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Network structure and urban mobility sustainability: A topological analysis of cities from the urban mobility readiness index
dc.contributor.author | Herrera Acevedo, Daniel | |
dc.contributor.author | Sierra Porta, David | |
dc.date.accessioned | 2025-01-13T18:36:36Z | |
dc.date.available | 2025-01-13T18:36:36Z | |
dc.date.issued | 2025-01-13 | |
dc.date.submitted | 2025-01-13 | |
dc.identifier.citation | Herrera-Acevedo, D. D., & Sierra-Porta, D. (2024). Network structure and urban mobility sustainability: A topological analysis of cities from the urban mobility readiness index. Sustainable Cities and Society, 106076. https://doi.org/10.1016/j.scs.2024.106076 | spa |
dc.identifier.uri | https://hdl.handle.net/20.500.12585/13223 | |
dc.description.abstract | In the context of rapid urbanization, efficient and sustainable urban mobility is critical. This study explores the impact of urban network structure and socio-demographic factors on Urban Mobility Readiness (UMRi) across 62 cities worldwide. Using complex network analysis, Principal Component Analysis, and multiple linear regression models, we identify significant relationships between network metrics — such as average node degree, clustering coefficient, and graph diameter — and urban mobility performance. Cities with denser, more interconnected networks tend to achieve higher UMRi scores, indicating better preparedness for modern mobility challenges. Our findings also highlight the importance of economic resources, with GDP per capita emerging as a significant predictor of UMRi. Cities with well-funded and well-designed transportation networks demonstrate stronger performance in terms of mobility readiness and sustainability. Conversely, cities with more dispersed networks face greater challenges in optimizing their transportation systems. These insights underscore the importance of compact, resilient networks that promote accessibility and efficiency. This study emphasizes the critical role of network structure in shaping urban mobility outcomes and offers strategic guidance for enhancing transportation systems in rapidly growing urban areas. Future research should focus on integrating emerging technologies, such as autonomous vehicles and smart city solutions, to further optimize urban mobility. This approach offers a novel perspective on how the structure of urban networks influences the sustainability and efficiency of public transport in diverse urban contexts. | spa |
dc.format.extent | 10 páginas | |
dc.format.mimetype | application/pdf | spa |
dc.language.iso | eng | spa |
dc.source | Sustainable Cities and Society | spa |
dc.title | Network structure and urban mobility sustainability: A topological analysis of cities from the urban mobility readiness index | spa |
dcterms.bibliographicCitation | Abdi, H., Williams, L.J., 2010. Principal component analysis. Wiley interdisciplinary reviews: computational statistics 2, 433–459. doi:https: //doi.org/10.1002/wics.101. | spa |
dcterms.bibliographicCitation | Abduljabbar, R.L., Liyanage, S., Dia, H., 2021. The role of micro-mobility in shaping sustainable cities: A systematic literature review. Transportation research part D: transport and environment 92, 102734. doi:https://doi.org/10.1016/j.trd.2021.102734. | spa |
dcterms.bibliographicCitation | Ahmed, U., Srivastava, G., Djenouri, Y., Lin, J.C.W., 2022. Knowledge graph based trajectory outlier detection in sustainable smart cities. Sustainable Cities and Society 78, 103580. doi:https://doi.org/10.1016/j.scs.2021.103580. | spa |
