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Exploring Modal Choices for Sustainable Urban Mobility: Insights from the Porto Metropolitan Area in Portugal

Author

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  • Hudyeron Rocha

    (CITTA—Centro de Investigação do Território, Transportes e Ambiente, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal)

  • António Lobo

    (CITTA—Centro de Investigação do Território, Transportes e Ambiente, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal)

  • José Pedro Tavares

    (CITTA—Centro de Investigação do Território, Transportes e Ambiente, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal)

  • Sara Ferreira

    (CITTA—Centro de Investigação do Território, Transportes e Ambiente, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal)

Abstract

Efficient and sustainable urban mobility is critical for contemporary cities, and understanding the factors influencing modal choices is essential for addressing transportation challenges in metropolitan areas. This study focuses on the Porto Metropolitan Area (AMP) in Portugal and aims to gain insights into these factors. Using data from the last mobility survey (IMob) conducted in 2017, a multinomial logit (MNL) model is used to analyze individual modal choices amongst private motorized vehicles (PMVs), public transport (PT), and active modes (AMs). The findings unveiled that demographic, socioeconomic, and travel-related characteristics substantially influence individual modal choices within the studied area. Moreover, probability scenarios highlight the importance of financial considerations, environmental consciousness, and accessibility to public transport in promoting sustainable transportation options. These insights have significant implications for policymakers and stakeholders involved in urban planning and transportation management. This study contributes to the literature by providing valuable insights into individuals’ transportation preferences and behaviors, facilitating decision-making based on evidence for infrastructure improvements and targeted interventions. By promoting sustainable transportation alternatives and reducing reliance on PMVs, this study aims to enhance the livability and sustainability of the AMP, aligning with long-term sustainability goals.

Suggested Citation

  • Hudyeron Rocha & António Lobo & José Pedro Tavares & Sara Ferreira, 2023. "Exploring Modal Choices for Sustainable Urban Mobility: Insights from the Porto Metropolitan Area in Portugal," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:14765-:d:1257791
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    References listed on IDEAS

    as
    1. Kamargianni, Maria, 2015. "Investigating next generation's cycling ridership to promote sustainable mobility in different types of cities," Research in Transportation Economics, Elsevier, vol. 53(C), pages 45-55.
    2. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    3. Saelens, B.E. & Sallis, J.F. & Black, J.B. & Chen, D., 2003. "Neighborhood-Based Differences in Physical Activity: An Environment Scale Evaluation," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1552-1558.
    4. Mingwei He & Jianbo Li & Zhuangbin Shi & Yang Liu & Chunyan Shuai & Jie Liu, 2022. "Exploring the Nonlinear and Threshold Effects of Travel Distance on the Travel Mode Choice across Different Groups: An Empirical Study of Guiyang, China," IJERPH, MDPI, vol. 19(23), pages 1-23, November.
    5. Aaron Gutiérrez & Daniel Miravet & Òscar Saladié & Salvador Anton Clavé, 2019. "Transport Mode Choice by Tourists Transferring from a Peripheral High-Speed Rail Station to Their Destinations: Empirical Evidence from Costa Daurada," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    6. Ferreira, Sara & Amorim, Marco & Lobo, António & Kern, Mira & Fanderl, Nora & Couto, António, 2022. "Travel mode preferences among German commuters over the course of COVID-19 pandemic," Transport Policy, Elsevier, vol. 126(C), pages 55-64.
    7. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    8. Jonas De Vos & Patricia L. Mokhtarian & Tim Schwanen & Veronique Van Acker & Frank Witlox, 2016. "Travel mode choice and travel satisfaction: bridging the gap between decision utility and experienced utility," Transportation, Springer, vol. 43(5), pages 771-796, September.
    9. Idris, Ahmed Osman & Nurul Habib, Khandker M. & Shalaby, Amer, 2015. "An investigation on the performances of mode shift models in transit ridership forecasting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 551-565.
    10. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    11. S., Minal & Chalumuri (Ch.), Ravi Sekhar, 2016. "Commuter's sensitivity in mode choice: An empirical study of New Delhi," Journal of Transport Geography, Elsevier, vol. 57(C), pages 207-217.
    12. Zaher Youssef & Habib Alshuwaikhat & Imran Reza, 2021. "Modeling the Modal Shift towards a More Sustainable Transport by Stated Preference in Riyadh, Saudi Arabia," Sustainability, MDPI, vol. 13(1), pages 1-19, January.
    13. Li, Weibo & Kamargianni, Maria, 2018. "Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 277-291.
    14. 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.
    15. Tyrinopoulos, Yannis & Antoniou, Constantinos, 2008. "Public transit user satisfaction: Variability and policy implications," Transport Policy, Elsevier, vol. 15(4), pages 260-272, July.
    16. Thamires Ferreira Schubert & Elisa Henning & Simone Becker Lopes, 2020. "Analysis of the Possibility of Transport Mode Switch: A Case Study for Joinville Students," Sustainability, MDPI, vol. 12(13), pages 1-20, June.
    17. Redman, Lauren & Friman, Margareta & Gärling, Tommy & Hartig, Terry, 2013. "Quality attributes of public transport that attract car users: A research review," Transport Policy, Elsevier, vol. 25(C), pages 119-127.
    18. Prieto, Marc & Baltas, George & Stan, Valentina, 2017. "Car sharing adoption intention in urban areas: What are the key sociodemographic drivers?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 218-227.
    19. Hudyeron Rocha & Manuel Filgueiras & José Pedro Tavares & Sara Ferreira, 2023. "Public Transport Usage and Perceived Service Quality in a Large Metropolitan Area: The Case of Porto," Sustainability, MDPI, vol. 15(7), pages 1-15, April.
    20. Rafael Maldonado-Hinarejos & Aruna Sivakumar & John Polak, 2014. "Exploring the role of individual attitudes and perceptions in predicting the demand for cycling: a hybrid choice modelling approach," Transportation, Springer, vol. 41(6), pages 1287-1304, November.
    21. Zhang, Junyi & Timmermans, Harry & Borgers, Aloys & Wang, Donggen, 2004. "Modeling traveler choice behavior using the concepts of relative utility and relative interest," Transportation Research Part B: Methodological, Elsevier, vol. 38(3), pages 215-234, March.
    22. Hickman, Robin & Hall, Peter & Banister, David, 2013. "Planning more for sustainable mobility," Journal of Transport Geography, Elsevier, vol. 33(C), pages 210-219.
    23. Lu, Xiao-Shan & Liu, Tian-Liang & Huang, Hai-Jun, 2015. "Pricing and mode choice based on nested logit model with trip-chain costs," Transport Policy, Elsevier, vol. 44(C), pages 76-88.
    24. Moneim Massar & Imran Reza & Syed Masiur Rahman & Sheikh Muhammad Habib Abdullah & Arshad Jamal & Fahad Saleh Al-Ismail, 2021. "Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative?," IJERPH, MDPI, vol. 18(11), pages 1-23, May.
    25. Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
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