Exploring the 15-Minutes City Concept: Global Challenges and Opportunities in Diverse Urban Contexts
Abstract
1. Introduction
2. Materials and Methods
3. Results and Discussion
3.1. Key Components of 15-Minute Cities and Global Urban Performance
3.2. Urban Planning Tools and Strategies
3.3. Comparative Analysis of 15 MC Implementation Across Global Regions
3.3.1. Europe (Paris, Barcelona, Oslo, Lisbon, Rome, Milan, etc.)
3.3.2. North America and Oceania (Portland, Montréal, Auckland, Hamilton)
3.3.3. Asia-Pacific Region (Beijing, Shanghai, Chengdu, Jakarta, Surabaya, Melbourne, Auckland etc.)
3.4. Challenges in Dense and Resource-Constrained Settings
4. Conclusions and Recommendations
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
15-minutes city | 15 MC |
Appendix A
Country | Cities Analyzed | # of Studies | Developed/Developing |
---|---|---|---|
Italy | Rome, Milan, Naples, Turin, Cagliari, Pisa, Palermo, Perugia, Trieste | 7 | Developed |
China | Beijing, Shanghai, Chengdu, Guangzhou | 5 | Developing |
USA | Portland, Kapolei | 3 | Developed |
France | Paris | 3 | Developed |
Australia | Melbourne | 2 | Developed |
Spain | Barcelona | 2 | Developed |
India | Mumbai, New Delhi, Bhubaneswar | 2 | Developing |
Indonesia | Surabaya, Surakarta, Jakarta | 2 | Developing |
UK | London | 2 | Developed |
Portugal | Lisbon | 2 | Developed |
Norway | Oslo | 1 | Developed |
Germany | Munich | 1 | Developed |
Poland | Krakow | 1 | Developed |
Greece | Thessaloniki | 1 | Developed |
New Zealand | Hamilton, Auckland | 2 | Developed |
Estonia | Tallinn | 1 | Developed |
Canada | Montréal | 2 | Developed |
Colombia | Bogotá | 1 | Developing |
UAE | Dubai | 1 | Developing |
Nigeria | Lagos | 1 | Developing |
S. No | Ref. | Year | Proximity | Accessibility and Walkability | Density | Diversity | Mixed Use | Adaptability | Flexibility | Human-Scale Urban Design | Connectivity | Digitalization | Inclusive Urban Design |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | [1] | 2024 | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ |
2 | [3] | 2024 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✗ | ✓ |
3 | [5] | 2023 | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ |
4 | [9] | 2022 | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ |
5 | [14] | 2022 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ |
6 | [17] | 2022 | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ |
7 | [18] | 2021 | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ |
8 | [20] | 2024 | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ |
9 | [24] | 2019 | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ |
10 | [25] | 2021 | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
11 | [26] | 2021 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ |
12 | [31] | 2022 | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
13 | [32] | 2022 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
14 | [34] | 2024 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
15 | [35] | 2023 | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ |
16 | [36] | 2023 | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
17 | [37] | 2022 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
18 | [38] | 2023 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
19 | [39] | 2024 | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
20 | [40] | 2021 | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ |
21 | [41] | 2022 | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
22 | [43] | 2024 | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✓ | ✓ | ✗ | ✗ |
23 | [45] | 2022 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
24 | [46] | 2023 | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ |
25 | [47] | 2023 | ✓ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
26 | [48] | 2023 | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ |
27 | [49] | 2023 | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ |
28 | [33] | 2023 | ✓ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✓ |
