With the rapid development of urbanization, the blind expansion of urban space has led to a series of social problems. In this process, the degree of urban function mixing affects the urbanization development level, making it particularly important to study the degree of coupling coordination between the two aspects. In this paper, taking Beijing as an example, we use urban point of interest (POI) data and taxi GPS trajectory data to calculate the urban POIs’ spatial entropy and taxis’ temporal entropy, based on the information entropy. We use the POIs’ spatial entropy and taxis’ temporal entropy to measure the urban function mixing degree. Also, the model of coupling coordination degree is used to measure the degree of coupling coordination between the urban function mixing degree and the urbanization development level. The results indicate the following: First, the POIs’ spatial entropy and taxis’ temporal entropy have significant regional imbalances. On the whole, both show a declining pattern when moving from the central urban area to the outer suburbs. The urban function mixing degree and urbanization development level are also higher in the central urban area than in the outer suburbs. Second, the coupling coordination among the urbanization development level, POIs’ spatial entropy, and taxis’ temporal entropy is distributed unevenly across various regions, which means that the three types of coupling coordination are in balanced development in the central urban area, but in unbalanced development in the outer suburbs. Third, from the perspective of spatial correlation characteristics, the higher is the degree of spatial agglomeration, the higher are the urban function mixing degree and urbanization development level, and the higher is the coupling coordination degree among the urbanization development level, POIs’ spatial entropy, and taxis’ temporal entropy. Therefore, relevant departments should plan the construction of urban functional areas reasonably, according to the degree of coupling coordination between the urban function mixing degree and the urbanization development level in different regions, so as to realize the healthy and sustainable development of a city.

The emergence and development of car sharing can not only satisfy people’s diverse travel demands, but also can bring a new solution to facilitate urban low-carbon and green development. With the increasing acceptance of car sharing, the market competition between car sharing and traditional taxis is becoming increasingly fierce. Therefore, we explore the advantages of car sharing to travelers compared with taxis. In this paper, we first use the GPS (Global Positioning System) trajectory data of car sharing orders to construct a comparative advantage model based on travel-cost. Then, we take Beijing as the research area to explore the travel-cost advantages of car sharing in terms of the time and space dimensions compared with taxis, through calculating the travel-cost of car sharing and using simulation to calculate that of taxis. The results of the comparison between car sharing and taxis from the perspective of travel-cost are as follows: (1) Compared with short trips, the travel-cost advantage of car sharing is relatively higher in medium and long trips; for travelers, the taxi has a higher travel-cost advantage when the travel time is either very long or very short. (2) On weekdays, it is more cost-effective to travel by shared cars for travelers before the rush hours in the evening, and the travel-cost advantage of using taxis is greater after the evening peak. (3) Compared with weekdays, it is more cost-effective to travel by shared cars on weekends wherever travelers are living in the main urban areas or in the remote suburbs. It is suggested that relevant departments should understand the travelers’ preference and analyze the influence mechanism of other various factors on the market demand for car sharing as per the focus on the market on the travel-cost advantages of car sharing, so as to promote the healthy and sustainable development of urban shared transportation.

