By the reference and creation of the predecessors\' theory, Paul Krugman introduces the achievements of New Trade and New Growth Theory into the traditional location theory, and puts forward a new location theory which is called New Economic Geography. Based on this theory and his achievements in the New Trade Theory, Krugman won the Nobel Prize in 2008. Krugman defined the New Economic Geography as the location theory of production, just as the concept of the classical location theory, which is proposed to explain the mechanism of formation and evolution of the economic spatial structure. The New Economic Geography theory of Krugman, scattered in his several books, is summed up as follows: a main idea, four propositions, four tools and three models. Krugman\'s new Economic Geography is based on the main idea that there exists multiple equilibrium state in the development of economic spatial structure. In order to analyze more clearly the process of formation and evolution of economic spatial structure, Krugman puts forward four propositions: (1) Transportation Costs play a key role in international trade and inter-regional trade; (2) Spatial agglomeration of interrelated economic activity could achieve cost-saving and benefit-increasing; (3) The cost-saving and benefit-increasing from the economic spatial agglomeration could promote the further concentration of economic development; (4) Early-development advantage could lead to the long-term accumulation of economic activity. Furthermore, Krugman introduces D-S Monopolistic Competition Model (built by A. Dixit and J. Stiglitz), "Iceberg"-type Transportation Costs, Self-organization Simulation and Computer Technology into the new Economic Geography, and builds three models, i.e., the Core-Periphery Model, Urban System Model and the International Model. The New Economic Theory of Krugman is a new development of Economic Geography under new situation, which can deal with the difficult problem in economic location study which has not been solved by traditional Economic Geography. But for a long time, the New Economic Theory of Krugman was considered a new academic field which is differentiated from or opposed to the classical Economic Geography in geographical circle. Therefore, this theory has attracted relatively little attention from the researchers in Geography. From the angle of geographic view, the paper reinterprets the theoretical connotation, significance of the New Economic Geography of Krugman and elaborates its relation with traditional location theory, analyses its effects on the development of Economic Geography, and hopes to provide the reference and consultation for innovation of the research paradigm of the Economic Geography in China and drafting of the long-term research program in regional development fields.
Through analysis of top 500 enterprises data of Chinese manufacturing industries, the paper reveals headquarter location characteristics of Chinese large and medium-sized enterprises, and explains the location factors of corporate headquarters in China. The study finds that top 500 enterprises of Chinese manufacturing industries are concentrated in the three major coastal economic regions, including the Yangtze River Delta, Pearl River Delta, Beijing-Tianjin-Hebei Region, Shandong and Liaoning provinces, as well as the areas along the Yangtze and Yellow rivers. Corporate headquarters of mega-cities are mainly located in the central districts, and economic and technological development zones, industrial parks or technological parks are main space of headquarter clusters in the medium-sized cities. In addition, small and medium-sized cities also accommodate a number of corporate headquarters. At the same time, the phenomenon of corporate headquarters relocation has already emerged in China, with Beijing and Shanghai as the main destinations. The location factors of corporate headquarters include urban scale, market capacity, domestic and foreign investment, financial capacity, science and technology conditions, urban infrastructures and urban location. Furthermore, urban economy scale is more explanatory to headquarters location. Chinese coastal developed regions have many advantages in these conditions, so Beijing, Shanghai and Shenzhen are attracting more and more corporate headquarters to further concentration.
The high-tech industry is the key to urban development and regional competitiveness in the context of globalization. However, the distribution of the high-tech industry is spatially uneven, and spatial factors significantly influence its location decision and spatial agglomeration. Although the substantial progress has been made in the studies on industrial agglomeration and location in China, little attention has been paid to the intra-city level. This paper analyzes spatial agglomeration and its influence on new firm location decision in Suzhou city, with a focus on the information and communication technology (ICT) industry. Based on point pattern analysis methods, we find that the level of agglomeration exhibits an inverted-U pattern, with the maximum being around 6 kilometers. Temporarily, hot spots of spatial agglomeration shifts from the old city district towards suburban areas, but ICT firms are still mainly concentrated in national-level development zones surrounding the old urban district. Meanwhile, new firm formation is highly correlated to the distribution of existing firms, which is re-enforcing spatial agglomeration. Poisson regression model has revealed the significant role of agglomeration, as well as development zones, transportation conditions and physical environments, in new firm formation.
