References

• 1. 1)
     • 25. Guo, Y.Y., Li, Z.B., Wu, Y., et al: ‘Evaluating factors affecting electric bike users’ registration of license plate in China using Bayesian approach’, Transp. Res. F, Traffic Psychol. Behav., 2018, 59, pp. 212–221.
  2. 2)
     • 9. Zhang, R., Yao, E., Liu, Z.: ‘School travel mode in Beijing, China’, J. Transp. Geogr., 2017, 62, pp. 98–110.
  3. 3)
     • 12. Spencer, P., Watts, R., Vivanco, L., et al: ‘The effect of environmental factors on bicycle commuters in Vermont: influences of a northern climate’, J. Transp. Geogr., 2013, 31, pp. 11–17.
  4. 4)
     • 15. Rubin, O., Mulder, C.H., Bertolini, L.: ‘The determinants of mode choice for family visits-evidence from Dutch panel data’, J. Transp. Geogr., 2014, 38, pp. 137–147.
  5. 5)
     • 5. Li, W., Kamargianni, M.: ‘Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: a mode choice mode and policy simulation for Taiyuan-China’, Transp. Res. A, Policy Pract., 2018, 111, pp. 277–291.
  6. 6)
     • 7. Haustein, S., Thorhauge, M., Cherchi, E.: ‘Commuter’ attitudes and norms related to travel time and punctuality: a psychographic segmentation to reduce congestion’, Travel Behav. Soc., 2018, 12, pp. 41–50.
  7. 7)
     • 8. Ye, R., Helena, T.: ‘Satisfaction with the commute: the role of travel mode choice, built environment and attitudes’, Transp. Res. D, Transp. Environ., 2017, 52, pp. 535–547.
  8. 8)
     • 22. Moore, D.N., Schneider, W.H.IV, Savolainen, P.T., et al: ‘Mixed logit analysis of bicyclist injury severity resulting from motor vehicle crashes at intersection and non-intersection locations’, Accident Anal. Prev., 2011, 43, pp. 621–630.
  9. 9)
     • 19. Pal, A., Zhang, Y.: ‘Free-floating bike sharing: solving real-life large-scale staticrebalancing problems’, Transp. Res. C, Emerg. Technol., 2017, 80, pp. 92–116.
  10. 10)
      • 26. Guo, Y.Y., Osama, A., Sayed, T.: ‘A cross-comparison of different techniques for modeling macro-level cyclist crashes’, Accident Anal. Prev., 2018, 113, pp. 38–46.
  11. 11)
      • 10. Zhan, G., Yan, X., Zhu, S., et al: ‘Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China’, Transp. Policy, 2016, 45, pp. 55–65.
  12. 12)
      • 20. Faghih-Imani, A., Anowar, S., Miller, E.J., et al: ‘Hail a cab or ride a bike? A travel time comparison of taxi and bicycle-sharing systems in New York city’, Transp. Res. A, Policy Pract., 2017, 101, pp. 11–21.
  13. 13)
      • 18. Darren, M.S., Celenna, C.: ‘What factors influence bike share ridership? An investigation of Hamilton, Ontario's bike share hubs’, Travel Behav. Soc., 2019, 16, pp. 50–58.
  14. 14)
      • 6. Jia, N., Li, L., Ling, S., et al: ‘Influence of attitudinal and low-carbon factors on behavioral intention of commuting mode choice – a cross-city study in China’, Transp. Res. A, Policy Pract., 2018, 111, pp. 108–118.
  15. 15)
      • 27. Guo, Y.Y., Li, Z.B., Liu, P., et al: ‘Modeling correlation and heterogeneity in crash rates by collision types using full Bayesian random parameters multivariate Tobit model’, Accident Anal. Prev., 2019, 128, pp. 164–174.
  16. 16)
      • 14. He, S.Y., Thøgersen, J.: ‘The impact of attitudes and perceptions on travel mode choice and car ownership in a Chinese megacity: the case of Guangzhou’, Res. Transp. Econ., 2017, 62, pp. 57–67.
  17. 17)
      • 24. Guo, Y.Y., Li, Z.B., Wu, Y., et al: ‘Exploring unobserved heterogeneity in bicyclists’ red-light running behaviors at different crossing facilities’, Accident Anal. Prev., 2018, 115, pp. 118–127.
  18. 18)
      • 21. Campbell, K.B., Brakewood, C.: ‘Sharing riders: how bike-sharing impacts bus ridership in New York city’, Transp. Res. A, Policy Pract., 2017, 100, pp. 264–282.
  19. 19)
      • 17. Geng, J., Long, R., Chen, H.: ‘Impact of information intervention on travel mode choice of urban residents with different goal frames: a controlled trial in Xuzhou, China’, Transp. Res. A, Policy Pract., 2016, 91, pp. 134–147.
  20. 20)
      • 4. Tsinghua Tongheng Urban Planning & Design Institute (THUPDI): ‘Bike-sharing and the City 2017 White Paper’. Available at http//www.sohu.com/a/133766880_58110, accessed 2017, in Chinese.
  21. 21)
      • 23. Gong, L., Fan, W.: ‘Modeling single-vehicle run-off-road crash severity in rural areas: accounting for unobserved heterogeneity and age difference’, Accident Anal. Prev., 2017, 101, pp. 124–134.
  22. 22)
      • 2. Faghih-Imani, A., Hampshire, R., Marla, L., et al: ‘An empirical analysis of bike sharing usage and rebalancing: evidence from Barcelona and Seville’, Transp. Res. A, Policy Pract., 2017, 97, pp. 177–191.
  23. 23)
      • 11. Habib, K.N., Mann, J., Mahmoud, M., et al: ‘Synopsis of bicycle demand in the city of Toronto: investigating the effects of perception, consciousness and comfortability on the purpose of biking and bike ownership’, Transp. Res. A, Policy Pract., 2014, 70, pp. 67–80.
  24. 24)
      • 13. Hu, H., Xu, J., Shen, Q., et al: ‘Travel mode choices in small cities of China: a case study of Changting’, Transp. Res. D, Transp. Environ., 2018, 59, pp. 361–374.
  25. 25)
      • 3. Campbell, A.A., Cherry, C.R., Ryerson, M.S., et al: ‘Factors influencing the choice of shared and shared electric bikes in Beijing’, Transp. Res. C, Emerg. Technol., 2016, 67, pp. 399–414.
  26. 26)
      • 1. Bachand-Marleau, J., Lee, B.H.Y., El-Geneidy, A.M.: ‘Better understanding of factors influencing likelihood of using shared bicycle systems and frequency of use’, Transp. Res. Rec., J. Transp. Res. Board, 2012, 2314, pp. 66–71.
  27. 27)
      • 16. Habib, K.N., Weiss, A.: ‘Evolution of latent modal captivity and mode patterns for commuting trips: a longitudinal analysis using repeated cross-sectional data sets’, Transp. Res. A, Policy Pract., 2014, 66, pp. 39–51.