Pub Date : 2026-01-01Epub Date: 2025-12-03DOI: 10.1016/j.apgeog.2025.103850
Shengjun Zhu , Xudong Zhang , Wenwan Jin , Wenqing Li
External knowledge serves as a critical source of industrial upgrading, yet existing research rarely examines the heterogeneity within the external knowledge set. Using customs transaction-level data, industrial survey, and patent data of the Chinese semiconductor industry (2000–2013), this paper shows that regional access to unrelated external knowledge facilitates the downstream firms to produce end-consumer products. Such access enables these firms to broaden their knowledge base, meet diverse market demands, and achieve upgrading. In contrast, related external knowledge is more advantageous for upstream firms involved in technology-intensive production. These findings indicate that not all external knowledge uniformly contributes to local firm upgrading; rather, its impact is conditioned by firms’ local product structure and positions within the value chain. By highlighting the complex composition of external knowledge, this study offers new insights into the upgrading of high-tech industry and the intersection of EEG, GVC, and innovation studies.
{"title":"Variety of external knowledge and industrial upgrading: Evidence from Chinese semiconductor industry","authors":"Shengjun Zhu , Xudong Zhang , Wenwan Jin , Wenqing Li","doi":"10.1016/j.apgeog.2025.103850","DOIUrl":"10.1016/j.apgeog.2025.103850","url":null,"abstract":"<div><div>External knowledge serves as a critical source of industrial upgrading, yet existing research rarely examines the heterogeneity within the external knowledge set. Using customs transaction-level data, industrial survey, and patent data of the Chinese semiconductor industry (2000–2013), this paper shows that regional access to unrelated external knowledge facilitates the downstream firms to produce end-consumer products. Such access enables these firms to broaden their knowledge base, meet diverse market demands, and achieve upgrading. In contrast, related external knowledge is more advantageous for upstream firms involved in technology-intensive production. These findings indicate that not all external knowledge uniformly contributes to local firm upgrading; rather, its impact is conditioned by firms’ local product structure and positions within the value chain. By highlighting the complex composition of external knowledge, this study offers new insights into the upgrading of high-tech industry and the intersection of EEG, GVC, and innovation studies.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103850"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684682","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 : 2026-01-01Epub Date: 2025-12-08DOI: 10.1016/j.apgeog.2025.103857
Xingrui Chen , Suqiu Tang , Chi Liu
The “special forces-style tourism” driven by digital technology poses challenges to traditional urban tourism theories, and existing single-perspective approaches struggle to explain the multidimensional coupling characteristics of time compression, functional complementarity, and digital drive. This study constructs a “spatio-temporal-functional-digital three-dimensional coupling” analytical framework. Based on 29,774 posts from Weibo and Xiaohongshu platforms and 5280 POI data points in Shanghai from January 2024 to March 2025, we employ difference-in-differences, pointwise mutual information algorithms, network centrality analysis, and K-means clustering methods for empirical testing. The findings reveal: (1) Under the 45-min spatio-temporal convergence threshold, the network coverage rate reaches 94.7 %, with an intra-community to inter-community time ratio of 2.29:1 and travel mode differentiation (walking 72 % vs. public transport 66 %), unveiling a dual-layer spatial logic; (2) Cross-category connections account for 85.4 %, with intra-community PMI values (2.34) significantly higher than inter-community values (1.67), proposing the concept of “spatially-dependent functional complementarity”; (3) Digital interaction exhibits an inverted U-shaped nonlinear association, with the dissemination network presenting a four-tier differentiation; (4) Eight spatial organization types are identified, with digital-functional interaction effects (η2 = 0.0118) stronger than temporal-functional interactions (η2 = 0.0041). This study extends time geography to a “constraint-optimization” paradigm, identifies the spatio-temporal constraint boundaries applicable to network theory, develops three operational management tools, and provides an analytical framework for theorizing urban tourism in the digital age.
