Pub Date : 2024-11-08DOI: 10.1016/j.cities.2024.105556
Anna Długozima , Ewa Kosiacka-Beck , Katarzyna Krzykawska
In recent years, the notions of European identity, values and heritage have been put on the public agenda. Cemeteries construct ‘European significance’. Eastern Europe is lacking in terms of research and the social use of cemeteries, where these sites are treated as strictly separate ‘gardens of silence’. As cities become denser, green spaces are in danger of decreasing. Cemeteries in Eastern Europe have an untapped green potential. How can the potential of cemeteries be used? What solutions can be implemented to shape the cemetery in Eastern Europe within a multifunctional paradigm? The countries included in this study share the same broad religious cultural heritage shaped by varied Christian traditions: Poland, Slovenia, Hungary, Lithuania, Croatia. A review of multiple case studies of burial sites in Poland and abroad allowed for the creation and compilation of a set of practises related to structure, functions and social role of cemeteries. Moreover, the Scenic Beauty Estimation method was used to determine social preferences regarding the perception of the cemeteries appearance. To highlight the societal value of cemeteries, the concept of a multifunctional municipal cemetery in Gniezno (Poland) was designed.
{"title":"Multiuse Cemetery Paradigm: Cemetery as a multifunctional place of social significance – Reshaping a cemetery in the urban space of Eastern Europe","authors":"Anna Długozima , Ewa Kosiacka-Beck , Katarzyna Krzykawska","doi":"10.1016/j.cities.2024.105556","DOIUrl":"10.1016/j.cities.2024.105556","url":null,"abstract":"<div><div>In recent years, the notions of European identity, values and heritage have been put on the public agenda. Cemeteries construct ‘European significance’. Eastern Europe is lacking in terms of research and the social use of cemeteries, where these sites are treated as strictly separate ‘gardens of silence’. As cities become denser, green spaces are in danger of decreasing. Cemeteries in Eastern Europe have an untapped green potential. How can the potential of cemeteries be used? What solutions can be implemented to shape the cemetery in Eastern Europe within a multifunctional paradigm? The countries included in this study share the same broad religious cultural heritage shaped by varied Christian traditions: Poland, Slovenia, Hungary, Lithuania, Croatia. A review of multiple case studies of burial sites in Poland and abroad allowed for the creation and compilation of a set of practises related to structure, functions and social role of cemeteries. Moreover, the Scenic Beauty Estimation method was used to determine social preferences regarding the perception of the cemeteries appearance. To highlight the societal value of cemeteries, the concept of a multifunctional municipal cemetery in Gniezno (Poland) was designed.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105556"},"PeriodicalIF":6.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-07DOI: 10.1016/j.cities.2024.105513
Mathieu Feagan , Tischa A. Muñoz-Erickson , Robert Hobbins , Kristin Baja , Mikhail Chester , Elizabeth M. Cook , Nancy Grimm , Morgan Grove , David M. Iwaniec , Seema Iyer , Timon McPhearson , Pablo Méndez-Lázaro , Clark Miller , Daniel Sauter , William Solecki , Claudia Tomateo , Tiffany Troxler , Claire Welty
With increasing frequency and severity, coastal cities are facing the effects of extreme weather events, such as sea-level rise, storm surges, hurricanes, and various types of flooding. Recent urban resilience scholarship suggests that responding to the cascading complexities of climate change requires an understanding of cities as social-ecological-technological systems, or SETS. Advances in data visualization, sensors, and analytics are making it possible for urban planners to gain more comprehensive views of cities. Yet, addressing climate complexity requires more than deploying the latest technologies; it requires transforming the institutional knowledge systems upon which cities rely for preparation and response in a climate-changed future. While debates in the theory and practice of knowledge co-production offer a rich contextual starting point, there are few practical examples of what it means to co-produce new knowledge systems capable of steering urban resilience planning in fundamentally new directions. This paper helps address this gap by offering a case study approach to co-producing new knowledge systems for SETS data visualization in three US coastal cities. Through a series of innovation spaces – dialogues, labs, and webinars – with residents, data experts, and other city stakeholders from multiple sectors, we show how to apply a knowledge systems approach to better understand, represent, and support cities as SETS. To illustrate what a redesigned knowledge system for urban resilience planning entails, we document the key steps and activities that led to a new prototype SETS platform that works with a wider range of ways of knowing – including community-based expertise, interdisciplinary research contributions, and various municipal actors' know-how – to build anticipatory capacity for visualizing and navigating the complex dynamics of a climate-changed future. Our findings point to new roles for activity-based learning, conflict, and SETS visualization technologies in connecting, amplifying, and reorganizing the knowledge assets of community perspectives previously ignored. We conclude with a new understanding of how innovation towards coastal city resilience resides within the co-production process for (re)designing knowledge systems to make them more robust and responsive to cross-sector and cross-city learning.
