Zooming in and out of compact urban centers in a rapidly developed metropolis: A multi-scale investigation through isobenefit lens in Seoul

Zooming in and out of compact urban centers in a rapidly developed metropolis: A multi-scale investigation through isobenefit lens in Seoul | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Zooming in and out of compact urban centers in a rapidly developed metropolis: A multi-scale investigation through isobenefit lens in Seoul Juhyun lee, Jiwon Lee, Moonhyun Lee, Tae-Hyoung Tommy Gim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6942294/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Compact city policy in rapidly developed metropolitan areas increasingly emphasizes balanced urban development. Cities like Seoul have pursued the balanced distribution of livability opportunities by expanding public transport networks and promoting multiple socio-economic hubs at key transit nodes – so called compact multi-centered urban policy. However, critical evaluations of whether and how such models fully achieve their intended outcomes, especially essential service and infrastructure across diverse localities remain limited. Aligned with the concept of isobenefit cities , this research develops and applies a Multi-Scale Investigation (MSI) as an integrative evaluation tool to assess social outcomes from compact multi-centered cities. Specifically, the MSI framework holistically investigates two interrelated dimensions: local service accessibility and city-wide connectivity by public transport, by “zooming in and out” socio-economic centers located at strategic nodes across a city. We applied this framework to evaluate varied Centers across the Seoul Metropolitan City, an exemplar of rapid urban growth and a compact polycentric urban policy. The MSI analysis revealed that while all selected centers exhibited strong city-wide connectivity, local service accessibility often fell short of expectations, primarily due to negative local-scale effects such as limited service diversity constrained mobility. Differences across varied center typologies were particularly noteworthy. The Central Business District (CBD) exhibited the highest level of city-wide connectivity but the lowest local accessibility, indicating a pronounced imbalance. The Quarter Center scored the lowest overall, suggesting its limited role as a hub of the quarter area. In contrast, the District Center achieved the highest MSI result, reflecting relatively stronger local outcomes. The MSI analysis exposes scalar tensions embedded within the isobenefit assumptions when applied to rapidly developed metropolitan contexts. Our research underscores that achieving a balanced distribution of urban benefits requires multi-scalar approaches that incorporate distinctive, yet flexible measures tailored for the functional roles and spatial conditions of different center typologies. Social science/Development studies Social science/Geography Figures Figure 1 Figure 2 Figure 3 1. Introduction Across the globe, compact city has been considered to be key for sustainable urban development, particularly in rapidly developed cities. In general, it refers to the compactness of the built environment, which has the following main characteristics: high-density mixed-use development, well-linked efficient public transport systems, and easy access to public amenities and job opportunities (Tan and Rinaldi, 2019 ). Increasingly, compact city planning is promoted for its potential to facilitate balanced urban development of metropolitan cities that experienced the excessive concentration of development in a city core after rapid urban growth (Liu et al., 2019 ). Mega cities including Tokyo, Hong Kong, and Seoul have attempted to create a compact polycentric form to facilitate the balanced distribution of goods and services across main and sub-centers in a city (Li and Monzur, 2017). Creating effective transit networks and socio-economic centers around key nodes was encouraged as a strategy for greater accessibility across a metropolitan area (Appleyard et al., 2019 ; Park et al., 2020 ). However, limited studies critically explore if the compact multi-centered urban model contributes to balanced distribution of essential services and infrastructure . In practice, social outcomes from such a model are rarely evaluated, especially in terms of its effects on social sustainability objectives including livability for all (Anabtawi, 2023 ). Notably, some scholars (e.g. Yang et al., 2012 ) have highlighted that the compact multi-center planning can inadvertently lead to the overconcentration of infrastructure investment and land development in certain areas, exacerbating disparities between major centers and others in more peripheral or underdeveloped zones. These concerns resonate with the normative framework of Isobenefit Cities , which emphasizes that every urban resident should enjoy an equivalent access to key urban benefits including public amenities, green spaces, and essential service, regardless of location (D’Acci, 2013 ). Such a framework urges planners to reconsider a comprehensive evaluation of livability opportunities (e.g. healthcare, recreational facilities, education) across designated urban centers of a metropolitan city as a social outcome . To investigate the social outcome, this paper establishes an integrative examination of socio-economic hubs – i.e. designated (sub)centers around key transport nodes across a city (Lee et al., 2021 ). These hubs are expected to serve both as service-providing localities and as gateways connected to other areas via public transit (Lim and Kim, 2011 ). Nevertheless, in practice, some hubs (e.g. particularly those located in a central part of a city) may not provide the greatest access to a wide range of local facilities (e.g. parks) while they are effectively connected to the whole urban area (Jang et al., 2017 ), or vice versa. In this context, to thoroughly evaluate the social outcomes, each hub needs to be holistically assessed in terms of both (i) city-wide connectivity and (ii) local-service accessibility, rather than either dimension alone. We posit that such an integrative, muti-scale investigation is critical to address the heterogeneity existing across centers within the compact polycentric development strategies. This research aims to develop and test a multi-scale investigation (MSI) framework as an evaluation tool for compact city policies that particularly promote balanced livability opportunities in rapidly-developed metropolitan contexts. Aligning with the isobenefit urbanism (D’Acci, 2019 ), our integrative framework zooms in and out socio-economic centers at key transit nodes, focusing on two core dimensions: local service accessibility and city-wide connectivity via public transport. We apply our MSI framework to evaluate the case of Seoul – an exemplar of a metropolis that experienced mounting pressure from its rapid growth and attempted a compact multinucleated urban policy to promote balanced spatial development (SMG, 2014). By nature, the analysis is comparative and center-sensitive, assessing (in)balance across different node types and scales. This research offers critical reflection on whether and to what extent compact, polycentric development strategies can genuinely deliver livability opportunities in an even and inclusive manner. 2. Developing a multi-scale investigation (MSI) framework 2.1 Social outcomes from a compact polycentric city: A multi-scale perspective on urban centers Amid ongoing urbanization, cities have expanded both physically and functionally across a wider metropolitan region, intensifying the need for a more effective and balanced distribution of urban services (ADBI, 2017). In practical terms, this requires rethinking urban layouts to ensure that amenities such as schools, healthcare, shops, parks cultural sites, as well as employment opportunities are not overly concentrated in a single district while remaining scarce in others. Instead, these urban benefits should be more evenly distributed, as envisioned in the concept of “isobenefit” cities (D’Acci et al., 2019). In response, compact city policies of a metropolis have increasingly emphasized high-density mixed-use development clustered around major transport nodes, supported by an effective public transport network (e.g. compact multi-centered urban development model) (Arvin and Pourahmad, 2021). Such policies aim to facilitate balanced livability opportunities across the main and sub-centers of a city by fostering a compact polycentric form (SMG, 2014). However, recent studies pointed out that in practice, rapidly developed mega cities such as Seoul found it challenging to fully achieve the desired intended outcomes, especially, distribution of essential services and infrastructure across varied localities (Lee et al., 2021 ; Aguilar and Hernandez-Lozano, 2024 ). First, investment in urban public transport does not necessarily guarantee greater accessibility for all. Recent studies (e.g. Beier, 2020 ) showed that urban transport development often induces varied patterns of spatial changes across a city over time, thus leading to differential outcomes among different urban communities. For example, in the Central Business District (CBD), high-density commercial development continuously takes place around transport nodes, attracting further investment in public transport infrastructure (Wegner and Fuerst, 2004). In contrast, in the center(s) of the periphery, with relatively little spatial development around nodes, further transport development could be limited (Yang et al., 2012 ). Consequently, in the long-term, the gap in the city-wide connectivity by public transport between nodes in main center and other sub centers could gradually increase, potentially affecting inequity across a metropolitan area (Lee et al., 2020 ). Encouraging primarily high-density mixed-use development and pedestrian access around key transport nodes may not always lead to enhancing access to local amenities and public facilities, either. For example, some studies (e.g. Byrne et al., 2010 ) showed that the central business district often provides limited opportunity to enjoy recreational and green space because high-density commercial development is increasingly concentrated around key nodes. Furthermore, development around the key nodes may increase traffic congestion, affecting movements of local communities (Zhu et al., 2018 ). Over a long time, unbalanced access to public amenities could be observed among different urban communities. Overall, compact multi-centered city policies need to carefully consider the issues relating to unbalanced distribution of the desired outcomes at both city and local scales. Recent studies on compact, transit-oriented urban development increasingly focused on differential outcomes (e.g. health and education) across a city (e.g. Appleyard et al., 2019 ; Jun, 2020 ). However, a comprehensive multi-scale investigation into the aforementioned-distributional issues among centers remain limited, particularly in terms of policy impacts across varied types of centers. For example, studies examining differential accessibility issues often focused either on local-level outcomes – e.g. retail and service accessibility (non-work trips) at a local scale or street connectivity within designated centers (Hajrasouliha and Yin, 2015 ) or at city-level – e.g. distribution of commuting trips at a metropolitan scale or travel time to central urban cores (Jang and Yi, 2021; Tiznado-Aitken et al., 2023 ). Moreover, studies addressing differential outcomes across (sub)centers often pay limited attention to the varying roles and socio-economic contexts of the centers. They tend to overlook the distinct characteristics of centers, which may differ significantly in terms of location, dominant commercial functions, development stage, and the coverage of residential areas (Hu et al., 2020 ). More comprehensive investigation on long-term, local-scale effects at centers – such as how varying levels of congestion shape local mobility in different centers (Lee et al., 2020 ; Zhu et al., 2018 ) – needs to be considered. In short, this related body of work does not necessarily provide a thorough understanding of the social outcomes from a compact multi-centered urban planning and policy in a rapidly developed metropolis. To assess how well different parts of the city are performing, there is a need for critically examining the city-level connectivity and the local-service accessibility in a much more holistic manner. 