Case Studies
Feb 11, 2022

Impacts of Public Bicycles on Young People's Travel Mode Choices with Consideration of Chosen Intentions

Publication: Journal of Urban Planning and Development
Volume 148, Issue 2

Abstract

This paper addresses a problem in evaluating the impacts of internet-app-based dockless public bicycles and public transport (i-PB&PT) on young people's mode choices considering their choice intentions. A method is proposed, based on the theory of planned behavior and structural equation modeling, to identify changes in the modal split and in travelers' willingness to buy and use private cars after having the intention to use the i-PB&PT mode. Guangzhou City was used as the study case, and an stated preference (SP) surveys was conducted. (1) The density of i-PBs was increased and, accordingly, the reduced cost of i-PB use strengthened travelers' intentions to choose i-PB&PT. For example, when the bicycle search time decreased from 4 to 1 min, the i-PB&PT modal split increased from 38.21% to 41.28%, whereas, if the transfer time between PT and i-PB use decreased from 3.5 to 2 min, the modal split of the combined mode increased from 40.72% to 49.59%. (2) Car ownership decreased from 1,190,465 (for the case without bicycles) to 650,556 as the travelers' intention (endogenous latent variable) to choose the combined mode became stronger. In particular, the values of the three exogenous latent variables (E––emotional attitudes, O––satisfaction, and S––subjective norms) increased (E = 2 to E = 5; OS = 1 to O = 4; S = 2 to S = 4). Therefore, the large-scale implementation and widespread use of the i-PB&PT model should significantly decrease car travel and transport emissions.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
This study was supported by the Natural Science Foundation of Zhejiang Province, China (LQ21E080004).

