In order to evaluate the development status of cities and their impact on economic growth, combined with the five new development concepts of innovation, coordination, green, openness and sharing, the evaluation index system of urban high-quality development was constructed, the indicators were screened by OLS least squares method, the impact of high-quality urban development on economic growth and the prediction effect the explored by deep learning method, and the prediction results and accuracy of the multivariate LSTM neural network model and the improved multivariate LSTM neural network model were compared. The results show that the multivariate LSTM neural network model with attention mechanism has better prediction effect, the root mean square error RMSE of the model is reduced by 25%, and the coefficient of determination R² reaches 0.9856.

Since its inception, new quality productive forces have garnered extensive attention from both theoretical and practical circles. To objectively grasp and deeply understand the research progress and evolution trends of new quality productive forces, the China National Knowledge Infrastructure(CNKI) database and the CiteSpace software were used to analyze 950 articles published in CSSCI, CSCD, and Peking University Core Chinese Journals. By sorting out the research progress and hotspots, and mapping a knowledge graph, the results reveal that since September 2023, the number of publications in the field of new quality productive forces has grown rapidly, and several influential scholars and research institutions have emerged. However, most scholars lack stable cooperation relationships, showing an overall pattern of “local agglomeration and overall dispersion”. The cooperation among research institutions is not tight, with noticeable regional cooperation but limited cross-disciplinary cooperation. In terms of research hotspots, technological innovation and digital economy have become the focus of scholars’ attention. The integration of new quality productive forces with technological innovation, new quality productive forces and emerging industries, as well as the empowerment of new quality productive forces, have emerged as new research trends. In the future, it needs to build upon current research achievements and continue to deepen the study of new quality productive forces from three aspects, such as strengthening the theoretical and rational explanation of new quality productive forces, expanding the research dimensions of new quality productive forces, and extending the research methods of new quality productive forces.

The core factors influencing production levels in manufacturing enterprises under the empowerment of the Industrial Internet and their mechanisms of action was investigated. Using grounded theory and the Analytic Hierarchy Process(AHP), key factors were systematically identified that enhance production levels in manufacturing enterprises empowered by the Industrial Internet. Supported by grounded theory, in-depth interviews and open coding were conducted to initially extract the main influencing factors. Subsequently, AHP was applied to perform a weight analysis on these factors, filtering out the most impactful ones. Finally, using a real case study, the mechanism was summarized by which the Industrial Internet empowers the enhancement of production levels in manufacturing enterprises. The results indicate that factors such as operational proficiency, equipment fault warning capability, and data cleansing efficiency significantly promote production levels in manufacturing enterprises under the empowerment of the Industrial Internet. These factors synergistically construct a systematic improvement mechanism. Based on the analysis results, targeted recommendations are provided, offering practical guidance for manufacturing enterprises to more effectively leverage Industrial Internet platforms to improve production levels.

In order to make enterprises more scientific and comprehensive when choosing photovoltaic investment projects, a comprehensive investment evaluation index system was established from the environment, economy and risk and a combination of empowerment-TOPSIS model investment decision-making method for photovoltaic projects was proposed. Game theory is used to combine the subjective and objective weights calculated by the order relationship analysis method and entropy weighting method, which take into account the subjective judgment of experts and also integrates the results of objective data analysis to make the decision more comprehensive and scientific. In the investment decision-making stage, TOPSIS is adopted to calculate the overall degree of superiority, and the alternative projects are ranked in order of superiority and inferiority, so as to select the optimal investment object. Finally, the applicability and feasibility of the model are verified with examples, a theoretical basis is provided for the sustainable development of the photovoltaic industry.

The data of A-share listed manufacturing enterprises from 2012 to 2021 were selected to empirically test the impact and mechanism of digital transformation on green ambidextrous innovation. The results show that digital transformation promotes green ambidextrous innovation of manufacturing enterprises, and its promotion effect on green substantive innovation is greater than that of strategic innovation. The mechanism test shows that the scale and social responsibility of enterprises positively regulate the role of digital transformation in promoting green ambidextrous innovation. The government regulation is positively adjusting strategic innovation. The heterogeneity test shows that digital transformation plays a greater role in promoting the substantive green innovation of light polluting enterprises. It plays a greater role in promoting strategic green innovation of heavily polluting enterprises.

