Pub Date : 2026-05-01Epub Date: 2026-03-11DOI: 10.1016/j.apgeog.2026.103974
Milad Abbasiharofteh , Lukas Kriesch
The twin (a joint green and digital) transition plays a key role in achieving Europe's Green Deal objectives. However, the interplay between regional capabilities and twin transition market applications is not well understood. This study employs Large Language Models to analyze web content from over 600,000 firms across German regions, identifying product-level contributions to the green and digital economy. The results indicate that artificial intelligence (AI) capabilities and the overall level of regional specialization are positively associated with the twin transition market applications. In contrast, we find no direct association between clean and twin (digital and clean) technological capabilities and the twin transition. This finding suggests that additional place-based conditions may be necessary to translate clean and twin technological capabilities into market applications. To support further research and evidence-based policymaking, we provide open access to the underlying dataset and the TwinTransition Mapper, our AI-based classification tool (https://huggingface.co/TwinTransitionMapper).
{"title":"Not all twins are identical: the geography of “twin” transition market applications","authors":"Milad Abbasiharofteh , Lukas Kriesch","doi":"10.1016/j.apgeog.2026.103974","DOIUrl":"10.1016/j.apgeog.2026.103974","url":null,"abstract":"<div><div>The twin (a joint green and digital) transition plays a key role in achieving Europe's Green Deal objectives. However, the interplay between regional capabilities and twin transition market applications is not well understood. This study employs Large Language Models to analyze web content from over 600,000 firms across German regions, identifying product-level contributions to the green and digital economy. The results indicate that artificial intelligence (AI) capabilities and the overall level of regional specialization are positively associated with the twin transition market applications. In contrast, we find no direct association between clean and twin (digital and clean) technological capabilities and the twin transition. This finding suggests that additional place-based conditions may be necessary to translate clean and twin technological capabilities into market applications. To support further research and evidence-based policymaking, we provide open access to the underlying dataset and the <em>TwinTransition Mapper</em>, our AI-based classification tool (<span><span>https://huggingface.co/TwinTransitionMapper</span><svg><path></path></svg></span>).</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"190 ","pages":"Article 103974"},"PeriodicalIF":5.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-03-06DOI: 10.1016/j.apgeog.2026.103973
Chunbo Zhu , Shiqiong Ding , Xiaoqing Li , Jiamei Ning , Gui Jin
Understanding the spatiotemporal differentiation and influencing mechanisms of urban spatial safety resilience (USSR) under climate change is of critical importance for coordinating urban development and safety. Based on systems theory and urban spatial structure theory, we construct an “Element-Function-Management” safety analysis framework. Using a comprehensive index method, obstacle degree model, and spatial analysis, we investigate the spatiotemporal evolution patterns and driving mechanisms of USSR in China. The results show that: (1) The level of USSR exhibits a gradual upward trend, with an increase in the number of Type IV and V cities and a marked decrease in Type I cities. Its spatial pattern follows a general east-high-west-low and south-high-north-low gradient. (2) The spatial mismatch index between USSR and its dimensions shows distinct regional variations. Negative mismatches are primarily clustered in coastal areas, whereas positive mismatches dominate the lower reaches of the Yangtze and Yellow River basins. (3) Among identified obstacle types, Type A, B, and C account for 57%, 32%, and 11%, respectively. Type A constitutes the largest proportion within each resilience dimension, while Type C is the smallest. (4) Surface pressure (SP) and relative humidity (RH) exert relatively strong influences on USSR, while potential evaporation (PE) and wind speed (Win)show weaker effects. All climatic factors exhibit dualistic positive and negative impacts. This study provides a foundation for enhancing comprehensive urban governance efficacy.