References

Ajzen, I. 1985. “From intentions to actions: A theory of planned behavior.” In Action-control: From cognition to behavior, edited by J. Kuhl and J. Beckmann, 11–39. New York: Springer.
Ajzen, I. 1991. “The theory of planned behavior.” Organ. Behav. Hum. Decis. Processes 50 (2): 179–211. https://doi.org/10.1016/0749-5978(91)90020-T.
Al-Rashid, M. A., H. C. Goh, Y. A. S. Harumain, Z. Ali, T. Campisi, and T. Mahmood. 2021. “Psychosocial barriers of public transport use and social exclusion among older adults: Empirical evidence from Lahore, Pakistan.” Int. J. Environ. Res. Public Health 18 (1): 185. https://doi.org/10.3390/ijerph18010185.
Bagozzi, R. P., and Y. Yi 1998. “On the evaluation of structural equation models.” J. Acad. Marketing Sci 16 (1): 74–94. https://doi.org/10.1007/BF02723327.
BigData-Research. 2017. Q1 2017 China shared bicycle market research report. Beijing: BigData-Research.
Boomsma, A. 1983. “On the robustness of LISREL (maximum likelihood estimation) against small sample size and non-normality.” J. Am. Stat. Assoc. 79 (386): 480–480.
CBIRI (China Business Industry Research Institute). 2018. Research report on market prospects and investment and financing strategies of bicycle industry in 2018–2023. Shenzhen, China: CBIRI.
Chang, C.-H., and V. V. Thai. 2016. “Do port security quality and service quality influence customer satisfaction and loyalty?” Marit. Policy Manage. 43 (6): 720–736. https://doi.org/10.1080/03088839.2016.1151086.
Chen, C.-F., and W.-H. Chao. 2011. “Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit.” Transp. Res. Part F Psychol. Behav. 14 (2): 128–137. https://doi.org/10.1016/j.trf.2010.11.006.
Chen, J., R. Li, and Z. Y. Fu. 2019. “Model of acceptance of unmanned buses based on UTAUT.” J. Transp. Syst. Eng. Inf. Technol. 19 (6): 38–44.
Cheng, Y.-H., and S.-Y. Chen. 2015. “Perceived accessibility, mobility, and connectivity of public transportation systems.” Transp. Res. Part A Policy Pract. 77: 386–403. https://doi.org/10.1016/j.tra.2015.05.003.
CHNCI. 2018. Research report on market prospects and investment and financing strategies of bicycle industry in 2018–2023. Shenzhen, China: CHNCI.
Cicchetti, D. V., and S. Sparrow. 1981. “Developing criteria for establishing interrater reliability of specific items: Application to assessment of adaptive behavior.” Am. J. Ment. Deficiency 86: 127–137.
Codoon Technology. 2017. Shared bicycle data report. Beijing: Lotion Information.
CUPTA (China Urban Public Transit Association)–Shared Bicycle Branch. 2020. Analysis report on China’s shared bicycle industry in 2020. Beijing: CUPTA–Shared Bicycle Branch.
Daniel, J. S., G. J. M. Velders, S. Solomon, M. McFarland, and S. A. Montzka. 2007. “Present and future sources and emissions of halocarbons: Toward new constraints.” J. Geophys. Res. Atmos. 112: D2. https://doi.org/10.1029/2006JD007275.
Ding, L., W. F. Velicer, and L. L. Harlow. 1995. “Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices.” Struct. Equation Modell. Multidiscip. J. 2 (2): 119–143. https://doi.org/10.1080/10705519509540000.
Fleiss, J. 1981. Statistical methods for rates and proportions. 2nd ed. New York: Wiley.
Gaode Map, Academy of Science, Ministry of Transport, Tsinghua University-Daimler Continuous Transportation Research Base, etc. 2017a. First quarter of 2017 China’s major urban transportation analysis statement. Beijing: Gaode Map.
Gaode Map, Xiaolan Bicycle. 2017b. Public bicycle chapter of Q1 traffic report. Beijing: Gaode Map.
Gardner, B. 2009. “Modelling motivation and habit in stable travel mode contexts.” Transp. Res. Part F Psychol. Behav. 12 (1): 68–76. https://doi.org/10.1016/j.trf.2008.08.001.
Guerrero, T. E., J. de Dios Ortuzar, and S. Raveaub. 2020. “Traffic accident risk perception among drivers: A latent variable approach.” Transp. Plann. Technol. 43 (3): 313–324. https://doi.org/10.1080/03081060.2020.1735763.
Hair, J. F., M. Sarstedt, C. M. Ringle, and J. A. Mena. 2012. “An assessment of the use of partial least squares structural equation modeling in marketing research.” J. Acad. Marketing Sci. 40 (3): 414–433. https://doi.org/10.1007/s11747-011-0261-6.
