Open Access
Issue
E3S Web Conf.
Volume 434, 2023
4th International Conference on Energetics, Civil and Agricultural Engineering (ICECAE 2023)
Article Number 02022
Number of page(s) 7
Section Civil Engineering
DOI https://doi.org/10.1051/e3sconf/202343402022
Published online 12 October 2023
  1. V. A. Arroyo et al., “Transportation Research Board 2015 Executive Committee*.” [Online]. Available: www.TRB.org [Google Scholar]
  2. R.A.M. Madhuwanthi, A. Marasinghe, R.P.C.J. Rajapakse, A.D. Dharmawansa, and S. Nomura, “Factors Influencing to Travel Behavior on Transport Mode Choice,” International Journal of Affective Engineering, vol. 15, no. 2, pp. 63–72, 2016, doi: 10.5057/ijae.ijae-d-15-00044. [Google Scholar]
  3. R. Shafi, “The role of culture and evolving attitudes in travel behaviour assimilation among south asian immigrants in Melbourne, Australia,” Transportation (Amst), Aug. 2022, doi: 10.1007/s11116-022-10277-w. [Google Scholar]
  4. S. A. Appiah, “Understanding Car Ownership among Households in Developing Countries: A Case Study of Accra, Ghana,” 2020. [Google Scholar]
  5. P. Jing, M. Zhao, M. He, and L. Chen, “Travel mode and travel route choice behavior based on Random Regret Minimization: A systematic review,” Sustainability (Switzerland), vol. 10, no. 4. MDPI, Apr. 14, 2018. doi: 10.3390/su10041185. [Google Scholar]
  6. X. Tang, D. Wang, Y. Sun, M. Chen, and E. O. D. Waygood, “Choice behavior of tourism destination and travel mode: A case study of local residents in Hangzhou, China,” J Transp Geogr, vol. 89, Dec. 2020, doi: 10.1016/j.jtrangeo.2020.102895. [CrossRef] [Google Scholar]
  7. R. Curtale, J. Larsson, and J. Nässén, “Understanding preferences for night trains and their potential to replace flights in Europe. The case of Sweden,” Tour Manag Perspect, vol. 47, Jun. 2023, doi: 10.1016/j.tmp.2023.101115. [Google Scholar]
  8. Y. Tao, A. Petrović, and M. van Ham, “Commuting behaviours and subjective wellbeing: a critical review of longitudinal research,” Transp Rev, vol. 43, no. 4, pp. 599–621, 2023, doi: 10.1080/01441647.2022.2145386. [CrossRef] [Google Scholar]
  9. K. Goulias, “Travel Behavior Models Access and Accessibility View project Harvesting Social Media View project.” [Online]. Available: https://www.researchgate.net/publication/311440725 [Google Scholar]
  10. Y. Tyrinopoulos and C. Antoniou, “Factors affecting modal choice in urban mobility,” European Transport Research Review, vol. 5, no. 1, pp. 27–39, Mar. 2013, doi: 10.1007/s12544-012-0088-3. [CrossRef] [Google Scholar]
  11. “Activity based approach to travel demand modelling: An overview.” [Online]. Available: https://www.researchgate.net/publication/340594411 [Google Scholar]
  12. I. Delponte and V. Costa, “Ligurian Internal Areas and Demand Responsive Transport: an innovative approach to tackle social exclusion and to re-design sustainable accessibility,” in Transportation Research Procedia, Elsevier B.V., Jan. 2023, pp. 179–186. doi: 10.1016/j.trpro.2023.02.160. [CrossRef] [Google Scholar]
  13. J. W. Feilzer, D. Stroosnier, E. Dugundji, and T. Koch, “Predicting lessee switch behavior using logit models,” in Procedia Computer Science, Elsevier B.V., 2021, pp. 380–387. doi: 10.1016/j.procs.2021.03.048. [CrossRef] [Google Scholar]
  14. B. A. Shah, L. B. Zala, and N. A. Desai, “An integrated estimation approach to incorporate latent variables through SEM into discrete mode choice models to analyze mode choice attitude of a rider,” Transp Res Interdiscip Perspect, vol. 19, May 2023, doi: 10.1016/j.trip.2023.100819. [Google Scholar]
  15. B. Van Wee and D. Banister, “How to Write a Literature Review Paper?,” Transp Rev, vol. 36, no. 2, pp. 278–288, Mar. 2016, doi: 10.1080/01441647.2015.1065456. [CrossRef] [Google Scholar]
  16. R. Etminani-Ghasrodashti and M. Ardeshiri, “Modeling travel behavior by the structural relationships between lifestyle, built environment and non-working trips,” Transp Res Part A Policy Pract, vol. 78, pp. 506–518, Aug. 2015, doi: 10.1016/j.tra.2015.06.016. [CrossRef] [Google Scholar]