{"title":"Towards to climate change spatial-temporal characteristics and influencing mechanisms of urban spatial safety resilience in China","authors":"Chunbo Zhu , Shiqiong Ding , Xiaoqing Li , Jiamei Ning , Gui Jin","doi":"10.1016/j.apgeog.2026.103973","DOIUrl":"10.1016/j.apgeog.2026.103973","url":null,"abstract":"<div><div>Understanding the spatiotemporal differentiation and influencing mechanisms of urban spatial safety resilience (USSR) under climate change is of critical importance for coordinating urban development and safety. Based on systems theory and urban spatial structure theory, we construct an “Element-Function-Management” safety analysis framework. Using a comprehensive index method, obstacle degree model, and spatial analysis, we investigate the spatiotemporal evolution patterns and driving mechanisms of USSR in China. The results show that: (1) The level of USSR exhibits a gradual upward trend, with an increase in the number of Type IV and V cities and a marked decrease in Type I cities. Its spatial pattern follows a general east-high-west-low and south-high-north-low gradient. (2) The spatial mismatch index between USSR and its dimensions shows distinct regional variations. Negative mismatches are primarily clustered in coastal areas, whereas positive mismatches dominate the lower reaches of the Yangtze and Yellow River basins. (3) Among identified obstacle types, Type A, B, and C account for 57%, 32%, and 11%, respectively. Type A constitutes the largest proportion within each resilience dimension, while Type C is the smallest. (4) Surface pressure (SP) and relative humidity (RH) exert relatively strong influences on USSR, while potential evaporation (PE) and wind speed (Win)show weaker effects. All climatic factors exhibit dualistic positive and negative impacts. This study provides a foundation for enhancing comprehensive urban governance efficacy.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"190 ","pages":"Article 103973"},"PeriodicalIF":5.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-03-04DOI: 10.1016/j.apgeog.2026.103959
Bin Zhang , Hui Li
With rapid global urbanization and energy transition, the configuration of urban spatial structure plays a pivotal role in sustainable development. However, the multidimensional nature of urban spatial structure poses significant challenges to understanding its influence on energy-related carbon emission efficiency (ECEE). This study adopts high-resolution population data to quantify the spatial configuration of Chinese cities from the perspective of polycentric development patterns. We apply the super-efficiency SBM model to evaluate ECEE by combining multidimensional indicators. Our study explores the impact characteristics and underlying mechanisms of polycentric spatial structure (PSS) on ECEE. Furthermore, the geographically and temporally weighted regression model is applied to explore the spatio-temporal heterogeneity of PSS impacts on ECEE. The findings demonstrate that a higher degree of urban polycentricity significantly enhances ECEE through industrial structure upgrading and green technological innovation. Road density exhibits a negative moderating effect on the impact of PSS on ECEE. Public transportation contributes to improving ECEE, and the effect is more pronounced in cities with a lower degree of urban polycentricity. Polycentric development pattern is more effective in enhancing ECEE in large and non-resource-based cities, while smaller and resource-dependent cities benefit more from strengthening agglomeration capacity in core areas. Spatiotemporal heterogeneity analysis further reveals that reinforcing the agglomeration effects of core functional zones in Northeast China is crucial for enhancing ECEE. Our research advances the understanding of the carbon reduction effects of urban spatial structures and provides policy insights to support sustainable urban planning.
