The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
<title>An application of GIS and Bayesian network in studying spatial-causal relations between enterprises and environmental factors</title>
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 2009
The paper intends to employ Geographic Information System (GIS) and Bayesian Network to discover ... more The paper intends to employ Geographic Information System (GIS) and Bayesian Network to discover the spatial causality between enterprises and environmental factors in Beijing Metropolis. The census data of Beijing was spatialized by means of GIS in the beginning, and then the training data was made using density mapping technique. Base on the training data, the structure of a Bayesian Network was learnt with the help of Maximum Weight Spanning Tree. Eight direct relations were discussed in the end, of which, the most exciting discovery, "Enterprise-Run Society", as the symbol of the former planned economy, was emphasized in the spatial relations between heavy industry and schools. Though the final result is not so creative in economic perspective, it is of significance in technique view due to all discoveries were drawn from data, therefore leading to the realization of the importance of GIS and data mining to economic geography research.
Urbanization and urban sprawl have profound effects on the environment at local, regional, and gl... more Urbanization and urban sprawl have profound effects on the environment at local, regional, and global scales. Fast, accurate and effective detection of urban change using remote sensing data will be an essential component of urban simulation, policy-making, urban planning and management. This paper presents an approach using MODIS data and Support Vector Machine (SVM) based remote sensing classifiers to monitor the urban sprawl in Beijing metropolitan area. Firstly, the authors reviewed the researches on remote sensing based urban change detection, discussed the possible advantages of MODIS data and SVM approach in urban change detection. Secondly, we designed and realized an one-class SVM classifier with Kernel function and judgmental functions. Thirdly, this contribution described the case study area and the classification process. Lastly, the result of the MODIS-SVM approach was compared with that of the TM and maximum-likelihood classifier approach and the accuracy, efficiency a...
The increase in China's skilled labor force has drawn much attention from policymakers, national ... more The increase in China's skilled labor force has drawn much attention from policymakers, national and international firms and media. Understanding how educated talent locates and relocates across the country can guide future policy discussions of equality, firm localization and service allocation. Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China. Yet, how the influence of these factors has evolved over time remains unexplored. Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China. Using four-year city-level panel data from national population censuses and 1% population sample surveys conducted every five years between 2000 and 2015, we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time. Our results revealed that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015, although the extent of this unevenness and concentration has decreased slightly over time. Results also showed that economic opportunities have remained main attraction and retention forces of talent in main cities, but that key local amenities have also played a role in shaping the residential decisions of talent, particularly urban public services and greening rate. These results highlight that China's talent's settlement patterns over the first fifteen years of the 21 st century have been mainly driven by urban economic opportunities versus amenity-related factors. Keywords: talent; spatial pattern; determinants; eigenvector spatial filtering; panel data analysis; China 1. Introduction Human capital accumulation has been recognized as a vital driving force in the development of knowledge-based economies (Lucas, 1988; Romer, 1990). As a result, policymakers have been universally concerned with ways of attracting and retaining human talent (Florida, 2002). In China, the national number and share of the highly educated population as a share of the labor force have both rapidly increased over the last fifteen years. The 2015 national 1% population sample survey reported that 170.93 million Chinese citizens held a college degree or above, an increase of 72.4% from the same sample collected in 2000. The rise of skilled individuals in China's labor force has drawn much attention from policymakers, employers, and the media. China's government has placed increasing emphasis on enlarging the national pool of highly skilled laborers by developing
Visualising global currents of international students between 1999 and 2018
Environment and Planning A: Economy and Space, 2021
The flows of international students are like the currents of the oceans, not only affecting the i... more The flows of international students are like the currents of the oceans, not only affecting the individuals adrift in them but the global circulation of policy, economics and academics as a whole, bearing pros and cons for each country or region along the way. To date, there has not been a detailed and elaborate description of the fluxes of international students over decades. In light of the research gap, the article utilises the chord diagram to draw threads between each pair of origin and destination of international students in the last 20 years and divides the periods into four main phases. With each phase exhibiting its specific features, we have tentatively concluded that the global student mobility structure has evolved from Arterial (1999–2003), Breakthrough (2004–2008) to Catch-Up (2009–2013), and lastly, Diversification (2014–2018). Corresponding reasons underpinning each change of the migration flows are also discussed briefly in the article.
