Jingdezhen is a world-renowned ceramics capital with a rich cultural heritage and economic potential. Through literature analysis and expert consultation, the evaluation index system of Jingdezhen’s cultural and economic influence was constructed from four dimensions, including employment absorption, cultural identity, cultural innovation and welfare improvement. The analytic hierarchy process was used to determine the weight of each index, and the fuzzy comprehensive evaluation method was used to obtain the comprehensive score of each index. The results show that the cultural and economic influence of Jingdezhen is generally good, and the industrial development and cultural resources are the main supports, and relevant suggestions are put forward according to the research results, aiming to provide reference significance for the development of Jingdezhen’s cultural economy.

With the advancement of technology and digital transformation, understanding and enhancing students’ emotional experiences are key concerns for educators and policymakers. In this study, 2 000 manually labeled review data were first used to train three machine learning models. The trained SVM model was then used to automatically label 76 000 review data. These labeled datasets were subsequently used to train a Convolutional Neural Network (CNN) model. The CNN model converged successfully after 10 iterations and achieved an accuracy of 94.96% on the validation set, significantly outperforming the SVM model. The results show that combining traditional machine learning with deep learning methods can effectively improve the accuracy of sentiment analysis. This provides data support for optimizing educational strategies.

Over the 40 years following the Reform and Opening-up, how does China manage to transform its major infrastructure from lagging behind to leading globally in such a short time? This question not only offers valuable practical insights but also poses a significant theoretical inquiry. By employing a comparative research approach, the implementation experiences of major infrastructure projects in China was systematically reviewed, developing theoretical insights in areas such as institutions, technology, management, finance and ideology. The feasibility of promoting these experiences internationally was also analyzed. The Beijing-Shanghai High-Speed Railway with overseas high-speed rail projects was further contrasted to illustrate the applicability and effectiveness of China’s infrastructure development experience. It is explored how to provide Chinese experiences and solutions to the global infrastructure market and offers references for Chinese enterprises, particularly those involved in Belt and Road infrastructure projects, as they enter the international market.

Based on the panel data samples of 30 provinces(due to the lack of data, the statistical data mentioned here do not include the Tibet Autonomous Region, the Hong Kong Special Administrative Region, the Macao Special Administrative Region and Taiwan Province) in China from 2012 to 2021,the three-stage DEA was used to measure S&T innovation efficiency,explored its spatial autocorrelation and the driving mechanism of S&T innovation efficiency. The results show that China’s S&T innovation efficiency is in an unbalanced and insufficient state, and on the whole, the S&T innovation efficiency in the eastern region is higher than that in the central region, which is higher than that in the western region. It is found that environmental factors and random noise have a significant impact and interference on the measurement of S&T innovation efficiency. From the perspective of spatial correlation, regions with high S&T innovation efficiency have not driven the overall situation of regions with low S&T innovation efficiency. Further analysis shows that the level of economic development, professional quality S&T personnel, innovation ability of scientific research institutions and technology export have a positive impact on S&T innovation efficiency. It is also found that expenditure, enterprise innovation ability and technology absorption have a negative impact on S&T innovation efficiency. Based on this, countermeasures and suggestions are proposed.

In order to clarify the influencing factors of airport service quality and the passengers’ satisfaction of airport service quality, and improve airport service quality, the evaluation model combining technique for order preference by similarity to an ideal solution(TOPSIS) and Bayesian network were used to establish an evaluation index system for large transportation airport service quality. The bidirectional inference diagnosis model was used to evaluate the airport service quality, including the forward inference of airport satisfaction and the backward sensitivity diagnosis of influencing indicators. The passenger airport service quality satisfaction and the influencing factors were studied deeply, and the feasibility of the method was verified by a large transportation airport as an example.The results show that the probability of passengers’ satisfaction with the service quality of the airport is 0.67, and the probability of general satisfaction is 0.21. The reverse diagnosis reveals that factors with high sensitivity include the baggage claim system, the convenience of integrated transportation and urban connection in and out of the airport, and the efficiency of security check services. A theoretical basis is provided for the airport to scientifically formulate measures to improve service quality.