{"title":"Unveiling the impact of urban spatial structure on energy-related carbon emission efficiency: Evidence from the polycentric development pattern of Chinese cities","authors":"Bin Zhang , Hui Li","doi":"10.1016/j.apgeog.2026.103959","DOIUrl":"10.1016/j.apgeog.2026.103959","url":null,"abstract":"<div><div>With rapid global urbanization and energy transition, the configuration of urban spatial structure plays a pivotal role in sustainable development. However, the multidimensional nature of urban spatial structure poses significant challenges to understanding its influence on energy-related carbon emission efficiency (ECEE). This study adopts high-resolution population data to quantify the spatial configuration of Chinese cities from the perspective of polycentric development patterns. We apply the super-efficiency SBM model to evaluate ECEE by combining multidimensional indicators. Our study explores the impact characteristics and underlying mechanisms of polycentric spatial structure (PSS) on ECEE. Furthermore, the geographically and temporally weighted regression model is applied to explore the spatio-temporal heterogeneity of PSS impacts on ECEE. The findings demonstrate that a higher degree of urban polycentricity significantly enhances ECEE through industrial structure upgrading and green technological innovation. Road density exhibits a negative moderating effect on the impact of PSS on ECEE. Public transportation contributes to improving ECEE, and the effect is more pronounced in cities with a lower degree of urban polycentricity. Polycentric development pattern is more effective in enhancing ECEE in large and non-resource-based cities, while smaller and resource-dependent cities benefit more from strengthening agglomeration capacity in core areas. Spatiotemporal heterogeneity analysis further reveals that reinforcing the agglomeration effects of core functional zones in Northeast China is crucial for enhancing ECEE. Our research advances the understanding of the carbon reduction effects of urban spatial structures and provides policy insights to support sustainable urban planning.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"190 ","pages":"Article 103959"},"PeriodicalIF":5.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-02-28DOI: 10.1016/j.apgeog.2026.103911
Amber DeJohn , Matthew Palm , Matthew Suandi
Light rail transit (LRT) projects have been associated with neighborhood change, attracting new residents and modifying the neighborhood’s affordability. However, evidence on their actual impacts remains mixed in part due to evolving methods for causal evaluation. Disentangling LRT’s effects from pre-existing trends is difficult, as station locations are rarely exogenous. To address this issue, this study deploys a novel quasi-experimental approach that leverages unbuilt station alternatives identified in federal environmental planning documents as counterfactuals. Rather than limiting our scope to an individual case study, we apply this study design to 15 LRT extensions in 11 U.S. cities since 2000, using station catchments to explore a suite of outcomes related to neighborhood composition. We identify two consistent patterns. Demographically, new LRT stations increase the proportion of residents who are middle-aged or older workers in lower-skilled sectors. However, the area’s older adult population (65+) slightly declines. Second, housing markets respond during the construction phase, with modest appreciation that dissipates by the time the lines open. These findings suggest that LRT investments diversify working-class geographies, while potentially disrupting aging in place, although this effect is small. Alternative alignment counterfactuals require additional research to further develop this approach.
{"title":"Causal effects of transit investment on neighborhoods: Evidence from unbuilt alternative alignments","authors":"Amber DeJohn , Matthew Palm , Matthew Suandi","doi":"10.1016/j.apgeog.2026.103911","DOIUrl":"10.1016/j.apgeog.2026.103911","url":null,"abstract":"<div><div>Light rail transit (LRT) projects have been associated with neighborhood change, attracting new residents and modifying the neighborhood’s affordability. However, evidence on their actual impacts remains mixed in part due to evolving methods for causal evaluation. Disentangling LRT’s effects from pre-existing trends is difficult, as station locations are rarely exogenous. To address this issue, this study deploys a novel quasi-experimental approach that leverages unbuilt station alternatives identified in federal environmental planning documents as counterfactuals. Rather than limiting our scope to an individual case study, we apply this study design to 15 LRT extensions in 11 U.S. cities since 2000, using station catchments to explore a suite of outcomes related to neighborhood composition. We identify two consistent patterns. Demographically, new LRT stations increase the proportion of residents who are middle-aged or older workers in lower-skilled sectors. However, the area’s older adult population (65+) slightly declines. Second, housing markets respond during the construction phase, with modest appreciation that dissipates by the time the lines open. These findings suggest that LRT investments diversify working-class geographies, while potentially disrupting aging in place, although this effect is small. Alternative alignment counterfactuals require additional research to further develop this approach.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"190 ","pages":"Article 103911"},"PeriodicalIF":5.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-02-18DOI: 10.1016/j.apgeog.2026.103943
Yehua Dennis Wei , Yu Wang , David S. Curtis , Sungeun Shin , Ning Xiong
Mortality patterns exhibit substantial spatial variation, yet potential geographic influences are not well-understood. This study develops an integrated framework to investigate how urban sprawl and natural environments contribute to county-level all-cause mortality risk and to examine intergenerational mobility (IM) as a mediator. The analysis incorporates machine learning and spatial regression methods with U.S. county data. Using a small-area disease risk model, we identify clusters of high mortality risk in the Southeast while lower-risk counties concentrate along the Pacific Coast, the Northern Great Plains, and the Northeastern metropolitan corridor. Using random forest regression, poverty exerted the strongest influence, with an importance index of 0.38, far exceeding that of built and natural environment factors. Yet, when nonlinear relationships are considered, the built and natural environments are more clearly associated with mortality risk. Specifically, population centering, employment mix, land-use mix, and transportation accessibility are associated with lower mortality rates while higher population density corresponds to elevated risk, but only within specific ranges of each variable. Air pollution is consistently associated with higher mortality risk, whereas green space composition exhibits an inverted U-shaped relationship with mortality. In structural equation models, IM was a critical pathway linking urban sprawl characteristics to mortality outcomes, as population centering and land-use mix are associated with lower mortality through higher IM, while employment centering increases mortality by suppressing IM. Substantial spatial heterogeneity characterizes these relationships. The results highlight the need for regionally tailored interventions that integrate urban form, the natural environment, and opportunity structures to reduce mortality inequalities.