{"title":"Digital-driven spatial organization of special forces tourism: A multi-dimensional coupling analysis","authors":"Xingrui Chen , Suqiu Tang , Chi Liu","doi":"10.1016/j.apgeog.2025.103857","DOIUrl":"10.1016/j.apgeog.2025.103857","url":null,"abstract":"<div><div>The “special forces-style tourism” driven by digital technology poses challenges to traditional urban tourism theories, and existing single-perspective approaches struggle to explain the multidimensional coupling characteristics of time compression, functional complementarity, and digital drive. This study constructs a “spatio-temporal-functional-digital three-dimensional coupling” analytical framework. Based on 29,774 posts from Weibo and Xiaohongshu platforms and 5280 POI data points in Shanghai from January 2024 to March 2025, we employ difference-in-differences, pointwise mutual information algorithms, network centrality analysis, and K-means clustering methods for empirical testing. The findings reveal: (1) Under the 45-min spatio-temporal convergence threshold, the network coverage rate reaches 94.7 %, with an intra-community to inter-community time ratio of 2.29:1 and travel mode differentiation (walking 72 % vs. public transport 66 %), unveiling a dual-layer spatial logic; (2) Cross-category connections account for 85.4 %, with intra-community PMI values (2.34) significantly higher than inter-community values (1.67), proposing the concept of “spatially-dependent functional complementarity”; (3) Digital interaction exhibits an inverted U-shaped nonlinear association, with the dissemination network presenting a four-tier differentiation; (4) Eight spatial organization types are identified, with digital-functional interaction effects (η<sup>2</sup> = 0.0118) stronger than temporal-functional interactions (η<sup>2</sup> = 0.0041). This study extends time geography to a “constraint-optimization” paradigm, identifies the spatio-temporal constraint boundaries applicable to network theory, develops three operational management tools, and provides an analytical framework for theorizing urban tourism in the digital age.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103857"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736597","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 : 2026-01-01Epub Date: 2025-12-09DOI: 10.1016/j.apgeog.2025.103859
Neema Simon Sumari , Patrick Brandful Cobbinah
African urbanization has gained momentum over recent decades, raising critical questions about urban planning and sustainability. Secondary cities are central to Africa's urban transition as they create opportunities for managing the pressures of urbanization on metropolitan regions. Yet secondary cities remain understudied compared to the metropolitan core. This paper examines urban expansion and density patterns in five Tanzanian secondary cities from 1990 to 2020, and the implications on sustainable urban development. We use multi-temporal Landsat data, the urban land density model, and landscape metrics to assess compactness and fragmentation. Results reveal outwards expansion with city-specific morphologies including infill near existing core, corridor growth and density shifts. In addition, the ANOVA and Tukey HSD test found no statistically significant differences across the five secondary cities or time periods, highlighting the limits of broad comparisons yet affirming the planning relevance of absolute changes. Our analysis expands the dialogue on African urbanization, and the findings advance understandings of SDG 11 (Sustainable Cities and Communities) and intersect with SDG 13 (Climate Action), and SDG 15 (Life on Land). The paper provides data-driven insights for policy makers and a replicable framework to guide sustainable secondary city planning in Sub-Saharan Africa.
