77) and the Impact Zone (0.69). The highly significant differences in SQR among the three management zones (P<0.001) and the highly significant difference in mean SQR between the Protected Zone and the Impact Zone (P<0.001) highlighted the role of forest management in fostering soil quality. The Protected Zone exhibited higher tree richness compared to the Intensive Management and the Impact Zones, suggesting the need for soil quality enhancement through management measures that also promote tree diversity. Furthermore, the community residing near the forest, which encompasses larger forest area demonstrated higher resilience score of 3.94 than the community residing relatively far, scoring 3.53. This suggests the contribution of forest ecosystem in building community resilience and recommends to strengthen agricultural diversity, agriculture innovation, and biodiversity-based livelihoods in community with low resilience score.

Climate variability is considered one of the major challenges facing agricultural productivity in ecologically fragile mountain regions such as the Garhwal Himalaya. A study on this topic examines whether temperature and rainfall are Granger-causing each other, considering crop yields; it applies a Granger Causality Test and ARIMA- based time series modelling. A time series dataset of climate, from 1951 to 2023, including maximum temperature (T-max), minimum temperature (T-min), and rainfall, was collected to determine casual relationships and further predict future trends. In addition, the results indicate that T-max has a significant influence on the pattern of rainfall; hence, temperature changes cause a change in precipitation, whereas the latter is not found to be causally related to the former. Lastly, T-max and T-min were strongly interdependent, meaning that the fluctuation in temperature played a central role in influencing agricultural outcomes. The ARIMA model reveals a minor cooling trend in T-max from 2024 to 2030; thus, this might benefit heat-sensitive crops like wheat and potatoes but possibly be a concern for warm temperature crops like rice and mango. Such outcomes, therefore, demand the significance of climate-responsive agricultural planning, especially in rain-fed farming systems that are vulnerable to irregularity in precipitation. With the implementation of predictive climate models and adaptive farming strategies, policymakers and farmers can develop more resilient agricultural systems. The study, therefore, calls for enhanced water resource management, climate-smart crop selection, and policy intervention to mitigate climate risks in the Garhwal Himalaya. Future research studies should include extra climatic and agronomic variables by using high-level machine learning models to better enhance the forecast accuracy and resilience of agriculture with ongoing climate change.

The rapid development of the rural digital economy has emerged as a global phenomenon affecting both developed and developing countries, and China is no exception. Based on field survey data from 432 citrus family farms in Jiangxi Province in 2023, the mediating effect test and heterogeneity analysis are employed in this study to assess the impact of digital applications (DA) on family farm income (FFI). The results show that DA significantly increases FFI, with its enabling effect spanning the entire production chain from pre-production information acquisition to mid-production management and post-production marketing. Mechanism analysis indicates that DA enhances economic returns through three synergistic pathways: improving policy resource acquisition efficiency, promoting resource-efficient technology adoption, and expanding market sales channels. Heterogeneity analysis further shows that the income-enhancing effect of DA is more pronounced among farms with smaller scales, lower incomes, weaker social capital, and poorer infrastructure. These findings reflect inclusive “catch-up” and “substitution” effects, rather than the emergence of a digital divide. This study enriches the theoretical framework of digital agricultural empowerment and provides policy-relevant evidence for the formulation of targeted digital agriculture policies.

Investigating the impact of rural digitalization on agricultural carbon emissions contributes to achieving carbon neutrality goals and facilitates the green transformation of agriculture with enhanced efficiency. Based on panel data from 31 provincial-level regions in China spanning 2005 to 2022, this study employs a dynamic panel model to analyze the influence of rural digitalization on agricultural carbon emission intensity. Heterogeneity analysis, mechanism testing, and spatial effect examination are also conducted. The main findings are fourfold. (1) Rural digitalization effectively promotes the reduction of agricultural carbon emissions. (2) Heterogeneity analysis revealed that the effect of rural digitalization on lowering agricultural carbon emission intensity is particularly significant in production-marketing balanced regions. (3) The carbon emission reduction effect of rural digitalization is primarily realized through the scaling of agricultural operations, the accumulation of human capital, and the improvement of total factor productivity. (4) A positive spatial correlation exists in the agricultural carbon emission intensity across provinces, and the inhibitory effect of rural digitalization on agricultural carbon emission intensity exhibits spatial spillover effects. Therefore, to accelerate rural digitalization and advance agricultural carbon emission reduction, it will be essential to promote the scaling of agricultural operations, guide farmers in adopting advanced technologies, and enhance their ability to utilize digital tools.