Under the “dual carbon” strategic goals, green credit has become an important driver for high-quality economic development and the transformation of enterprises. Based on operational data from A-share listed companies in China from 2004 to 2022, the implementation of the 2012 “Green Credit Guidelines” was used as a quasi-natural experiment. Employing double machine learning approach to construct an empirical model, the findings indicate that after the implementation of the Guidelines, the reduction of financing constraints, increased R&D investment, and promotion of joint ownership between banks and enterprises effectively drive continued green innovation in environmental protection enterprises.

Enhancing the science and technology reward system plays an important role in maintaining regional innovation competitiveness in Guangdong Province. A comparative framework of inter-provincial reward systems and analyzes the reward systems of 31 provinces in China was constructed. Findings indicate that the reward system in Guangdong underemphasizes the role of enterprise innovation subjects, does not align with the region’s innovation capabilities in terms of reward scale, exhibits a scarcity of mandatory guidelines within the nomination process, lacks openness in the evaluation mechanism, and has inadequate supervision and management structures. Moreover, there is a lack of incentive measures for social-force awards. It is recommended that Guangdong Province should moderately increase the scale of awards, establish specific categories for enterprise innovation, expedite revisions to award implementation regulations, refine the nomination process, conduct timely third-party performance evaluations, and introduce pioneering incentives for social entities to establish awards.

Data mining techniques was used to analyze the impact of internal control quality on the disclosure of risk warning information and the mediating role of ownership concentration was explored. Based on data from A-share listed companies in China from 2018 to 2022, it is found that improving internal control quality can reduce the disclosure of risk warning information and validate the mediating effect of ownership concentration. Additionally, internal control quality positively influences the quality of risk warning information disclosure. Enterprises are more sensitive to operational, financial, political and legal risks, but less sensitive to strategic risks. Therefore, companies should strengthen internal control management and adjust ownership concentration appropriately to reduce the disclosure of risk warning information.

Tourism gaze profoundly influences the perception of ancient town landscapes by both tourists and residents. Taking the photos and reviews of Qikou Ancient Town posted by tourists on Dianping website as data sources, combined with content analysis and social network analysis methods, NVivo11.0 and Gephi software was employed to investigate the perceptual characteristics of Qikou Ancient Town’s cultural landscapes from the perspective of tourism gaze. The results reveal that tourists primarily focus on cultural landscape elements such as the ancient town’s rivers, streets and traditional dwellings which perceive material cultural landscapes significantly more than non-material cultural landscapes. In terms of landscape combination perception, tourists have the highest perception of the combination of natural and material cultural landscapes, while their perception of non-material cultural landscape combinations is relatively low. Under the gaze of tourism, the perceptual interaction pattern between tourists and the ancient town landscape exhibits a deep integration of selectivity and interactivity. Moreover, residents’ perception of Qikou Ancient Town’s cultural landscapes has undergone significant changes, including a re-recognition of the value of the ancient town’s cultural landscapes and selective changes in cultural landscape perception based on tourist interest and economic value. In light of this, the study recommends balancing the display of material and non-material cultural heritage, enhancing the quality of the ancient town landscape, and promoting harmonious integration of the ancient town landscape to enhance the perceived experience and satisfaction of tourists and residents.

The recent wave of scientific and technological advancements, has resulted in the emergence of sophisticated digital products and premium digital service components. Furthermore, the enhancement of the quality of export products serves as a significant indicator of the high-quality development of China’s foreign trade. Utilizing data from A-share listed companies and corresponding data from the customs database spanning the years 2005 to 2015, the implications of the liberalization of digital service trade was examined. The findings suggest that the digital service trade substantially contributes to the improvement of export product quality among manufacturing firms. Furthermore, the influence of digital service trade liberalization on the quality of export products varies across different dimensions. The impact of export product quality enhancement is more pronounced in foreign-funded enterprises, capital-intensive industries, and particularly in the central and western regions of the country. Furthermore, larger enterprises located in these regions exhibit a more significant effect on product quality improvement. The mechanisms through which the openness of digital services trade influences the export product quality of manufacturing firms include enterprise productivity and the servicization of manufacturing processes.