2.2 Measurements of multi-scale investigation (MSI) The MSI is designed to evaluate varied socio-economic hubs within a city by examining two interrelated dimensions of livability: (1) city-wide connectivity and (2) local-service accessibility. This dual focus reflects the core principles of isobenefit urbanism, which posits that a truly livable city requires both networked opportunities (macro connectivity) and equitable local service in daily life (micro connectivity) for all communities (D’Acci et al., 2024 ). By “zooming in and out” of a designated center or hub, MSI enables an integrated assessment of each center’s overall performance in providing urban benefits. The details of MSI measurements are explained below. City-wide connectivity by public transport Having an efficient public transport system across a metropolitan area is vital for effective and equitable distribution of (access to) livelihood opportunities (OECD, 2012 ). Hyper connectivity between centers – acheived through high-capacity transit networks (e.g. metro) – allows even smaller districts can access the employment and specialized amenities of distance areas (D’Acci et al., 2024 ). Compact multi-centered city planning and evaluation needs to consider if key transport nodes are well connected within the public transport network, enabling passengers at each node to effectively reach jobs and services across a city. In MSI, centrality (i.e. the extent to which a node is connected to the whole network) is an important concept for measuring the city-wide connectivity of transport networks (e.g. Derrible, 2012 ; Háznagy et al., 2015 ). Betweenness centrality (BC) and Degree centrality (DC) can be considered to capture the importance of a node within a network. Betweenness represents the degree of which nodes stand between each other. BC measures the number of times a node lies on the shortest path between other nodes within a network (Freeman, 1978). High level of BC means that a node plays an important role as a bridge to minimize time and/or distance of movement (Porta et al., 2009 ). \(\:{g}_{ij}\) is the number of shortest paths that connect node i and j, and \(\:{g}_{ij}\left(k\right)\) is the shortest path that passes node k between nodes i and j. Weighting of travel time between nodes can also be included-not shown in the equation below-to reflect that people prefer and choose routes that minimize travel time (Stradling, 2002 ). $$\:BC\:\left(k\right)=\:{\sum\:}_{i\ne\:j\ne\:k}^{}\frac{{g}_{ij}\left(k\right)}{{g}_{ij}}$$ Degree centrality is another important concept that has been used for evaluating the importance of a node. It is often used to measure the extent to which a node is connected to other nodes (Freeman, 1978). For the assessment of a public transport network, DC can be defined as a proportion of transport nodes directly connected to a node in question out of the totality of nodes within the network. To measure DC more accurately, Pagerank centrality, an algorithm to identify core nodes within a multilayer network, can be used for differentiating nodes according to the relative importance of each node (e.g. the number of passengers travelling between two nodes). (Page et al., 1999 ; Tu et al., 2018 ). When a network has n’ node, pagerank of Node ( \(\:{PR}_{i}\) ) can be: $$\:{PR}_{i}\left(t+1\right)=\:\alpha\:{\sum\:}_{j=1}^{N}{A}_{ji}\frac{{PR}_{j}\left(t\right)}{{h}_{j}}+\left(1-\alpha\:\right)\frac{1}{N},\:$$ \(\:{h}_{j}\) refers to out-neighbors of j in undirected and directed network and \(\:{A}_{ji}\) is the adjacency matrix. α is a damping factor(0 < a < 1). Node i conveys α of centrality to the out-neighbors of j equally. It distributes an average of (1-α) of its total scores to each node in the network. The ranking process starts with each node being given the same centrality, which goes on until a steady state is reached. The number of passengers boarding and alighting between stations can be considered for weighting, given that an area with high ridership indicates the importance of a node within a network (Ramli et al., 2014 ). Overall, with the assessment of both BC and DC, it is possible to determine the relative importance of transfer nodes within a public transport system, and to evaluate route and interchange capacity (Scheurer et al., 2006). The BC value shows the level of contribution (of a node) to an effective travel while the DC will show the level of actual usage of a node. Incongruence between the BC and the DC at a node may indicate disintegration between transport and land use planning (Lee et al., 2020 ). Local services accessibility Creating high-density mixed-use development and pedestrian access around key transport nodes is expected to facilitate easy access to local amenities and services, which could contribute to enhancing social activities and interaction (Kaido, 2006 ; OECD, 2012 ). Therefore, compact multi-centered city planning and evaluation should consider if in socio-economic hubs, a range of local services and facilities are provided especially within walking distance from the node so that people can easily use them in the daily routine (Dempsey et al., 2012 ). High local service accessibility means the center providing a share of benefits comparable to other areas. The gravity model has been one of the most widely used methods for estimating local-scale accessibility (Feng et al.,2023). It looks at movement from service points to population points and other factors affecting the movement (Gualiardo, 2004). The model of Talen and Anselin ( 1998 ), one of the most used gravity models, measures accessibility by considering distance (d ij ) between two points as well as the capacity (e.g. size) of facilities (S j ). Higher accessibility refers to shorter distance to facilities and greater availability of the facilities. $$\:{A}_{i}=\:{\sum\:}_{j}^{}\frac{{S}_{j}}{{d}_{ij}}$$ To measure the accessibility to local services from a transport node by the gravity model, the capacities of varied kinds of local facilities and amenities as well as distance between a node and facilities need to be considered. Local facilities and amenities include schools, libraries, basic medical services, sport facilities, parks, and security services, and local stores (e.g. grocery stores), which are vital for the livability of a local community (Yhee et al., 2020 ). The capacity can be measured by examining the gross floor area (i.e. sum of the floor area of each floor of a building) (Kang, 2014 ). It is important to set varied buffers from a transport node to comprehend the potential of walking to the services. 400m can be an ideal access coverage of public transit (i.e. approximately 5-minute walking distance) while 800m is approximately 10-minute walking distance (Yigitcanlar et al., 2007 ). 1600m can be a cycling or running scale (Xiao et al., 2015). Overall, the adopted gravity mode captures what kinds of local service at what capacities (unit: m²) are (not) located within walking and cycling distances from a transport node (unit: meter). Higher accessibility to local services means a wide range of local facilities with greater capacities can be reached on foot. Ultimately, the combined assessment of city-wide connectivity and local service accessibility offers a structured approach to measuring and comparing livability opportunities across different center types and locations. Comparative analysis of MSI results across socio-economic hub reveals center-specific challenges and policy implications into the distribution of livability as a social outcome from a compact city planning. This approach enables a deeper understanding of how the principles of isobenefit cities manifest in real metropolitan contexts. 3. Application of the MSI framework: A case of Seoul Metropolitan City 3.1 Assessment of Seoul Metropolitan City We tested our MSI framework, using a Seoul Metropolitan City (SMC), which can be an exemplar of rapidly developed cities that have experienced rapid economic and population growth and have promoted a compact city policy to achieve balanced urban development. Seoul had experienced socio-economic and environmental pressures from its rapid growth since the 1950s (Cho, 2005 ). It had seen continuously increasing employment growth concentrated in the center and severe traffic congestion, while its boundary expanded with growing population (SMG, 2015 ). The city implemented several policies and plans to achieve competitive and balanced development, attempting a high-density multinucleated city (Jun, 2020 ). In the official comprehensive urban plans (2011 and 2020), establishing an extensive transfer system and creating varied socio-economic hubs around key transport nodes were promoted for effective and even (access to) infrastructure and services (SMG, 1997 , 2006 ) (Fig. 1 ). The metropolis has continually extended its public transport networks (21 subway lines of 933.4 km as of 2021) (Korea Railroad, 2021 ). As of 2021, most trips in Seoul (61.4%) were made by public transport, and the subway had been the most used public transport – i.e. 64.66% of the trips (Seoul, 2022). The extensive development of subway networks had induced changes in spatial structure, land use, and physical environment of a city (Jin and Kim, 2017 ). Sources: Urbanrail. Net (a); adapted from Lee et al. (2016) (b) To conduct the MSI, we considered transport nodes that were located in Centers – i.e. socio-economic hubs across the city, designated by Seoul Metropolitan Government based on criteria such as centrality, development potentials, and available transit infrastructure and services (Fig. 1 ). The Centers were supposed to play roles of providing key socio-economic activities, as well as cultural and public services (SMG, 2011). They were categorized into three groups according to their key functions and roles: City Centers (CBD); Quarter Centers; and District Centers (SMG, 2011). Each group had a different focus and priority: City center to strengthen global and metropolitan competitiveness, Quarter center to balance residential and commercial function, and District center to increase commercial land use and enhance local access to varied amenities (Lee et al., 2021 ). We randomly selected one node from the Centers under each category. Then, we considered the validity of the samples by carefully reviewing the comprehensive urban plans of SMC and consulting with urban policy and planning experts of the city. To maintain anonymity, which was part of an informed consent agreement with discussants, selected nodes in the Centers were named A, B and C. First, to assess the city-wide connectivity, we collected data of five hundred twenty stops and twenty-one subway lines. To measure the centralities, ridership between subway stops and distance (time) between the stops were considered. For examining the ridership, we collected Origin and Destination (OD) data of September 19th in 2019 because the public transport ridership in 2020 was highly likely to be influenced by the COVID-19. For examining the distance and time between subway stops, we collected the distance data, then, using the data of scheduled speed of all the subway lines, we calculated travel time between subway stops. We used R version 4.1.2., analyzing centralities with tidygraph package (Pedersen, 2023 ). Second, to assess the local service accessibility, we considered various facilities including libraries, community sport facilities, public services, basic medical facilities, parks, schools, public safety facilities, and local traditional markets (Supplementary Table S1 ). Data (i.e. locations, numbers, and capacities of each type of facility) was collected from the Public Data Portal and the National Spatial Data Infrastructure Portal of Korea. The 400m, 800m, and 1600m buffers (of the selected transport nodes in the three Centers) were drawn on GIS and straight-line distance from the nodes to the identified facilities was calculated. In addition, although business facilities were not the scope of the assessment, we checked them on the GIS-based maps to understand dominant land use patterns of the selected Center. Furthermore, we checked the number of residents living within the 1600m buffer, using data from the Public Data Portal. The numbers within each area were 82,666 (A), 90,600 (B), and 88,311 (C), respectively, which indicated that the three areas had a similar level of demand for the local basic services and amenities. A schematic diagram depicting the MSI assessment is provided in Fig. 2 , which illustrates the assessment of city-wide connectivity of three selected nodes in the Centers of the SMC and the assessment of local service accessibility at each node together. Furthermore, this research corroborated the MSI with previous qualitative study using focus groups that had been conducted with elected local representatives in the three Centers (see Lee et al., 2021 for details). Elected local representatives were those local residents who were officially chosen to serve as leaders of the smallest administrative unit in Korea. The focus group participants have lived in the area for more than 15 years and have been involved in local spatial planning. There were eight focus group discussions (3 in A, 2 in B, and 3 in C), each of which had 5 or 6 people and lasted between 60 minutes to 90 minutes. Discussion centered on the long-term residents’ experiences and perceptions on the networked opportunities (macro connectivity) and local service accessibility (micro connectivity) in everyday life. Moreover, using the focus groups, we checked the extent to which traffic congestion and pedestrian crowding (owing to the concentration of commercial development around the selected node) influenced local services accessibility in daily life. 3.2 Multi-scale investigation Result City-wide connectivity by public transport The result of the city-wide connectivity assessment indicated the relative importance of the key transport nodes within the whole networks across the city (see Table 1 ). The BCs of A, B, and C were ranked top 7.31%, 34.81%, and 8.08% respectively, and DCs were ranked top 1.92%, 17.88%, and 14.04%. The assessment of BCs showed that among the three nodes, A was the most influential node, with only a little difference with C. If these nodes do not function, the travel time of many passengers could be considerably affected. The results of DC revealed that A had the highest connectivity to other nodes in the network, being most greatly used by urban populations. The higher DC of A (than the other two nodes) indicated a relatively higher concentration of activities around the node in the CBD. Table 1 BCs and DCs of A, B, and C BC (time weighted) Rank Rank (Top %) DC Pagerank (number of passengers weighted) Rank Rank (Top %) A. node in City Center 14,409 38 7.31 0.0084 10 1.92 B. node in Quarter center 4,725 181 34.81 0.0033 93 17.88 