{"title":"Co-producing new knowledge systems for resilient and just coastal cities: A social-ecological-technological systems framework for data visualization","authors":"Mathieu Feagan , Tischa A. Muñoz-Erickson , Robert Hobbins , Kristin Baja , Mikhail Chester , Elizabeth M. Cook , Nancy Grimm , Morgan Grove , David M. Iwaniec , Seema Iyer , Timon McPhearson , Pablo Méndez-Lázaro , Clark Miller , Daniel Sauter , William Solecki , Claudia Tomateo , Tiffany Troxler , Claire Welty","doi":"10.1016/j.cities.2024.105513","DOIUrl":"10.1016/j.cities.2024.105513","url":null,"abstract":"<div><div>With increasing frequency and severity, coastal cities are facing the effects of extreme weather events, such as sea-level rise, storm surges, hurricanes, and various types of flooding. Recent urban resilience scholarship suggests that responding to the cascading complexities of climate change requires an understanding of cities as social-ecological-technological systems, or SETS. Advances in data visualization, sensors, and analytics are making it possible for urban planners to gain more comprehensive views of cities. Yet, addressing climate complexity requires more than deploying the latest technologies; it requires transforming the institutional knowledge systems upon which cities rely for preparation and response in a climate-changed future. While debates in the theory and practice of knowledge co-production offer a rich contextual starting point, there are few practical examples of what it means to co-produce new knowledge systems capable of steering urban resilience planning in fundamentally new directions. This paper helps address this gap by offering a case study approach to co-producing new knowledge systems for SETS data visualization in three US coastal cities. Through a series of <em>innovation spaces</em> – dialogues, labs, and webinars – with residents, data experts, and other city stakeholders from multiple sectors, we show how to apply a knowledge systems approach to better understand, represent, and support cities as SETS. To illustrate what a redesigned knowledge system for urban resilience planning entails, we document the key steps and activities that led to a new prototype SETS platform that works with a wider range of ways of knowing – including community-based expertise, interdisciplinary research contributions, and various municipal actors' know-how – to build anticipatory capacity for visualizing and navigating the complex dynamics of a climate-changed future. Our findings point to new roles for activity-based learning, conflict, and SETS visualization technologies in connecting, amplifying, and reorganizing the knowledge assets of community perspectives previously ignored. We conclude with a new understanding of how innovation towards coastal city resilience resides within the co-production process for (re)designing knowledge systems to make them more robust and responsive to cross-sector and cross-city learning.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105513"},"PeriodicalIF":6.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.cities.2024.105540
Alexander Rammert
This paper discusses the multifaceted challenges associated with translating the concept of human mobilities into practical application within the realm of international planning. Additionally, it introduces the utilization of a scientific index methodology as a viable solution to address these challenges. Although scientific indices are not commonly employed in planning practices, they prove to be well-suited for the structured operationalization of intricate phenomena, such as mobility. Following a concise theoretical overview, this paper systematically outlines the process of operationalizing a social science-based concept of mobility to create an index. To facilitate this endeavor, a theoretical framework for a Mobility Index is constructed, and a comprehensive list of essential indicators required for its computation is developed, drawing from international research. Subsequently, this spatial mobility index is computed using accessibility and user survey data from a district in Berlin, Germany. The outcomes of this index are then visually depicted on maps, offering a clear representation of disparities in mobility options across the studied area. Consequently, the mobility index introduces an innovative approach for planning professionals to identify variations in human mobilities within their study areas, facilitating more informed decision-making.
