Journal of Urban Management最新文献

{"title":"Building urban resilience: Lessons from the COVID-19 pandemic for future-proofing city infrastructure","authors":"Tzu-Ling Chen,&nbsp;Yue-En Li","doi":"10.1016/j.jum.2024.11.016","DOIUrl":"10.1016/j.jum.2024.11.016","url":null,"abstract":"<div><div>COVID-19 pandemic has become a global issue of increasing concern in recent years. As time has passed, existing urban planning and design have gradually been challenged and transformed. The World Health Organization has provided numerous recommendations to the public regarding the transmission of COVID-19, with social distancing being the primary measure. However, the implementation of social distancing policies has altered people's lifestyles. With nearly three years of ongoing pandemic transmission and the advent of the post-pandemic era due to increased vaccination rates, it is essential to consider the adjustments of urban elements in response to the changing lifestyles of residents. The pandemic has underscored the need for cities to not only reduce damage but also to maintain functionality and livability, thus enhancing economic development and urban vibrancy. It applies the Analytic Hierarchy Process to select principles based on expert opinions, constructing specific criteria accordingly. Critical Infrastructure (CI) criteria and their weights in the Taipei metropolitan area are then obtained, establishing a sequence for the reallocation of critical infrastructure. The study delves into whether critical infrastructure should be reallocated in the post-pandemic era, aiming to build urban resilience. Through expert questionnaires based on the Analytic Hierarchy Process and matrix statistical calculations, the true importance weights are derived. The results show that the highest priority criteria is \"policy management,\" followed by \"built environment and public facilities,\" and third is \"green-blue infrastructure.\" These criteria will serve as important measures for adjusting urban design in the post-pandemic era, with Wanhua as the study area, to respond to the impact of public facility data analysis on urban development and to understand the pandemic's effects on cities. The findings aim to provide governmental units with a framework to evaluate and improve essential urban infrastructure, ensuring cities are better prepared for future health crises and environmental challenges.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 3","pages":"Pages 913-926"},"PeriodicalIF":5.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GIS and remote sensing methods in predicting the dissipation time of rural settlements under the influence of climate change in the Republic of Serbia","authors":"Aleksandar Valjarević","doi":"10.1016/j.jum.2024.12.002","DOIUrl":"10.1016/j.jum.2024.12.002","url":null,"abstract":"<div><div>In this research the specific methodology used to better analyzed rural settlements and they properties. The Geographical Information Systems and Remote Sensing approaches taken to connect rural settlements with the climate change effects in Serbia. For the first time the classification of settlements after approved methodology divided in accordance of new spatial relations within the situation in Serbia. Ten morphometric types of rural settlements were analyzed in terms of social, economic, transport, demographic and climatic factors. The effects of climate change, estimated in this study, will become even more noticeable by 2050. The results showed that the rural settlements (villages) in southern and eastern Serbia are very similar to the villages in central Banat in terms of resolution and low value of mitigation of the effects of climate change. In 2050, 35% of the villages in the south, 30% in the east, and 23% in other regions will be dissipated. The total number of dissipated rural settlements in the period from 2011 to 2050 is 680 or 15% in total. By means of GIS and remote sensing methods, all rural settlements were mapped and presented statistically, along with their characteristics. This method is useful for the analysis of rural settlements with 0–15,000 inhabitants. The shape of the settlements was also analyzed and the zones with the strongest impacts of climate change were marked. The hazardous events are divided into extreme rainfall, wind, drought and maximum temperatures and compared with the types of rural settlements. The climate factors included, together with other parameters such as socio-economic, demographic and urban planning factors, provide a complete overview and a better understanding of the survival of rural settlements in the future. The main contribution of this research is the creation of a new classification of rural settlements, taking into account the effects of climate change and new socio-economic theories. In this way, the old classifications and theories that were established fifty years ago will be improved.