There is evidence that the built environment has an influence on street vitality. However, previous studies seldom assess the direct, indirect, and total effect of multiple environmental elements at the city level. In this study, the features of the street vitality on Xiamen Island are described based on the location-based service Big Data. Xiamen Island is the central urban area of Xiamen, one of the national central cities in China. With the help of multi-source data such as street view images, the condition of design that is difficult to effectively measure with traditional data can be better explored in detail on a macro scale. The built environment is measured through a 5D system at the city level, including Density, Diversity, Design, Destination accessibility, and Distance to transit. Spatial panel Durbin models are constructed to analyze the influence of the built environment on the street vitality on weekdays and weekends, and the direct, indirect, and total effects are evaluated. Results indicate that at the city level, the built environment plays a significant role in promoting street vitality. Functional density is not statistically significant. Most of the elements have spatial effects, except for several indicators in the condition of the design. Compared with the conclusions of previous studies, some indicators have different effects on different spatial scales. For instance, on the micro scale, greening can enhance the attractiveness of streets. However, on the macro scale, too much greening brings fewer functions along the street, which inhibits the street vitality. The condition of design has the greatest effect, followed by destination accessibility. The differences in the influences of weekdays and weekends are mainly caused by commuting behaviors. Most of the built environment elements have stronger effects on weekends, indicating that people interact with the environment more easily during this period.

Previous studies substantiate built environment influences street vitality. However, most of them focus on whether the built environmental elements have an influence on the street vitality, and ignore the spatiotemporal heterogeneity of the influences at the district scale. Using multisource big data, we comprehensively measure the street vitalities of different periods and the built environment in different dimensions on Xiamen Island. Geographically and temporally weighted regression (GTWR) models are constructed to systematically analyze the spatiotemporal heterogeneity of the influences of the built environment on the street vitality. Results show that the influence of function remains constant over time. Transit has the strongest effect on the improvement of street vitality during peak hours. The impact of design is strongest in the evening. The effect of accessibility gradually strengthened over time, reaching the highest in the evening. In terms of the spatial dimension, the heterogeneity brought about by the new and old urban areas is significant. The spatial heterogeneity of design’s influences is prominently brought about by large green lands and landscape streets. Density, bus station and spatial scale have strong temporal and spatial stability. Length is the most unstable during the weekdays. In order to maintain street vitality and form sustainable traffic, differentiated strategies of vitality enhancement should be formulated according to the locations and attributes of the streets.

Under the control of multi-dimensional factors such as industry and enterprise characteristics, this paper examines the impact of government R&D subsidies on enterprise R&D activities, both theoretically and empirically. Theoretically, on the basis of Symeonidis model, this paper establishes a three-stage dynamic game model by introducing the government R&D subsidy, in order to expand the existing theory. Taking the data of the listed enterprises in China as the research sample, the Spatial Quantile Autoregressive Regression method, which has the ability to examine both spatial effect and quantile effect, is used to test the theoretical results. It is found that R&D subsidies play a significant positive role in stimulating the R&D activities of enterprises, and the incentive effect of subsidies is more obvious with the increase of R&D investment and R&D efficiency. Furthermore, the spillover effect can improve R&D efficiency, and this effect will be gradually strengthened with the increase of quantile.