29 | [51] | 2022 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ |
30 | [52] | 2020 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ | ✗ |
31 | [53] | 2024 | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✗ | ✓ |
32 | [55] | 2024 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ |
33 | [56] | 2024 | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ |
Ref. | Year | City | Country | Tool/Assessment Method | Parameters Assessed | |
---|---|---|---|---|---|---|
1 | [1] | 2024 | Hong Kong | China | GIS, Walk Score, accessibility tools | Proximity, Accessibility, Walkability, Urban Services |
2 | [3] | 2024 | Cagliari, Perugia, Pisa, Trieste | Italy | Urban Morphology, GIS | Accessibility, Morphological Features, Walkability |
3 | [5] | 2023 | Various Italian Cities | Italy | Next Proximity Index (based on open data) | Proximity, Accessibility, Open Data Analysis |
4 | [9] | 2022 | Not specific (urban China) | China | Urban Heat Adaptation Framework | Urban Climate Adaptability |
5 | [17] | 2022 | Guangzhou | China | GPS Trajectory Data | Mobility, Traffic Exposure, Individual Movement Patterns |
6 | [18] | 2021 | Multiple cities in the US | USA | Longitudinal Mobility Study using Mobile & GIS Data | Pandemic Impact on Movement & Access |
7 | [20] | 2024 | Surabaya | Indonesia | Urban morphology, policy review | Proximity, spatial layout |
8 | [14] | 2022 | General (India) | India | Geospatial analysis | Micro-mobility, access time |
9 | [56] | 2024 | Surakarta | Indonesia | Big Data, GIS | Green space accessibility |
10 | [24] | 2019 | Urban China | China | GIS, walkability index | Walkable neighborhoods, inequality |
11 | [26] | 2021 | Cagliari | Italy | GIS, reuse potential (Porosity, Crossing, etc.) | Reuse of public buildings |
12 | [32] | 2022 | Barcelona | Spain | Pedestrian travel time, GIS | Accessibility and proximity via walk times |
13 | [35] | 2023 | Oslo, Lisbon | Norway, Portugal | Case studies, planning analysis | Remote workspaces, mixed-use planning |
14 | [34] | 2024 | Oslo | Norway | Accessibility modelling, travel distance | 15-minutes city accessibility in Oslo |
15 | [36] | 2023 | Rome, London, Paris | Italy, UK, France | Graph theory and spatial network analysis | Comparative network-based accessibility |
16 | [25] | 2021 | Naples, London | Italy, UK | Accessibility analysis using GIS | Comparative analysis of neighborhood accessibility |
17 | [48] | 2023 | Beijing | China | Post-pandemic urban analysis, spatial mapping | Living circle analysis under an epidemic context |
18 | [49] | 2023 | Beijing-Tianjin-Hebei | China | GIS and visual analysis | 15-minutes facility distribution |
19 | [43] | 2024 | Terni, Matera | Italy | Configurational urban analysis | Urban quality through a 15-minutes city lens |
20 | [45] | 2022 | Palermo | Italy | Urban policy and spatial design analysis | Palermo’s structure in the 15-minutes context |
21 | [46] | 2023 | Sicily | Italy | Case study analysis (COVID-19 period) | COVID-19 effects on proximity and service access |
22 | [47] | 2023 | Montréal | Canada | Behavioral surveys, urban lifestyle analysis | Behavioral perspective on 15/30-minutes city lifestyles |
23 | [37] | 2022 | Turin | Italy | Service accessibility measurement | Access to services in a 15-minutes city framework |
24 | [39] | 2024 | Auckland | New Zealand | GIS-based spatial analysis Custom indexes: Porosity, Crossing, Attractiveness | Spatial connectivity, Accessibility of services, Urban morphology and walkability |
25 | [33] | 2023 | Montréal | Canada | Accessibility metrics by travel purpose Mode-based spatial analysis | Travel time to key services, Mode-based access differences (e.g., walk, cycle, transit), Functional diversity and proximity, |
26 | [38] | 2023 | Dubai | UAE | GIS-based service area mapping Walkability analysis | Walking distance to services, Spatial distribution of services, Service coverage efficiency |