{"title":"Secondary cities in African urbanization: On urban expansion and density patterns in Tanzania's mid-sized cities","authors":"Neema Simon Sumari , Patrick Brandful Cobbinah","doi":"10.1016/j.apgeog.2025.103859","DOIUrl":"10.1016/j.apgeog.2025.103859","url":null,"abstract":"<div><div>African urbanization has gained momentum over recent decades, raising critical questions about urban planning and sustainability. Secondary cities are central to Africa's urban transition as they create opportunities for managing the pressures of urbanization on metropolitan regions. Yet secondary cities remain understudied compared to the metropolitan core. This paper examines urban expansion and density patterns in five Tanzanian secondary cities from 1990 to 2020, and the implications on sustainable urban development. We use multi-temporal Landsat data, the urban land density model, and landscape metrics to assess compactness and fragmentation. Results reveal outwards expansion with city-specific morphologies including infill near existing core, corridor growth and density shifts. In addition, the ANOVA and Tukey HSD test found no statistically significant differences across the five secondary cities or time periods, highlighting the limits of broad comparisons yet affirming the planning relevance of absolute changes. Our analysis expands the dialogue on African urbanization, and the findings advance understandings of SDG 11 (Sustainable Cities and Communities) and intersect with SDG 13 (Climate Action), and SDG 15 (Life on Land). The paper provides data-driven insights for policy makers and a replicable framework to guide sustainable secondary city planning in Sub-Saharan Africa.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103859"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736695","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 : 2026-01-01Epub Date: 2025-10-22DOI: 10.1016/j.apgeog.2025.103822
Selena Hinojos , Kathryn Roscoe , Caitlin Grady
Social vulnerability indices (SVIs) are tools for spatially identifying populations vulnerable to natural hazards. However, their construction involves methodological choices that can introduce epistemic uncertainty. While previous efforts have explored how construction processes influence outcomes, further validation is needed to ensure SVIs accurately capture vulnerability. This study advances validation efforts by examining how scale, both areal units (Census block groups and tracts) and geographic boundaries (state, coastal, and city), impact SVI construction and indicator behavior. We applied two indicator sets, the Centers for Disease Control (CDC) SVI and the Hazards Vulnerability and Resilience Institute SoVI, and compared across three index structures: inductive with z-score standardization, hierarchical with percentile ranking normalization, and hierarchical with z-score standardization. Using geospatial and hotspot mapping, we analyze how interactions across index model stages impact vulnerability rankings and spatial patterns. We also examine how indicators influence shifts across scales in vulnerable areas. Results show that scale and indicator selection shift spatial patterns and reshape indicators' roles in SVIs. Notably, the hierarchical structure with z-score standardization—unlike those used in the CDC SVI or SoVI—produced the most consistent rankings, hotspot identification, and indicator performance. These findings highlight the importance of scale-indicator interactions and model structure selection in SVI design.
{"title":"Examining the role of indicators and scale in social vulnerability index construction: A comparative geospatial analysis of inductive and hierarchical models","authors":"Selena Hinojos , Kathryn Roscoe , Caitlin Grady","doi":"10.1016/j.apgeog.2025.103822","DOIUrl":"10.1016/j.apgeog.2025.103822","url":null,"abstract":"<div><div>Social vulnerability indices (SVIs) are tools for spatially identifying populations vulnerable to natural hazards. However, their construction involves methodological choices that can introduce epistemic uncertainty. While previous efforts have explored how construction processes influence outcomes, further validation is needed to ensure SVIs accurately capture vulnerability. This study advances validation efforts by examining how scale, both areal units (Census block groups and tracts) and geographic boundaries (state, coastal, and city), impact SVI construction and indicator behavior. We applied two indicator sets, the Centers for Disease Control (CDC) SVI and the Hazards Vulnerability and Resilience Institute SoVI, and compared across three index structures: inductive with z-score standardization, hierarchical with percentile ranking normalization, and hierarchical with z-score standardization. Using geospatial and hotspot mapping, we analyze how interactions across index model stages impact vulnerability rankings and spatial patterns. We also examine how indicators influence shifts across scales in vulnerable areas. Results show that scale and indicator selection shift spatial patterns and reshape indicators' roles in SVIs. Notably, the hierarchical structure with z-score standardization—unlike those used in the CDC SVI or SoVI—produced the most consistent rankings, hotspot identification, and indicator performance. These findings highlight the importance of scale-indicator interactions and model structure selection in SVI design.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103822"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365415","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 : 2026-01-01Epub Date: 2025-12-13DOI: 10.1016/j.apgeog.2025.103869
Haofu Liu , Zhifeng Liu , Binghua Gong , Dongjie Guan , Zhengtao Zhang , Shuhui Liu , Xufeng Mao , Chunyang He
Urban water source areas (UWSAs) are vital to urban water security and sustainability. Identifying important water source areas (IWSAs) is essential for their protection but is impeded by the lack of effective methods. We propose a novel method for assessing the importance of UWSAs by integrating the water supply capacity and the population of beneficiary cities and identify the spatial patterns of IWSAs for 100 major Chinese cities. Compared with traditional methods that consider only the water supply capacity, incorporating the population of beneficiary cities markedly enhances the importance of UWSAs in the upper Yellow River Basin (the importance of UWSAs up by 14.86 %), the upper Han River Basin (42.76 %), the lower Huai River Basin (21.52 %), and the Yalu River Basin (25.23 %). A total of 68.82 % of IWSAs are severely stressed by human activities. A protection gap of 0.54 million km2 remains in IWSAs, which are not included in protected areas or key ecological function zones and continue to experience severe human stress. Even within protected IWSAs, 0.56 million km2 of these areas continue to experience severe human stress. To ensure the security of urban water supplies, expanding protection coverage, strengthening management and oversight, establishing ecological compensation mechanisms, transforming urban water resource management, and encouraging public participation in conservation are crucial.