dcterms.bibliographicCitation | Al-Malki, A., Madandola, M., Al Thani, S., Bayram, G., Al-Kandari, A., Furlan, R., 2024. Advancing urban mobility in the state of qatar—establishing a framework for autonomous vehicles in doha. Journal of Infrastructure, Policy and Development 8, 3051. doi:https: //doi.org/10.24294/jipd.v8i3.3051. | spa |
dcterms.bibliographicCitation | Alessandretti, L., Natera Orozco, L.G., Saberi, M., Szell, M., Battiston, F., 2023. Multimodal urban mobility and multilayer transport networks. Environment and Planning B: Urban Analytics and City Science 50, 2038–2070. doi:https://doi.org/10.1177/23998083221108190. | spa |
dcterms.bibliographicCitation | Alessandrini, A., Delle Site, P., Filippi, F., 2023. A new planning paradigm for urban sustainability. Transportation Research Procedia 69, 203–210. doi:https://doi.org/10.1016/j.trpro.2023.02.163. | spa |
dcterms.bibliographicCitation | Badhrudeen, M., Derrible, S., Verma, T., Kermanshah, A., Furno, A., 2022. A geometric classification of world urban road networks. Urban Science 6, 11. doi:https://doi.org/10.3390/urbansci6010011. | spa |
dcterms.bibliographicCitation | Bardoscia, M., Barucca, P., Battiston, S., Caccioli, F., Cimini, G., Garlaschelli, D., Saracco, F., Squartini, T., Caldarelli, G., 2021. The physics of financial networks. Nature Reviews Physics 3, 490–507. doi:https://doi.org/10.1038/s42254-021-00322-5. | spa |
dcterms.bibliographicCitation | Bibri, S.E., Krogstie, J., Karrholm, M., 2020. Compact city planning and development: Emerging practices and strategies for achieving the goals ¨ of sustainability. Developments in the built environment 4, 100021. doi:https://doi.org/10.1016/j.dibe.2020.100021. | spa |
dcterms.bibliographicCitation | Bier, T., Lange, A., Glock, C.H., 2020. Methods for mitigating disruptions in complex supply chain structures: a systematic literature review. International Journal of Production Research 58, 1835–1856. doi:https://doi.org/10.1080/00207543.2019.1687954. | spa |
dcterms.bibliographicCitation | Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.U., 2006. Complex networks: Structure and dynamics. Physics reports 424, 175–308. doi:https://doi.org/10.1016/j.physrep.2005.10.009 | spa |
dcterms.bibliographicCitation | Boeing, G., 2017a. Osmnx: A python package to work with graph-theoretic openstreetmap street networks. Journal of Open Source Software 2. doi:https://doi.org/10.21105/joss.00215. | spa |
dcterms.bibliographicCitation | Boeing, G., 2017b. Osmnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, environment and urban systems 65, 126–139. doi:https://doi.org/10.1016/j.compenvurbsys.2017.05.004. | spa |
dcterms.bibliographicCitation | Bro, R., Smilde, A.K., 2014. Principal component analysis. Analytical methods 6, 2812–2831. doi:https://doi.org/10.1039/C3AY41907J. | spa |
dcterms.bibliographicCitation | Brohl, T., Lehnertz, K., 2019. Centrality-based identification of important edges in complex networks. Chaos: An Interdisciplinary Journal of ¨ Nonlinear Science 29. doi:https://doi.org/10.1063/1.5081098. | spa |
dcterms.bibliographicCitation | Cai, H., Zheng, V.W., Chang, K.C.C., 2018. A comprehensive survey of graph embedding: Problems, techniques, and applications. IEEE transactions on knowledge and data engineering 30, 1616–1637. doi:https://doi.org/10.1109/TKDE.2018.2807452. | spa |
dcterms.bibliographicCitation | Cai, J., Li, R., Liu, Z., Liu, X., Wu, H., 2024. Quantifying spatial interaction centrality in urban population mobility: A mobility feature-and network topology-based locational measure. Sustainable Cities and Society 114, 105769. doi:https://doi.org/10.1016/j.scs.2024.105769. | spa |
dcterms.bibliographicCitation | Ceder, A., 2021. Urban mobility and public transport: future perspectives and review. International Journal of Urban Sciences 25, 455–479. doi:https://doi.org/10.1080/12265934.2020.1799846. | spa |