27 | [51] | 2022 | Paris, Barcelona, Milan | France, Spain, Italy | Comparative urban spatial analysis, Morphological and functional indicators | Proximity of daily service, Urban density, and land-use mix Human-scale design and public space integration |
28 | [52] | 2020 | Lombardy | Italy | Chrono-urbanism (time-based spatial assessment), Station catchment area analysis | Access to urban functions via railway stations, Temporal proximity of daily needs, Transport-oriented spatial planning |
29 | [41] | 2022 | Krakow | Poland | GIS-based spatial analysis | Proximity to services, walking coverage, and service distribution |
30 | [31] | 2022 | Naples | Italy | GIS, network analysis | Accessibility index, spatial equity, 15-minutes walking coverage |
31 | [40] | 2021 | Bogotá | Colombia | Mobility & behavior surveys, temporal analysis | Mobility change, activity patterns, and access to daily needs |
32 | [55] | 2024 | Tallinn | Estonia | Two-level GIS spatial analysis | Urban + expansion area service proximity, suitability mapping |
33 | [53] | 2024 | Hamilton | New Zealand | GIS, catchment mapping, mobility analysis | Accessibility to services, multimodal coverage, and equity |
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Concept | Inclusion Criteria | Exclusion Criteria |
---|---|---|
Content | Articles published between 2019 and 2024. Answers the research question Papers containing at least one relevant keyword related to the 15 MC concept. Focus on urban planning, policy discourse, and implementation of the 15 MC model. | Non-English language papers were removed. Papers that did not have titles and abstracts relevant to the core research questions were excluded. Full-text screening further eliminated papers that only mentioned the 15 MC concept without directly engaging with it in a meaningful way. |
Article type | Academic: empirical, peer-reviewed articles. Conference papers Grey literature, including case studies from reputable sources | Blogs Editorials Commentary Media Secondary research |
Geographical focus | Developing countries, LMICs [World Bank criteria] HICs [World Bank criteria] |
City | GIS Spatial Analysis | Walkability Index [Walk Score] | Mixed-Use Development Analysis | Transport Network Analysis [Public Transport Accessibility Index] | Urban Morphology [Space Syntax] | Cycling Infrastructure |
---|---|---|---|---|---|---|
Paris | High service accessibility mapping [33] | 98 [High] | Strong mixed-use zoning | Metro, tram, bus, well-integrated [2] | Compact urban form [2] | Extensive bike lanes, bike-sharing system [2] |
Milan | Service accessibility mapping in urban studies [5] | 85 [High] | High-density mixed-use zoning [5] | Metro, trams, and buses are well-connected [5] | Compact historical core with expanding modern zones [5] | Strong investments in cycling lanes [5] |
Melbourne | Not specifically used in GIS tools | 92 [High] | Mixed-use zoning is integrated in new developments [12] | Not discussed | Not discussed | Expanding bike lanes and infrastructure [19] |
Lagos | Limited GIS accessibility mapping [13] | 50 [Low] | Highly informal settlement areas lack structured mixed-use planning [13] | Public transport lacks integration [13] | High-density, unstructured urban expansion [13] | Very limited cycling infrastructure [13] |
Mumbai | Inconsistent service accessibility [14] | 58 [Low] | Limited mixed-use planning [14] | High-density rail, poor last-mile connectivity [14] | Unstructured, informal settlements [14] | Weak cycling infrastructure [14] |
Portland | Not specifically used in GIS tools | 89 [High] | Mixed-use zoning policies implemented [19] | Not discussed | Not discussed | Not discussed |
Jakarta | Limited GIS application [21] | 65 [Medium] | Some mixed-use developments but lack consistency [21] | Bus rapid transit, weak metro system [21] | High-density urban sprawl [21] | Few dedicated bike lanes [21] |
Shanghai | GIS urban mobility analysis [24] | 87 [High] | High urban density supports mixed-use zoning [24] | Extensive metro network [24] | Dense urban core [24] | Growing cycling infrastructure, but still car-reliant [24] |