{"title":"Mapping mobility: Introduction of an index-based approach to understanding human mobilities","authors":"Alexander Rammert","doi":"10.1016/j.cities.2024.105540","DOIUrl":"10.1016/j.cities.2024.105540","url":null,"abstract":"<div><div>This paper discusses the multifaceted challenges associated with translating the concept of human mobilities into practical application within the realm of international planning. Additionally, it introduces the utilization of a scientific index methodology as a viable solution to address these challenges. Although scientific indices are not commonly employed in planning practices, they prove to be well-suited for the structured operationalization of intricate phenomena, such as mobility. Following a concise theoretical overview, this paper systematically outlines the process of operationalizing a social science-based concept of mobility to create an index. To facilitate this endeavor, a theoretical framework for a Mobility Index is constructed, and a comprehensive list of essential indicators required for its computation is developed, drawing from international research. Subsequently, this spatial mobility index is computed using accessibility and user survey data from a district in Berlin, Germany. The outcomes of this index are then visually depicted on maps, offering a clear representation of disparities in mobility options across the studied area. Consequently, the mobility index introduces an innovative approach for planning professionals to identify variations in human mobilities within their study areas, facilitating more informed decision-making.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105540"},"PeriodicalIF":6.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.cities.2024.105535
Yihan Zhu , Ye Zhang , Filip Biljecki
With people-centered approaches gaining prominence in urban development, studying urban public spaces from the user's perspective has become crucial for effective urban design, planning, and policy-making. The rapid advancement of Machine Learning (ML) techniques has enhanced the ability to analyze and understand user data in urban public spaces, such as usage patterns, activities, and public opinions. However, limited efforts have been made on a structured understanding of urban public spaces from the user's perspective. These knowledge gaps have also hindered the full realization of ML's potential in describing and analyzing urban public spaces. After systematically reviewing 319 relevant papers, this study analyzes ten dimensions of the user's perspective on urban public spaces and identifies three unaddressed issues: (1) interpretation of user's perception, (2) overlooked user demographics, and (3) data acquisition. In addition, this review also examines the applications of ML to these dimensions and their potential to tackle the three issues, and highlights two main opportunities to integrate ML for more rigorous and data-driven public spaces studies: (1) combining Computer Vision and Natural Language Processing in public spaces quality measurement and (2) investing in high-quality user data.
{"title":"Understanding the user perspective on urban public spaces: A systematic review and opportunities for machine learning","authors":"Yihan Zhu , Ye Zhang , Filip Biljecki","doi":"10.1016/j.cities.2024.105535","DOIUrl":"10.1016/j.cities.2024.105535","url":null,"abstract":"<div><div>With people-centered approaches gaining prominence in urban development, studying urban public spaces from the user's perspective has become crucial for effective urban design, planning, and policy-making. The rapid advancement of Machine Learning (ML) techniques has enhanced the ability to analyze and understand user data in urban public spaces, such as usage patterns, activities, and public opinions. However, limited efforts have been made on a structured understanding of urban public spaces from the user's perspective. These knowledge gaps have also hindered the full realization of ML's potential in describing and analyzing urban public spaces. After systematically reviewing 319 relevant papers, this study analyzes ten dimensions of the user's perspective on urban public spaces and identifies three unaddressed issues: (1) interpretation of user's perception, (2) overlooked user demographics, and (3) data acquisition. In addition, this review also examines the applications of ML to these dimensions and their potential to tackle the three issues, and highlights two main opportunities to integrate ML for more rigorous and data-driven public spaces studies: (1) combining Computer Vision and Natural Language Processing in public spaces quality measurement and (2) investing in high-quality user data.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105535"},"PeriodicalIF":6.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.cities.2024.105552
Xiaying Feng , Xiaoya Ma , Jianbo Lu , Qingyan Tang , Zihan Chen
In the pursuit of sustainable development, western China's underdeveloped regions may face challenges in balancing economic growth with the carrying capacity of resources and the environment. As a new driving force for economic transformation, whether the digital economy impacts sustainable development in the underdeveloped regions of western China is a worthy question for further empirical investigation. Using panel data from 12 provinces in western China's underdeveloped regions from 2011 to 2022, this study employs double machine learning to objectively assess the impact of the digital economy on sustainable development in these regions. The findings reveal that the digital economy considerably promotes sustainable development in western China's underdeveloped regions. Each dimension of the digital economy—digital infrastructure, digital industrialization, digitization of industry, and digital innovation—has a notable positive impact on sustainable development. Therefore, promoting industry's digital transformation in western China's underdeveloped regions and strengthening digital infrastructure construction can promote sustainable development in these regions.