c. node in District center 13,813 42 8.08 0.0036 73 14.04 Our analysis indicated that the CBD played a role as a key bridge, being greatly connected to other nodes in the subway network of the SMC. The highest level of the centralities of the node in the CBD reflected the key function of the area as a major commercial center, which had the highest employment density in the city (Shin and Lee, 2012 ). The selected node in the District Center also appeared to have a high level of city-wide connectivity, which suggested that the area had been also visited or passed by a large population from a wide area. In particular, the high BC (top 8%) of the District Center showed that the node played an important role in facilitating effective trips across the metropolitan area. The node in the Quarter Center had the lowest values of both BC and DC. The centralities of the node in B being lower than the other two (especially C) suggested that the role of the designated Quarter Center as a socio-economic hub of the area might have been relatively limited. Furthermore, the difference between the BC rank (top 34.81%) and the DC rank (top 17.88%) of the node in the Quarter Center indicated that the subway network design might not have been supportive of the compact land use policy – i.e. key transport nodes to be integrated with high-density development in socio-economic hubs). All the focus group discussions consistently highlighted residents’ strong sense of city-wide connectivity, largely attributed to the effective subway network. Participants in all study areas emphasized the convenience and efficiency of reaching diverse destinations across the city via major public transit system, subway. However, a recurring issue was the limited availability of local transit options between subway nodes and residential areas, which discouraged some residents from fully utilizing the major network. This challenge was especially pronounced in the Quarter Center, where mobility was hindered by the low frequency and limited coverage of local transport services—ironically, even as the needs for movement increased with the gradual concentration of commercial development around the node. Residents living on the periphery of the catchment area often had no alternative but to rely on private cars or the limited services available near their homes. Local service accessibility. At all the selected areas, a limited number of local facilities and amenities was noted within the ideal access coverage of public transit (i.e. 400m from a node) (Fig. 3 ), in which the dominant land use was business and commercial. The majority of the facilities were located beyond walking distance. A had the least number of facilities both within 400m and between 400m and 800m, which indicated that the CBD area might have provided the least favorable setting for walking to essential services. B appeared to have the highest number of local facilities that locals could reach on foot. Table 2 shows the result of the adapted gravity analysis that considered the numbers and the capacities of the varied types of local facilities and amenities within each buffer. First, the analysis pointed out that within the 400m buffer, the Quarter Center had the highest accessibility (160.868) while the CBD had a much lower value (9.353) than the other two. The Quarter and the District Centers had some facilities such as libraries and public services whereas the CBD area did not provide any except parks. Second, the assessment of areas between 400m and 800m buffers revealed that the District Center had much higher accessibility (700.523) than the other two centers. The highest accessibility at C was attributed to a community park that included sports facilities of greatest capacity. The District Center provided the widest range of essential services, while A had the lowest accessibility (68.133), lacking basic facilities including medical facilities, sports facilities, and schools. Third, in cycling distance (between 800m and 1600m), accessibility in CBD and District Center appeared to be relatively high, particularly, to parks and community sport centers. Table 2 The result of the adapted gravity analysis CBD Quarter Center District Center 400m 4-800m 8-1600m 400m 4-800m 8-1600m 400m 4-800m 8-1600m Library 0 15.291 7.994 0 2.389 27.260 12.545 0.757 12.681 Community Sports facilities 0 0 0 0 0 237.833 0 668.479 15.266 Public services 0 16.474 13.833 0 3.102 37.572 7.676 0 4.792 Basic medical facilities 0 0 0.000 0 0 2.378 0 3.322 46.008 Parks 9.353 34.911 228.824 13.738 15.302 0.075 - 1.678 33.824 School 0 0 218.570 144.782 104.802 189.218 - 0.026 0.058 Public safety facilities 0 1.456 1.756 2.347 11.193 7.265 2.123 0.437 8.227 Local open market 0 0 0 0 0 22.743 0 25.824 0 Total 9.353 68.133 470.977 160.868 136.788 524.344 22.344 700.523 120.855 Walkable zone 77.486 470.977 297.656 524.344 722.867 120.855 Sums 548.463 822 843.722 Overall, the local-scale assessment revealed that the CBD area had the lowest accessibility to the essential services within walking distance. In the area, local service accessibility increased as the distance from the transport node increased (from 9.353 to 470.977), which indicated that most facilities were too far to walk from the subway station. The lowest accessibility around A could be attributed to the highest level of commercial activities and continuously increasing land price around nodes in CBD (Padeiro et al., 2019 ). In contrast, the District Centre had the highest accessibility, owing to the relatively higher number of varied facilities at a greater capacity, especially community sports facilities and basic medical facilities. Only in the District Center, accessibility within walking distance was higher than accessibility within cycling distance (area between 800m and 1600m buffers). The issues related to access to local services were well recognized by the focus groups in all the selected areas. Much concern about the limited access to local facilities within walking distance was repeatedly noted. The discussions also pointed out that there was limited local transport to reach the facilities (especially in CBD). The focus groups clearly identified that the local service accessibility might have been also affected by traffic and pedestrian congestion, especially near the major transit nodes. Participants emphasized that the concentration of commercial and business activities around a subway station created such congestion, affecting the ease of moving around in the area. Importantly, the intensity of these negative effects varied across the different Centers. In the CBD, the local expressed the extreme level of difficulty of walking due to overcrowding and parking on many pedestrian roads. In the Quarter Center, focus groups highlighted high levels of disruption to pedestrian movement in the immediate vicinity of the nodes, especially during commuting hours. By contrast, in the District Center, residents confirmed the moderate level of difficulty since the main streets had been widened and congestion was noted mainly in a few back streets. Our field observations aligned with these findings, confirming that congestion-related impacts were most pronounced around transit nodes. Interestingly, residents living on the periphery of the catchment areas reported greater satisfaction with their local quality of life, citing better accessibility to green space and local mobility compared to those closer to the transit nodes. Comparison of the MSI results The overall result of the MSI of Seoul (Table 3 ) reveals that despite strong transit connectivity across all centers, disparities in local access to amenities persist, particularly in high density commercial centers like CBD. The CBD area emerged as an extreme case of imbalance with the highest city-wide connectivity and the lowest local service accessibility at the same time. In other words, it excels at connecting people to distance opportunities but falls short in providing a rich mix of nearby daily-life services. People living in the inner city might have been greatly affected by varied difficulties in using essential services, although they benefited from the hyper connectivity. At the District Center level, the MSI results were more encouraging, showing a better balance. The Center appeared to have the highest MSI result since it combined the best local service accessibility with high transit connectivity (similar to CBD), functioning as both a local town center and a node in the transport network. Compared to the other two Centers, people living in the District Center were likely to have better chances of enjoying walking to a wide range of services at greater capacities before or after using the effective transport system. In contrast, the Quarter Center showed the most pronounced shortfall in the MSI evaluation. It had the lowest city-wide connectivity and only middling local accessibility. Such a lower MSI result suggests that the Quarter Center has not fully realized its intended role as a well-connected, vibrant regional hub. They are neither fully self-sufficient nor well-connected to the broader urban system. Table 3 MSI result of the SMC CBD Quarter Center District Center City-wide connectivity Between centrality 14,409 4,725 13,813 Degree centrality 0.00844 0.0033 0.00363 Rank (total) 1 (14,409) 3 (4,725) 2 (13,813) Local-service accessibility Access to local services (within walking distance) 548.463 (77.486) 822 (297.656) 843.722 (722.867) Ease of movement Very low Low Moderate Rank 3 2 1 The MSI result clearly indicated that the transit-oriented compact urban policy of Seoul did not fully achieve the long-standing desired social outcomes – i.e. balanced distribution of livability opportunities across the metropolitan area. The effort of Seoul contributed to balancing city-scale connectivity across the metropolis; however, it did not quite succeed in achieving great accessibility to local services in the hubs, which had been one of the aspirations of the city. Except the District Center, people living near transport nodes had experienced recognizable disadvantages – e.g. lack of a wide range of services and heightened local congestions, underscoring the critical need for localized mitigation strategies. The result implied that producing higher city-wide connectivity of key transport nodes alone could not guarantee the desired outcomes at local level as previously expected (Ewing and Cervero, 2010). Overall, it is difficult to conclude that the city accomplished its goal of the effective and even distribution of goods and services with its strategy of creating transit-oriented compact urban centers across a metropolitan area. 4. Discussion Our multi-scale investigation of compact urban centers engages with the complex nature of the distributional issues inherent in the compact multi-centered city model (Lee et al., 2020 ), analyzed through the lens of isobenefit urbanism. It shows that even in a metropolis like Seoul—where balanced livability is proactively pursued through transit-oriented compact planning—the isobenefit ideal remains unrealized across different spatial scales and center typologies. This persist imbalance highlights a fundamental scalar tension between macro-level connectivity and micro-level livability embedded in the practical application of the model. While development of effective transit networks and compact nodes is central, these efforts alone do not guarantee meaningful societal benefits, because of the limited effects at the local scale. As evidenced in Seoul, compact urban design around key transport nodes can result in multiple disadvantages for nearby residents, rather than delivering the anticipated health benefits or more social activities (e.g. Ewing and Cervero, 2010; Lang et al., 2020 ). CBD is not necessarily a winner, unlike numerous cases observed by previous research, because the highest city-wide connectivity at the CBD could be closely linked to the highest level of disadvantages. This paradox supports concerns that major centers could gradually experience the decline of living environment and main functions despite their connectivity strength (e.g. Han and Park, 2019). In contrast, District centers tend to offer a better quality of environs and access to essential activities while people living in the area still need to make frequent trips to join major activities in the CBD. Overall, these disparities highlight that not all centers fulfill their intended function as well-connected and self-sufficient hubs, underscoring the intra-urban heterogeneity masked by the broad application of the compact city model. The MSI result also reinforces ongoing debates that transport and land use coordination (TLC) remains fundamental for the effective and equitable provision of access to essential services and infrastructure (Appleyard et al., 2019 ) in rapidly developed cities. The analysis revealed a persistent accessibility mismatch between quality of infrastructure and proximity to facilities (Olaru and Curtis, 2015 ), whereby neighborhoods with a great standard of infrastructure (e.g. public transit with high centralities) do not have corresponding facilities nearby (e.g. public facilities) that locals may walk. This suggests that although the transport related goal of the compact city policy of Seoul has been achieved to some extent, transport planning and land use planning may not have been fully congruent. At both at macro and micro scales, barriers and opportunities to land use transport integration (Lee et al., 2020 ) should be carefully addressed to make significant advancements towards balanced distribution of livability and accessibility. In practice, achieving a balanced distribution of essential