As one of the kernel parts of Assessment of Regional Carrying Capacity of the Wenchuan Earthquake Struck Areas, this study developed a decision-making model for estimating the population capacity of the involved townships and cities based on the assessment of the suitability for reconstruction of the areas. It identified the critical constraints of population capacity and analyzed the spatial differentiations of the post-quake development conditions across different regions. The expected levels of urbanization, family incomes and income structures, levels of land output, and the reliance of agricultural population on arable lands are estimated by regions. With these parameters, the population capacities of townships and cities under several scenarios were estimated. According to the status of over-population, the townships and cities were classified and relevant policy suggestions on post-quake resettlement were presented.
Based on the theoretical foundation of urban innovation function and the urban system theory in knowledge economy, this paper examines the Chinese urban innovation pattern, rank system and inter-urban innovation relationships by using the methods of the questionnaire, the interviews, factorial analysis, mathematics model and so on. The study indicates that the Chinese innovation urban system consists of five levels of tower innovation urban system structure headed by Shanghai and Beijing. Generally, the eastern coastal cities have the important positions in the Chinese urban innovation city system, the capital cities of each province and the economically developed cities have been the centers of the regional innovation. The Chinese innovation urban system were driven by factors, such as urban innovational scale, the urban scientific research scale and efficiency, the urban innovation potential and urban innovation environment and so on. By using the number of co-authored papers among the cities to measure interurban innovational relationship, the study shows that Beijing has been in the central positions of the knowledge dissemination and knowledge cooperation innovation, much more knowledge dissemination among high level cities have occurred than that among the low level cities as well as between the low level cities and high level cities, provincial capital cities and the regional central cities with strong economy have played a vital role in knowledge dissemination.
Traffic jam is now becoming one of the most serious problems in urban China. Transportation supply can not meet with the increase of traffic demand, thus Traffic Demand Management (TDM) is another important way for resolving the problem. The mismatch of jobs-housing is one of the key reasons of traffic demand during rush hour every day. A case study is conducted in Guangzhou based on a historic survey of peoples\' jobs-housing relocation for the period 1996-2007, and some conclusions are obtained. The original planning system of China still plays an important role in people\'s jobs-housing hunting and daily activities. The more marketing, the longer distance and the more frequent relocation of jobs and housing is emerging. During 1996-2007, the distance of jobs and housing is increasing for most of the people, especially for those living in commercial houses. Price, environment and the attribute of the jobs are given more priority. In order to get better jobs and housing, people sometimes would have to commute longer. At the same time, the main composition of the housing property right in Government-led low-income housing communities has transferred, and the jobs-housing mismatch among the residents in alleviatory (Jiekun fang) houses and commercial houses in these communities has become striking. Moreover, location of housing and personal attribute also have some influence on job-housing location. The closer to the jobs center, the shorter distance and relocation is between jobs and housing. The middle class changes their jobs and housing much more frequently. Jobs-housing mismatch, expansion of urban space, political welfare and the transformation of social and economic system are the main courses of jobs-housing relocation.
Coupled with rapidly elevation of urbanization, the use efficiency of urban land is low in development in China\'s city, the traffic jam increasingly extrude, and the environment pollution is strictness. But because of the disjoint between the urban land use planning and the urban traffic planning, the existing urban planning method is not effective on resolve the problem faced by city. This paper construct new method of Floor Area Rate Planning guide by Railway Traffic based on analysis of land use influence on urban traffic. Take Tianjin as an example, penmen carry through demonstration analysis on this method. Compared with existing Floor Area Rate Planning project, the new project in this paper not only can enhance the hold amount of public traffic and figure better urban sight, but also can save 10% traffic time, reduce 35% energy consume and 44% contamination, and stay much land used to greenbelt and park and other public land, make the city environment better to live. Therefore, this new method not only remedy the lack of our existing urban planning method, but also can solve the problem faced by our urban development.