London | Used in transport and accessibility analysis [25] | 94 [High] | Mixed-use development strategies applied [25] | Well-integrated transit system [25] | Polycentric urban layout [25] | London Cycleways program improving connectivity [25] |
Bogotá | GIS-based cycling and transit analysis [31] | 75 [Medium] | Strong community-based planning [31] | BRT system is well-developed [31] | Polycentric urban structure [31] | Expanding bike lanes, urban cycling culture [31] |
Naples | Limited application [31] | 78 [Medium] | Unstructured mixed-use zoning [31] | Moderate public transport efficiency [31] | Fragmented urban morphology [31] | Weak cycling infrastructure [31] |
Barcelona | GIS-based analysis for superblocks [32] | 90 [High] | Strong mixed-use model [32] | Metro and BRT systems integrated [32] | Compact grid layout [32] | Superblocks prioritize pedestrian and cycling mobility [32] |
Oslo | Public transport-oriented GIS mapping | 95 [High] | High integration of mixed-use neighborhoods [34] | Strong metro, tram, and bus connectivity [34] | Compact city design [35] | Extensive cycling lanes, investments in bike-sharing [34] |
Lisbon | Spatial accessibility mapping applied [35] | 88 [High] | Moderate mixed-use zoning [35] | Moderate metro and bus network [35] | Historic core limits transformation [35] | Expanding cycling network but still underdeveloped [35] |
Rome | Not specifically used in GIS tools | 80 [Medium] | Mixed-use policies improving accessibility [36] | Not discussed | Not discussed | Not discussed |
Turin | GIS-based spatial planning tools applied [37] | 82 [Medium-High] | Mixed-use zoning improves accessibility [37] | Moderate public transport efficiency [37] | Well-structured central layout [37] | Expanding cycling network [37] |
Dubai | GIS used in transport analysis [38] | 64 [Medium-Low] | Gated communities hinder mixed-use integration [38] | High reliance on car-based transport [38] | Urban expansion challenges proximity planning [38] | Limited cycling infrastructure, improving policies [38] |
Auckland | GIS applied in walkability and proximity studies [39] | 70 [Medium-High] | Moderate mixed-use zoning [39] | Public transport efficiency varies by district [39] | Car-dependent suburban areas impact morphology [39] | Cycling infrastructure is expanding, but unevenly distributed [39] |
Tallinn | Spatial analysis for 15 MC assessment [40] | 80 [Medium-High] [40] | Improving mixed-use urban development [40] | Expanding the bus and tram network [40] | Compact city design [40] | Growing cycling infrastructure, but still developing [40] |
Krakow | Used in urban accessibility research [41] | 77 [Medium] | Moderate mixed-use zoning [41] | Tram-based public transport [41] | Historic core limits accessibility improvements [41] | Low cycling infrastructure, improving gradually [41] |
Thessaloniki | GIS applied in accessibility mapping [42] | 72 [Medium] | Mixed-use developments emerging [42] | Bus-dominant public transport [42] | Historic layout limits transformation [42] | Growing cycling network [42] |
Aspect | Developed Countries [e.g., Paris, Melbourne, Portland, Oslo] | Developing Countries [e.g., Mumbai, Jakarta, Lagos, Surabaya] |
---|---|---|
Urban Infrastructure | Well-planned, existing pedestrian-friendly neighborhoods, extensive cycling infrastructure [2,37] | Unplanned urban sprawl, weak cycling and pedestrian infrastructure, reliance on cars [19,20] |
Governance and Policy | Strong zoning laws, integrated public transport, and sustainability-focused urban planning [36] | Weak enforcement of zoning laws, informal settlements, and limited funding for infrastructure [13,21] |
Public Transportation | High public transit efficiency, multimodal connectivity, and investments in green transport [18] | Underdeveloped or overcrowded public transport, informal modes [rickshaws, minibuses] dominate [46] |