Hamilton, T. L., and C. J. Wichman. 2018. “Bicycle infrastructure and traffic congestion: Evidence from DC’s capital bikeshare.” J. Environ. Econ. Manage. 87: 72–93. https://doi.org/10.1016/j.jeem.2017.03.007.
Hoogland, J. J., and A. Boomsma. 1998. “Robustness studies in covariance structure modeling: An overview and a meta-analysis.” Soc. Meth. & Res., 26 (3): 329–367.
Hoyle, P. K. 1999. Statistical strategies for small sample research. London: Sage.
Huang, L. S., and W. R. Su. 2018. “Exploration on the behavior patterns of public bicycle users in Kaohsiung City from the perspective of theory of planned behavior and structural equation model.” Preprints, submitted February 12, 2018: 2018020088. https://doi.org/10.20944/preprints201802.0088.v1.
Green, J., R. Steinbach, A. Jones, P. Edwards, C. Kelly, J. Nellthorp, A. Goodman, H. Roberts, M. Petticrew, and P. Wilkinson. 2014. “On the buses: A mixed-method evaluation of the impact of free bus travel for young people on the public health.” Public Health Res. 2 (1): 1–206.
Jiang, M. F. 2017. “A study on residents’ travel behavior under the impact of public bicycle: A case study of Siming District, Xiamen City. China urban planning Society and Dongguan Municipal People’s Government.” In Rational Planning for Sustainable Development - Papers Collection of the 2017 Annual Chinese Urban Planning Conf. (06 Urban Traffic Planning). Beijing: China Urban Planning Society and Dongguan Municipal People’s Government.
Kline, R. B. 2011. Principles and practice of structural equation modeling. 3. Baskı. New York: Guilford.
Klöckner, C. A., and T. Friedrichsmeier. 2011. “A multi-level approach to travel mode choice – How person characteristics and situation specific aspects determine car use in a student sample.” Transp. Res. Part F Psychol. Behav. 14 (4): 261–277. https://doi.org/10.1016/j.trf.2011.01.006.
Li, J., S. P. Jia, J. P. Qian, Y. Q. Wang, and S. J. Zhang. 2018. “Intention formation mechanism in the intercity travel mode choice influenced by the habit.” J. Transp. Syst. Eng. Inf. Technol. 18 (2): 7–12.
Line, T., K. Chatterjee, and G. Lyons. 2010. “The travel behavior intentions of young people in the context of climate change.” J. Transp. Geogr. 18 (2): 238–246. https://doi.org/10.1016/j.jtrangeo.2009.05.001.
Liu, X., Q. Wang, H.-H. Wei, H.-L. Chi, Y. Ma, and I. Y. Jian. 2020. “Psychological and demographic factors affecting household energy-saving intentions: A TPB-based study in northwest China.” Sustainability 12 (3): 836. https://doi.org/10.3390/su12030836.
Lu, J., and W. Wang. 2004. “Confirming method of urban taxi quantity.” J. Traffic Transp. Eng. 4 (1): 92–95.
Mallah, N., R. Rodríguez-Cano, A. Figueiras, and B. Takkouche. 2020. “Design, reliability and construct validity of a knowledge, attitude and practice questionnaire on personal use of antibiotics in Spain.” Sci. Rep. 20: 1–10.
Munoz-Mendez, F., K. Klemmer, K. Han, and S Jarvis. 2018. “Community structures, interactions and dynamics in London’s bicycle sharing network.” In Proc. 2018 ACM Int. Joint Conf. and 2018 Int. Symp. on Pervasive and Ubiquitous Computing and Wearable Computers. New York: Association for Computing Machinery.
Polit, D. F., C. T. Beck, and S. V. Owen. 2007. “Is the CVI an acceptable indicator of content validity? Appraisal and recommendations.” Res. Nurs. Health 30: 459–467. https://doi.org/10.1002/nur.20199.
Prospective Industry Research Institute. 2019. Analysis report on market prospect and investment planning of shared bicycle industry. Beijing: Prospective Industry Research Institute.
Schellinck, T., and M. R. Brooks. 2014. “Improving port effectiveness through determinance/performance gap analysis.” Marit. Policy Manage. 41 (4): 328–345. https://doi.org/10.1080/03088839.2013.809632.
Shaaban, K., and A. Maher. 2020. “Using the theory of planned behavior to predict the use of an upcoming public transportation service in Qatar.” Case Stud. Transp. Policy 8 (2): 484–491. https://doi.org/10.1016/j.cstp.2019.11.001.
Shaheen, S. A., E. W. Martin, and A. Cohen. 2013. “Public bikesharing and modal shift behavior: A comparative study of early bikesharing systems in North America.” Int. J. Transp. 1 (1): 35–54. https://doi.org/10.14257/ijt.2013.1.1.03.