What Drives Migrants to Settle in Chinese Cities: a Panel Data Analysis
Applied Spatial Analysis and Policy, 2020
Understanding the drivers of the floating population’s settlement intentions in Chinese cities is... more Understanding the drivers of the floating population’s settlement intentions in Chinese cities is vital to guide evidence-based urban economic development policies. Prior studies have been inclined to use static cross-sectional analysis providing insights into the relative importance of the factors that drive the distribution of urban settlement intentions. Yet, little has adopted longitudinal data approaches to delve into their spatial-temporal patterns and changes in determinants. This study applies China Migrants Dynamic Survey data of 2014–2017 to examine the spatial distribution of urban settlement intentions of floating migrants and their determinants over time. It reveals a persistent and spatially differentiated pattern of urban settlement intentions, where floating migrants relocating to some small and medium-sized cities in several northern parts of China are more willing to settle down. Results from a two-way fixed-effects panel model indicate that both internal motivations and external constraints are closely related to the settlement decision process of floating migrants. The number of family members living together, marriage rate, duration of stay, insurance coverage, the average wage of employees, the proportion of employees in the education industry, and per capita fiscal expenditure positively correlate with settlement intentions, while the proportion of interprovincial floating migrants and urban employment rate have a negative relationship with settlement intentions. Our results further suggest that internal drivers are a prerequisite for external drivers to play a role in driving the urban settlement of migrants.
The Urban Regeneration Engine Model: An analytical framework and case study of the renewal of old communities
Land Use Policy, 2021
Abstract The regeneration of old residential areas in China is facing a complex trap involving al... more Abstract The regeneration of old residential areas in China is facing a complex trap involving all kinds of stakeholders. On the one hand, ambiguous property rights, huge infrastructure investment arrears, and strict urban planning regulations make it challenging for market forces and social capital to enter the field of regeneration of old residential areas. On the other hand, the lack of an effective urban governance and social mobilization system leads to governance failures in the regeneration process. To break out of the above traps theoretically and practically, we construct an analytical framework called the Urban Regeneration Engine Model, in which the city government and the urban regeneration operator act as dual engines of urban regeneration. This dual engine drives the increase in social capital in the regeneration process and promotes the participation of the government, enterprises, residents, social organizations, and financial institutions. The positive feedback that comes from social capital increase further diversifies the fundraising sources, reduces the governance cost, and promotes the sustainable development of the community. Taking the Jinsong Community, one of the earliest residential communities in Beijing after the reform and opening up, as an example, this paper shows that the Urban Regeneration Engine Model provides a feasible and effective model for the regeneration of old residential areas in China and other developing countries facing similar problems.
How does rural homestead influence the hukou transfer intention of rural-urban migrants in China?
Habitat International, 2020
Abstract The household registration (hukou) system in China allows hukou to be transferred in the... more Abstract The household registration (hukou) system in China allows hukou to be transferred in the process of rural-urban migration, and such transfers exert a significant influence on the pace of urbanization and regional development in contemporary China. Rural-urban migrants who transfer their hukou to urban areas can use the collectively-owned rural homesteads in their hometowns that they had occupied until the housing properties on these lands disappear. Understanding the role of rural homesteads in rural-urban migrants’ hukou transfer intentions is of significance for efforts to promote urbanization and to formulate appropriate policies regarding hukou transfer and agricultural land management. Nevertheless, the influence of access to rural homesteads on hukou transfer intentions has gone largely underexplored. In the present study, the 2017 China Migrants Dynamic Survey data provide a basis for exploring these issues at the national level. The findings reveal that rural-urban migrants with access to a rural homestead show a 12% decrease in their propensities for transferring hukou than those without such access. Results derived from models with interaction terms suggest that two mechanisms are responsible for this outcome, an opportunity cost effect (OCE) and a revenue effect (RE). The OCE strengthens the inhibition effect of age on hukou transfer intentions but weakens the positive impact of labor contract coverage. The RE includes the absolute revenue effect (ARE) and the relative revenue effect (RRE). The former is evident in the weakened positive influence of non-village hometowns (townships, counties, or cities) on hukou transfer intentions and the latter in the strengthened positive influence of city size. The results further indicate that rural homesteads mediate hukou transfer intentions rather than affect them directly.