{"title":"Urban sprawl, natural environments, and mortality inequality: Socioeconomic pathways and spatial heterogeneity across U.S. counties","authors":"Yehua Dennis Wei , Yu Wang , David S. Curtis , Sungeun Shin , Ning Xiong","doi":"10.1016/j.apgeog.2026.103943","DOIUrl":"10.1016/j.apgeog.2026.103943","url":null,"abstract":"<div><div>Mortality patterns exhibit substantial spatial variation, yet potential geographic influences are not well-understood. This study develops an integrated framework to investigate how urban sprawl and natural environments contribute to county-level all-cause mortality risk and to examine intergenerational mobility (IM) as a mediator. The analysis incorporates machine learning and spatial regression methods with U.S. county data. Using a small-area disease risk model, we identify clusters of high mortality risk in the Southeast while lower-risk counties concentrate along the Pacific Coast, the Northern Great Plains, and the Northeastern metropolitan corridor. Using random forest regression, poverty exerted the strongest influence, with an importance index of 0.38, far exceeding that of built and natural environment factors. Yet, when nonlinear relationships are considered, the built and natural environments are more clearly associated with mortality risk. Specifically, population centering, employment mix, land-use mix, and transportation accessibility are associated with lower mortality rates while higher population density corresponds to elevated risk, but only within specific ranges of each variable. Air pollution is consistently associated with higher mortality risk, whereas green space composition exhibits an inverted U-shaped relationship with mortality. In structural equation models, IM was a critical pathway linking urban sprawl characteristics to mortality outcomes, as population centering and land-use mix are associated with lower mortality through higher IM, while employment centering increases mortality by suppressing IM. Substantial spatial heterogeneity characterizes these relationships. The results highlight the need for regionally tailored interventions that integrate urban form, the natural environment, and opportunity structures to reduce mortality inequalities.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"189 ","pages":"Article 103943"},"PeriodicalIF":5.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-02-26DOI: 10.1016/j.apgeog.2026.103954
Pu Zhang , Yiliang Li , Zheng Wei , Pan Hui , Na Jiang
The escalating conflict between doctors and patients in China has become a critical societal issue, with social media emerging as a primary arena for public grievance. However, the thematic content, spatial heterogeneity, and underlying drivers of this vast online discourse remain poorly understood. This study addresses this gap by analyzing over 300,000 user comments from the social media platform Douyin, linked to provincial-level socioeconomic and healthcare statistics. Employing a hybrid method combining manual open coding with a Large Language Model (LLM), we identify core discussion themes and use a normalized “Topic Index” with Lasso-selected Multiple Linear Regression (MLR) and SHAP-GIS analysis to explain their geographical distribution. Our findings reveal a discourse dominated by grievances, yet a counter-narrative of empathy for professionals is highly endorsed by users. Geographically, the analysis uncovers a distinct “Modernization Paradox.” Nationally, Hospital Density serves as a significant stabilizer, showing a negative correlation with grievance levels. However, SHAP visualization reveals that in modernized coastal regions, this buffering effect is offset by the “Modernization Penalty”, where higher Life Expectancy actively drives critical systemic discourse. We conclude that online public grievance is not a simple function of scarcity but is shaped by a structural tension between the stabilizing effects of infrastructure and the escalating pressures of patient complexity and rising expectations in modernized regions. This suggests that solutions must move beyond simply expanding physical infrastructure to focus on optimizing patient flow and humanizing service interactions in high-pressure medical centers.