services solely through the development of a compact, multi-centered urban structure may be overly ambitious or uncertain—particularly in rapidly developed metropolises. Discussion on compact mega cities, especially in relation to social sustainability, must go beyond idealized urban forms or fixed notions of optimal density. Our analysis suggests that realizing a genuinely isobenefit city requires context-sensitive interventions that iteratively balance macro-level network integration with localized service provision, tailored to the different characteristics of each center typology. It is critical to pay much more attention how to address specific local issues and different planning priorities for each area when applying a compact polycentric city model (SMG, 2022 ). As indicated in the case of Seoul, in the CBD, interventions should focus on improving the quality of pedestrian roads and environs and reducing local traffic, especially in the vicinity of the major transit nodes, using measures such as parking space cab (SMG, 2022 ). In non-CBD areas, the priority should be enhancing local mobility by strengthening local-level transport networks – i.e. introducing shared mobility hubs or demand responsive transport in underserved areas (Kim, 2023 ), rather than implying focusing on increasing commercial activities around nodes. More broadly, our results highlight the importance of critically examining how to calibrate the balance between top-down planning and local spontaneity (D’Acchi et al., 2024). While centrally orchestrated infrastructure investments are essential to ensure baseline connectivity and metropolitan coherence, the lived quality of urban environments often emerges from localized spatial adaptations that address context-specific priorities (Lee, 2022 ). By revealing the persistent spatial and scalar mismatches that persist within a highly planned urban system, this study points out the need to embrace not only robust evaluative frameworks like MSI, but also more flexible and typology-specific planning logics that respect how livability emerges differently across and within diverse urban fabrics. In rapidly developed metropolises like Seoul, the challenge is not only to distribute urban benefits evenly but also to foster a hybrid governance approach: strategically coordinated at the metropolitan level, but open to local placemaking at the ground level. This paper presents a methodology for the multi-scale assessment of compact centers, offering a feasible and context-appropriate evaluation tool for rapidly developed metropolitan areas. The MSI framework serves not only as a diagnostic instrument for identifying urban disparities in accessibility and livability, but also as a critical mechanism for evaluating the extent to which current urban development strategies align with the normative goals of isobenefit urbanism. In particular, it integrates both objective, macro-level assessment with localized, subjective perspectives – capturing both the structural dimensions of connectivity and the lived experiences of residents. Building on the previous research (Lee et al., 2021 ), our study highlights the value of a mix-method approach to the holistic evaluation of social outcomes from a compact multi-centered city. While the quantitative assessment facilitates straight-forward comparison of differential outcomes at centers using official statistical data, the qualitative dimensions adds vital depth by capturing the local-scale effects experienced and perceived by the long-term residents. Together, these methods provide a more holistic understanding of the scalar mismatches and lived realities that shape the success or failure of compact multi-centered strategies. 5. Conclusion The compact multi-centered city model, as implemented in metropolises like Seoul, is not a silver bullet; it does not inherently produce equitable outcomes across spatial scales and social contexts, as envisioned by the isobenefit urbanism. Advancing this ideal requires multi-scalar and flexible approaches, tailored to the distinct roles and conditions of each center typology. In this regard, our MSI framework offers a replicable, evidence-based tool for planners and policymakers — particularly valuable in rapidly evolving metropolitan contexts where reconciling planning efficiency with social inclusivity remains a critical challenge. While MSI presents clear potential as a transferable framework, several considerations must be addressed in its future application. For instance, developing an index system may enhance the robustness of cross-city or intra-city comparisons — for example, through clustering analyses to classify the results of city-wide connectivity assessments. Moreover, MSI should be contextually grounded in the specific priorities, values, and cultural conditions of each city, recognizing the relational and situated nature of compact urbanism (Kjæret, 2021). Ultimately, this research affirms that advancing isobenefit urbanism requires more reflexive and balanced planning logics—one that meaningfully integrate mobility, land use, and everyday urban experiences in pursuit of equitable urban transformation. Declarations Competing interests The author(s) declares no competing interests Ethical approval Ethical clearance for this study was made by the Ethics Committee of the University of Groningen in 16th of December 2019 (Approval number: 2019-18). All procedures involving human participants were conducted in accordance with the ethical standards of the committee and the principles outlined in the Declaration of Helsinki. Informed consent Informed consent was obtained in writing from all participants prior to their involvement in the study. Consent was obtained by the lead researcher between January 2020 and March 2020, who provided participants with a detailed information sheet and answered any questions before participants signed the consent form. The scope of the consent covered participation in the study, the use of anonymised data for research analysis, and the publication of aggregated findings. Participants were informed that they could withdraw from the study at any point without any consequence. Funding statement This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF- 2021S1A3A2A01087370). 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1","display":"","copyAsset":false,"role":"figure","size":469444,"visible":true,"origin":"","legend":"\u003cp\u003eSubway networks (a) and designated centers (b) of Seoul Metropolitan City\u003c/p\u003e\n\u003cp\u003eSources: Urbanrail. Net (a); adapted from Lee et al. (2016) (b)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6942294/v1/704cb147074c137661a3629c.png"},{"id":91861826,"identity":"0ffc2cfd-b3d9-475e-b1d5-c8b1e6ca10ff","added_by":"auto","created_at":"2025-09-22 12:41:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":305120,"visible":true,"origin":"","legend":"\u003cp\u003eA simplified multi-scale investigation on centers: City-wide connectivity by public transport networks (left) and Local service accessibility to in Centers (right)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6942294/v1/6023c03a44d561579ad25347.png"},{"id":91861835,"identity":"40d32620-7992-4704-a5b1-a2c97c471a0c","added_by":"auto","created_at":"2025-09-22 12:41:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":405290,"visible":true,"origin":"","legend":"\u003cp\u003eLocal facilities within 400m, 800m, and 1600m from the key transport nodes [CBD (a); Quarter Center (b); District Center (c)]\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6942294/v1/ddfcdee4b3939bf2a7e32d81.png"},{"id":91862204,"identity":"6b600e5b-7c68-4392-ada5-4f5e036c38c5","added_by":"auto","created_at":"2025-09-22 12:49:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1880641,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6942294/v1/ff2f33d3-f696-4bdd-838c-8ce241a0c433.pdf"},{"id":91861849,"identity":"47454327-af4b-46d8-9795-c67c192fa0e4","added_by":"auto","created_at":"2025-09-22 12:41:16","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17201,"visible":true,"origin":"","legend":"","description":"","filename":"Supplymentarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6942294/v1/fbef4ddf601e0b83e9050e90.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eZooming in and out of compact urban centers in a rapidly developed metropolis: A multi-scale investigation through isobenefit lens in Seoul\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAcross the globe, \u003cem\u003ecompact city\u003c/em\u003e has been considered to be key for sustainable urban development, particularly in rapidly developed cities. In general, it refers to the compactness of the built environment, which has the following main characteristics: high-density mixed-use development, well-linked efficient public transport systems, and easy access to public amenities and job opportunities (Tan and Rinaldi, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Increasingly, compact city planning is promoted for its potential to facilitate balanced urban development of metropolitan cities that experienced the excessive concentration of development in a city core after rapid urban growth (Liu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Mega cities including Tokyo, Hong Kong, and Seoul have attempted to create a compact polycentric form to facilitate the balanced distribution of goods and services across main and sub-centers in a city (Li and Monzur, 2017). Creating effective transit networks and socio-economic centers around key nodes was encouraged as a strategy for greater accessibility across a metropolitan area (Appleyard et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Park et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, limited studies critically explore if the compact multi-centered urban model contributes to balanced distribution of \u003cem\u003eessential services and infrastructure\u003c/em\u003e. In practice, social outcomes from such a model are rarely evaluated, especially in terms of its effects on social sustainability objectives including livability for all (Anabtawi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Notably, some scholars (e.g. Yang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) have highlighted that the compact multi-center planning can inadvertently lead to the overconcentration of infrastructure investment and land development in certain areas, exacerbating disparities between major centers and others in more peripheral or underdeveloped zones. These concerns resonate with the normative framework of \u003cem\u003eIsobenefit Cities\u003c/em\u003e, which emphasizes that every urban resident should enjoy an equivalent access to key urban benefits including public amenities, green spaces, and essential service, regardless of location (D\u0026rsquo;Acci, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Such a framework urges planners to reconsider a comprehensive evaluation of livability opportunities (e.g. healthcare, recreational facilities, education) across designated urban centers of a metropolitan city as \u003cem\u003ea social outcome\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eTo investigate the social outcome, this paper establishes an integrative examination of socio-economic hubs \u0026ndash; i.e. designated (sub)centers around key transport nodes across a city (Lee et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These hubs are expected to serve both as service-providing localities and as gateways connected to other areas via public transit (Lim and Kim, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Nevertheless, in practice, some hubs (e.g. particularly those located in a central part of a city) may not provide the greatest access to a wide range of local facilities (e.g. parks) while they are effectively connected to the whole urban area (Jang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), or vice versa. In this context, to thoroughly evaluate the social outcomes, each hub needs to be holistically assessed in terms of both (i) city-wide connectivity and (ii) local-service accessibility, rather than either dimension alone. We posit that such an integrative, muti-scale investigation is critical to address the heterogeneity existing across centers within the compact polycentric development strategies.\u003c/p\u003e\u003cp\u003eThis research aims to develop and test a multi-scale investigation (MSI) framework as an evaluation tool for compact city policies that particularly promote balanced livability opportunities in rapidly-developed metropolitan contexts. Aligning with the \u003cem\u003eisobenefit urbanism\u003c/em\u003e (D\u0026rsquo;Acci, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), our integrative framework zooms in and out socio-economic centers at key transit nodes, focusing on two core dimensions: local service accessibility and city-wide connectivity via public transport. We apply our MSI framework to evaluate the case of Seoul \u0026ndash; an exemplar of a metropolis that experienced mounting pressure from its rapid growth and attempted a compact multinucleated urban policy to promote balanced spatial development (SMG, 2014). By nature, the analysis is comparative and center-sensitive, assessing (in)balance across different node types and scales. This research offers critical reflection on whether and to what extent compact, polycentric development strategies can genuinely deliver livability opportunities in an even and inclusive manner.