The main factor that decides the location of traditional businesses is the physical distance between their location and their target customers. Development of information and communication technologies (ICT) means the influence that physical distance exerts on businesses has decreased; however, the influence of time (the time it takes customers to visit physical retail outlets) has increased. However, it is not known if the costs associated with time are the main factors dictating the location of e-commerce businesses that decide to open a physical outlet: this paper tries to answer this question. The paper establishes a spatial relationship between the market size of online-to-offline (O2O) businesses and the accessibility and the location advantage relating to time/physical distance in Chengdu, in China's Sichuan Province. The results show that: (1) Overall, time has a greater impact than physical distance on business activities in Chengdu, and is the primary factor in the location selection of O2O businesses. (2) The O2O business whose location is dictated by physical distance has freedom to develop; however, the one whose location is dictated by time is more sensitive, and the spatial distribution of market size is more suitable to the location advantage based on time-cost. Hence, the spatial matching and the dependence between market size and location advantage show that there are slightly more businesses whose location is dictated by time than by distance in Chengdu. (3) Moving from the urban center to the outskirts of Chengdu, the influence of time on the location of O2O businesses remains almost the same, and the influence of physical distance gradually weakens. This means that, outside the urban centers, time has a greater influence than distance. Physical distance dictates the location of O2O businesses in Chengdu's urban center and time dictates their location in Chengdu's outskirts. (4) The impact that physical distance has on the location of O2O businesses is important in Chengdu because of its urbanization and ICT levels, and because of the behavior of consumers and suppliers. This means that both time and distance play a key role in the location development of O2O businesses. (5) The main factors that encourage an e-commerce business to open a physical outlet include demands from the consumers and the suppliers on reducing time-related costs, and the convenience of ICT.

The purpose of this study is to explore the employment center system in the central city of Shanghai by using commuting data obtained from mobile phone signaling data in Shanghai. Based on the signaling data it is possible to identify the phone users' home residence and where their employment is. We compile the employment density map using the employment places data in order to identify the employment centers in Shanghai. Then the employment center system is measured based on two perspectives, namely employment density and commuting connection. We measure the level, the hinterland and influence sphere of each employment center in Shanghai central city. Our main conclusions are as follows: firstly, the employment center system in Shanghai central city is a weak multi-centric system with a strong primary center. Secondly, centers with higher employment densities also contain stronger commuting connections to other areas, and the discrepancies of commuting connections between centers are even more significant. Thirdly, centers with higher levels also have larger hinterlands, but their influence spheres are not necessarily larger. Fourthly, the mixed degree of residential and employment land use is a more significant determinant of the residential and employment land use pattern balance of employment center than the level of the center. Finally, influence spheres are alternately distributed in areas that lack employment centers. To some extent, this paper helps to solve the problems of identifying employment centers and measuring commuting connections. Previous studies have been unable to perfectly identify such centers due to either an overly large spatial unit of measurement or lack of commuting data. This paper will be helpful for constructing multi-center employment system in the central city of Shanghai.

China has been experiencing rapid urbanization at an unprecedented rate and as a result, urban internal space structure has evolved significantly. It is of great significance to label different functional regions (DFR) inside a city for urban structure analysis, policy making, and resource allocation. These DFRs include residential district, industrial district, education district, and the administration district. This paper explored the characteristics and distribution of urban functional regions based on big geographic data. With the latest road network data, the study area (i.e., 6 districts of Guangzhou city in Guangdong Province, China) was partitioned into 439 segments. By applying the employment of spatial and temporal semantic mining method to the one-week massive floating cars GPS data and the point of interest data, we developed a Latent Dirichlet Allocation (LDA) and Dirichlet Multinomial Regression (DMR) model. Moreover, OPTICS clustering method was employed to process the results of LDA and DMR to identify different functional zones. Meanwhile, status map of Guangzhou urban planning, and resident travel characteristics were used to verify the verification of mentioned results. The results show that this method can identify the obvious characteristics of urban functional areas, such as mature residential area, science and education culture area, commercial area, and development zone. The results also show that residential and commercial areas are dominant DFRs in Guangzhou city, which are surrounded by other types of functional regions. This paper brings a new perspective on using large-scale and high quality individual space-time data to study human migration and daily activities, as well as to explore social space to unveil the formation and mechanism of urban functional zones.

On the basis of defining the connotation of the environmental adaptability of industrial system, this paper builds the environmental adaptability evaluation index system of industrial system and establishes an evaluation model in the perspective of the adaptive elements such as sensitivity, stability, and system response. And it analyzes the environmental adaptive evolution characteristics and the influencing factors of industrial system of the Songhua River Basin in Jilin Province. The results indicate that: (1) The development of industrial system has been under the double disturbance effect of internal and external factors. The internal impact is that the heavy industrial development leads to the poor industrial system operation condition. (2) The different adaptability elements and adaptability subsystem showed completely different regional evolution characteristics. The environmental and industrial system had the characteristics of nonlinear relationship, and so did the environmental system adaptability and the industrial system adaptability. (3) The environmental adaptability of industrial system turned from a feature of decreasing from upstream to downstream to a feature of the center-periphery with Changchun as the center. Obviously, the environmental adaptability of basin's industrial system represented a watershed characteristic to some extent. Meanwhile, the basin's central city functions could also influence and change the development trend of the adaptability. (4) The factors influencing the environmental adaptability of industrial system of the Songhua River Basin in Jilin Province include industrial structure, science and technology, economic development level and government regulation.