{"title":"Digital grievances: A geospatial analysis of public discourse on doctor-patient conflict in China","authors":"Pu Zhang , Yiliang Li , Zheng Wei , Pan Hui , Na Jiang","doi":"10.1016/j.apgeog.2026.103954","DOIUrl":"10.1016/j.apgeog.2026.103954","url":null,"abstract":"<div><div>The escalating conflict between doctors and patients in China has become a critical societal issue, with social media emerging as a primary arena for public grievance. However, the thematic content, spatial heterogeneity, and underlying drivers of this vast online discourse remain poorly understood. This study addresses this gap by analyzing over 300,000 user comments from the social media platform Douyin, linked to provincial-level socioeconomic and healthcare statistics. Employing a hybrid method combining manual open coding with a Large Language Model (LLM), we identify core discussion themes and use a normalized “Topic Index” with Lasso-selected Multiple Linear Regression (MLR) and SHAP-GIS analysis to explain their geographical distribution. Our findings reveal a discourse dominated by grievances, yet a counter-narrative of empathy for professionals is highly endorsed by users. Geographically, the analysis uncovers a distinct “Modernization Paradox.” Nationally, Hospital Density serves as a significant stabilizer, showing a negative correlation with grievance levels. However, SHAP visualization reveals that in modernized coastal regions, this buffering effect is offset by the “Modernization Penalty”, where higher Life Expectancy actively drives critical systemic discourse. We conclude that online public grievance is not a simple function of scarcity but is shaped by a structural tension between the stabilizing effects of infrastructure and the escalating pressures of patient complexity and rising expectations in modernized regions. This suggests that solutions must move beyond simply expanding physical infrastructure to focus on optimizing patient flow and humanizing service interactions in high-pressure medical centers.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"189 ","pages":"Article 103954"},"PeriodicalIF":5.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-02-23DOI: 10.1016/j.apgeog.2026.103952
Guoqing Lyu , Ingo Liefner , Haining Jiang
Trans-local linkages are central mechanism for peripheral regions to sustain innovation systems, but their spatial configuration and mechanisms remain underexplored. This paper proposes four hypotheses based on the tri-polar framework integrating actor, network, and contextual dimensions, and tests them using co-invention patents from China's high-end equipment manufacturing industry covering 1985-2021. Employing Exponential Random Graph Models, the analysis reveals several key findings: (1) state-owned enterprises and large firms dominate peripheral innovation; (2) the spatial configuration of peripheral innovation is relatively stable; and (3) peripheral cities prioritize cross-hierarchy cooperation, resulting in open network configurations rather than locally closed structures. Overall, peripheral innovation in China is predominantly firm-led, cross-boundary, and selectively oriented toward higher-tier partners. By placing firms at the center of analysis and identifying differentiated types of peripheral cities, this study advances understanding of peripheral regional innovation systems in emerging economies. The findings contribute to the applied geography literature by providing spatially explicit evidence that informs place-based innovation and regional development policy.