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 500-511"},"PeriodicalIF":3.9,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the dynamics of urban just transitions: An interdisciplinary analysis with latent dirichlet allocation (LDA)","authors":"Yuhang Sun ,&nbsp;Ye Luo ,&nbsp;Xuepeng Qian ,&nbsp;Liang Dong","doi":"10.1016/j.jum.2024.12.001","DOIUrl":"10.1016/j.jum.2024.12.001","url":null,"abstract":"<div><div>Despite the presence of literature on just transitions in cities, the knowledge gap exists in analyzing the evolving trends and trajectories of justice themes in urban transitions. This study develops a comprehensive analytical framework to identify the emerging research trends related to urban just transition by using LDA. Based on the socio-ecological-technological system (SETS) analytical framework and justice-related theoretical frameworks, this research examines the evolving characteristics and prominent issues in existing studies on just transition in urban contexts. We find that the E-T dimension within SETS is receiving increasing attention from researchers, while the inclusiveness and restorativeness dimensions within urban justice are more specifically analyzed. The study not only identifies the complex trends and dynamic changes in the process of urban just transition but also identifies key research areas for future investigations. It provides scholars and practitioners in the field of urban transformation with valuable insights and references, aiming to foster the development of more sustainable and just urban areas.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 485-499"},"PeriodicalIF":3.9,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial structure and mechanism of cross-city patient mobility network in the Yangtze River economic belt of China","authors":"Bowen Xiang ,&nbsp;Mengyao Hong ,&nbsp;Fang Guo ,&nbsp;Wei Wei","doi":"10.1016/j.jum.2024.11.013","DOIUrl":"10.1016/j.jum.2024.11.013","url":null,"abstract":"<div><div>Cross-city patient mobility reflects the geographic mismatch in medical resources, posing significant challenges for healthcare accessibility and equitable resource allocation. However, existing research methods inadequately capture the complex relationships between healthcare supply and demand as well as the proximity mechanisms influencing patient mobility. In this study, we used 500,120 patient online evaluations to build the 2023 Cross-city Patient Mobility Network (CPMN) for the Yangtze River Economic Belt (YREB), and analyzed its spatial structure and influencing factors using healthcare relative size index, dominant association analysis, and explainable machine learning modeling. The results show that: (1) There is a double logarithmic linear relationship between healthcare supply size and intensity (coefficient 0.627), and a weak negative correlation between demand size and intensity; (2) While the spatial organization of healthcare aligns with administrative boundaries and hierarchies, exceptions are observed in parts of Shanghai and Chongqing's healthcare catchment areas; (3) Social proximity, geographical proximity and institutional proximity are significant in patient mobility. This research contributes new data and methods to health geography and offers theoretical and empirical insights critical for optimizing healthcare resource allocation in the YREB, ultimately addressing the challenges of equitable healthcare access.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 562-576"},"PeriodicalIF":3.9,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive geospatial analysis of urban expansion dynamic in Lahore, Pakistan (1998–2023)","authors":"Sona Karim ,&nbsp;Yaning Chen ,&nbsp;Patient Mindje Kayumba ,&nbsp;Ishfaq Ahmad ,&nbsp;Hassan Iqbal","doi":"10.1016/j.jum.2024.11.012","DOIUrl":"10.1016/j.jum.2024.11.012","url":null,"abstract":"<div><div>Lahore, a UNESCO city in Pakistan, is projected to rise from the sixth to the third fastest-growing city worldwide by 2030. This rapid urbanization challenges its commitment to cultural and ecological preservation, positioning it as an international case study in urbanization research. Thus, the Lahore Development Authority emphasizes the need for ongoing monitoring of urban dynamics to support effective planning and achieve sustainability targets, including Sustainable Development Goal 11. To contribute, we used high-resolution Landsat imagery to analyze the spatial diverging patterns of urban extent from 1998 to 2023 in Lahore. Additionally, we employed a Cellular Automata (CA) Markov Chain model to project urban growth over the next 25 years. As of 2023, we estimated that approximately 53.6% (92,660.9 ha) of Lahore is urbanized, while 46.4% remains unaffected by urban activities. Projections for 2048 suggest that the urban footprint may expand to 75.8% (131,031.5 ha), leaving only 24.2% of the area free from urbanization. Our analysis also revealed divergent urban expansion patterns significantly impacting local ecosystems. It showed a 31% reduction in inland water bodies, a 39.8% loss of vegetation, and a 60.1% decrease in sparse areas, all attributable to urban development. As natural landscapes are replaced by built environments, Lahore is likely facing increasing challenges that could jeopardize the city's green growth and urban ecological balance. Therefore, we urge land use managers, urban planners, and stakeholders in Pakistan to promote initiatives that enhance urban resilience, particularly through smart city planning and creating green and blue spaces. By focusing on Lahore, this study also provides valuable insights that can serve as a benchmark for other rapidly urbanizing cities facing similar challenges.