dcterms.bibliographicCitation | Chang, J., Nimer Kadry, S., Krishnamoorthy, S., 2020. Review and synthesis of big data analytics and computing for smart sustainable cities. IET Intelligent Transport Systems 14, 1363–1370. doi:https://doi.org/10.1049/iet-its.2020.0006. | spa |
dcterms.bibliographicCitation | Chaudhry, A.G., Masoumi, H., Dienel, H.L., 2023. A systematic literature review of mobility attitudes and mode choices: Mena and south asian cities. Frontiers in Sustainable Cities 4, 1085784. doi:https://doi.org/10.3389/frsc.2022.1085784 | spa |
dcterms.bibliographicCitation | Chen, W., Wu, A.N., Biljecki, F., 2021. Classification of urban morphology with deep learning: Application on urban vitality. Computers, Environment and Urban Systems 90, 101706. doi:https://doi.org/10.1016/j.compenvurbsys.2021.101706. | spa |
dcterms.bibliographicCitation | Cheng, Z., Ouyang, M., Du, C., Zhang, H., Wang, N., Hong, L., 2023. Boundary effects on topological characteristics of urban road networks. Chaos: An Interdisciplinary Journal of Nonlinear Science 33. doi:https://doi.org/10.1063/5.0145079. | spa |
dcterms.bibliographicCitation | Cordero, D., Rodriguez, G., 2022. Merger of network graph indicators to estimate resilience in latin american cities. IEEE Access 10, 81071–81093. doi:https://doi.org/10.1109/ACCESS.2022.3195894. | spa |
dcterms.bibliographicCitation | Cresswell, T., 2011. Mobilities i: catching up. Progress in human geography 35, 550–558. doi:https://doi.org/10.1177/ 0309132510383348. | spa |
dcterms.bibliographicCitation | Estrada, E., 2012. The structure of complex networks: theory and applications. American Chemical Society. URL: https://strathprints. strath.ac.uk/id/eprint/34153. | spa |
dcterms.bibliographicCitation | Farid, A.M., Viswanath, A., Al-Junaibi, R., Allan, D., Van der Wardt, T.J., 2021. Electric vehicle integration into road transportation, intelligent transportation, and electric power systems: an abu dhabi case study. Smart Cities 4, 1039–1057. doi:https://doi.org/10.3390/ smartcities4030055 | spa |
dcterms.bibliographicCitation | Folt‘ynova, H.B., Vejchodsk ´ a, E., Rybov ´ a, K., Kv ´ eto ˇ n, V., 2020. Sustainable urban mobility: One definition, di ˇ fferent stakeholders’ opinions. Transportation research part D: Transport and environment 87, 102465. doi:https://doi.org/10.1016/j.trd.2020.102465 | spa |
dcterms.bibliographicCitation | Franz, W., 2020. Algebraic topology. Walter de Gruyter GmbH & Co KG. doi:https://doi.org/10.1515/9783112318522. | spa |
dcterms.bibliographicCitation | Friman, M., Lattman, K., Olsson, L.E., 2020. Public transport quality, safety, and perceived accessibility. Sustainability 12, 3563. doi: ¨ https: //doi.org/10.3390/su12093563. | spa |
dcterms.bibliographicCitation | Furlan, R., Zaina, S., Patel, S., 2021. The urban regeneration’s framework for transit villages in qatar: The case of al sadd in doha. Environment, Development and Sustainability 23, 5920–5936. doi:https://doi.org/10.1007/s10668-020-00853-4. | spa |
dcterms.bibliographicCitation | Gallo, M., Marinelli, M., 2020. Sustainable mobility: A review of possible actions and policies. Sustainability 12, 7499. doi:https://doi.org/ 10.3390/su12187499 | spa |
dcterms.bibliographicCitation | Giblin, P., 2013. Graphs, surfaces and homology: an introduction to algebraic topology. Springer Science & Business Media. doi:https: //doi.org/10.1007/978-94-009-5953-8. | spa |
dcterms.bibliographicCitation | Girardet, H., 2021. Sustainable cities: A contradiction in terms?, in: The earthscan reader in sustainable cities. Routledge, pp. 413–425. doi:https: //doi.org/10.4324/9781315800462. | spa |