\u003c/p\u003e"},{"header":"2. Developing a multi-scale investigation (MSI) framework","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Social outcomes from a compact polycentric city: A multi-scale perspective on urban centers\u003c/h2\u003e\u003cp\u003eAmid ongoing urbanization, cities have expanded both physically and functionally across a wider metropolitan region, intensifying the need for a more effective and balanced distribution of urban services (ADBI, 2017). In practical terms, this requires rethinking urban layouts to ensure that amenities such as schools, healthcare, shops, parks cultural sites, as well as employment opportunities are not overly concentrated in a single district while remaining scarce in others. Instead, these urban benefits should be more evenly distributed, as envisioned in the concept of \u0026ldquo;isobenefit\u0026rdquo; cities (D\u0026rsquo;Acci et al., 2019). In response, compact city policies of a metropolis have increasingly emphasized high-density mixed-use development clustered around major transport nodes, supported by an effective public transport network (e.g. compact multi-centered urban development model) (Arvin and Pourahmad, 2021). Such policies aim to facilitate balanced livability opportunities across the main and sub-centers of a city by fostering a compact polycentric form (SMG, 2014).\u003c/p\u003e\u003cp\u003eHowever, recent studies pointed out that in practice, rapidly developed mega cities such as Seoul found it challenging to fully achieve the desired intended outcomes, especially, distribution of essential services and infrastructure across varied localities (Lee et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Aguilar and Hernandez-Lozano, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). First, investment in urban public transport does not necessarily guarantee greater accessibility for all. Recent studies (e.g. Beier, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) showed that urban transport development often induces varied patterns of spatial changes across a city over time, thus leading to differential outcomes among different urban communities. For example, in the Central Business District (CBD), high-density commercial development continuously takes place around transport nodes, attracting further investment in public transport infrastructure (Wegner and Fuerst, 2004). In contrast, in the center(s) of the periphery, with relatively little spatial development around nodes, further transport development could be limited (Yang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Consequently, in the long-term, the gap in the \u003cem\u003ecity-wide connectivity by public transport\u003c/em\u003e between nodes in main center and other sub centers could gradually increase, potentially affecting inequity across a metropolitan area (Lee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEncouraging primarily high-density mixed-use development and pedestrian access around key transport nodes may not always lead to enhancing access to local amenities and public facilities, either. For example, some studies (e.g. Byrne et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) showed that the central business district often provides limited opportunity to enjoy recreational and green space because high-density commercial development is increasingly concentrated around key nodes. Furthermore, development around the key nodes may increase traffic congestion, affecting movements of local communities (Zhu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Over a long time, \u003cem\u003eunbalanced access to public amenities\u003c/em\u003e could be observed among different urban communities. Overall, compact multi-centered city policies need to carefully consider the issues relating to unbalanced distribution of the desired outcomes at both city and local scales.\u003c/p\u003e\u003cp\u003eRecent studies on compact, transit-oriented urban development increasingly focused on differential outcomes (e.g. health and education) across a city (e.g. Appleyard et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jun, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, a comprehensive multi-scale investigation into the aforementioned-distributional issues among centers remain limited, particularly in terms of policy impacts across varied types of centers. For example, studies examining differential accessibility issues often focused either on local-level outcomes \u0026ndash; e.g. retail and service accessibility (non-work trips) at a local scale or street connectivity within designated centers (Hajrasouliha and Yin, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) or at city-level \u0026ndash; e.g. distribution of commuting trips at a metropolitan scale or travel time to central urban cores (Jang and Yi, 2021; Tiznado-Aitken et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, studies addressing differential outcomes across (sub)centers often pay limited attention to the varying roles and socio-economic contexts of the centers. They tend to overlook the distinct characteristics of centers, which may differ significantly in terms of location, dominant commercial functions, development stage, and the coverage of residential areas (Hu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). More comprehensive investigation on long-term, local-scale effects at centers \u0026ndash; such as how varying levels of congestion shape local mobility in different centers (Lee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) \u0026ndash; needs to be considered.\u003c/p\u003e\u003cp\u003eIn short, this related body of work does not necessarily provide a thorough understanding of the social outcomes from a compact multi-centered urban planning and policy in a rapidly developed metropolis. To assess how well different parts of the city are performing, there is a need for critically examining the city-level connectivity and the local-service accessibility in a much more holistic manner.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Measurements of multi-scale investigation (MSI)\u003c/h2\u003e\u003cp\u003eThe MSI is designed to evaluate varied socio-economic hubs within a city by examining two interrelated dimensions of livability: (1) city-wide connectivity and (2) local-service accessibility. This dual focus reflects the core principles of isobenefit urbanism, which posits that a truly livable city requires both networked opportunities (macro connectivity) and equitable local service in daily life (micro connectivity) for all communities (D\u0026rsquo;Acci et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). By \u0026ldquo;zooming in and out\u0026rdquo; of a designated center or hub, MSI enables an integrated assessment of each center\u0026rsquo;s overall performance in providing urban benefits. The details of MSI measurements are explained below.\u003c/p\u003e\u003cp\u003e\u003cem\u003eCity-wide connectivity by public transport\u003c/em\u003e\u003c/p\u003e\u003cp\u003eHaving an efficient public transport system across a metropolitan area is vital for effective and equitable distribution of (access to) livelihood opportunities (OECD, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Hyper connectivity between centers \u0026ndash; acheived through high-capacity transit networks (e.g. metro) \u0026ndash; allows even smaller districts can access the employment and specialized amenities of distance areas (D\u0026rsquo;Acci et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Compact multi-centered city planning and evaluation needs to consider if key transport nodes are well connected within the public transport network, enabling passengers at each node to effectively reach jobs and services across a city.\u003c/p\u003e\u003cp\u003eIn MSI, centrality (i.e. the extent to which a node is connected to the whole network) is an important concept for measuring the city-wide connectivity of transport networks (e.g. Derrible, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; H\u0026aacute;znagy et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Betweenness centrality (BC) and Degree centrality (DC) can be considered to capture the importance of a node within a network. Betweenness represents the degree of which nodes stand between each other. BC measures the number of times a node lies on the shortest path between other nodes within a network (Freeman, 1978). High level of BC means that a node plays an important role as a bridge to minimize time and/or distance of movement (Porta et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{g}_{ij}\\)\u003c/span\u003e\u003c/span\u003e is the number of shortest paths that connect node i and j, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{g}_{ij}\\left(k\\right)\\)\u003c/span\u003e\u003c/span\u003e is the shortest path that passes node k between nodes i and j. Weighting of travel time between nodes can also be included-not shown in the equation below-to reflect that people prefer and choose routes that minimize travel time (Stradling, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:BC\\:\\left(k\\right)=\\:{\\sum\\:}_{i\\ne\\:j\\ne\\:k}^{}\\frac{{g}_{ij}\\left(k\\right)}{{g}_{ij}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eDegree centrality is another important concept that has been used for evaluating the importance of a node. It is often used to measure the extent to which a node is connected to other nodes (Freeman, 1978). For the assessment of a public transport network, DC can be defined as a proportion of transport nodes directly connected to a node in question out of the totality of nodes within the network. To measure DC more accurately, Pagerank centrality, an algorithm to identify core nodes within a multilayer network, can be used for differentiating nodes according to the relative importance of each node (e.g. the number of passengers travelling between two nodes). (Page et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Tu et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). When a network has n\u0026rsquo; node, pagerank of Node (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PR}_{i}\\)\u003c/span\u003e\u003c/span\u003e) can be:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{PR}_{i}\\left(t+1\\right)=\\:\\alpha\\:{\\sum\\:}_{j=1}^{N}{A}_{ji}\\frac{{PR}_{j}\\left(t\\right)}{{h}_{j}}+\\left(1-\\alpha\\:\\right)\\frac{1}{N},\\:$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{j}\\)\u003c/span\u003e\u003c/span\u003e refers to out-neighbors of j in undirected and directed network and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{A}_{ji}\\)\u003c/span\u003e\u003c/span\u003e is the adjacency matrix. α is a damping factor(0\u0026thinsp;\u0026lt;\u0026thinsp;a\u0026thinsp;\u0026lt;\u0026thinsp;1). Node i conveys α of centrality to the out-neighbors of j equally. It distributes an average of (1-α) of its total scores to each node in the network. The ranking process starts with each node being given the same centrality, which goes on until a steady state is reached. The number of passengers boarding and alighting between stations can be considered for weighting, given that an area with high ridership indicates the importance of a node within a network (Ramli et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Overall, with the assessment of both BC and DC, it is possible to determine the relative importance of transfer nodes within a public transport system, and to evaluate route and interchange capacity (Scheurer et al., 2006). The BC value shows the level of contribution (of a node) to an effective travel while the DC will show the level of actual usage of a node. Incongruence between the BC and the DC at a node may indicate disintegration between transport and land use planning (Lee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eLocal services accessibility\u003c/em\u003e\u003c/p\u003e\u003cp\u003eCreating high-density mixed-use development and pedestrian access around key transport nodes is expected to facilitate easy access to local amenities and services, which could contribute to enhancing social activities and interaction (Kaido, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; OECD, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Therefore, compact multi-centered city planning and evaluation should consider if in socio-economic hubs, a range of local services and facilities are provided especially within walking distance from the node so that people can easily use them in the daily routine (Dempsey et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). High local service accessibility means the center providing a share of benefits comparable to other areas.\u003c/p\u003e\u003cp\u003eThe gravity model has been one of the most widely used methods for estimating local-scale accessibility (Feng et al.,2023). It looks at movement from service points to population points and other factors affecting the movement (Gualiardo, 2004). The model of Talen and Anselin (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), one of the most used gravity models, measures accessibility by considering distance (d\u003csub\u003eij\u003c/sub\u003e) between two points as well as the capacity (e.g. size) of facilities (S\u003csub\u003ej\u003c/sub\u003e). Higher accessibility refers to shorter distance to facilities and greater availability of the facilities.\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{A}_{i}=\\:{\\sum\\:}_{j}^{}\\frac{{S}_{j}}{{d}_{ij}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo measure the accessibility to local services from a transport node by the gravity model, the capacities of varied kinds of local facilities and amenities as well as distance between a node and facilities need to be considered. Local facilities and amenities include schools, libraries, basic medical services, sport facilities, parks, and security services, and local stores (e.g. grocery stores), which are vital for the livability of a local community (Yhee et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The capacity can be measured by examining the gross floor area (i.e. sum of the floor area of each floor of a building) (Kang, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It is important to set varied buffers from a transport node to comprehend the potential of walking to the services. 