Tourism efficiency is an effective index of measuring the development quality of the tourism industry. In this study, the tourism efficiency of 30 provinces in China during the period from 2006 to 2018 was measured with the SBM model and Malmquist index. On the basis of ESDA and GWR models, we explored the spatial pattern of China’s tourism efficiency and the spatial heterogeneity of the influencing factors in depth. The results revealed that China’s tourism efficiency has been constantly enhanced with an increasingly balanced pattern. Meanwhile, the utilization degrees of various input factors have constantly been improving. Both technological efficiency and technological progress jointly promote rapid growth of total-factor productivity. Accompanied with constant enhancement of the spatial agglomeration effect, the local spatial pattern also showed obvious differentiation. In general, low-efficiency regions were mainly concentrated in northern China, while high-efficiency regions were concentrated in southern China. The distinct spatial–temporal differentiation characteristics of tourist economic efficiency can be attributed to different influencing strengths of various factors in various regions and different action tendencies. The level of economic development, traffic conditions, the professional level of tourism, and openness degree can significantly promote tourism efficiency. Tourism resource endowment and environmental cost impose slight effects and differ in action direction, thereby inhibiting the tourism efficiency of many regions.

Based on the data of 59 prefecture-level cities in the Yellow River Basin from 2011 to 2019, this paper uses the Slack Based Measure-Global Malmquist Luenberger (SBM-GML) model to measure green total factor productivity (GTFP) of the cities. Under the space–time concept of the Basin, heterogeneity analysis of the upper, middle and lower reaches of the Yellow River Basin is conducted. On this basis, a panel Tobit model is constructed to analyze the impact of environmental regulation on GTFP in the whole basin, upstream region, middle region and downstream region. The results show that the intensity of environmental regulation in the Yellow River Basin increases gradually, which is the highest in the lower reaches, followed by the middle reaches; spatially, the intensity of environmental regulation shows a certain aggregation trend. The green economic growth is realized in the whole basin, and the green technology progress effect is the driving factor of GTFP. The GTFP distribution in the upstream region is relatively concentrated, showing a slow upward trend. The distribution of GTFP in the middle reaches is discrete, and the annual difference is large. In the downstream region, it shows a trend of decline first and then increase. Environmental regulation promotes GTFP in the whole basin, upper, middle and lower reaches, accompanied by certain spatial differences. The Yellow River Basin breaks through the cost effect brought by environmental regulation and triggers technological innovation, thereby enhancing GTFP; the “Porter hypothesis” has been verified in the Yellow River Basin.

Waste is increasingly used as a renewable resource. Industrial symbiosis is an innovative concept for more efficient use of waste streams within industrial complexes, with the aim of reducing the overall environmental impact of the complex. Industrial symbiosis plays a more important role in promoting green economic growth and building low-carbon cities. Based on the ecological theoretical framework, combined with Waste Flow Analysis (WFA), the material flow analysis (MFA) and production matrix methods were used as the core to construct the Industrial Symbiosis System Waste Flow Metabolism Analysis (ISSWFMA) model. In addition, taking the “Jinchang Model” as an example, a typical case selected by the National Development and Reform Commission of China’s regional circular economy development model, we conducted a refined quantitative study on the flow and metabolism of waste flow in the regional industrial symbiosis system at the City-Region level using the circulation degree index. The following conclusions were obtained from the study: The ISSWFMA model can better describe the flow and metabolism of waste streams in the industrial symbiosis system at the City-Region Level and can provide data and methods for storage management. As the internal industrial chain and the correlation between various departments continuously improved, the Circulation Index (CI) of solid waste, wastewater, and exhaust gas in the industrial symbiosis system of Jinchang City showed an overall increasing trend, the degree of recycling was continuously increasing, the industrial symbiosis ability was continuously enhanced, and the system structure was more complete. At the same time, based on the analysis of different wastes, the industrial symbiosis is developed at different stages; based on the analysis of solid wastes, the industrial symbiosis ability of Jinchang’s Industrial Symbiosis System has strengthened and accelerated the fastest from 2005 to 2010; based on the analysis of wastewater, the industrial symbiosis ability of the system strengthened slowly during the whole study period; and based on the analysis of exhaust gas, the industrial symbiosis ability of the system continued to strengthen rapidly during the whole study period. Finally, on the basis of further discussion on the selection of waste recycling paths, we proposed to give full play to the role of market mechanisms, and to build recycling areas and ecological areas by strengthening industrial symbiosis and its derived urban symbiosis to achieve the goals of natural resource conservation, ecological environment protection, and harmonious coexistence between human and nature.

Taking the main district in Lanzhou city of China as an example, the questionnaires were designed and distributed, and then the effects of five factors, i.e., behavioral attitude, subjective norm, perceived behavioral control, perceived ease of use and perceived usefulness, on the behavioral intention of dockless bike-sharing (DBS) use were empirically analyzed based on the integrated model of technology acceptance model (TAM) and the theory of planned behavior (TPB) as well as the structural equation model. Results show that the five factors all impose significantly positive effects on the public’s behavioral intention of DBS use but differ in influencing degrees. Behavioral attitude, subjective norm and perceived behavioral control can all directly affect the public’s behavioral intention of DBS use, with direct influence coefficients of 0.691, 0.257 and 0.198, while perceived ease of use and perceived usefulness impose indirectly effects on behavioral intention, with indirect influence coefficients of 0.372 and 0.396. Overall, behavioral attitude imposes the most significant effect, followed by perceived ease of use, perceived usefulness and subjective norm, and finally perceived behavioral control. This indicates that the public’s behavioral intention of DBS use depends heavily on their behavioral attitude towards the shared bikes. In view of the limited open space of the main district in Lanzhou, the explosive growth of shared bikes, oversaturated arrangements, disordered competition, unclear and unscientific divisions of parking regions, and hindrance of traffic, this study proposes a lot of policy suggestions from the research results. A series of supporting service systems related to DBS should be formulated. The shared bikes with different characteristics should be launched for different age groups, gender groups and work groups. The corresponding feedback platform for realtime acquisition, organization, analysis and solution of data information, as well as the adequate platform feedback mechanism, should be established.

Based on the measurement of producer service industry agglomeration and export technological complexity of manufactured products in 288 Chinese cities from 2000 to 2015, this paper illustrates the evolvement and spatial characteristics of the two factors through visualization figures, and discusses the effects of producer services agglomeration on export technological complexity of manufacturing through robust panel data models. The findings are as follows: as with the influence of industrial connection, empirical outcomes indicate that urban producer service agglomeration can promote technological complexity of export manufacturing on the full-sample level. Visualization analysis shows that the scale of producer service industry agglomeration and the export technological complexity of manufactured products around Chinese cities kept rising constantly during the study period. However, although the export technological complexity displayed a trickle-down effect, the producer service industry agglomeration experienced continuous polarization both on the national and the regional levels. Accordingly, as is shown in the empirical analysis by areas, regions with strong support from producer service industry saw a remarkable promotion in the export manufacturing technology, while the northwest and the northeast gradually lagged behind. Such results sufficiently prove that heterogeneity does exist in the performances of industrial connection between producer service industry and export manufacturing in cities of different regions in China.