{"title":"The configuration and mechanism of peripheral innovation in China: Empirical analysis from the high-end equipment manufacturing industry","authors":"Guoqing Lyu , Ingo Liefner , Haining Jiang","doi":"10.1016/j.apgeog.2026.103952","DOIUrl":"10.1016/j.apgeog.2026.103952","url":null,"abstract":"<div><div>Trans-local linkages are central mechanism for peripheral regions to sustain innovation systems, but their spatial configuration and mechanisms remain underexplored. This paper proposes four hypotheses based on the tri-polar framework integrating actor, network, and contextual dimensions, and tests them using co-invention patents from China's high-end equipment manufacturing industry covering 1985-2021. Employing Exponential Random Graph Models, the analysis reveals several key findings: (1) state-owned enterprises and large firms dominate peripheral innovation; (2) the spatial configuration of peripheral innovation is relatively stable; and (3) peripheral cities prioritize cross-hierarchy cooperation, resulting in open network configurations rather than locally closed structures. Overall, peripheral innovation in China is predominantly firm-led, cross-boundary, and selectively oriented toward higher-tier partners. By placing firms at the center of analysis and identifying differentiated types of peripheral cities, this study advances understanding of peripheral regional innovation systems in emerging economies. The findings contribute to the applied geography literature by providing spatially explicit evidence that informs place-based innovation and regional development policy.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"189 ","pages":"Article 103952"},"PeriodicalIF":5.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-02-24DOI: 10.1016/j.apgeog.2026.103946
Fangye Du , Jiaoe Wang , Pei Zhang
With the acceleration of digital transformation, demand for computing resources has surged, positioning computing power infrastructure (CPI) as a critical driver of emerging industries and a new force reshaping the geography of economic activity. Although existing research has examined the regional patterns of CPI, the mechanisms through which it shapes industrial spatial dynamics remain insufficiently understood. Using the artificial intelligence (AI) industry as an empirical case, this study applies a structural equation model to investigate how CPI, measured primarily through the service coverage and capacity of data centers, influences the spatial distribution of AI enterprises. The results show that: (1) CPI and AI enterprises exhibit strong spatial coupling, characterized by a marked east-west imbalance, although signs of synergistic growth have begun to appear in several regions. (2) The spatial configuration of AI enterprises is shaped by multiple forces, with CPI, economic development, innovation environment, policy support, and traditional infrastructure emerging as the most influential. A bidirectional but asymmetric relationship is observed between CPI and AI enterprise agglomeration. (3) The impact of CPI on AI enterprise location choices is significantly strengthened by regional economic development, innovation conditions, policy environment, and transportation and digital connectivity, which together enhance its ability to guide industrial clustering. This study provides new empirical evidence for understanding how digital infrastructure reorganizes spatial resource allocation, and offers policy implications for optimizing the spatial deployment of AI enterprises, improving regional CPI efficiency, and promoting more balanced digital development.
{"title":"Role of computing power infrastructure in shaping the geographic landscape AI enterprise in China","authors":"Fangye Du , Jiaoe Wang , Pei Zhang","doi":"10.1016/j.apgeog.2026.103946","DOIUrl":"10.1016/j.apgeog.2026.103946","url":null,"abstract":"<div><div>With the acceleration of digital transformation, demand for computing resources has surged, positioning computing power infrastructure (CPI) as a critical driver of emerging industries and a new force reshaping the geography of economic activity. Although existing research has examined the regional patterns of CPI, the mechanisms through which it shapes industrial spatial dynamics remain insufficiently understood. Using the artificial intelligence (AI) industry as an empirical case, this study applies a structural equation model to investigate how CPI, measured primarily through the service coverage and capacity of data centers, influences the spatial distribution of AI enterprises. The results show that: (1) CPI and AI enterprises exhibit strong spatial coupling, characterized by a marked east-west imbalance, although signs of synergistic growth have begun to appear in several regions. (2) The spatial configuration of AI enterprises is shaped by multiple forces, with CPI, economic development, innovation environment, policy support, and traditional infrastructure emerging as the most influential. A bidirectional but asymmetric relationship is observed between CPI and AI enterprise agglomeration. (3) The impact of CPI on AI enterprise location choices is significantly strengthened by regional economic development, innovation conditions, policy environment, and transportation and digital connectivity, which together enhance its ability to guide industrial clustering. This study provides new empirical evidence for understanding how digital infrastructure reorganizes spatial resource allocation, and offers policy implications for optimizing the spatial deployment of AI enterprises, improving regional CPI efficiency, and promoting more balanced digital development.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"189 ","pages":"Article 103946"},"PeriodicalIF":5.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-02-09DOI: 10.1016/j.apgeog.2026.103925
Jin Rui , Chenyu Shao , Lei Qin , Wenlin Zhao
With the deepening of urban digitalization, existing research has focused on the growth effects of the digital economy, while paying less attention to its impact on residents' life satisfaction and equity, particularly among vulnerable groups. This study aims to address these gaps by integrating the dual perspectives of regional disparities and characteristics of vulnerable groups, and by examining the impact mechanisms of the digital economy on life satisfaction and its equity in different geographical and socio-economic contexts. We analyzed life satisfaction by integrating advanced language models with social media data, employing ridge regression and XGBoost combined with GeoShapley to quantify the spatial contributions of features. The results indicated that: First, the digital economy is positively associated with residents’ life satisfaction but is also correlated with widening gaps; Second, elderly, low-income, and low-education groups experience both the benefits and the growing divide in digital finance and mobile internet adoption; Third, the strengthening of digital infrastructure in the eastern coastal regions improves satisfaction but intensifies regional imbalances; Fourth, increasing internet employment opportunities in northern regions can enhance both life satisfaction and its equity; finally, coastal port cities demonstrate a “win–win” scenario, where high life satisfaction coexists with greater equity. In short, balancing “expanding digital dividends” with narrowing gaps for vulnerable groups is key to fostering inclusive digital economy development.