  17. I. Makarova, A. Pashkevich, and K. Shubenkova, “Ensuring Sustainability of Public Transport System through Rational Management,” in Procedia Engineering, Elsevier Ltd, 2017, pp. 137–146. doi: 10.1016/j.proeng.2017.01.078. [CrossRef] [Google Scholar]
  18. R. Ndebele, C. Aigbavboa, and A. Ogra, “Urban Transport Infrastructure Development in African Cities: Challenges and Opportunities.” [Google Scholar]
  19. A. Fattah and S. Riad Morshed, “Assessing the sustainability of transportation system in a developing city through estimating CO2 emissions and bio-capacity for vehicular activities,” Transp Res Interdiscip Perspect, vol. 10, Jun. 2021, doi: 10.1016/j.trip.2021.100361. [Google Scholar]
  20. T. M. Thanh Truong and A. M. Ngoc, “Parking behavior and the possible impacts on travel alternatives in motorcycle-dominated cities,” in Transportation Research Procedia, Elsevier B.V., 2020, pp. 3469–3485. doi: 10.1016/j.trpro.2020.08.105. [CrossRef] [Google Scholar]
  21. M. Adolphson, “Urban morphology, lifestyles and work-related travel behaviour: Evidence from the Stockholm region,” Transp Res Interdiscip Perspect, vol. 16, Dec. 2022, doi: 10.1016/j.trip.2022.100706. [Google Scholar]
  22. J. O. Vidana-Bencomo, E. Balal, J.C. Anderson, and S. Hernandez, “Modeling route choice criteria from home to major streets: A discrete choice approach,” International Journal of Transportation Science and Technology, vol. 7, no. 1, pp. 74–88, Mar. 2018, doi: 10.1016/j.ijtst.2017.12.002. [CrossRef] [Google Scholar]
  23. R. Krueger, M. Bierlaire, and P. Bansal, “A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections,” Transp Res Part C Emerg Technol, vol. 152, Jul. 2023, doi: 10.1016/j.trc.2023.104180. [CrossRef] [Google Scholar]
  24. M. Kante and B. Michel, “Use of partial least squares structural equation modelling (PLS-SEM) in privacy and disclosure research on social network sites: A systematic review,” Computers in Human Behavior Reports, vol. 10. Elsevier B.V., May 01, 2023. doi: 10.1016/j.chbr.2023.100291. [CrossRef] [Google Scholar]
  25. J. F. Hair, M. Sarstedt, L. Hopkins, and V. G. Kuppelwieser, “Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research,” European Business Review, vol. 26, no. 2. Emerald Group Publishing Ltd., pp. 106–121, 2014. doi: 10.1108/EBR-10-2013-0128. [CrossRef] [Google Scholar]
  26. A. Sukhov, M. Friman, and L. E. Olsson, “Unlocking potential: An integrated approach using PLS-SEM, NCA, and fsQCA for informed decision making,” Journal of Retailing and Consumer Services, vol. 74, Sep. 2023, doi: 10.1016/j.jretconser.2023.103424. [CrossRef] [Google Scholar]
  27. H. Zhou, J. L. Dorsman, M. Mandjes, and M. Snelder, “Sustainable mobility strategies and their impact: a case study using a multimodal activity based model,” Case Stud Transp Policy, vol. 11, Mar. 2023, doi: 10.1016/j.cstp.2022.100945. [Google Scholar]
  28. Y. Wang, Y. Wang, and C. Choudhury, “Modelling heterogeneity in behavioral response to peak-avoidance policy utilizing naturalistic data of Beijing subway travelers,” Transp Res Part F Traffic Psychol Behav, vol. 73, pp. 92–106, Aug. 2020, doi: 10.1016/j.trf.2020.06.016. [CrossRef] [Google Scholar]
  29. A. Tembe, F. Nakamura, S. Tanaka, R. Ariyoshi, and S. Miura, “The demand for public buses in sub-Saharan African cities: Case studies from Maputo and Nairobi,” IATSS Research, vol. 43, no. 2, pp. 122–130, Jul. 2019, doi: 10.1016/j.iatssr.2018.10.003. [CrossRef] [Google Scholar]
  30. M. Wardhana, “Spatial Analysis of Users Movement Pattern and its Socialization on Public Facilities and Environment through the ESVA,” Procedia Soc Behav Sci, vol. 227, pp. -106, Jul. 2016, doi: 10.1016/j.sbspro.2016.06.049. [CrossRef] [Google Scholar]
  31. C. Sofi and M. H. Dewi Susilowati, “Faktor Pengaruh Pola Pergerakan Wisatawan di Kota dan Kabupaten Tegal.” [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.