Theoretical analysis shows that the effect of rail transit on housing price is greater in suburbs than that in the central area. Empirical results validate this point by using the hedonic pricing method and housing transaction data nearby No.13 rail line in Beijing. In suburban areas, the housing prices within 1 km of rail stations are nearly 20% higher than those beyond that distance. However, with the development of surrounding urban transportation networks, the impact of rail transit is declining. Also, rail transit has significant impacts on urban land development intensity. The operation of No.13 Line encourages the land development in the north suburbs of Beijing, and raises the land development intensity around the stations. The FAR of new housing projects decreases by 1.0 every 3.3 km further away from the stations in suburban areas. These empirical results have important policy implications for the TOD strategy, the cost-benefit analysis and value capture strategy of rail transit construction in Chinese cities.
The Northeast China region is one of the areas covered by plenty of primeval forests. As an important region for ecological protection, it contributes a lot to the conservation of water resources and land, produces timber production and provides habitats for a huge number of wild animals and plants. With changes in socio-economic conditions as well as the geophysical environment, there are more and more severe decreasing trends of forestry area. Therefore, it is of significance to find the underlining reasons for the changes of forestry areas. To grasp the determinants of forestry area in Northeast China, we develop the econometric model with three equations identifying forest industrial production, conversion from sparse woodland to closed forest and conversion from non-forestry land uses to forestry area, and then explore the impacts on the changes of forestry area from such factors as demography, society, economy, location and geophysical conditions. On this basis, we employ Dynamics of Land System (DLS) simulation software to simulate land conversions between forestry area and non-forestry land uses and the land conversion inside forestry area for the period 2000-2020 under baseline scenario, environmental conservation scenario and development as the top priority. The research results show that forestry area will expand continuously and there exist various kinds of changing patterns for the secondary forestry classes, indicating that closed forest will expand continuously while sparse woodland and shrubs decrease a little bit, area of other forest uses will remain unchanged. The research results provide valuable information for decision-making in development and utilization of forest resources and forestry development plan in Northeast China.
Based on the micro-data sets of 13 counties, 273 villages and 2774 households of Honghe Hani and Yi Autonomous Prefecture of Yunnan Province, this article designed a two-level household income function model to analyze empirically the impact of geographical factors on the household income. The main conclusions are drawn as follows. (1) 61.25% of the total variance of the household income in the sample is caused by the external environment of the farmer\'s living village. There exist obvious differences for the influence effects of household income among farmer\'s per capita arable land area, the number of families that received training in agricultural technology, and the production and management structure, which can be partially explained by geographical factors. (2) Geographical factors lead to endowment differences of farmer\'s cultivated land, forests and other resources, which directly influence household income. The farmer\'s per capita net income in plain villages is 14.53% more than that in mountain village; The farmer\'s per capita net income for the village within 5 km from city is 30.63% higher than that of village 5 km away from city. (3) After controlling the geographical factors and the labor factor, the physical capital, production and management structure, and the labor quality of human capital of farmers has a positive significant effect, while the amount of labor has a negative significant effect. (4) Geographical factors affect farmer\'s agricultural infrastructure conditions, migrant workers and so on, and thus indirectly affect the income effects of the per capita arable land of farmers, the number of families that received training in agricultural technology, and the production and management structure. Finally it is suggested that some policies should be formulated to increase household income.
Tourists\' behavior is an important content in the research of behavior geography. Tourists\' experience quality assessment is a sort of cognition evaluation to the destination, and it is the conscious awareness of tourists\' cognition in both rational and emotional aspects, which has a direct impact on tourists\' behavior intention. By building the SEM among tourists\' cognition, perceived value and behavior intention, taking the overseas tourists in Xi\'an city as an example, this paper concludes that, first, individual tourists\' cognitive behavior has a positive correlation with the perceived value and behavior intention. When individual cognitive assessment rises, the individual perceived value correspondingly increases, and this positive correlation results in the same correlation between perceived value and behavior intention, that is to say, the higher the level of individual perceived value, the stronger the behavior intention. Second, tourists\' perceived value on tourism facilities, tourism consumption and tourism attraction are the key elements which dominate tourists\' behavior. Third, the paper not only proves the correlation among tourists\' cognition, perceived value and tourists\' behavior intention in technique level, but also fills a gap in the theoretical and methodological study of the relation between individual cognition and other behavior variables with the generative theory. Obviously it is indicated that individual perceptive assessment level and individual behavior intention have positive correlation, which supports the example of "cognition-impacting-behavior" in experience points as well. The result shows that individual cognition research can predict tourists\' behavior intention properly, which has significant theoretical and practical significance to the research of destination image and other areas.