{"title":"Revealing the importance of urban water source areas in China by integrating supply and beneficiaries","authors":"Haofu Liu , Zhifeng Liu , Binghua Gong , Dongjie Guan , Zhengtao Zhang , Shuhui Liu , Xufeng Mao , Chunyang He","doi":"10.1016/j.apgeog.2025.103869","DOIUrl":"10.1016/j.apgeog.2025.103869","url":null,"abstract":"<div><div>Urban water source areas (UWSAs) are vital to urban water security and sustainability. Identifying important water source areas (IWSAs) is essential for their protection but is impeded by the lack of effective methods. We propose a novel method for assessing the importance of UWSAs by integrating the water supply capacity and the population of beneficiary cities and identify the spatial patterns of IWSAs for 100 major Chinese cities. Compared with traditional methods that consider only the water supply capacity, incorporating the population of beneficiary cities markedly enhances the importance of UWSAs in the upper Yellow River Basin (the importance of UWSAs up by 14.86 %), the upper Han River Basin (42.76 %), the lower Huai River Basin (21.52 %), and the Yalu River Basin (25.23 %). A total of 68.82 % of IWSAs are severely stressed by human activities. A protection gap of 0.54 million km<sup>2</sup> remains in IWSAs, which are not included in protected areas or key ecological function zones and continue to experience severe human stress. Even within protected IWSAs, 0.56 million km<sup>2</sup> of these areas continue to experience severe human stress. To ensure the security of urban water supplies, expanding protection coverage, strengthening management and oversight, establishing ecological compensation mechanisms, transforming urban water resource management, and encouraging public participation in conservation are crucial.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103869"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789749","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}
The spatial agglomeration and diffusion of the Information and communication technology industry significantly shape industrial landscapes and transformation in cities of developing countries. However, micro-scale analyses of this process remain limited. This study employs kernel density estimation, nearest neighbor index, standard deviational ellipse analysis, and conditional logit regression to examine the spatial evolution of Guangzhou's esports firms and the location-choice factors of new firms from 2003 to 2023. The findings reveal that: (i) The esports industry underwent a dynamic process of “agglomeration—diffusion—reagglomeration” process, resulting in a dual-core spatial structure comprising a central business district and government-led suburban hubs; (ii) Agglomeration economies, innovation and entrepreneurship ecosystem, and locational attributes are key determinants of firm location, though the dominant factors varied across different periods. These findings challenge the traditional core-periphery model by highlighting the role of suburban digital infrastructure and government intervention in shaping digital clusters at the street level. For policymakers, this suggests that fostering esports development can be achieved by building innovation hubs and concentrating resources for targeted support, thereby enhancing spatial agglomeration effects under conducive market conditions.
