IDEAS home Printed from https://ideas.repec.org/a/wly/complx/v2025y2025i1n4130063.html

Exploring Land Use‐Transportation Nexus: A Comprehensive Analysis of Complexity Between Spatial Dynamics and Urban Travel Behavior in Developing Cities

Author

Listed:
  • Mahir Shahrier
  • Abdulla Al Kafy
  • Mohamed Alshayeb

Abstract

Urban travel behavior in developing cities forms a complex system with nonlinear interactions among socioeconomic factors, land use patterns, and transportation infrastructure. This study examines these intricate dynamics in Rajshahi City Corporation (RCC), Bangladesh, using a multimodel approach to capture emergent properties of urban mobility. Analyzing data from 2286 households across six zones, we developed three interconnected models: Trip Production Model (TPM), Trip Attraction Model (TAM), and Household Kilometers Traveled Model (HKTM). The TPM showed that increasing household size by one unit boosts trip production by 1.537 times, while a one‐unit increase in accessibility raises it by 1.930 times. Interestingly, the TAM revealed that higher accessibility can decrease trip attractions (coefficient: −1.412), indicating emergent congestion effects. The HKTM indicated that a one‐unit improvement in road connectivity leads to an increase of 2.652 km in household travel. Our results demonstrate that socioeconomic and land use factors explain 75.1% of the variability in trip production, emphasizing the system’s complexity. The City Center, with the highest entropy index (0.80), attracted the most trips, whereas the Northern Fringe, despite a low entropy (0.52), generated the highest number of trips. These surprising findings highlight the nonlinear relationships in urban mobility and stress the importance of context‐specific solutions to address urban transportation challenges. By applying complex systems theory, including concepts of self‐organization and feedback loops, we provide a comprehensive framework for understanding and modeling urban transport dynamics in developing areas, offering valuable insights for adaptive policy‐making amid rapid urban growth.