China's rapid urbanization has aroused substantial attention all over the world. Though there exi... more China's rapid urbanization has aroused substantial attention all over the world. Though there exists a strong connection between urban system and intercity migration, an overall prediction of China's urban population of all cities based on migration network has rarely been conducted. This study proposes an extended NEG (New Economic Geography) model to simulate China's urban system evolution with actual data and further predicts the future development of China's urban system under three different urbanization scenarios. We discover that China's future development trend is centralized urbanization dominated by large cities with a population of above 1 million. This prediction result is of great significance to provide scientific evidence for China's population flow management and new-type urbanization planning.
Using data from the 2015 national one percentage population sample survey, this paper examines th... more Using data from the 2015 national one percentage population sample survey, this paper examines the distribution, driving forces, and spatial effect of highly educated talents at the prefecture level. It involves spatial autocorrelation analysis and spatial econometrics models. The results show that the spatial pattern of talents is highly concentrated, unbalanced, and clustered among cities. Economic opportunities are the main forces affecting the distribution of talents, although some amenity variables (e.g., public services and accessibility) also matter. Our findings suggest that spatial spillover effect of the distribution of talents mainly comes from the influence of cross-city or country specific talent policies and social network linkages.
Interregional migration is a key issue affecting China's future pattern of urbanisation and regio... more Interregional migration is a key issue affecting China's future pattern of urbanisation and regional development. In response to the phenomenon of network autocorrelation (NA) commonly found in migration networks, this paper combines eigenvector spatial filtering (ESF) with a negative binomial gravity model based on four-stage panel data derived from censuses and population sampling surveys, and it analyses the factors that influenced China's interprovincial migration from 1995 to 2015. The results showed that (a) there is a significant spatial spillover effect in the interprovincial migration network. ESF can effectively capture NA in the data to reduce the model's estimation bias. The top 1.4% eigenvectors can extract high NA. (b) There is overdispersion in the interprovincial migration flows. A negative binomial regression gravity model is more appropriate for estimating the driving mechanism for migration than other models. (c) As with the initial variables of the gravity model, population size still exerts a great impact on both outflows and inflows. After considering the influence of NA, the effect of spatial distance is weakening. Additionally, economic, employment, social security, and educational factors are the main forces that are shaping the pattern of interprovincial migration. If the regional unemployment rate and average wages increase by 1%, the outflows and inflows increase by 0.351% and 0.502%, respectively; the coefficient of regional sex ratio at origin is also high, which has a close relationship with the migration motivations and gender differences in the employment market.
Industrial land supply has long been a powerful tool for local economic growth and government com... more Industrial land supply has long been a powerful tool for local economic growth and government competition in China. Based on Chinese prefecture-level cities' panel data from 2007 to 2016, our study investigates how industrial land supply responded to two key transitions in state strategy: the "Fiscal Stimulus Package" of 2008 and the "New-type Urbanization" and "Innovation Driven Development" of 2012. The results show that: (1) a response bifurcation of cities occurred in the four economic-geographical regions (eastern, central, western, and northeastern). The response in eastern and central regions was led by urban agglomerations, with neighbors mimicking one another. In the western region, most of the cities demonstrated an active and strong response to the two transitions. Nonetheless, it showed the characteristic of siphon effect, and local governments interacted in a zero-sum game. Meanwhile, the response of the northeastern region was not sensitive to state strategic transitions, and there was no strategic interaction among its cities. (2) We find various responses of cities at different levels of socioeconomic development. In traditional industrial land (TIL) supply, cities with higher socioeconomic levels were more adaptive to state strategic transitions. In high-tech industrial land (HIL) supply, most cities paid more attention to attracting investment in high-tech industries during the second transitional period. Among them, the smaller the economic strength of the city, the more willing it was to supply more land for high-tech enterprises. The paper concludes with implications for state strategies and regional industrial land supply policies.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
<title>An application of GIS and Bayesian network in studying spatial-causal relations between enterprises and environmental factors</title>
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 2009
The paper intends to employ Geographic Information System (GIS) and Bayesian Network to discover ... more The paper intends to employ Geographic Information System (GIS) and Bayesian Network to discover the spatial causality between enterprises and environmental factors in Beijing Metropolis. The census data of Beijing was spatialized by means of GIS in the beginning, and then the training data was made using density mapping technique. Base on the training data, the structure of a Bayesian Network was learnt with the help of Maximum Weight Spanning Tree. Eight direct relations were discussed in the end, of which, the most exciting discovery, "Enterprise-Run Society", as the symbol of the former planned economy, was emphasized in the spatial relations between heavy industry and schools. Though the final result is not so creative in economic perspective, it is of significance in technique view due to all discoveries were drawn from data, therefore leading to the realization of the importance of GIS and data mining to economic geography research.
