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Decoding Urban Archetypes: Exploring Mobility-Related Homogeneity among Cities

Author

Listed:
  • Sascha von Behren

    (BMW AG, 80807 Munich, Germany)

  • Maximilian Turek

    (BMW AG, 80807 Munich, Germany)

  • Lukas Barthelmes

    (Institute for Transport Studies, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Hanna Scholta

    (Chair of Management Accounting, Technical University of Munich (TUM), 80333 Munich, Germany)

  • Frank Hansen

    (BMW AG, 80807 Munich, Germany)

  • Martin Kagerbauer

    (Institute for Transport Studies, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Christine Eisenmann

    (Chair of Infrastructure and Mobility Planning, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany)

Abstract

To make cities more sustainable and livable and to achieve climate targets in transportation, cities around the globe must undergo sustainable transformations. However, disparities in initial conditions pose challenges when trying to implement these sustainable changes. Identifying these differences aids in the comprehension of future developments. In this study, we establish an international comparison by decoding the mobility-related characteristics of cities and determining urban archetypes. Using publicly accessible data, we analyze and classify 96 cities in different countries. Therefore, we utilize principal component analysis to simplify the data. The emerging components serve as input for segmentation. This approach yields nine unique urban archetypes, ranging from Well-Functioning and Ancient Hybrid Cities in Europe to Paratransit and Traffic-Saturated Cities in the southern hemisphere. Our results show that there is a significant advantage to using a multidimensional segmentation basis, which we identify in an extensive literature review. The result is a finer segmentation, which is especially clear for European cities that demonstrate four different clusters. We discuss that the effect of future restrictions on private car usage will vary widely between the urban archetypes.

Suggested Citation

  • Sascha von Behren & Maximilian Turek & Lukas Barthelmes & Hanna Scholta & Frank Hansen & Martin Kagerbauer & Christine Eisenmann, 2023. "Decoding Urban Archetypes: Exploring Mobility-Related Homogeneity among Cities," Sustainability, MDPI, vol. 15(19), pages 1-23, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14231-:d:1248148
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    References listed on IDEAS

    as
    1. Carmen Cantuarias-Villessuzanne & Romain Weigel & Jeffrey Blain, 2021. "Clustering of European Smart Cities to Understand the Cities’ Sustainability Strategies," Post-Print hal-03362185, HAL.
    2. Iragaël Joly & Sophie Masson & Romain Petiot, 2004. "The determinants of urban public transport: an international comparison and econometric analysis," Post-Print halshs-00087456, HAL.
    3. Carmen Cantuarias-Villessuzanne & Romain Weigel & Jeffrey Blain, 2021. "Clustering of European Smart Cities to Understand the Cities’ Sustainability Strategies," Sustainability, MDPI, vol. 13(2), pages 1-20, January.
    4. Zhuge, Chengxiang & Wei, Binru & Shao, Chunfu & Shan, Yuli & Dong, Chunjiao, 2020. "The role of the license plate lottery policy in the adoption of Electric Vehicles: A case study of Beijing," Energy Policy, Elsevier, vol. 139(C).
    5. Ismagilova, Elvira & Hughes, Laurie & Dwivedi, Yogesh K. & Raman, K. Ravi, 2019. "Smart cities: Advances in research—An information systems perspective," International Journal of Information Management, Elsevier, vol. 47(C), pages 88-100.
    6. Miriam Magdolen & Sascha von Behren & Lukas Burger & Bastian Chlond, 2021. "Mobility Styles and Car Ownership—Potentials for a Sustainable Urban Transport," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    7. Karathodorou, Niovi & Graham, Daniel J. & Noland, Robert B., 2010. "Estimating the effect of urban density on fuel demand," Energy Economics, Elsevier, vol. 32(1), pages 86-92, January.
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