{"title":"Assessing the impact of the digital economy on sustainable development in the underdeveloped regions of western China","authors":"Xiaying Feng , Xiaoya Ma , Jianbo Lu , Qingyan Tang , Zihan Chen","doi":"10.1016/j.cities.2024.105552","DOIUrl":"10.1016/j.cities.2024.105552","url":null,"abstract":"<div><div>In the pursuit of sustainable development, western China's underdeveloped regions may face challenges in balancing economic growth with the carrying capacity of resources and the environment. As a new driving force for economic transformation, whether the digital economy impacts sustainable development in the underdeveloped regions of western China is a worthy question for further empirical investigation. Using panel data from 12 provinces in western China's underdeveloped regions from 2011 to 2022, this study employs double machine learning to objectively assess the impact of the digital economy on sustainable development in these regions. The findings reveal that the digital economy considerably promotes sustainable development in western China's underdeveloped regions. Each dimension of the digital economy—digital infrastructure, digital industrialization, digitization of industry, and digital innovation—has a notable positive impact on sustainable development. Therefore, promoting industry's digital transformation in western China's underdeveloped regions and strengthening digital infrastructure construction can promote sustainable development in these regions.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105552"},"PeriodicalIF":6.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.cities.2024.105543
Jie Li , Jing Fu , Jun Gao , Rui Zhou , Zhenyu Zhao , Panpan Yang , Yang Yi
Urban green spaces (UGSs) are major settings of human–nature interaction and important to public well-being. Visitation and satisfaction are indicators that reflect the utilization degree of and feedback regarding UGSs. The focus of this study is to analyze the visitation and satisfaction characteristics of different types of UGSs, analyze the dominant factors affecting these indicators, and rank their importance to provide strategies for improving management. Here, 50 typical UGSs in Shanghai are selected. All-subset regression, hierarchical partitioning analysis and other methods are comprehensively used to explore the influencing factors. The results are as follows: 1) Comprehensive parks have the highest visitation rates, whereas community parks have the lowest visitation rates but the highest satisfaction rates. 2) UGS size has the greatest influence on visitation, followed by connectivity, building shape index, and edge density, with contributions of 69.35 %, 16.40 %, 8.50 %, and 5.75 %, respectively. 3) Transportation facility density and edge density have the greatest influences on satisfaction, with contributions of 51.49 % and 48.51 %, respectively. In this study, the applicability of using multisource data to analyze UGS attributes and their factors affecting visitation and satisfaction are demonstrated. Targeted strategies for constructing UGSs will help authorities plan and manage UGSs effectively.