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 577-589"},"PeriodicalIF":3.9,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution logic of urban spatial growth governance and its enlightenment in China: From a perspective of spatial governance","authors":"Ju He ,&nbsp;Yongzhong Tan","doi":"10.1016/j.jum.2024.11.014","DOIUrl":"10.1016/j.jum.2024.11.014","url":null,"abstract":"<div><div>As the governance modernization and new-type urbanization deepens, China's urbanization process is gradually entering the \"second half\". Understanding the policy practices and transformation logic of China's urban spatial growth in a systematic perspective is significant in clarifying the enhancement path of future urban spatial growth governance. This study, based on the perspective of spatial governance, focuses on the basic elements of urban spatial growth governance such as goals, actors, methods, and objects. It comprehensively examines the evolution of China's urban spatial growth governance since the reform and opening-up, and analyzes the underlying logic of the transformation. The study finds that the governance of urban spatial growth in China has gone through four main stages, with the multidimensional shifts in governance goals, subject relations, governance methods, and spatial objects behind each stage constituting the basic storyline of governance evolution, influenced by a combination of macro environment, system reforms, spatial issues, and technological changes. In the future, clarifying the governance concepts of urban spatial growth in the new stage, shaping interactive and collaborative subject relations, improving institutional systems and innovative technological tools, and designing differentiated governance strategies based on the characteristics of spatial objects will become important directions for enhancing China's urban spatial governance capacity and even spatial governance modernization.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 590-606"},"PeriodicalIF":3.9,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of urban expansion susceptibility in major urban units of Bangladesh leveraging machine learning and geostatistical approach","authors":"Mafrid Haydar,&nbsp;Sakib Hosan,&nbsp;Al Hossain Rafi","doi":"10.1016/j.jum.2024.11.011","DOIUrl":"10.1016/j.jum.2024.11.011","url":null,"abstract":"<div><div>This study examines the governing factors and susceptibility zones for urban expansion in Bangladesh's major urban areas, including Dhaka, Barisal, Chittagong, Comilla, Narayanganj, Gazipur, Khulna, Sylhet, Rajshahi, Rangpur, and Mymensingh. The main goals of this research are to determine the impact of governing factors and to identify susceptibility zones for urban expansion in major urban units using a data-driven approach. By using governing factors (DEM, Slope, LST, NDVI, Population, distance to (industry, growth center, settlement, facilities, waterbody, road), and machine learning (Random Forest) and geostatistical approach (Binary Logistic Regression), the research identifies the most important factors influencing urban expansion, including NDVI, LST, waterbodies, roads, and settlements. The RF model's ROC-AOC values showed the highest accuracy (1.00) in Comilla and Mymensingh, moderate accuracy (0.99) in Barisal, Chittagong, Narayanganj, Gazipur, Khulna, and Rajshahi, and lower accuracy in Dhaka (0.98), Sylhet (0.89), and Rangpur (0.85). For the Binary Logistic Regression model, Comilla, Narayanganj, Gazipur, and Mymensingh had the best fit (Nagelkerke R² ​= ​1.00), while Sylhet had the lowest significance (0.482). Furthermore, Khulna, a major urban unit, is the highest urban expansion susceptibility zone which is 35.72%. Rajshahi and Barisal are the moderate and low urban expansion susceptibility where 83.17% and 0.88% respectively. This unplanned and rapid urban expansion zone has also confronted policymakers and planners with an insurmountable challenge and stressed local governments' ability to manage and use their scarce land-based resources with geospatial data. Thus, this study's machine learning and geostatistical findings will help explain land cover change and urban expansion in Bangladesh's eleven metropolitan areas. This study will improve urban development understanding in Bangladesh. Findings will help planners, stakeholders, and policymakers understand urban expansion patterns, enabling better environmental planning.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 451-467"},"PeriodicalIF":3.9,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying pareto frontier theory and ball tree algorithms to optimize growth boundaries for sustainable mountain cities","authors":"Lindan Zhang ,&nbsp;Guangjie Wang ,&nbsp;Li Peng ,&nbsp;Wenfu Peng ,&nbsp;Ji Zhang","doi":"10.1016/j.jum.2024.11.015","DOIUrl":"10.1016/j.jum.2024.11.015","url":null,"abstract":"<div><div>The terrain complexity of mountain cities often limits the rational layout and agglomeration distribution of newly added urban land. To this end, this paper proposes an innovative urban growth boundary optimization model —— Pareto Frontier theory and Ball-Tree algorithm optimized model (SP-BT). By treating newly added urban land as agents, the model dynamically optimizes the land patch locations based on the two goals of urban landscape compactness degree and suitability for urban construction. The SP-BT model is unique in that its optimal search and update process always unfolds along the Pareto front, achieving a balance between urban land agglomeration and suitability. In addition, compared with Suitability Optimum Evaluation Model (SOE), Artificial Neural Network in Cellular Automata (ANN-CA), and Ant Colony Optimization Model (ACO), the model has simplified parameter setting, fast evolution speed, flexible output results, and excellent defragmentation effect, especially suitable for mountain cities under complex terrain conditions. In the empirical study taking Bazhong city, China as an example: (1) SP-BT model significantly increased the mean size of urban landscape patch from 8.86 to 22.74–95.88, and the decrease of urban total suitability was controlled at 3.14%. (2) The SP-BT model excels in handling urban planning in mountainous cities, particularly in reducing landscape fragmentation, making it suitable for practical urban planning in mountainous environments. In general, the model proposed in this paper provides an efficient and flexible solution to the problem of new land use optimization under the complex terrain conditions of mountainous cities, which has important practical application value and can provide planners with more scientific and practical decision support tools.