{"title":"The spatial evolution of E - sports firms and the location choice of new firms: A case study of Guangzhou, China","authors":"Guoshen Huang , Han Chu , Yifei Ouyang , Dixiang Xie","doi":"10.1016/j.apgeog.2025.103832","DOIUrl":"10.1016/j.apgeog.2025.103832","url":null,"abstract":"<div><div>The spatial agglomeration and diffusion of the Information and communication technology industry significantly shape industrial landscapes and transformation in cities of developing countries. However, micro-scale analyses of this process remain limited. This study employs kernel density estimation, nearest neighbor index, standard deviational ellipse analysis, and conditional logit regression to examine the spatial evolution of Guangzhou's esports firms and the location-choice factors of new firms from 2003 to 2023. The findings reveal that: (i) The esports industry underwent a dynamic process of “agglomeration—diffusion—reagglomeration” process, resulting in a dual-core spatial structure comprising a central business district and government-led suburban hubs; (ii) Agglomeration economies, innovation and entrepreneurship ecosystem, and locational attributes are key determinants of firm location, though the dominant factors varied across different periods. These findings challenge the traditional core-periphery model by highlighting the role of suburban digital infrastructure and government intervention in shaping digital clusters at the street level. For policymakers, this suggests that fostering esports development can be achieved by building innovation hubs and concentrating resources for targeted support, thereby enhancing spatial agglomeration effects under conducive market conditions.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103832"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466813","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 : 2026-01-01Epub Date: 2025-10-15DOI: 10.1016/j.apgeog.2025.103806
Anxin Lian , Yonglin Zhang , Yuying Liu , Yaran Jiao , Yue Cai , Zerui Wang , Xiaomeng Sun , Rencai Dong
As urbanization continues to accelerate, ecological challenges in cities have intensified, resulting in a growing number of environmental complaints from residents. Effectively exploring the potential public emotions behind complaints is helpful for improving the urban environmental governance capacity. However, most existing studies emphasize the drivers of environmental complaints, while giving limited attention to the mechanisms underlying residents' negative sentiment (RNS). In addition, the influence of the built environment on RNS remains insufficiently examined. Taking Guangzhou as a case study, this research applies the BERT model to conduct sentiment analysis on environmental complaint text data. Furthermore, a Light Gradient Boosting Machine-SHapley Additive exPlanation (LGB-SHAP) model is employed to characterize the nonlinear associations between RNS and its potential drivers. Results indicate that RNS is predominantly concentrated in the central built-up areas of Guangzhou, with stronger expressions observed during nighttime. Spatial overlap is evident between high-density complaint zones and RNS hotspots, highlighting critical areas for enhanced environmental surveillance. The plot ratio emerges as the strongest determinant of RNS. Moreover, the plot ratio often interacts with other factors, exerting either amplifying or mitigating effects on RNS within different threshold ranges. The influence of driving factors also varies across different land use types, where plot ratio and openness exert dominant impacts. This study integrates multimodal data to detect the emotional dynamics of residents’ environmental complaints and elucidates the driving mechanisms of RNS in relation to the built environment and socioeconomic factors, thereby providing a reference for more targeted and responsive urban environmental governance strategies.
{"title":"Exploring sentiment dynamics and their driving factors in megacity residents’ environmental complaints through deep learning and multimodal data","authors":"Anxin Lian , Yonglin Zhang , Yuying Liu , Yaran Jiao , Yue Cai , Zerui Wang , Xiaomeng Sun , Rencai Dong","doi":"10.1016/j.apgeog.2025.103806","DOIUrl":"10.1016/j.apgeog.2025.103806","url":null,"abstract":"<div><div>As urbanization continues to accelerate, ecological challenges in cities have intensified, resulting in a growing number of environmental complaints from residents. Effectively exploring the potential public emotions behind complaints is helpful for improving the urban environmental governance capacity. However, most existing studies emphasize the drivers of environmental complaints, while giving limited attention to the mechanisms underlying residents' negative sentiment (RNS). In addition, the influence of the built environment on RNS remains insufficiently examined. Taking Guangzhou as a case study, this research applies the BERT model to conduct sentiment analysis on environmental complaint text data. Furthermore, a Light Gradient Boosting Machine-SHapley Additive exPlanation (LGB-SHAP) model is employed to characterize the nonlinear associations between RNS and its potential drivers. Results indicate that RNS is predominantly concentrated in the central built-up areas of Guangzhou, with stronger expressions observed during nighttime. Spatial overlap is evident between high-density complaint zones and RNS hotspots, highlighting critical areas for enhanced environmental surveillance. The plot ratio emerges as the strongest determinant of RNS. Moreover, the plot ratio often interacts with other factors, exerting either amplifying or mitigating effects on RNS within different threshold ranges. The influence of driving factors also varies across different land use types, where plot ratio and openness exert dominant impacts. This study integrates multimodal data to detect the emotional dynamics of residents’ environmental complaints and elucidates the driving mechanisms of RNS in relation to the built environment and socioeconomic factors, thereby providing a reference for more targeted and responsive urban environmental governance strategies.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103806"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324261","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 : 2026-01-01Epub Date: 2025-11-03DOI: 10.1016/j.apgeog.2025.103838