{"title":"How do urban green space attributes affect visitation and satisfaction? An empirical study based on multisource data","authors":"Jie Li , Jing Fu , Jun Gao , Rui Zhou , Zhenyu Zhao , Panpan Yang , Yang Yi","doi":"10.1016/j.cities.2024.105543","DOIUrl":"10.1016/j.cities.2024.105543","url":null,"abstract":"<div><div>Urban green spaces (UGSs) are major settings of human–nature interaction and important to public well-being. Visitation and satisfaction are indicators that reflect the utilization degree of and feedback regarding UGSs. The focus of this study is to analyze the visitation and satisfaction characteristics of different types of UGSs, analyze the dominant factors affecting these indicators, and rank their importance to provide strategies for improving management. Here, 50 typical UGSs in Shanghai are selected. All-subset regression, hierarchical partitioning analysis and other methods are comprehensively used to explore the influencing factors. The results are as follows: 1) Comprehensive parks have the highest visitation rates, whereas community parks have the lowest visitation rates but the highest satisfaction rates. 2) UGS size has the greatest influence on visitation, followed by connectivity, building shape index, and edge density, with contributions of 69.35 %, 16.40 %, 8.50 %, and 5.75 %, respectively. 3) Transportation facility density and edge density have the greatest influences on satisfaction, with contributions of 51.49 % and 48.51 %, respectively. In this study, the applicability of using multisource data to analyze UGS attributes and their factors affecting visitation and satisfaction are demonstrated. Targeted strategies for constructing UGSs will help authorities plan and manage UGSs effectively.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105543"},"PeriodicalIF":6.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.cities.2024.105573
Ming Gao , Congying Fang
Cycling behavior significantly contributes to urban sustainability and enhances public health. However, revealing the relationship between the built environment and public cycling volume, particularly at the street scale, and achieving urban bicycle-friendly objectives remains a challenge due to a lack of large-scale quantitative methodologies and variability in estimation techniques. This study introduces a novel approach employing street-view imagery and machine learning technologies (specifically training deep learning models on large datasets) to overcome the limitations of traditional methods characterized by low efficiency and narrow geographic coverage. For the implementation of this method, we focus on the correlation between urban built environments and cycling volume using Amsterdam, known as a cycling haven, as a case study. The research identifies a dual interaction between street-level and surrounding greenery, manifesting in collaborative and competitive dynamics that jointly shape cycling volume. Moreover, the application of a 4D framework to assess built environments in relation to urban perceptual qualities shows significant correlations with cycling volume. To foster the development of bicycle-friendly cities and enhance public cycling practices, policymakers and urban planners may need to pay greater attention to multidimensional interventions in urban environments.
{"title":"Pedaling through the cityscape: Unveiling the association of urban environment and cycling volume through street view imagery analysis","authors":"Ming Gao , Congying Fang","doi":"10.1016/j.cities.2024.105573","DOIUrl":"10.1016/j.cities.2024.105573","url":null,"abstract":"<div><div>Cycling behavior significantly contributes to urban sustainability and enhances public health. However, revealing the relationship between the built environment and public cycling volume, particularly at the street scale, and achieving urban bicycle-friendly objectives remains a challenge due to a lack of large-scale quantitative methodologies and variability in estimation techniques. This study introduces a novel approach employing street-view imagery and machine learning technologies (specifically training deep learning models on large datasets) to overcome the limitations of traditional methods characterized by low efficiency and narrow geographic coverage. For the implementation of this method, we focus on the correlation between urban built environments and cycling volume using Amsterdam, known as a cycling haven, as a case study. The research identifies a dual interaction between street-level and surrounding greenery, manifesting in collaborative and competitive dynamics that jointly shape cycling volume. Moreover, the application of a 4D framework to assess built environments in relation to urban perceptual qualities shows significant correlations with cycling volume. To foster the development of bicycle-friendly cities and enhance public cycling practices, policymakers and urban planners may need to pay greater attention to multidimensional interventions in urban environments.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105573"},"PeriodicalIF":6.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Global studies show a disparity in subjective well-being (SWB) between urban and rural areas, though the evidence is mixed. Some research finds lower SWB in rural areas, while others suggest urban materialism also reduces happiness. If SWB is constrained more by environmental factors than by personal choices, addressing these disparities is crucial. Understanding their root causes is key to developing targeted interventions that enhance well-being and ensure equity across different living environments. Policies should prioritize improving well-being where it is most needed, rather than enhancing happiness where it is already high. Previous efforts focused on material improvements but haven't fully bridged the gap. Our study, using Gallup World Poll data and instrumental variable regression, highlights the importance of postmaterial values—such as freedom of choice, community attachment, and youth development—in reducing these disparities. Based on Inglehart's theory of human aspirations, our research shows that deficiencies in postmaterial values, especially in education quality, significantly lower rural well-being, widening the urban-rural SWB gap. This issue persists across countries with varying GDP levels, suggesting that improving access to postmaterial values in rural areas can effectively reduce these disparities. Our findings advocate for policy strategies that prioritize these values in rural communities to address SWB disparities.