The establishment of Science and Technology Innovation Hubs (STIHs) has become a critical element of the innovation-driven development strategy. Employing bibliometric methodologies, 380 relevant documents published in the field of STIHs research were analyzed between 2000 and 2023. The analysis included co-authorship networks, institutional affiliations, keyword co-occurrence, clustering and burst detection. The findings reveal that the majority of significant research on STIHs in China is published after the 18th National Congress of the Communist Party of China, indicating a strong policy orientation. The data also suggest a relatively weak collaboration among scholars and a fragmented landscape of cooperation and exchange between institutions, characterized by a pattern of widespread dispersion with localized clusters. The primary focus of the research has been on the conceptual foundations, formation mechanisms, developmental impacts and innovation ecosystems of STIHs. Future research should be guided by the emergence of new forms of productive capacity, deepen the understanding of the essence of STIHs, explore diverse models for different types and hierarchical levels of these centers, conduct in-depth analyses of their impact effects, and place greater emphasis on policy design for collaborative innovation within urban agglomerations as hosts for STIHs.

With the development of the deep integration of culture and tourism, “Hanfu fever”as a new business form has been widely concerned by the society and the industry. By collecting the postings of tourists on the two social media platforms of Weibo and Douyin on Luoyang Hanfu tourism, text analysis was adopted and ROST CM-6 software was used to conduct high-frequency words, semantic network and emotion analysis to explore tourists’perception of Luoyang Hanfu tourism image.The results show that the overall image perception of tourists to Luoyang Hanfu tourism is dominated by positive emotions, but there are still some negative emotions. Based on the theory of symbol interaction, concrete and feasible suggestions are put forward from the aspects of symbol interaction, consumption and cultural experience of Hanfu culture, so as to promote the in-depth development of the integration of Hanfu culture and tourism in Luoyang.

With the development of information technology and digitization, the scale and complexity of scientific data are increasing. How to reasonably manage and utilize scientific data has become an important issue faced by governments and scientific research institutions. Based on the policy diffusion theory, this study uses the policy document measurement method and policy network analysis method to conduct a quantitative analysis of 46 national and 197 provincial scientific data policies from 2005 to 2022 in six dimensions, including time, space, intensity, breadth, speed and direction, to explore the diffusion of China’s scientific data policies. Policy inspiration are put forward, such as optimizing the top-level design of policies and giving play to the role of national government administrative instructions; streamlining administration and delegating power to lower levels, and making our policies more targeted in areas and regions; expanding the mode of policy diffusion and strengthening the exchange of policy information among various parties.

Driven by digital economy, Guizhou rural sports tourism industry is ushering in a critical period of its digital transformation and upgrading. As the engine of the new era, the digital economy provides a powerful impetus for the digital transformation and upgrading of Guizhou rural sports tourism industry through cutting-edge technologies such as big data, cloud computing, Internet of Things and artificial intelligence. Research methods such as literature method, expert interview method and fieldwork method were used to demonstrate the background of digital economy driving digital transformation and upgrading of Guizhou rural sports tourism industry, the connotation of digital economy driving digital transformation and upgrading of Guizhou rural sports tourism industry were analyzed, the power mechanism of digital economy driving digital transformation and upgrading of Guizhou rural sports tourism industry were constructed. The strategy of digital economy driving digital transformation are put forward for upgrading of Guizhou rural sports tourism digital transformation and upgrading of the industry, aiming to provide theoretical references and countermeasure suggestions for the promotion of Guizhou rural sports tourism industry to achieve high-quality development.

Driven by the “double cycle” strategy, the expansion of the domestic demand market has become an important driving force for economic development. Currently, the consumer market is weak, and the consumption structure of rural residents is prominent, which needs to be studied and discussed urgently. Based on the statistical yearbook data from 2014 to 2023, the consumption structure of rural residents was analyzed in depth using the extended linear expenditure model (ELES model). The results show that there is a significant positive correlation between the expenditure of various consumption items and disposable income, which reveals the great potential of the rural consumer market. The analysis of marginal propensity to consume shows that with increased income, rural residents are more inclined to developmental consumption. At the same time, the income elasticity of demand shows that income is the key factor affecting rural consumption, and health care, transportation and communication, food, tobacco, alcohol and housing are the focus of consumption. Finally, a series of strategic suggestions are put forward to optimize the consumption structure, guide the improvement of the consumption structure of rural residents in China, promote the full release of rural consumption potential and inject new vitality into rural economic development.