dcterms.bibliographicCitation | Grassi, Y.S., D´ıaz, M.F., 2024. Post-pandemic urban mobility in a medium-sized latin american city. is sustainable micro-mobility gaining ground? International Journal of Environmental Studies 81, 1579–1595. doi:https://doi.org/10.1080/00207233.2023.2195327 | spa |
dcterms.bibliographicCitation | Guzman, L.A., Arellana, J., Alvarez, V., 2020. Confronting congestion in urban areas: Developing sustainable mobility plans for public and private organizations in bogota. Transportation Research Part A: Policy and Practice 134, 321–335. doi: ´ https://doi.org/10.1016/j.tra.2020. 02.019 | spa |
dcterms.bibliographicCitation | Haseli, G., Bonab, S.R., Hajiaghaei-Keshteli, M., Ghoushchi, S.J., Deveci, M., 2024. Fuzzy ze-numbers framework in group decision-making using the bcm and cocoso to address sustainable urban transportation. Information Sciences 653, 119809. doi:https://doi.org/10.1016/ j.ins.2023.119809. | spa |
dcterms.bibliographicCitation | Hoornweg, D., Sugar, L., Gomez, C.L.T., 2020. Cities and greenhouse gas emissions: moving forward. Urbanisation 5, 43–62. doi:https: //doi.org/10.1177/0956247810392270. | spa |
dcterms.bibliographicCitation | Jacyna, M., Kotylak, P., 2020. Decision-making problems of collective transport development in terms of sustainable urban mobility. Journal of KONBiN 50, 359–375. doi:https://doi.org/10.2478/jok-2020-0044. | spa |
dcterms.bibliographicCitation | Jiang, Y., Han, Y., Liu, M., Ye, Y., 2022. Street vitality and built environment features: A data-informed approach from fourteen chinese cities. Sustainable cities and society 79, 103724. doi:https://doi.org/10.1016/j.scs.2022.103724. | spa |
dcterms.bibliographicCitation | Jimenez-Espada, M., Naranjo, J.M.V., Garc ´ ´ıa, F.M.M., 2022. Identification of mobility patterns in rural areas of low demographic density through stated preference surveys. Applied sciences 12, 10034. doi:https://doi.org/10.3390/app121910034. | spa |
dcterms.bibliographicCitation | Jolliffe, I.T., Cadima, J., 2016. Principal component analysis: a review and recent developments. Philosophical transactions of the royal society A: Mathematical, Physical and Engineering Sciences 374, 20150202. doi:https://doi.org/10.1098/rsta.2015.0202. | spa |
dcterms.bibliographicCitation | Kaiser, N., Barstow, C.K., 2022. Rural transportation infrastructure in low-and middle-income countries: a review of impacts, implications, and interventions. Sustainability 14, 2149. doi:https://doi.org/10.3390/su14042149. | spa |
dcterms.bibliographicCitation | Kaminski, B., Prałat, P., Theberge, F., 2021. Mining complex networks. Chapman and Hall ´ /CRC. doi:https://doi.org/10.1201/ 9781003218869. | spa |
dcterms.bibliographicCitation | Kandt, J., Batty, M., 2021. Smart cities, big data and urban policy: Towards urban analytics for the long run. Cities 109, 102992. doi:https: //doi.org/10.1016/j.cities.2020.102992. | spa |
dcterms.bibliographicCitation | Karimi, H., Ghadirifaraz, B., Shetab Boushehri, S.N., Hosseininasab, S.M., Rafiei, N., 2021. Reducing traffic congestion and increasing sustainability in special urban areas through one-way traffic reconfiguration. Transportation , 1–24doi:https://doi.org/10.1007/ s11116-020-10162-4. | spa |
dcterms.bibliographicCitation | Khattak, F.W., Alhwaiti, Y.S., Ali, A., Faisal, M., Siddiqi, M.H., 2021. Protein-protein interaction analysis through network topology (oral cancer). Journal of Healthcare Engineering 2021. doi:https://doi.org/10.1155/2021/6623904. | spa |
dcterms.bibliographicCitation | Kim, J., Wilhelm, T., 2008. What is a complex graph? Physica A: Statistical Mechanics and its Applications 387, 2637–2652. doi:https: //doi.org/10.1016/j.physa.2008.01.015 | spa |