Qianliang Jiang , Liang Ma , Mengmeng Zhang
Improvements in various life domains can increase overall life satisfaction. However, owing to resource constraints, commuters often face trade-offs among job satisfaction, community satisfaction, and commute satisfaction. Understanding how individuals navigate these trade-offs—and whether their decisions are voluntary or constrained—can offer nuanced insights for policy intervention. Drawing on survey data from 3259 commuters in Beijing, this study identifies and profiles distinct commuter groups based on their satisfaction levels across the three domains and examines the voluntariness of their trade-off decisions. The analysis reveals four groups with distinct socioeconomic characteristics: struggling commuters (low satisfaction with all domains, 21.8 %), work-oriented commuters (high satisfaction with their commute and job, 13.6 %), place-seekers (high satisfaction with their community, 19.9 %), and well-balanced commuters (high satisfaction with all domains, 44.6 %). These groups also display differing preferences, with some placing little emphasis on specific domains. Notably, struggling commuters appear to be involuntarily constrained, particularly in terms of commuting burdens, whereas the other groups demonstrate more voluntary trade-offs. These findings highlight the importance of targeted policies to support struggling commuters, who may be most in need of intervention.
{"title":"From struggling to well-balanced: Understanding the spectrum of commuter satisfaction","authors":"Qianliang Jiang , Liang Ma , Mengmeng Zhang","doi":"10.1016/j.apgeog.2025.103838","DOIUrl":"10.1016/j.apgeog.2025.103838","url":null,"abstract":"<div><div>Improvements in various life domains can increase overall life satisfaction. However, owing to resource constraints, commuters often face trade-offs among job satisfaction, community satisfaction, and commute satisfaction. Understanding how individuals navigate these trade-offs—and whether their decisions are voluntary or constrained—can offer nuanced insights for policy intervention. Drawing on survey data from 3259 commuters in Beijing, this study identifies and profiles distinct commuter groups based on their satisfaction levels across the three domains and examines the voluntariness of their trade-off decisions. The analysis reveals four groups with distinct socioeconomic characteristics: struggling commuters (low satisfaction with all domains, 21.8 %), work-oriented commuters (high satisfaction with their commute and job, 13.6 %), place-seekers (high satisfaction with their community, 19.9 %), and well-balanced commuters (high satisfaction with all domains, 44.6 %). These groups also display differing preferences, with some placing little emphasis on specific domains. Notably, struggling commuters appear to be involuntarily constrained, particularly in terms of commuting burdens, whereas the other groups demonstrate more voluntary trade-offs. These findings highlight the importance of targeted policies to support struggling commuters, who may be most in need of intervention.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103838"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466814","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 : 2026-01-01Epub Date: 2025-11-02DOI: 10.1016/j.apgeog.2025.103837
Yibo Wang, Yan Liu, Jonathan Corcoran, Scott N. Lieske
Understanding carbon generation from Individual Travel Activities (ITAs) requires moving beyond aggregate household or per-capita measures to examine frequency distributions across diverse set of trip characteristics. Yet, current research lacks a well-established empirical framework operating at a disaggregated level to profile the relationship between ITAs and carbon generation. Drawing on household travel survey data for South East Queensland, Australia, this study details a frequency-distribution modelling approach that employs the Lévy distribution to characterise how carbon generation varies across ITAs. The method enhances existing carbon estimation practices beyond traditional mean-based or aggregate approaches. A seven-parameter framework derived from normal-Lévy distribution coefficients captures the relationship between travel frequency and carbon generation, enabling systematic comparison across travel modes, purposes, and household locations. The model empirically derives carbon generation thresholds (2.88 kg CO2 per trip) to distinguish between intra-urban and inter-city trips, replacing administratively-defined boundaries with a data-driven spatial delineation alternative. Results reveal that while 83.5 % of trips generate relatively low carbon emission (no more than 2.88 kg per trip), these frequent, low intensity intra-urban activities constitute the majority of total carbon generation, challenging the typical conventional focus on high-emission trip reduction. This frequency-distribution approach provides urban planners and policymakers with an empirical framework for quantifying carbon impacts at the ITA level through which tailored interventions can be designed to encourage a shift to lower-carbon alternatives.