400m can be an ideal access coverage of public transit (i.e. approximately 5-minute walking distance) while 800m is approximately 10-minute walking distance (Yigitcanlar et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). 1600m can be a cycling or running scale (Xiao et al., 2015). Overall, the adopted gravity mode captures what kinds of local service at what capacities (unit: m\u0026sup2;) are (not) located within walking and cycling distances from a transport node (unit: meter). Higher accessibility to local services means a wide range of local facilities with greater capacities can be reached on foot.\u003c/p\u003e\u003cp\u003eUltimately, the combined assessment of city-wide connectivity and local service accessibility offers a structured approach to measuring and comparing livability opportunities across different center types and locations. Comparative analysis of MSI results across socio-economic hub reveals center-specific challenges and policy implications into the distribution of livability as a social outcome from a compact city planning. This approach enables a deeper understanding of how the principles of isobenefit cities manifest in real metropolitan contexts.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Application of the MSI framework: A case of Seoul Metropolitan City","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Assessment of Seoul Metropolitan City\u003c/h2\u003e\u003cp\u003eWe tested our MSI framework, using a Seoul Metropolitan City (SMC), which can be an exemplar of rapidly developed cities that have experienced rapid economic and population growth and have promoted a compact city policy to achieve balanced urban development. Seoul had experienced socio-economic and environmental pressures from its rapid growth since the 1950s (Cho, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). It had seen continuously increasing employment growth concentrated in the center and severe traffic congestion, while its boundary expanded with growing population (SMG, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe city implemented several policies and plans to achieve competitive and balanced development, attempting a high-density multinucleated city (Jun, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In the official comprehensive urban plans (2011 and 2020), establishing an extensive transfer system and creating varied socio-economic hubs around key transport nodes were promoted for effective and even (access to) infrastructure and services (SMG, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1997\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The metropolis has continually extended its public transport networks (21 subway lines of 933.4 km as of 2021) (Korea Railroad, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As of 2021, most trips in Seoul (61.4%) were made by public transport, and the subway had been the most used public transport \u0026ndash; i.e. 64.66% of the trips (Seoul, 2022). The extensive development of subway networks had induced changes in spatial structure, land use, and physical environment of a city (Jin and Kim, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSources: Urbanrail. Net (a); adapted from Lee et al. (2016) (b)\u003c/p\u003e\u003cp\u003eTo conduct the MSI, we considered transport nodes that were located in Centers \u0026ndash; i.e. socio-economic hubs across the city, designated by Seoul Metropolitan Government based on criteria such as centrality, development potentials, and available transit infrastructure and services (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Centers were supposed to play roles of providing key socio-economic activities, as well as cultural and public services (SMG, 2011). They were categorized into three groups according to their key functions and roles: City Centers (CBD); Quarter Centers; and District Centers (SMG, 2011). Each group had a different focus and priority: City center to strengthen global and metropolitan competitiveness, Quarter center to balance residential and commercial function, and District center to increase commercial land use and enhance local access to varied amenities (Lee et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We randomly selected one node from the Centers under each category. Then, we considered the validity of the samples by carefully reviewing the comprehensive urban plans of SMC and consulting with urban policy and planning experts of the city. To maintain anonymity, which was part of an informed consent agreement with discussants, selected nodes in the Centers were named A, B and C.\u003c/p\u003e\u003cp\u003eFirst, to assess the city-wide connectivity, we collected data of five hundred twenty stops and twenty-one subway lines. To measure the centralities, ridership between subway stops and distance (time) between the stops were considered. For examining the ridership, we collected Origin and Destination (OD) data of September 19th in 2019 because the public transport ridership in 2020 was highly likely to be influenced by the COVID-19. For examining the distance and time between subway stops, we collected the distance data, then, using the data of scheduled speed of all the subway lines, we calculated travel time between subway stops. We used R version 4.1.2., analyzing centralities with tidygraph package (Pedersen, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSecond, to assess the local service accessibility, we considered various facilities including libraries, community sport facilities, public services, basic medical facilities, parks, schools, public safety facilities, and local traditional markets (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Data (i.e. locations, numbers, and capacities of each type of facility) was collected from the Public Data Portal and the National Spatial Data Infrastructure Portal of Korea. The 400m, 800m, and 1600m buffers (of the selected transport nodes in the three Centers) were drawn on GIS and straight-line distance from the nodes to the identified facilities was calculated. In addition, although business facilities were not the scope of the assessment, we checked them on the GIS-based maps to understand dominant land use patterns of the selected Center. Furthermore, we checked the number of residents living within the 1600m buffer, using data from the Public Data Portal. The numbers within each area were 82,666 (A), 90,600 (B), and 88,311 (C), respectively, which indicated that the three areas had a similar level of demand for the local basic services and amenities.\u003c/p\u003e\u003cp\u003eA schematic diagram depicting the MSI assessment is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, which illustrates the assessment of city-wide connectivity of three selected nodes in the Centers of the SMC and the assessment of local service accessibility at each node together.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurthermore, this research corroborated the MSI with previous qualitative study using focus groups that had been conducted with elected local representatives in the three Centers (see Lee et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e for details). Elected local representatives were those local residents who were officially chosen to serve as leaders of the smallest administrative unit in Korea. The focus group participants have lived in the area for more than 15 years and have been involved in local spatial planning. There were eight focus group discussions (3 in A, 2 in B, and 3 in C), each of which had 5 or 6 people and lasted between 60 minutes to 90 minutes. Discussion centered on the long-term residents\u0026rsquo; experiences and perceptions on the networked opportunities (macro connectivity) and local service accessibility (micro connectivity) in everyday life. Moreover, using the focus groups, we checked the extent to which traffic congestion and pedestrian crowding (owing to the concentration of commercial development around the selected node) influenced local services accessibility in daily life.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Multi-scale investigation Result\u003c/h2\u003e\u003cp\u003e\u003cem\u003eCity-wide connectivity by public transport\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe result of the city-wide connectivity assessment indicated the relative importance of the key transport nodes within the whole networks across the city (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The BCs of A, B, and C were ranked top 7.31%, 34.81%, and 8.08% respectively, and DCs were ranked top 1.92%, 17.88%, and 14.04%. The assessment of BCs showed that among the three nodes, A was the most influential node, with only a little difference with C. If these nodes do not function, the travel time of many passengers could be considerably affected. The results of DC revealed that A had the highest connectivity to other nodes in the network, being most greatly used by urban populations. The higher DC of A (than the other two nodes) indicated a relatively higher concentration of activities around the node in the CBD.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBCs and DCs of A, B, and C\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBC\u003c/p\u003e\u003cp\u003e(time weighted)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003cp\u003e(Top %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDC Pagerank\u003c/p\u003e\u003cp\u003e(number of passengers weighted)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003cp\u003e(Top %)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA. node in City\u003c/p\u003e\u003cp\u003eCenter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14,409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB. node in Quarter center\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,725\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ec. node in District center\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13,813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e14.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOur analysis indicated that the CBD played a role as a key bridge, being greatly connected to other nodes in the subway network of the SMC. The highest level of the centralities of the node in the CBD reflected the key function of the area as a major commercial center, which had the highest employment density in the city (Shin and Lee, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The selected node in the District Center also appeared to have a high level of city-wide connectivity, which suggested that the area had been also visited or passed by a large population from a wide area. In particular, the high BC (top 8%) of the District Center showed that the node played an important role in facilitating effective trips across the metropolitan area. The node in the Quarter Center had the lowest values of both BC and DC. The centralities of the node in B being lower than the other two (especially C) suggested that the role of the designated Quarter Center as a socio-economic hub of the area might have been relatively limited. Furthermore, the difference between the BC rank (top 34.81%) and the DC rank (top 17.88%) of the node in the Quarter Center indicated that the subway network design might not have been supportive of the compact land use policy \u0026ndash; i.e. key transport nodes to be integrated with high-density development in socio-economic hubs).\u003c/p\u003e\u003cp\u003eAll the focus group discussions consistently highlighted residents\u0026rsquo; strong sense of city-wide connectivity, largely attributed to the effective subway network. Participants in all study areas emphasized the convenience and efficiency of reaching diverse destinations across the city via major public transit system, subway. However, a recurring issue was the limited availability of local transit options between subway nodes and residential areas, which discouraged some residents from fully utilizing the major network. This challenge was especially pronounced in the Quarter Center, where mobility was hindered by the low frequency and limited coverage of local transport services\u0026mdash;ironically, even as the needs for movement increased with the gradual concentration of commercial development around the node. Residents living on the periphery of the catchment area often had no alternative but to rely on private cars or the limited services available near their homes.\u003c/p\u003e\u003cp\u003e\u003cem\u003eLocal service accessibility.\u003c/em\u003e At all the selected areas, a limited number of local facilities and amenities was noted within the ideal access coverage of public transit (i.e. 400m from a node) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), in which the dominant land use was business and commercial. The majority of the facilities were located beyond walking distance. A had the least number of facilities both within 400m and between 400m and 800m, which indicated that the CBD area might have provided the least favorable setting for walking to essential services. B appeared to have the highest number of local facilities that locals could reach on foot.