dcterms.bibliographicCitation | Kovaciˇ c, M., Mutavd ´ zija, M., Buntak, K., 2022. New paradigm of sustainable urban mobility: Electric and autonomous vehicles—a review and ˇ bibliometric analysis. Sustainability 14, 9525. doi:https://doi.org/10.3390/su14159525 | spa |
dcterms.bibliographicCitation | Lee, T.J., Kakehashi, M., Rao, A.S.S., 2021. Network models in epidemiology, in: Handbook of Statistics. Elsevier. volume 44, pp. 235–256. doi:https://doi.org/10.1016/bs.host.2020.09.002. | spa |
dcterms.bibliographicCitation | Lenormand, M., Samaniego, H., Chaves, J.C., da Fonseca Vieira, V., da Silva, M.A.H.B., Evsukoff, A.G., 2020. Entropy as a measure of attractiveness and socioeconomic complexity in rio de janeiro metropolitan area. Entropy 22, 368. doi:https://doi.org/10.3390/e22030368. | spa |
dcterms.bibliographicCitation | Li, Z.T., Nie, W.P., Cai, S.M., Zhao, Z.D., Zhou, T., 2023. Exploring the topological characteristics of urban trip networks based on taxi trajectory data. Physica A: Statistical Mechanics and its Applications 609, 128391. doi:https://doi.org/10.1016/j.physa.2022.128391. | spa |
dcterms.bibliographicCitation | Lin, J., Ban, Y., 2013. Complex network topology of transportation systems. Transport reviews 33, 658–685. doi:https://doi.org/10.1080/ 01441647.2013.848955. | spa |
dcterms.bibliographicCitation | Liu, J., Yuan, Y., 2024. Exploring dynamic urban mobility patterns from traffic flow data using community detection. Annals of GIS , 1– 20doi:https://doi.org/10.1080/19475683.2024.2324393. | spa |
dcterms.bibliographicCitation | Maltese, I., Gatta, V., Marcucci, E., 2021. Active travel in sustainable urban mobility plans. an italian overview. Research in Transportation Business & Management 40, 100621. doi:https://doi.org/10.1016/j.rtbm.2021.100621. | spa |
dcterms.bibliographicCitation | Mantzaris, A.V., Chen, Y.H., Domenikos, G.R., Choudur, L., 2024. Exploring the effects of urban network topologies on entropy trajectories of segregation. Scientific Reports 14, 19188. doi:https://doi.org/10.1038/s41598-024-70029-x. | spa |
dcterms.bibliographicCitation | Mareeva, V.M., Ahmad, A.M., Ferwati, M.S., Garba, S.B., 2022. Sustainable urban regeneration of blighted neighborhoods: The case of al ghanim neighborhood, doha, qatar. Sustainability 14, 6963. doi:https://doi.org/10.3390/su14126963. | spa |
dcterms.bibliographicCitation | Mavlutova, I., Atstaja, D., Grasis, J., Kuzmina, J., Uvarova, I., Roga, D., 2023. Urban transportation concept and sustainable urban mobility in smart cities: a review. Energies 16, 3585. doi:https://doi.org/10.3390/en16083585 | spa |
dcterms.bibliographicCitation | Mouratidis, K., 2021. Urban planning and quality of life: A review of pathways linking the built environment to subjective well-being. Cities 115, 103229. doi:https://doi.org/10.1016/j.cities.2021.103229. | spa |
dcterms.bibliographicCitation | Mouratidis, K., Yiannakou, A., 2022. What makes cities livable? determinants of neighborhood satisfaction and neighborhood happiness in different contexts. Land use policy 112, 105855. doi:https://doi.org/10.1016/j.landusepol.2021.105855 | spa |
dcterms.bibliographicCitation | Park, J., Choi, J., Choi, J.Y., 2021. Network analysis in systems epidemiology. Journal of Preventive Medicine and Public Health 54, 259. doi:https://doi.org/10.3961\%2Fjpmph.21.190. | spa |
dcterms.bibliographicCitation | Patil, P., 2021. Sustainable transportation planning: Strategies for reducing greenhouse gas emissions in urban areas. Empirical Quests for Management Essences 1, 116–129. URL: https://researchberg.com/index.php/eqme/article/view/121 | spa |