{"title":"The digital economy enhances overall life satisfaction but reduces equity among vulnerable groups: Empirical evidence from 287 cities in China","authors":"Jin Rui , Chenyu Shao , Lei Qin , Wenlin Zhao","doi":"10.1016/j.apgeog.2026.103925","DOIUrl":"10.1016/j.apgeog.2026.103925","url":null,"abstract":"<div><div>With the deepening of urban digitalization, existing research has focused on the growth effects of the digital economy, while paying less attention to its impact on residents' life satisfaction and equity, particularly among vulnerable groups. This study aims to address these gaps by integrating the dual perspectives of regional disparities and characteristics of vulnerable groups, and by examining the impact mechanisms of the digital economy on life satisfaction and its equity in different geographical and socio-economic contexts. We analyzed life satisfaction by integrating advanced language models with social media data, employing ridge regression and XGBoost combined with GeoShapley to quantify the spatial contributions of features. The results indicated that: First, the digital economy is positively associated with residents’ life satisfaction but is also correlated with widening gaps; Second, elderly, low-income, and low-education groups experience both the benefits and the growing divide in digital finance and mobile internet adoption; Third, the strengthening of digital infrastructure in the eastern coastal regions improves satisfaction but intensifies regional imbalances; Fourth, increasing internet employment opportunities in northern regions can enhance both life satisfaction and its equity; finally, coastal port cities demonstrate a “win–win” scenario, where high life satisfaction coexists with greater equity. In short, balancing “expanding digital dividends” with narrowing gaps for vulnerable groups is key to fostering inclusive digital economy development.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"189 ","pages":"Article 103925"},"PeriodicalIF":5.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-02-23DOI: 10.1016/j.apgeog.2026.103947
Pablo Villar-Abeijón , Carme Miralles-Guasch , Oriol Marquet
Cities worldwide are increasingly implementing pedestrianization policies to enhance urban livability, promote sustainable mobility, and stimulate local economic activity. However, while these interventions are often celebrated for revitalizing public space, their potential role in triggering processes of commercial gentrification remains underexplored. This study investigates whether pedestrianization has contributed to commercial gentrification processes in Barcelona. Adopting a quasi-experimental design, pedestrianized streets were matched with comparable non-pedestrianized ones to form treatment and control groups. Using detailed commercial census data from 2014 to 2022, the study constructs indicators capturing shifts in commercial turnover, diversity, and composition. Results indicate that pedestrianization is associated with an increase in commercial closures and a reduction in retail diversity, but not with higher rates of new commercial openings or growth in the number of leisure-oriented businesses. These findings suggest that pedestrianization, while capable of reshaping local retail dynamics, does not by itself trigger full processes of commercial gentrification. Instead, other drivers, particularly touristic pressure, appear more influential in fostering substitution toward discretionary, leisure-oriented commerce. The study contributes to the growing body of research on the socio-economic effects of pedestrianization, offering nuanced evidence on its commercial impacts.
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