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the result of the adapted gravity analysis that considered the numbers and the capacities of the varied types of local facilities and amenities within each buffer. First, the analysis pointed out that within the 400m buffer, the Quarter Center had the highest accessibility (160.868) while the CBD had a much lower value (9.353) than the other two. The Quarter and the District Centers had some facilities such as libraries and public services whereas the CBD area did not provide any except parks. Second, the assessment of areas between 400m and 800m buffers revealed that the District Center had much higher accessibility (700.523) than the other two centers. The highest accessibility at C was attributed to a community park that included sports facilities of greatest capacity. The District Center provided the widest range of essential services, while A had the lowest accessibility (68.133), lacking basic facilities including medical facilities, sports facilities, and schools. Third, in cycling distance (between 800m and 1600m), accessibility in CBD and District Center appeared to be relatively high, particularly, to parks and community sport centers.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe result of the adapted gravity analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eCBD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eQuarter Center\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003eDistrict Center\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e400m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4-800m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8-1600m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e400m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4-800m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8-1600m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e400m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4-800m\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e8-1600m\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLibrary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.389\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12.545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e12.681\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommunity\u003c/p\u003e\u003cp\u003eSports facilities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e237.833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e668.479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e15.266\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic services\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37.572\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.676\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4.792\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasic medical facilities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e46.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.353\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.911\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e228.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.738\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.302\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e33.824\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e218.570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e144.782\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e104.802\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e189.218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic safety facilities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.756\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.437\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e8.227\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocal open\u003c/p\u003e\u003cp\u003emarket\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22.743\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e25.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.353\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e470.977\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e160.868\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e136.788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e524.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e22.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e700.523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e120.855\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWalkable zone\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e77.486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e470.977\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e297.656\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e524.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003e722.867\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e120.855\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSums\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003e548.463\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e\u003cb\u003e822\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003e843.722\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOverall, the local-scale assessment revealed that the CBD area had the lowest accessibility to the essential services within walking distance. In the area, local service accessibility increased as the distance from the transport node increased (from 9.353 to 470.977), which indicated that most facilities were too far to walk from the subway station. The lowest accessibility around A could be attributed to the highest level of commercial activities and continuously increasing land price around nodes in CBD (Padeiro et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In contrast, the District Centre had the highest accessibility, owing to the relatively higher number of varied facilities at a greater capacity, especially community sports facilities and basic medical facilities. Only in the District Center, accessibility within walking distance was higher than accessibility within cycling distance (area between 800m and 1600m buffers). The issues related to access to local services were well recognized by the focus groups in all the selected areas. Much concern about the limited access to local facilities within walking distance was repeatedly noted. The discussions also pointed out that there was limited local transport to reach the facilities (especially in CBD).\u003c/p\u003e\u003cp\u003eThe focus groups clearly identified that the local service accessibility might have been also affected by traffic and pedestrian congestion, especially near the major transit nodes. Participants emphasized that the concentration of commercial and business activities around a subway station created such congestion, affecting the ease of moving around in the area. Importantly, the intensity of these negative effects varied across the different Centers. In the CBD, the local expressed the extreme level of difficulty of walking due to overcrowding and parking on many pedestrian roads. In the Quarter Center, focus groups highlighted high levels of disruption to pedestrian movement in the immediate vicinity of the nodes, especially during commuting hours. By contrast, in the District Center, residents confirmed the moderate level of difficulty since the main streets had been widened and congestion was noted mainly in a few back streets. Our field observations aligned with these findings, confirming that congestion-related impacts were most pronounced around transit nodes. Interestingly, residents living on the periphery of the catchment areas reported greater satisfaction with their local quality of life, citing better accessibility to green space and local mobility compared to those closer to the transit nodes.\u003c/p\u003e\u003cp\u003e\u003cem\u003eComparison of the MSI results\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe overall result of the MSI of Seoul (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) reveals that despite strong transit connectivity across all centers, disparities in local access to amenities persist, particularly in high density commercial centers like CBD. The CBD area emerged as an extreme case of imbalance with the highest city-wide connectivity and the lowest local service accessibility at the same time. In other words, it excels at connecting people to distance opportunities but falls short in providing a rich mix of nearby daily-life services. People living in the inner city might have been greatly affected by varied difficulties in using essential services, although they benefited from the hyper connectivity.\u003c/p\u003e\u003cp\u003eAt the District Center level, the MSI results were more encouraging, showing a better balance. The Center appeared to have the highest MSI result since it combined the best local service accessibility with high transit connectivity (similar to CBD), functioning as both a local town center and a node in the transport network. Compared to the other two Centers, people living in the District Center were likely to have better chances of enjoying walking to a wide range of services at greater capacities before or after using the effective transport system. In contrast, the Quarter Center showed the most pronounced shortfall in the MSI evaluation. It had the lowest city-wide connectivity and only middling local accessibility. Such a lower MSI result suggests that the Quarter Center has not fully realized its intended role as a well-connected, vibrant regional hub. They are neither fully self-sufficient nor well-connected to the broader urban system.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMSI result of the SMC\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCBD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQuarter Center\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDistrict Center\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eCity-wide connectivity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBetween centrality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14,409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,725\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13,813\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDegree centrality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00844\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRank (total)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (14,409)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (4,725)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (13,813)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eLocal-service accessibility\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAccess to local services (within walking distance)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e548.463\u003c/p\u003e\u003cp\u003e(77.486)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e822\u003c/p\u003e\u003cp\u003e(297.656)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e843.722\u003c/p\u003e\u003cp\u003e(722.867)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEase of movement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVery low\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRank\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe MSI result clearly indicated that the transit-oriented compact urban policy of Seoul did not fully achieve the long-standing desired social outcomes \u0026ndash; i.e. balanced distribution of livability opportunities across the metropolitan area. The effort of Seoul contributed to balancing \u003cem\u003ecity-scale\u003c/em\u003e connectivity across the metropolis; however, it did not quite succeed in achieving great \u003cem\u003eaccessibility to local services\u003c/em\u003e in the hubs, which had been one of the aspirations of the city. Except the District Center, people living near transport nodes had experienced recognizable disadvantages \u0026ndash; e.g. lack of a wide range of services and heightened local congestions, underscoring the critical need for localized mitigation strategies. The result implied that producing higher city-wide connectivity of key transport nodes alone could not guarantee the desired outcomes at local level as previously expected (Ewing and Cervero, 2010). Overall, it is difficult to conclude that the city accomplished its goal of the effective and even distribution of goods and services with its strategy of creating transit-oriented compact urban centers across a metropolitan area.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur multi-scale investigation of compact urban centers engages with the complex nature of the distributional issues inherent in the compact multi-centered city model (Lee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), analyzed through the lens of isobenefit urbanism. It shows that even in a metropolis like Seoul\u0026mdash;where balanced livability is proactively pursued through transit-oriented compact planning\u0026mdash;the isobenefit ideal remains unrealized across different spatial scales and center typologies. This persist imbalance highlights a fundamental scalar tension between macro-level connectivity and micro-level livability embedded in the practical application of the model. While development of effective transit networks and compact nodes is central, these efforts alone do not guarantee meaningful societal benefits, because of the limited effects at the local scale. As evidenced in Seoul, compact urban design around key transport nodes can result in multiple disadvantages for nearby residents, rather than delivering the anticipated health benefits or more social activities (e.g. Ewing and Cervero, 2010; Lang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCBD is not necessarily a winner, unlike numerous cases observed by previous research, because the highest city-wide connectivity at the CBD could be closely linked to the highest level of disadvantages. This paradox supports concerns that major centers could gradually experience the decline of living environment and main functions despite their connectivity strength (e.g. Han and Park, 2019). In contrast, District centers tend to offer a better quality of environs and access to essential activities while people living in the area still need to make frequent trips to join major activities in the CBD. Overall, these disparities highlight that not all centers fulfill their intended function as well-connected and self-sufficient hubs, underscoring the intra-urban heterogeneity masked by the broad application of the compact city model.