dcterms.bibliographicCitation | Pedregosa, F., 2011. Scikit-learn: Machine learning in python fabian. Journal of machine learning research 12, 2825. doi:https://doi.org/ 10.48550/arXiv.1201.0490. | spa |
dcterms.bibliographicCitation | Perozzi, B., Al-Rfou, R., Skiena, S., 2014. Deepwalk: Online learning of social representations, in: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 701–710. doi:https://doi.org/10.1145/2623330.2623732 | spa |
dcterms.bibliographicCitation | Pokharel, R., Bertolini, L., te Brommelstroet, M., 2023. How does transportation facilitate regional economic development? a heuristic mapping of ¨ the literature. Transportation Research Interdisciplinary Perspectives 19, 100817. doi:https://doi.org/10.1016/j.trip.2023.100817. | spa |
dcterms.bibliographicCitation | Polterovich, L., Rosen, D., Samvelyan, K., Zhang, J., 2020. Topological persistence in geometry and analysis. volume 74. American Mathematical Soc. doi:https://doi.org/10.48550/arXiv.1904.04044. | spa |
dcterms.bibliographicCitation | Porru, S., Misso, F.E., Pani, F.E., Repetto, C., 2020. Smart mobility and public transport: Opportunities and challenges in rural and urban areas. Journal of traffic and transportation engineering (English edition) 7, 88–97. doi:https://doi.org/10.1016/j.jtte.2019.10.002. | spa |
dcterms.bibliographicCitation | Punzo, G., Panarello, D., Castellano, R., 2022. Sustainable urban mobility: evidence from three developed european countries. Quality & Quantity 56, 3135–3157. doi:https://doi.org/10.1007/s11135-021-01253-0. | spa |
dcterms.bibliographicCitation | Purvis, B., Mao, Y., Robinson, D., 2019. Entropy and its application to urban systems. Entropy 21, 56. doi:https://doi.org/10.3390/ e21010056. | spa |
dcterms.bibliographicCitation | Putro, A.N.S., Mokodenseho, S., Aziz, A.M., 2023. Analysis of information system development in the context of the latest technological era: Challenges and potential for success. West Science Information System and Technology 1, 19–26. doi:https://doi.org/10.58812/wsist. v1i01.168 | spa |
dcterms.bibliographicCitation | Ristvej, J., Lacinak, M., Ondrejka, R., 2020. On smart city and safe city concepts. Mobile Networks and Applications 25, 836–845. doi: ´ https: //doi.org/10.1007/s11036-020-01524-4. | spa |
dcterms.bibliographicCitation | Ruktanonchai, C.W., Lai, S., Utazi, C.E., Cunningham, A.D., Koper, P., Rogers, G.E., Ruktanonchai, N.W., Sadilek, A., Woods, D., Tatem, A.J., et al., 2021. Practical geospatial and sociodemographic predictors of human mobility. Scientific reports 11, 15389. doi:https://doi.org/ 10.1038/s41598-021-94683-7. | spa |
dcterms.bibliographicCitation | Scardoni, G., Laudanna, C., 2012. Centralities based analysis of complex networks. New frontiers in graph theory 323. doi:https://doi.org/ 10.5772/35846 | spa |
dcterms.bibliographicCitation | Shamsuzzoha, A., Nieminen, J., Piya, S., Rutledge, K., 2021. Smart city for sustainable environment: A comparison of participatory strategies from helsinki, singapore and london. Cities 114, 103194. doi:https://doi.org/10.1016/j.cities.2021.103194. | spa |
dcterms.bibliographicCitation | Shang, W.L., Chen, Y., Bi, H., Zhang, H., Ma, C., Ochieng, W.Y., 2020. Statistical characteristics and community analysis of urban road networks. Complexity 2020, 1–21. doi:https://doi.org/10.1155/2020/6025821. | spa |
dcterms.bibliographicCitation | Sierra Porta, D., Herrera Acevedo, D., 2024. Topological data analysis and network analysis approach for sustainable mobility in cities. URL: https://doi.org/10.17632/gmyt9wrgst.1, doi:10.17632/gmyt9wrgst.1. | spa |