Sheffi, Y. 1985. Urban transportation networks. Englewood Cliffs, NJ: Prentice-Hall.
Shelat, S., R. Huisman, and N. van Oort. 2018. “Analysing the trip and user characteristics of the combined bicycle and transit mode.” Res. Transp. Econ. 69: 68–76. https://doi.org/10.1016/j.retrec.2018.07.017.
Shen, W., W. Xiao, and X. Wang. 2016. “Passenger satisfaction evaluation model for urban rail transit: A structural equation modeling based on partial least squares.” Transp. Policy 46: 20–31. https://doi.org/10.1016/j.tranpol.2015.10.006.
Shenzhen Institute of Urban Transportation Planning and Design. 2017. Shenzhen Internet bicycle development evaluation and analysis report. Shenzhen, China: Shenzhen Transportation Commission.
Ulleberg, P., and T. Rundmo. 2003. “Personality, attitudes and risk perception as predictors of risky driving behaviour among young drivers.” Saf. Sci. 41: 427–443. https://doi.org/10.1016/S0925-7535(01)00077-7.
Wang, R. L. 2017. “Analysis of user characteristics of public bicycle in Shanghai and its relation with public transit development.” Commun. Ship. 4 (6): 46–52+80.
Wang, X. D., Z. H. Cheng, M. Trepanier, and L. J. Sun. 2021. “Modeling bike-sharing demand using a regression model with spatially varying coefficients.” J. Transp. Geogr. 93: 1–12.
Wang, Y. H., and Q. Wang. 2013. “Influencing factors of Beijing residents’ purchasing intention for new energy vehicles: A study based on TAM and TPB integration model.” Chin. J. Manage. Sci. S221: 691–698.
Wolf, E. J., K. M. Harrington, S. L. Clark, and M. W. Miller. 2013. “Sample size requirements for structural equation models.” Educ. Psychol. Meas. 73 (6): 913–934. https://doi.org/10.1177/0013164413495237.
Xu, C. X., and M. Jiang. 2014. “The formation mechanism of urban residents’ behavioral intention to travel by HSR: A case study of CHANGSHA.” Hum. Geogr. 1: 122–128.
Yang, X., D. Y. Peng, and F. Xie. 2016. “A study on the effects of TAM/TPB-based perceived risk cognition on user’s trust and behavior: Taking Yu’ebao, a value-added payment product as an example.” Manage. Rev. 28 (6): 229–240.
Yang, Z.-z., Y. Sun, J.-j. Li, and F. Lian. 2020. “Optimization of public bicycle distribution density considering the price curve of public space occupancy.” J. Urban Plann. Dev. 146 (3): 05020009. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000591.
Yiche Research Institute. 2019. China passenger vehicle “user age” insight report. Beijing: Yiche Research Institute.
Yuan, P. C., S. J. Wang, Y. Hu, and J. J. Cai. 2021. “A study on the intention of online car hailing: The mediating role of customer satisfaction.” Logist. Sci. Technol. 8: 77–81.
Zhou, J. J., Y. Zhao, and D. H. Long. 2011. “Prediction and analysis of urban taxi ownership.” Technol. Econ. Areas Commun. 13 (6): 27–31.
Zhou, Q., Y. Li, C. Meng, and H. P. Lu. 2008. “Analysis of travel demand based on a structural equation model.” J. Tsinghua Univ. 48 (5): 879–882.
Zhou, Y. L., J. M. Lu, S. Xu, and J. X. Cao. 2014. “Research on the site selection of the public bicycle system.” Adv. Mat. Res. 1030: 2292–2295.
Zhu, W., Y. Q. Pang, D. Wang, and X. W. Yu. 2012. “Travel behavior change after the introduction of public bicycle system: A case study of Minhang district, Shanghai.” Urban Plann. Forum 5: 76–81.

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Journal of Urban Planning and Development
Volume 148Issue 2June 2022

History

Received: Feb 26, 2021
Accepted: Nov 9, 2021
Published online: Feb 11, 2022
Published in print: Jun 1, 2022
Discussion open until: Jul 11, 2022

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Professor, Faculty of Maritime and Transportation, Ningbo Univ., Haiyun Building, Ningbo, China. ORCID: https://orcid.org/0000-0003-3402-0088. Email: [email protected]
Professor, Faculty of Maritime and Transportation, Ningbo Univ., Haiyun Building, Ningbo, China. Email: [email protected]
Dongxu Chen [email protected]
Lecturer, Faculty of Maritime and Transportation, Ningbo Univ., Haiyun Building, Ningbo, China (corresponding author). Email: [email protected]

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