{"title":"Postmaterial values contribute to and alleviate global well-being disparities: Evidence from Gallup world poll data","authors":"Sunbin Yoo , Junya Kumagai , Thierry Yerema Coulibaly , Shunsuke Managi","doi":"10.1016/j.cities.2024.105510","DOIUrl":"10.1016/j.cities.2024.105510","url":null,"abstract":"<div><div>Global studies show a disparity in subjective well-being (SWB) between urban and rural areas, though the evidence is mixed. Some research finds lower SWB in rural areas, while others suggest urban materialism also reduces happiness. If SWB is constrained more by environmental factors than by personal choices, addressing these disparities is crucial. Understanding their root causes is key to developing targeted interventions that enhance well-being and ensure equity across different living environments. Policies should prioritize improving well-being where it is most needed, rather than enhancing happiness where it is already high. Previous efforts focused on material improvements but haven't fully bridged the gap. Our study, using Gallup World Poll data and instrumental variable regression, highlights the importance of postmaterial values—such as freedom of choice, community attachment, and youth development—in reducing these disparities. Based on Inglehart's theory of human aspirations, our research shows that deficiencies in postmaterial values, especially in education quality, significantly lower rural well-being, widening the urban-rural SWB gap. This issue persists across countries with varying GDP levels, suggesting that improving access to postmaterial values in rural areas can effectively reduce these disparities. Our findings advocate for policy strategies that prioritize these values in rural communities to address SWB disparities.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105510"},"PeriodicalIF":6.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-05DOI: 10.1016/j.cities.2024.105538
He Yue , Y. Wei , H. Yuan , H. Li
This study shows how smart city development revitalizes urban industrial heritage (UIH) and traditional industrial areas, especially by fostering public trust in government through open big data analysis. Rapid urbanization and industrialization have led to the degradation of many old industrial areas, causing urban decay and environmental concerns. However, smart city technologies show new opportunities for rejuvenating these locations, transforming them into vibrant, sustainable, and livable environments. The research shows challenges faced by UIH, such as outdated infrastructure, pollution, and neglect, and explores how smart city technologies can enhance resource efficiency, mobility, connectivity, and the built environment. It indicates the potential of open big data analysis to foster transparency and accountability, thereby enhancing public trust in government efforts. Various international examples of smart city initiatives illustrate the benefits of these technologies, stressing the importance of community involvement to ensure the success and sustainability of revitalization efforts. Additionally, the study shows an artificial neural network (ANN) to analyze relationships among various parameters, showing its effectiveness in understanding complex functions, even with training data errors. By modeling the connections between aging infrastructure, pollution, and factors such as resource use and mobility, the research achieves high predictive accuracy. The study advocates for a holistic approach to urban revitalization that emphasizes social, economic, and environmental sustainability. It suggests that integrating smart city development with open big data analysis can transform urban industrial heritage into vibrant, resilient areas, effectively addressing 21st-century challenges and enhancing public trust in government initiatives.