dcterms.bibliographicCitation | Tokuda, E.K., Comin, C.H., da F Costa, L., 2022. Impact of the topology of urban streets on mobility optimization. Journal of Statistical Mechanics: Theory and Experiment 2022, 103204. doi:https:/doi.org/10.1088/1742-5468/ac9471. | spa |
dcterms.bibliographicCitation | Toli, A.M., Murtagh, N., 2020. The concept of sustainability in smart city definitions. Frontiers in Built Environment 6, 77. doi:https: //doi.org/10.3389/fbuil.2020.00077. | spa |
dcterms.bibliographicCitation | Tsavachidis, M., Le Petit, Y., 2022. Re-shaping urban mobility–key to europe´ s green transition. Journal of Urban Mobility 2, 100014. doi:https: //doi.org/10.1016/j.urbmob.2022.100014. | spa |
dcterms.bibliographicCitation | Valeri, M., Baggio, R., 2021. Italian tourism intermediaries: A social network analysis exploration. Current Issues in Tourism 24, 1270–1283. doi:https://doi.org/10.1080/13683500.2020.1777950. | spa |
dcterms.bibliographicCitation | Vecchio, G., Tiznado-Aitken, I., Hurtubia, R., 2020. Transport and equity in latin america: a critical review of socially oriented accessibility assessments. Transport reviews 40, 354–381. doi:https://doi.org/10.1080/01441647.2020.1711828 | spa |
dcterms.bibliographicCitation | Vecchio, G., Tiznado-Aitken, I., Mora-Vega, R., 2021. Pandemic-related streets transformations: Accelerating sustainable mobility transitions in latin america. Case Studies on Transport Policy 9, 1825–1835. doi:https://doi.org/10.1016/j.cstp.2021.10.002. | spa |
dcterms.bibliographicCitation | Wang, J., 2015. Resilience of self-organised and top-down planned cities—a case study on london and beijing street networks. PloS one 10, e0141736. doi:https://doi.org/10.1371/journal.pone.0141736. | spa |
dcterms.bibliographicCitation | Wang, L., Deng, X., Gui, J., Jiang, P., Zeng, F., Wan, S., 2023. A review of urban air mobility-enabled intelligent transportation systems: Mechanisms, applications and challenges. Journal of Systems Architecture , 102902doi:https://doi.org/10.1016/j.sysarc.2023. 102902. | spa |
dcterms.bibliographicCitation | Wang, X., You, S., Wang, L., 2017. Classifying road network patterns using multinomial logit model. Journal of Transport Geography 58, 104–112. doi:https://doi.org/10.1016/j.jtrangeo.2016.11.013. | spa |
dcterms.bibliographicCitation | Wen, Y., 2023. Rightful resistance: How do digital platforms achieve policy change? Technology in Society 74, 102266. doi:https://doi.org/ 10.1016/j.techsoc.2023.102266. | spa |
dcterms.bibliographicCitation | Wimbadi, R.W., Djalante, R., Mori, A., 2021. Urban experiments with public transport for low carbon mobility transitions in cities: A systematic literature review (1990–2020). Sustainable Cities and Society 72, 103023. doi:https://doi.org/10.1016/j.scs.2021.103023. | spa |
dcterms.bibliographicCitation | Wu, C.Y., Hu, M.B., Jiang, R., Hao, Q.Y., 2021. Effects of road network structure on the performance of urban traffic systems. Physica A: Statistical Mechanics and its Applications 563, 125361. doi:https://doi.org/10.1016/j.physa.2020.125361. | spa |
dcterms.bibliographicCitation | Xie, F., Levinson, D., 2007. Measuring the structure of road networks. Geographical analysis 39, 336–356. doi:https://doi.org/10.1111/j. 1538-4632.2007.00707.x | spa |
dcterms.bibliographicCitation | Xu, G., Zhou, Z., Jiao, L., Zhao, R., 2020. Compact urban form and expansion pattern slow down the decline in urban densities: A global perspective. Land Use Policy 94, 104563. doi:https://doi.org/10.1016/j.landusepol.2020.104563. | spa |
dcterms.bibliographicCitation | Yadav, K.K., Singh, A.K., 2022. Topology-based protein–protein interaction analysis of oral cancer proteins. Current Science (00113891) 123. doi:https://doi.org/10.18520/cs/v123/i10/1216-1224. | spa |