Urbanization and urban sprawl have profound effects on the environment at local, regional, and gl... more Urbanization and urban sprawl have profound effects on the environment at local, regional, and global scales. Fast, accurate and effective detection of urban change using remote sensing data will be an essential component of urban simulation, policy-making, urban planning and management. This paper presents an approach using MODIS data and Support Vector Machine (SVM) based remote sensing classifiers to monitor the urban sprawl in Beijing metropolitan area. Firstly, the authors reviewed the researches on remote sensing based urban change detection, discussed the possible advantages of MODIS data and SVM approach in urban change detection. Secondly, we designed and realized an one-class SVM classifier with Kernel function and judgmental functions. Thirdly, this contribution described the case study area and the classification process. Lastly, the result of the MODIS-SVM approach was compared with that of the TM and maximum-likelihood classifier approach and the accuracy, efficiency a...
The increase in China's skilled labor force has drawn much attention from policymakers, national ... more The increase in China's skilled labor force has drawn much attention from policymakers, national and international firms and media. Understanding how educated talent locates and relocates across the country can guide future policy discussions of equality, firm localization and service allocation. Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China. Yet, how the influence of these factors has evolved over time remains unexplored. Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China. Using four-year city-level panel data from national population censuses and 1% population sample surveys conducted every five years between 2000 and 2015, we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time. Our results revealed that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015, although the extent of this unevenness and concentration has decreased slightly over time. Results also showed that economic opportunities have remained main attraction and retention forces of talent in main cities, but that key local amenities have also played a role in shaping the residential decisions of talent, particularly urban public services and greening rate. These results highlight that China's talent's settlement patterns over the first fifteen years of the 21 st century have been mainly driven by urban economic opportunities versus amenity-related factors. Keywords: talent; spatial pattern; determinants; eigenvector spatial filtering; panel data analysis; China 1. Introduction Human capital accumulation has been recognized as a vital driving force in the development of knowledge-based economies (Lucas, 1988; Romer, 1990). As a result, policymakers have been universally concerned with ways of attracting and retaining human talent (Florida, 2002). In China, the national number and share of the highly educated population as a share of the labor force have both rapidly increased over the last fifteen years. The 2015 national 1% population sample survey reported that 170.93 million Chinese citizens held a college degree or above, an increase of 72.4% from the same sample collected in 2000. The rise of skilled individuals in China's labor force has drawn much attention from policymakers, employers, and the media. China's government has placed increasing emphasis on enlarging the national pool of highly skilled laborers by developing
Visualising global currents of international students between 1999 and 2018
Environment and Planning A: Economy and Space, 2021
The flows of international students are like the currents of the oceans, not only affecting the i... more The flows of international students are like the currents of the oceans, not only affecting the individuals adrift in them but the global circulation of policy, economics and academics as a whole, bearing pros and cons for each country or region along the way. To date, there has not been a detailed and elaborate description of the fluxes of international students over decades. In light of the research gap, the article utilises the chord diagram to draw threads between each pair of origin and destination of international students in the last 20 years and divides the periods into four main phases. With each phase exhibiting its specific features, we have tentatively concluded that the global student mobility structure has evolved from Arterial (1999–2003), Breakthrough (2004–2008) to Catch-Up (2009–2013), and lastly, Diversification (2014–2018). Corresponding reasons underpinning each change of the migration flows are also discussed briefly in the article.