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 468-484"},"PeriodicalIF":3.9,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the efficacy of artificial intelligence based city-scale blue green infrastructure mapping using Google Earth Engine in the Bangkok metropolitan region","authors":"Md. Mehedi Hasan ,&nbsp;Malay Pramanik ,&nbsp;Iftekharul Alam ,&nbsp;Atul Kumar ,&nbsp;Ram Avtar ,&nbsp;Mohamed Zhran","doi":"10.1016/j.jum.2024.11.009","DOIUrl":"10.1016/j.jum.2024.11.009","url":null,"abstract":"<div><div>Urbanization disrupts natural water, energy, and nutrient cycles, but integrating green and blue infrastructures (BGI) can mitigate these effects by facilitating processes like evapotranspiration, soil water infiltration, and root nutrient absorption. In Bangkok Metropolitan Region (BMR), escalating urbanization poses challenges to these natural cycles. Mapping Land Use and Land Cover (LULC) and identifying green infrastructure locations are crucial for effective urban planning, sustainable development, and environmental conservation amidst rapid urban growth. Continuous monitoring of dynamic urban areas is time-consuming, labor-intensive, and costly. Previous research primarily focused on land use and land cover classification followed by BGI identification. An automated classification system focusing solely on BGI can greatly enhance efficiency, accuracy, and cost-effectiveness in land classification for urban planning and decision-making. However, automating this system remains a significant challenge for the remote sensing community. Therefore, the research is first to develop a cloud based artificial intelligence tools such as Smile Random Forest and Smile CART integration with Google Earth Engine (GEE) to identify BGI for BMR. For this analysis, we have used open-sources and mostly used satellite images (e.g., Landsat and Sentinel) and consider to analyze seasonal changes for waterbodies, natural vegetations and human intervened vegetations with developing cloud-based artificial intelligence (AI). Surprisingly, Landsat-9 data demonstrated superior accuracy compared to Sentinel-2, indicating that the advanced technology of Landsat 9 may be more effective for BGI classification using AI. The study revealed a most distinct transition from deep green to green infrastructures during the transition from summer to monsoon season, whereas significant changes in blue infrastructure occurred between the monsoon and winter seasons. Seasonal variations in BGI are complex and influenced by factors such as the types of BGI implemented and the nuances of local climatic conditions. These advancements could provide precise insights for urban managers and policymakers, offering valuable tools to identify and understand BGI dynamics across various urban scales.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 434-450"},"PeriodicalIF":3.9,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tracing the dual-circulation value chain: Measurement on the embedding characteristics and evidence from China","authors":"Yi Ren ,&nbsp;Jinniu Zhang ,&nbsp;Yuan Tian","doi":"10.1016/j.jum.2024.11.008","DOIUrl":"10.1016/j.jum.2024.11.008","url":null,"abstract":"<div><div>The rational allocation of value chain space can effectively promote regional development. In China, various regions have optimized their National Value Chain (NVC) by participating in the Global Value Chain (GVC), forming a structure of Dual-Circulation Value Chain (DCVC) dominated by NVC. This study aims to integrate multiple analytical models to construct an analytical method for studying the DCVC, thereby addressing the existing gaps in the literature in this field. When considering each province in China as the research subject, the following conclusions can be drawn: ①Point analysis results indicate that provinces such as Beijing and Jiangsu excel in connecting domestic and international markets, while resource-rich regions like Tibet and Xinjiang exhibit lower coupling between the NVC and the GVC. Coastal cities such as Shanghai and Guangdong are primarily situated in the mid-to-downstream segments, closely linked to the GVC; in contrast, resource-rich areas like Xinjiang and Shanxi predominantly occupy upstream positions. The effects of value creation and value transfer contribute to the relatively low value rate of return in provinces such as Beijing and Jiangsu. ②Area analysis further reveals that the coupling degree of the dual circulation value chain presents an east-to-west gradient, with domestic circulation as the dominant component, gradually forming a structure centered on the domestic cycle. The division of labour in the value chain is linear: inland areas focus on upstream resource production, central regions emphasize primary processing, and coastal areas are concentrated in downstream manufacturing and trade. Overall, the value chain return decreases from west to east, indicating that despite higher production levels in coastal regions, actual profits remain relatively low.</div></div>","PeriodicalId":45131,"journal":{"name":"Journal of Urban Management","volume":"14 2","pages":"Pages 418-433"},"PeriodicalIF":3.9,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}