dcterms.bibliographicCitation | Yang, Y., Lu, X., Chen, J., Li, N., 2022. Factor mobility, transportation network and green economic growth of the urban agglomeration. Scientific Reports 12, 20094. doi:https://doi.org/10.1038/s41598-022-24624-5 | spa |
dcterms.bibliographicCitation | Yu, J., Stettler, M.E., Angeloudis, P., Hu, S., Chen, X.M., 2020. Urban network-wide traffic speed estimation with massive ride-sourcing gps traces. Transportation Research Part C: Emerging Technologies 112, 136–152. doi:https://doi.org/10.1016/j.trc.2020.01.023. | spa |
dcterms.bibliographicCitation | Zhang, M., Huang, T., Guo, Z., He, Z., 2022a. Complex-network-based traffic network analysis and dynamics: A comprehensive review. Physica A: Statistical Mechanics and its Applications 607, 128063. doi:https://doi.org/10.1016/j.physa.2022.128063 | spa |
dcterms.bibliographicCitation | Zhang, T., Duan, X., Li, Y., 2021. Unveiling transit mobility structure towards sustainable cities: An integrated graph embedding approach. Sustainable Cities and Society 72, 103027. doi:https://doi.org/10.1016/j.scs.2021.103027 | spa |
dcterms.bibliographicCitation | Zhang, Y., Chen, Y., Zhu, W., Wang, W., Zhang, Q., 2022b. The topological structure of urban roads and its relation with human activities at the street-based community level. Frontiers in Earth Science 10, 966907. doi:https://doi.org/10.3389/feart.2022.966907. | spa |
dcterms.bibliographicCitation | Zhang, Y., Cheng, L., 2023. The role of transport infrastructure in economic growth: Empirical evidence in the uk. Transport Policy 133, 223–233. doi:https://doi.org/10.1016/j.tranpol.2023.01.017. | spa |
dcterms.bibliographicCitation | Zhang, Y., Wang, X., Zeng, P., Chen, X., 2011. Centrality characteristics of road network patterns of traffic analysis zones. Transportation research record 2256, 16–24. doi:https://doi.org/10.3141/2256-03. | spa |
dcterms.bibliographicCitation | Zhang, Y., Zheng, X., Helbich, M., Chen, N., Chen, Z., 2022c. City2vec: Urban knowledge discovery based on population mobile network. Sustainable Cities and Society 85, 104000. doi:https://doi.org/10.1016/j.scs.2022.104000. | spa |
dcterms.bibliographicCitation | Zhao, S., Zhao, P., Cui, Y., 2017. A network centrality measure framework for analyzing urban traffic flow: A case study of wuhan, china. Physica A: Statistical Mechanics and its Applications 478, 143–157. doi:https://doi.org/10.1016/j.physa.2017.02.069. | spa |
datacite.rights | http://purl.org/coar/access_right/c_abf2 | spa |
oaire.version | http://purl.org/coar/version/c_b1a7d7d4d402bcce | spa |
dc.type.driver | info:eu-repo/semantics/article | spa |
dc.type.hasversion | info:eu-repo/semantics/draft | spa |
dc.identifier.doi | 10.1016/j.scs.2024.106076 | |
dc.subject.keywords | Urban mobility | spa |
dc.subject.keywords | Complex network analysis | spa |
dc.subject.keywords | Sustainable transportation | spa |
dc.subject.keywords | Sustainable urban development | spa |
dc.subject.keywords | Urban planning | spa |
dc.subject.keywords | Topological data analysis | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.identifier.instname | Universidad Tecnológica de Bolívar | spa |
dc.identifier.reponame | Repositorio Universidad Tecnológica de Bolívar | spa |
dc.publisher.place | Cartagena de Indias | spa |
dc.subject.armarc | LEMB | |
dc.publisher.faculty | Ciencias Básicas | spa |
dc.type.spa | http://purl.org/coar/resource_type/c_2df8fbb1 | spa |
dc.audience | Público general | spa |
dc.publisher.sede | Campus Tecnológico | spa |
oaire.resourcetype | http://purl.org/coar/resource_type/c_2df8fbb1 | spa |
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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.