What Drives Migrants to Settle in Chinese Cities: a Panel Data Analysis
Applied Spatial Analysis and Policy, 2020
Understanding the drivers of the floating population’s settlement intentions in Chinese cities is... more Understanding the drivers of the floating population’s settlement intentions in Chinese cities is vital to guide evidence-based urban economic development policies. Prior studies have been inclined to use static cross-sectional analysis providing insights into the relative importance of the factors that drive the distribution of urban settlement intentions. Yet, little has adopted longitudinal data approaches to delve into their spatial-temporal patterns and changes in determinants. This study applies China Migrants Dynamic Survey data of 2014–2017 to examine the spatial distribution of urban settlement intentions of floating migrants and their determinants over time. It reveals a persistent and spatially differentiated pattern of urban settlement intentions, where floating migrants relocating to some small and medium-sized cities in several northern parts of China are more willing to settle down. Results from a two-way fixed-effects panel model indicate that both internal motivations and external constraints are closely related to the settlement decision process of floating migrants. The number of family members living together, marriage rate, duration of stay, insurance coverage, the average wage of employees, the proportion of employees in the education industry, and per capita fiscal expenditure positively correlate with settlement intentions, while the proportion of interprovincial floating migrants and urban employment rate have a negative relationship with settlement intentions. Our results further suggest that internal drivers are a prerequisite for external drivers to play a role in driving the urban settlement of migrants.
The Urban Regeneration Engine Model: An analytical framework and case study of the renewal of old communities
Land Use Policy, 2021
Abstract The regeneration of old residential areas in China is facing a complex trap involving al... more Abstract The regeneration of old residential areas in China is facing a complex trap involving all kinds of stakeholders. On the one hand, ambiguous property rights, huge infrastructure investment arrears, and strict urban planning regulations make it challenging for market forces and social capital to enter the field of regeneration of old residential areas. On the other hand, the lack of an effective urban governance and social mobilization system leads to governance failures in the regeneration process. To break out of the above traps theoretically and practically, we construct an analytical framework called the Urban Regeneration Engine Model, in which the city government and the urban regeneration operator act as dual engines of urban regeneration. This dual engine drives the increase in social capital in the regeneration process and promotes the participation of the government, enterprises, residents, social organizations, and financial institutions. The positive feedback that comes from social capital increase further diversifies the fundraising sources, reduces the governance cost, and promotes the sustainable development of the community. Taking the Jinsong Community, one of the earliest residential communities in Beijing after the reform and opening up, as an example, this paper shows that the Urban Regeneration Engine Model provides a feasible and effective model for the regeneration of old residential areas in China and other developing countries facing similar problems.
How does rural homestead influence the hukou transfer intention of rural-urban migrants in China?
Habitat International, 2020
Abstract The household registration (hukou) system in China allows hukou to be transferred in the... more Abstract The household registration (hukou) system in China allows hukou to be transferred in the process of rural-urban migration, and such transfers exert a significant influence on the pace of urbanization and regional development in contemporary China. Rural-urban migrants who transfer their hukou to urban areas can use the collectively-owned rural homesteads in their hometowns that they had occupied until the housing properties on these lands disappear. Understanding the role of rural homesteads in rural-urban migrants’ hukou transfer intentions is of significance for efforts to promote urbanization and to formulate appropriate policies regarding hukou transfer and agricultural land management. Nevertheless, the influence of access to rural homesteads on hukou transfer intentions has gone largely underexplored. In the present study, the 2017 China Migrants Dynamic Survey data provide a basis for exploring these issues at the national level. The findings reveal that rural-urban migrants with access to a rural homestead show a 12% decrease in their propensities for transferring hukou than those without such access. Results derived from models with interaction terms suggest that two mechanisms are responsible for this outcome, an opportunity cost effect (OCE) and a revenue effect (RE). The OCE strengthens the inhibition effect of age on hukou transfer intentions but weakens the positive impact of labor contract coverage. The RE includes the absolute revenue effect (ARE) and the relative revenue effect (RRE). The former is evident in the weakened positive influence of non-village hometowns (townships, counties, or cities) on hukou transfer intentions and the latter in the strengthened positive influence of city size. The results further indicate that rural homesteads mediate hukou transfer intentions rather than affect them directly.