{"title":"Revitalizing urban industrial heritage: Enhancing public trust in government through smart city development and open big data analysis using artificial neural network (ANN) modeling","authors":"He Yue , Y. Wei , H. Yuan , H. Li","doi":"10.1016/j.cities.2024.105538","DOIUrl":"10.1016/j.cities.2024.105538","url":null,"abstract":"<div><div>This study shows how smart city development revitalizes urban industrial heritage (UIH) and traditional industrial areas, especially by fostering public trust in government through open big data analysis. Rapid urbanization and industrialization have led to the degradation of many old industrial areas, causing urban decay and environmental concerns. However, smart city technologies show new opportunities for rejuvenating these locations, transforming them into vibrant, sustainable, and livable environments. The research shows challenges faced by UIH, such as outdated infrastructure, pollution, and neglect, and explores how smart city technologies can enhance resource efficiency, mobility, connectivity, and the built environment. It indicates the potential of open big data analysis to foster transparency and accountability, thereby enhancing public trust in government efforts. Various international examples of smart city initiatives illustrate the benefits of these technologies, stressing the importance of community involvement to ensure the success and sustainability of revitalization efforts. Additionally, the study shows an artificial neural network (ANN) to analyze relationships among various parameters, showing its effectiveness in understanding complex functions, even with training data errors. By modeling the connections between aging infrastructure, pollution, and factors such as resource use and mobility, the research achieves high predictive accuracy. The study advocates for a holistic approach to urban revitalization that emphasizes social, economic, and environmental sustainability. It suggests that integrating smart city development with open big data analysis can transform urban industrial heritage into vibrant, resilient areas, effectively addressing 21st-century challenges and enhancing public trust in government initiatives.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105538"},"PeriodicalIF":6.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-05DOI: 10.1016/j.cities.2024.105559
Chao Li, Shunsuke Managi
Community attachment and livability have been identified as critical factors impacting people's willingness to pay for environmental activities. However, the concrete interactions among spending on environmental activities, income, community attachment, and livability remain inconclusive. Herein, we demonstrate their complex associations by employing an extreme gradient boost model, the SHapley Additive exPlanation (SHAP) method, and linear connections between variable contributions and their real values through a global dataset containing 100,956 observations. We linearly link SHAP values and real values to generalize the relationships and estimate the impacts of community attachment and community livability on the connections. Our findings suggest that individuals with strong community attachment and high incomes are most likely to allocate additional funds for environmental activities and that high community attachment strengthens the relationship between income and spending on environmental activity. A 1 % improvement in community attachment has the same effect on environmental activity willingness as a 6.683 thousand USD/year increase in household income. Conversely, residents in more livable environments tend to spend less on such activities, and greater community livability weakens the effects of income. A 1 % increase in livability is equivalent to a decrease of 1.462 thousand USD/year in household income. Our research underscores potential strategies to encourage participation in environmental activities and build a sustainable society, including improving community attachment and expanding people's horizons regarding environmental issues.
{"title":"Impacts of community attachment and community livability on environmental activity according to XGBoost and SHAP","authors":"Chao Li, Shunsuke Managi","doi":"10.1016/j.cities.2024.105559","DOIUrl":"10.1016/j.cities.2024.105559","url":null,"abstract":"<div><div>Community attachment and livability have been identified as critical factors impacting people's willingness to pay for environmental activities. However, the concrete interactions among spending on environmental activities, income, community attachment, and livability remain inconclusive. Herein, we demonstrate their complex associations by employing an extreme gradient boost model, the SHapley Additive exPlanation (SHAP) method, and linear connections between variable contributions and their real values through a global dataset containing 100,956 observations. We linearly link SHAP values and real values to generalize the relationships and estimate the impacts of community attachment and community livability on the connections. Our findings suggest that individuals with strong community attachment and high incomes are most likely to allocate additional funds for environmental activities and that high community attachment strengthens the relationship between income and spending on environmental activity. A 1 % improvement in community attachment has the same effect on environmental activity willingness as a 6.683 thousand USD/year increase in household income. Conversely, residents in more livable environments tend to spend less on such activities, and greater community livability weakens the effects of income. A 1 % increase in livability is equivalent to a decrease of 1.462 thousand USD/year in household income. Our research underscores potential strategies to encourage participation in environmental activities and build a sustainable society, including improving community attachment and expanding people's horizons regarding environmental issues.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"156 ","pages":"Article 105559"},"PeriodicalIF":6.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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