\u003c/p\u003e\u003cp\u003eThe MSI result also reinforces ongoing debates that transport and land use coordination (TLC) remains fundamental for the effective and equitable provision of access to essential services and infrastructure (Appleyard et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) in rapidly developed cities. The analysis revealed a persistent accessibility mismatch between quality of infrastructure and proximity to facilities (Olaru and Curtis, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), whereby neighborhoods with a great standard of infrastructure (e.g. public transit with high centralities) do not have corresponding facilities nearby (e.g. public facilities) that locals may walk. This suggests that although the transport related goal of the compact city policy of Seoul has been achieved to some extent, transport planning and land use planning may not have been fully congruent. At both at macro and micro scales, barriers and opportunities to land use transport integration (Lee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) should be carefully addressed to make significant advancements towards balanced distribution of livability and accessibility.\u003c/p\u003e\u003cp\u003eIn practice, achieving a balanced distribution of essential services solely through the development of a compact, multi-centered urban structure may be overly ambitious or uncertain\u0026mdash;particularly in rapidly developed metropolises. Discussion on compact mega cities, especially in relation to social sustainability, must go beyond idealized urban forms or fixed notions of optimal density. Our analysis suggests that realizing a genuinely isobenefit city requires context-sensitive interventions that iteratively balance macro-level network integration with localized service provision, tailored to the different characteristics of each center typology. It is critical to pay much more attention how to address specific local issues and different planning priorities for each area when applying a compact polycentric city model (SMG, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As indicated in the case of Seoul, in the CBD, interventions should focus on improving the quality of pedestrian roads and environs and reducing local traffic, especially in the vicinity of the major transit nodes, using measures such as parking space cab (SMG, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In non-CBD areas, the priority should be enhancing local mobility by strengthening local-level transport networks \u0026ndash; i.e. introducing shared mobility hubs or demand responsive transport in underserved areas (Kim, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), rather than implying focusing on increasing commercial activities around nodes.\u003c/p\u003e\u003cp\u003eMore broadly, our results highlight the importance of critically examining how to calibrate the balance between top-down planning and local spontaneity (D\u0026rsquo;Acchi et al., 2024). While centrally orchestrated infrastructure investments are essential to ensure baseline connectivity and metropolitan coherence, the lived quality of urban environments often emerges from localized spatial adaptations that address context-specific priorities (Lee, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). By revealing the persistent spatial and scalar mismatches that persist within a highly planned urban system, this study points out the need to embrace not only robust evaluative frameworks like MSI, but also more flexible and typology-specific planning logics that respect how livability emerges differently across and within diverse urban fabrics. In rapidly developed metropolises like Seoul, the challenge is not only to distribute urban benefits evenly but also to foster a hybrid governance approach: strategically coordinated at the metropolitan level, but open to local placemaking at the ground level.\u003c/p\u003e\u003cp\u003eThis paper presents a methodology for the multi-scale assessment of compact centers, offering a feasible and context-appropriate evaluation tool for rapidly developed metropolitan areas. The MSI framework serves not only as a diagnostic instrument for identifying urban disparities in accessibility and livability, but also as a critical mechanism for evaluating the extent to which current urban development strategies align with the normative goals of isobenefit urbanism. In particular, it integrates both objective, macro-level assessment with localized, subjective perspectives \u0026ndash; capturing both the structural dimensions of connectivity and the lived experiences of residents. Building on the previous research (Lee et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), our study highlights the value of a mix-method approach to the holistic evaluation of social outcomes from a compact multi-centered city. While the quantitative assessment facilitates straight-forward comparison of differential outcomes at centers using official statistical data, the qualitative dimensions adds vital depth by capturing the local-scale effects experienced and perceived by the long-term residents. Together, these methods provide a more holistic understanding of the scalar mismatches and lived realities that shape the success or failure of compact multi-centered strategies.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe compact multi-centered city model, as implemented in metropolises like Seoul, is not a silver bullet; it does not inherently produce equitable outcomes across spatial scales and social contexts, as envisioned by the isobenefit urbanism. Advancing this ideal requires multi-scalar and flexible approaches, tailored to the distinct roles and conditions of each center typology. In this regard, our MSI framework offers a replicable, evidence-based tool for planners and policymakers \u0026mdash; particularly valuable in rapidly evolving metropolitan contexts where reconciling planning efficiency with social inclusivity remains a critical challenge. While MSI presents clear potential as a transferable framework, several considerations must be addressed in its future application. For instance, developing an index system may enhance the robustness of cross-city or intra-city comparisons \u0026mdash; for example, through clustering analyses to classify the results of city-wide connectivity assessments. Moreover, MSI should be contextually grounded in the specific priorities, values, and cultural conditions of each city, recognizing the relational and situated nature of compact urbanism (Kj\u0026aelig;ret, 2021). Ultimately, this research affirms that advancing isobenefit urbanism requires more reflexive and balanced planning logics\u0026mdash;one that meaningfully integrate mobility, land use, and everyday urban experiences in pursuit of equitable urban transformation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe author(s) declares no competing interests\u003c/p\u003e\u003ch2\u003eEthical approval\u003c/h2\u003e\u003cp\u003eEthical clearance for this study was made by the Ethics Committee of the University of Groningen in 16th of December 2019 (Approval number: 2019-18). All procedures involving human participants were conducted in accordance with the ethical standards of the committee and the principles outlined in the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003cp\u003eInformed consent was obtained in writing from all participants prior to their involvement in the study. Consent was obtained by the lead researcher between January 2020 and March 2020, who provided participants with a detailed information sheet and answered any questions before participants signed the consent form. The scope of the consent covered participation in the study, the use of anonymised data for research analysis, and the publication of aggregated findings. Participants were informed that they could withdraw from the study at any point without any consequence.\u003c/p\u003e\u003ch2\u003eFunding statement\u003c/h2\u003e\u003cp\u003eThis work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF- 2021S1A3A2A01087370).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: JHL, JL, ML, TTG; Methodology: JHL, JL, ML, TTG; Analysis and investigation: JHL, JL, ML; Writing- review and editing: JHL, JL, ML; Resources: TTG; Supervision: TTG.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF- 2021S1A3A2A01087370).\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analysed during the current study are not publicly available but can be available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAguilar A, Hernandez-Lozano J (2024) Mega-urbanization, territorial fragmentation and social inequality in the Global South: The case of Mexico City and its city-region. 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Transp Plann Technol 41(8):816\u0026ndash;829\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6942294/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6942294/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCompact city policy in rapidly developed metropolitan areas increasingly emphasizes balanced urban development. Cities like Seoul have pursued the balanced distribution of livability opportunities by expanding public transport networks and promoting multiple socio-economic hubs at key transit nodes \u0026ndash; so called compact multi-centered urban policy. However, critical evaluations of whether and how such models fully achieve their intended outcomes, especially essential service and infrastructure across diverse localities remain limited. Aligned with the concept of \u003cem\u003eisobenefit cities\u003c/em\u003e, this research develops and applies a Multi-Scale Investigation (MSI) as an integrative evaluation tool to assess social outcomes from compact multi-centered cities. Specifically, the MSI framework holistically investigates two interrelated dimensions: local service accessibility and city-wide connectivity by public transport, by \u0026ldquo;zooming in and out\u0026rdquo; socio-economic centers located at strategic nodes across a city. We applied this framework to evaluate varied Centers across the Seoul Metropolitan City, an exemplar of rapid urban growth and a compact polycentric urban policy. The MSI analysis revealed that while all selected centers exhibited strong city-wide connectivity, local service accessibility often fell short of expectations, primarily due to negative local-scale effects such as limited service diversity constrained mobility. Differences across varied center typologies were particularly noteworthy. The Central Business District (CBD) exhibited the highest level of city-wide connectivity but the lowest local accessibility, indicating a pronounced imbalance. The Quarter Center scored the lowest overall, suggesting its limited role as a hub of the quarter area. In contrast, the District Center achieved the highest MSI result, reflecting relatively stronger local outcomes. The MSI analysis exposes scalar tensions embedded within the isobenefit assumptions when applied to rapidly developed metropolitan contexts. Our research underscores that achieving a balanced distribution of urban benefits requires multi-scalar approaches that incorporate distinctive, yet flexible measures tailored for the functional roles and spatial conditions of different center typologies.\u003c/p\u003e","manuscriptTitle":"Zooming in and out of compact urban centers in a rapidly developed metropolis: A multi-scale investigation through isobenefit lens in Seoul","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 12:40:13","doi":"10.21203/rs.3.rs-6942294/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-20T09:13:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-08T02:38:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162850329650884205500889437701631593383","date":"2025-11-19T08:54:39+00:00","index":"hide","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-13T08:29:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-14T15:34:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83081612378215711183772154750768478432","date":"2025-09-17T13:12:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-14T21:59:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-17T06:22:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-09T08:52:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-07-09T08:49:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3912c2a6-6cd4-47f3-a32e-88ca02a6cbc5","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55120821,"name":"Social science/Development studies"},{"id":55120822,"name":"Social science/Geography"}],"tags":[],"updatedAt":"2026-05-12T05:23:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 12:40:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6942294","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6942294","identity":"rs-6942294","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}