China's rapid urbanization has aroused substantial attention all over the world. Though there exi... more China's rapid urbanization has aroused substantial attention all over the world. Though there exists a strong connection between urban system and intercity migration, an overall prediction of China's urban population of all cities based on migration network has rarely been conducted. This study proposes an extended NEG (New Economic Geography) model to simulate China's urban system evolution with actual data and further predicts the future development of China's urban system under three different urbanization scenarios. We discover that China's future development trend is centralized urbanization dominated by large cities with a population of above 1 million. This prediction result is of great significance to provide scientific evidence for China's population flow management and new-type urbanization planning.
Using data from the 2015 national one percentage population sample survey, this paper examines th... more Using data from the 2015 national one percentage population sample survey, this paper examines the distribution, driving forces, and spatial effect of highly educated talents at the prefecture level. It involves spatial autocorrelation analysis and spatial econometrics models. The results show that the spatial pattern of talents is highly concentrated, unbalanced, and clustered among cities. Economic opportunities are the main forces affecting the distribution of talents, although some amenity variables (e.g., public services and accessibility) also matter. Our findings suggest that spatial spillover effect of the distribution of talents mainly comes from the influence of cross-city or country specific talent policies and social network linkages.
Interregional migration is a key issue affecting China's future pattern of urbanisation and regio... more Interregional migration is a key issue affecting China's future pattern of urbanisation and regional development. In response to the phenomenon of network autocorrelation (NA) commonly found in migration networks, this paper combines eigenvector spatial filtering (ESF) with a negative binomial gravity model based on four-stage panel data derived from censuses and population sampling surveys, and it analyses the factors that influenced China's interprovincial migration from 1995 to 2015. The results showed that (a) there is a significant spatial spillover effect in the interprovincial migration network. ESF can effectively capture NA in the data to reduce the model's estimation bias. The top 1.4% eigenvectors can extract high NA. (b) There is overdispersion in the interprovincial migration flows. A negative binomial regression gravity model is more appropriate for estimating the driving mechanism for migration than other models. (c) As with the initial variables of the gravity model, population size still exerts a great impact on both outflows and inflows. After considering the influence of NA, the effect of spatial distance is weakening. Additionally, economic, employment, social security, and educational factors are the main forces that are shaping the pattern of interprovincial migration. If the regional unemployment rate and average wages increase by 1%, the outflows and inflows increase by 0.351% and 0.502%, respectively; the coefficient of regional sex ratio at origin is also high, which has a close relationship with the migration motivations and gender differences in the employment market.
Industrial land supply has long been a powerful tool for local economic growth and government com... more Industrial land supply has long been a powerful tool for local economic growth and government competition in China. Based on Chinese prefecture-level cities' panel data from 2007 to 2016, our study investigates how industrial land supply responded to two key transitions in state strategy: the "Fiscal Stimulus Package" of 2008 and the "New-type Urbanization" and "Innovation Driven Development" of 2012. The results show that: (1) a response bifurcation of cities occurred in the four economic-geographical regions (eastern, central, western, and northeastern). The response in eastern and central regions was led by urban agglomerations, with neighbors mimicking one another. In the western region, most of the cities demonstrated an active and strong response to the two transitions. Nonetheless, it showed the characteristic of siphon effect, and local governments interacted in a zero-sum game. Meanwhile, the response of the northeastern region was not sensitive to state strategic transitions, and there was no strategic interaction among its cities. (2) We find various responses of cities at different levels of socioeconomic development. In traditional industrial land (TIL) supply, cities with higher socioeconomic levels were more adaptive to state strategic transitions. In high-tech industrial land (HIL) supply, most cities paid more attention to attracting investment in high-tech industries during the second transitional period. Among them, the smaller the economic strength of the city, the more willing it was to supply more land for high-tech enterprises. The paper concludes with implications for state strategies and regional industrial land supply policies.
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