The emergence and development of car-sharing has not only satisfied people’s diverse travel needs, but also brought new solutions for improving urban traffic conditions and achieving low-carbon and green sustainable development. In recent years, car-sharing has had competition with other ways of getting around, as the acceptance of car-sharing has grown, notably taxis. Therefore, it is particularly important to explore car-sharing travel costs advantages from the perspective of consumers and discover the competitive and complementary spaces between car-sharing and other modes. Therefore, taking Beijing as an example, this paper uses GPS trajectory data based on car-sharing orders to design a travel cost framework of car-sharing and taxis. We calculate and compare the travel cost difference between these two modes under different travel characteristics. The results indicate that car-sharing is a more economical way for consumers to travel for short or medium lengths of time, while people are more inclined to take taxis for distances of long duration. Compared with on workdays, at the weekend, the cost advantage of car-sharing is greater for long-distance trips. Moreover, the cost advantage of car-sharing increases gradually with the increase in travel distance. In addition, the travel costs of car-sharing and taxis are also affected by peak and off-peak traffic periods. Compared with off-peak periods, it is more cost-effective for travelers to take taxis during peak traffic periods for various travel distances. From the perspective of the travel cost, it is of great theoretical significance to discuss the substitution (market competition) and complementary relationship (market cooperation) between car-sharing and taxis in a detailed and systematic way. It provides methods and ideas for the comparative cost calculation of car-sharing and other travel modes. This paper also provides enlightenment and guidance for the development of car-sharing. Enterprises should implement differentiated pricing, designing different charging methods for different traffic periods, travel miles, and rental times, and set up additional stations in the surrounding areas of the city. Relevant government departments should also strictly manage the market access of car-sharing, and add or open car-sharing parking lots in centralized areas and for specific periods.

The large increase in the number of tourists brings challenges to the tourist carrying capacity of tourist destinations. By constructing a tourism carrying capacity indicator system and a coupling coordination model, we calculate and compare the development of tourism carrying capacity and the coupling coordination between all first-class indicators of tourism carrying capacity for provinces and cities in China. We find that the tourism carrying capacity and the coupling coordination between all first-class indicators of tourism carrying capacity for provinces and cities in China both showed an upward trend from 2008 to 2017, but the development was not balanced. In coastal provinces, their development level was high although lately showing a downward trend. In the provinces of the northwest China, their development level is low, and their development speed is relatively slow. The provinces and cities in the middle reaches of the Yangtze River and the southwest China recorded the fastest growth rate. In addition, we found that the development of tourism carrying capacity is closely related to coupling coordination between all first-class indicators of tourism carrying capacity.

Being at the forefront of China’s regional innovation and development, enterprises in the National Innovation Demonstration Zones must take the lead in completing high-quality transformation and upgrading. In this study, we use data from 1770 manufacturing companies from China’s 21 National Innovation Demonstration Zones. Based on the multi-factor influence model, we quantitatively study a series of factors that affect enterprise transformation and upgrading capability in terms of innovation-driven input, economically beneficial output, regional high-quality development, and the enterprise’s basic environment. The research results show a good trend in enterprise transformation and upgrading capability, and 45% of the enterprises have higher capabilities than the average of these zones. There are significant differences in these capabilities across the different National Innovation Demonstration Zones. Economically beneficial output has a relatively large impact on enterprise transformation and upgrading capability, while innovation-driven input, regional high-quality development, and the enterprise’s basic environment all have a relatively small impact. We suggest that the National Innovation Demonstration Zones and relevant departments should provide policy guarantees for enterprise transformation and upgrading in terms of regional systems, industrial chain layout, and soft environment optimization, so as to fully enable policy benefits from top-level design.

Urban multimodal transportation effectively meets the diversified travel demand of residents. However, it also generates extensive development problems such as traffic congestion, exhaust emissions and low operational efficiency. Therefore, there is an urgent need in urban sustainable development to achieve the coordinated and stable development of various modes of transportation. In this study, we took 36 major cities in China as the research object; measured the comprehensive development level of urban multimodal transportation; used the coupling coordination degree model (CCDM) to research the coordinated development relationship among buses, rail transit, and taxis; and clarified the shortcomings of the coordinated development of multimodal transportation. The results show that the comprehensive development of urban multimodal transportation in China has shown a significant upward trend from 2016 to 2020, with an average annual growth rate of about 7.36%. There are significant differences in the development levels of multimodal transportation in different cities. In addition, the relationship among buses, rail transit, and taxis in the major cities in China presents a state of uncoordinated development. Therefore, the relevant departments of cities should optimize the allocation of transportation resources, in terms of infrastructure construction and operation, according to these development levels and coordination of multimodal transportation.