Proximity and Accessibility | Most services within a 15-minutes walking or cycling distance, high accessibility score [24] | Services may require 20–30 min due to congestion, lack of mixed-use zoning [13,47] |
Socio-Economic Barriers | Gentrification risks, rising housing costs near accessible hubs [6] | High economic inequality, informal housing, poor service distribution [38] |
Adaptation Strategies | Expansion of pedestrian zones, cycling lanes, and smart mobility [15] | Incremental improvements to community-led projects, micro-mobility solutions [21,53] |
Challenge | Scientific Debate & Challenges | Key Studies, Perspectives, and Solutions |
---|---|---|
Gentrification & Socioeconomic Exclusion | Critics argue that the 15 MC model can lead to gentrification, pricing out low-income residents from well-connected areas. While proximity increases livability, it can also exacerbate socio-economic divides, as seen in Paris and Barcelona. There is an ongoing debate on whether rent control or subsidized housing can mitigate displacement risks. | Ref. [6]—The 15 MC creates “exclusive proximity” where only high-income residents benefit from walkability. [32] Superblock initiatives in Barcelona incorporate social housing policies to counteract displacement. |
Infrastructure Constraints in Developing Cities | Many developing cities lack the infrastructure to implement the 15 MC model due to poor road networks, informal settlements, and a lack of planning frameworks. The scientific debate centers on whether this model can be adapted to informal urban areas or if a 20- or 30-min model is more realistic. | [20] A “10 min city” model was tested in India, showing that shorter proximity models can be successful in dense areas. [21] Studied Surabaya’s urban expansion, showing how micro-infrastructure projects help integrate informal areas. |
Car Dependency & Urban Sprawl | Cities with urban sprawl and low-density suburbs struggle with the 15 MC model due to long travel distances. There is a scientific divide on whether retrofitting suburbs for walkability is feasible or if transport-oriented solutions are a better alternative. | [34] Found that in Oslo, transit-oriented developments helped suburban areas meet 15-minutes criteria. [46] Argued that in Auckland, a hybrid 30-min city model is more practical due to car dependency. |
Land-Use & Zoning Barriers | Rigid zoning laws in some cities prevent mixed-use developments, making the 15 MC hard to implement. Scientific debate focuses on whether existing zones should be reformed or if new urban developments should be built instead. | [12] Found that in Athens, mixed-use zoning regulations improved urban mobility. [18] Suggest “soft zoning” policies that encourage gradual transitions to mixed-use neighborhoods. |
Digital Divide & Smart Mobility | The digital divide makes it harder for some residents [especially elderly and low-income populations] to access smart mobility services. - Some researchers argue that digital tools enhance accessibility, while others warn that they may increase exclusion. | [8] Advocated for a “hybrid mobility” approach that integrates digital tools with traditional urban planning. |
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Iqbal, A.; Nazir, H.; Qazi, A.W. Exploring the 15-Minutes City Concept: Global Challenges and Opportunities in Diverse Urban Contexts. Urban Sci. 2025, 9, 252. https://doi.org/10.3390/urbansci9070252
Iqbal A, Nazir H, Qazi AW. Exploring the 15-Minutes City Concept: Global Challenges and Opportunities in Diverse Urban Contexts. Urban Science. 2025; 9(7):252. https://doi.org/10.3390/urbansci9070252
Chicago/Turabian StyleIqbal, Asifa, Humaira Nazir, and Ammad Waheed Qazi. 2025. "Exploring the 15-Minutes City Concept: Global Challenges and Opportunities in Diverse Urban Contexts" Urban Science 9, no. 7: 252. https://doi.org/10.3390/urbansci9070252
APA StyleIqbal, A., Nazir, H., & Qazi, A. W. (2025). Exploring the 15-Minutes City Concept: Global Challenges and Opportunities in Diverse Urban Contexts. Urban Science, 9(7), 252. https://doi.org/10.3390/urbansci9070252