Suggested Citation

  • Mahir Shahrier & Abdulla Al Kafy & Mohamed Alshayeb, 2025. "Exploring Land Use‐Transportation Nexus: A Comprehensive Analysis of Complexity Between Spatial Dynamics and Urban Travel Behavior in Developing Cities," Complexity, John Wiley & Sons, vol. 2025(1).
    • Handle: RePEc:wly:complx:v:2025:y:2025:i:1:n:4130063
    DOI: 10.1155/cplx/4130063
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/cplx/4130063
    Download Restriction: no
    File URL: https://libkey.io/10.1155/cplx/4130063?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Marlon Boarnet, 2011. "A Broader Context for Land Use and Travel Behavior, and a Research Agenda," Journal of the American Planning Association, Taylor & Francis Journals, vol. 77(3), pages 197-213.
    3. Ruben Cordera & Pierluigi Coppola & Luigi dell’Olio & Ángel Ibeas, 2017. "Is accessibility relevant in trip generation? Modelling the interaction between trip generation and accessibility taking into account spatial effects," Transportation, Springer, vol. 44(6), pages 1577-1603, November.
    4. Konstantinos Gkiotsalitis & Oded Cats, 2021. "Public transport planning adaption under the COVID-19 pandemic crisis: literature review of research needs and directions," Transport Reviews, Taylor & Francis Journals, vol. 41(3), pages 374-392, May.
    5. Gilles Duranton & Matthew A. Turner, 2011. "The Fundamental Law of Road Congestion: Evidence from US Cities," American Economic Review, American Economic Association, vol. 101(6), pages 2616-2652, October.
    6. Abdulla Al Kafy & Md. Abdul Fattah & Mahir Shahrier & Hamad Ahmed Altuwaijri & Jordi Duch, 2024. "Unraveling Spatial Dynamics of Urban Complexity Between Land Use Patterns and Travel Behavior Using Structural Equation Modeling," Complexity, Hindawi, vol. 2024, pages 1-16, December.
    7. Melika Mehriar & Houshmand Masoumi & Inmaculada Mohino, 2024. "Street connectivity and active mobility in emerging economies: disparities of socioeconomic features and travel behavior in sprawling versus compact urban neighbourhoods," International Planning Studies, Taylor & Francis Journals, vol. 29(3), pages 287-308, July.
    8. Lisa Winkler & Drew Pearce & Jenny Nelson & Oytun Babacan, 2023. "The effect of sustainable mobility transition policies on cumulative urban transport emissions and energy demand," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    9. Wen-Long Shang & Yanyan Chen & Huibo Bi & Haoran Zhang & Changxi Ma & Washington Y. Ochieng, 2020. "Statistical Characteristics and Community Analysis of Urban Road Networks," Complexity, Hindawi, vol. 2020, pages 1-21, September.
    10. Lei Zhang & Jin Hyun Hong & Arefeh Nasri & Qing Shen, 2012. "How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(3), pages 40-52.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dubé, Jean & Le Gallo, Julie & Champagne, Marie-Pier & Hilal, Mohamed & Legros, Diègo, 2026. "Can public investment in transport influence densification and land use? Evidence from the tramway of Dijon (France)," Transport Policy, Elsevier, vol. 176(C).
    2. Guerra, Erick & Caudillo, Camilo & Monkkonen, Paavo & Montejano, Jorge, 2018. "Urban form, transit supply, and travel behavior in Latin America: Evidence from Mexico's 100 largest urban areas," Transport Policy, Elsevier, vol. 69(C), pages 98-105.
    3. Harbering, Marie & Schlüter, Jan, 2020. "Determinants of transport mode choice in metropolitan areas the case of the metropolitan area of the Valley of Mexico," Journal of Transport Geography, Elsevier, vol. 87(C).
    4. Choi, Kwangyul & Zhang, Ming, 2017. "The impact of metropolitan, county, and local land use on driving emissions in US metropolitan areas: Mediator effects of vehicle travel characteristics," Journal of Transport Geography, Elsevier, vol. 64(C), pages 195-202.
    5. Li, Jingjing & Kim, Changjoo & Sang, Sunhee, 2018. "Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors," Journal of Transport Geography, Elsevier, vol. 70(C), pages 141-147.
    6. Ding, Yu & Lu, Huapu, 2016. "Activity participation as a mediating variable to analyze the effect of land use on travel behavior: A structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 52(C), pages 23-28.
    7. Singh, Abhilash C. & Faghih Imani, Ahmadreza & Sivakumar, Aruna & Luna Xi, Yang & Miller, Eric J., 2024. "A joint analysis of accessibility and household trip frequencies by travel mode," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    8. Steven Spears & Marlon G Boarnet & Douglas Houston, 2017. "Driving reduction after the introduction of light rail transit: Evidence from an experimental-control group evaluation of the Los Angeles Expo Line," Urban Studies, Urban Studies Journal Limited, vol. 54(12), pages 2780-2799, September.
    9. Yu, Haitao & Peng, Zhong-Ren, 2019. "Exploring the spatial variation of ridesourcing demand and its relationship to built environment and socioeconomic factors with the geographically weighted Poisson regression," Journal of Transport Geography, Elsevier, vol. 75(C), pages 147-163.
    10. Li, Shanjun & Liu, Yanyan & Purevjav, Avralt-Od & Yang, Lin, 2019. "Does subway expansion improve air quality?," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 213-235.
    11. van de Coevering, Paul & Maat, Kees & van Wee, Bert, 2018. "Residential self-selection, reverse causality and residential dissonance. A latent class transition model of interactions between the built environment, travel attitudes and travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 466-479.
    12. Chen, Faan & Zhu, Yilin & Cao, Chuanpu & Yang, Xinyi & Ji, Xiang & Lai, Mingming & Qiu, Waishan & Nielsen, Chris P. & Wu, Jiaorong & Chen, Xiaohong, 2025. "Examining nonlinear causal relationship between the built environment and VKT using RF–XGBoost," Transport Policy, Elsevier, vol. 171(C), pages 661-681.
    13. Faizeh Hatami & Jean-Claude Thill, 2022. "Spatiotemporal Evaluation of the Built Environment’s Impact on Commuting Duration," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    14. Guan, Xiaodong & Wang, Donggen, 2019. "Influences of the built environment on travel: A household-based perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 710-724.
    15. Nicolas, Jean-Pierre & Pelé, Nicolas, 2017. "Measuring trends in household expenditures for daily mobility. The case in Lyon, France, between 1995 and 2015," Transport Policy, Elsevier, vol. 59(C), pages 82-92.
    16. Phani Kumar, P. & Ravi Sekhar, Ch. & Parida, Manoranjan, 2018. "Residential dissonance in TOD neighborhoods," Journal of Transport Geography, Elsevier, vol. 72(C), pages 166-177.
    17. Yang, Zhuo & Franz, Mark L. & Zhu, Shanjiang & Mahmoudi, Jina & Nasri, Arefeh & Zhang, Lei, 2018. "Analysis of Washington, DC taxi demand using GPS and land-use data," Journal of Transport Geography, Elsevier, vol. 66(C), pages 35-44.
    18. Islam, Md Rabiul & Saphores, Jean-Daniel M., 2022. "An L.A. story: The impact of housing costs on commuting," Journal of Transport Geography, Elsevier, vol. 98(C).
    19. repec:osf:socarx:93h82_v1 is not listed on IDEAS
    20. Yu Sang Chang & Sung Jun Jo & Yoo-Taek Lee & Yoonji Lee, 2021. "Population Density or Populations Size. Which Factor Determines Urban Traffic Congestion?," Sustainability, MDPI, vol. 13(8), pages 1-21, April.
    21. Zuo, Ting & Wei, Heng & Liu, Hao & Yang, Y. Jeffrey, 2019. "Bi-level optimization approach for configuring population and employment distributions with minimized vehicle travel demand," Journal of Transport Geography, Elsevier, vol. 74(C), pages 161-172.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:complx:v:2025:y:2025:i:1:n:4130063. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/8503 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.