{"title":"Modelling carbon generated from individual urban travel activities: An empirical approach using the Lévy distribution","authors":"Yibo Wang, Yan Liu, Jonathan Corcoran, Scott N. Lieske","doi":"10.1016/j.apgeog.2025.103837","DOIUrl":"10.1016/j.apgeog.2025.103837","url":null,"abstract":"<div><div>Understanding carbon generation from Individual Travel Activities (ITAs) requires moving beyond aggregate household or per-capita measures to examine frequency distributions across diverse set of trip characteristics. Yet, current research lacks a well-established empirical framework operating at a disaggregated level to profile the relationship between ITAs and carbon generation. Drawing on household travel survey data for South East Queensland, Australia, this study details a frequency-distribution modelling approach that employs the Lévy distribution to characterise how carbon generation varies across ITAs. The method enhances existing carbon estimation practices beyond traditional mean-based or aggregate approaches. A seven-parameter framework derived from normal-Lévy distribution coefficients captures the relationship between travel frequency and carbon generation, enabling systematic comparison across travel modes, purposes, and household locations. The model empirically derives carbon generation thresholds (2.88 kg CO<sub>2</sub> per trip) to distinguish between intra-urban and inter-city trips, replacing administratively-defined boundaries with a data-driven spatial delineation alternative. Results reveal that while 83.5 % of trips generate relatively low carbon emission (no more than 2.88 kg per trip), these frequent, low intensity intra-urban activities constitute the majority of total carbon generation, challenging the typical conventional focus on high-emission trip reduction. This frequency-distribution approach provides urban planners and policymakers with an empirical framework for quantifying carbon impacts at the ITA level through which tailored interventions can be designed to encourage a shift to lower-carbon alternatives.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"186 ","pages":"Article 103837"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466812","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 : 2026-01-01Epub Date: 2025-12-08DOI: 10.1016/j.apgeog.2025.103863
Zhang Bin , Zhong Linsheng
This study addresses the uneven spatial distribution of China's 5A scenic spots, proposing a comprehensive approach for identifying and optimizing tourism gaps. By examining the relationship between the supply capacity of scenic spots and societal population demand, spatial patterns of tourism opportunities were evaluated under multiple threshold distance scenarios to identify tourism gaps, which are areas where the current supply of 5A scenic spots fails to meet population demand. To optimize the spatial layout of tourism resources, four machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), random forest (RF), logistic regression (LR), and support vector machine (SVM), are employed to construct a scenic spot location optimization framework, enabling spatial compensation and efficient resource allocation in gap areas. The study indicates that 60.22 % of regions in China show tourism gaps, 15.25 % of which are classified as “triple tourism gap areas,” meaning they lack tourism opportunities across all scenic spot types and are predominantly situated in the interior of the Qinghai-Tibet Plateau. In comparison to natural scenic spots, man-made and historical scenic spots exhibit more significant spatial disparities in tourism gaps. A decline in spatial unevenness of tourism opportunities across different threshold distances is observed in the optimized gap areas. By integrating machine learning to optimize the spatial layout of 5A scenic spots, this study provides scientific evidence and technical support for promoting regional coordinated development and achieving tourism spatial justice.
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