Motivations and Mode-choice Behavior of Micromobility Users in Washington, DC
DOI:
https://doi.org/10.13021/jmms.2020.2894Keywords:
micromobility, e-scooter, dockless, bikeshare, Capital Bikeshare, COVID-19, survey, multimodal, logistic regressionAbstract
The COVID-19 pandemic has reduced travel in general and disrupted travel patterns across the United States. The transit and ridehailing service ridership are particularly severely impacted. After an initial dip, shared micromobility services, including bikeshare, e-scooters, and e-bikeshare, have gained popularity as social distancing promoters with fewer points of contact. The findings of this article are based on the first phase of a two-phase mixed-mode survey of users and non-users of micromobility in Washington DC (n=440) in the Summer of 2019. While the phase-2 of the study is impacted by COVID-19 prevalence, results from the phase-1 are expected to serve as a critical baseline for post-pandemic travel behavior analysis and policy design. Findings indicate that each micromobility mode caters to different trip purposes and trip lengths of riders. While pleasure and time are identified as the biggest motivator for users, safety and pricing remain the most prominent barriers to users and non-users. Women and ethnic groups prefer to stay unimodal. Young and low-income users tend to be multimodal in their micromobility usage.
References
6 REFERENCES
[1] K. B. Campbell and C. Brakewood, "Sharing riders: How bikesharing impacts bus ridership in New York City," Transp. Res. Part A Policy Pract., vol. 100, pp. 264–282, Jun. 2017.
[2] S. A. Shaheen, S. Guzman, and H. Zhang, "Bikesharing in Europe, the Americas, and Asia," Transp. Res. Rec. J. Transp. Res. Board, vol. 2143, no. 1, pp. 159–167, Jan. 2010.
[3] S. Kaviti, M. M. Venigalla, and K. Lucas, "Travel behavior and price preferences of bikesharing members and casual users: A Capital Bikeshare perspective," Travel Behav. Soc., vol. 15, pp. 133–145, Apr. 2019.
[4] M. Venigalla, S. Kaviti, and T. Brennan, "Impact of Bikesharing Pricing Policies on Usage and Revenue: An Evaluation Through Curation of Large Datasets from Revenue Transactions and Trips," J. Big Data Anal. Transp., vol. 2, no. 1, pp. 1–16, Feb. 2020.
[5] E. Fishman, S. Washington, N. Haworth, and A. Mazzei, "Barriers to bikesharing: An analysis from Melbourne and Brisbane," J. Transp. Geogr., 2014.
[6] M. Chen, D. Wang, Y. Sun, E. O. D. Waygood, and W. Yang, "A comparison of users' characteristics between station-based bikesharing system and free-floating bikesharing system: case study in Hangzhou, China," Transportation (Amst)., vol. 47, no. 2, pp. 689–704, Apr. 2020.
[7] R. Buehler and A. Hamre, "Business and Bikeshare User Perceptions of the Economic Benefits of Capital Bikeshare," Transp. Res. Rec. J. Transp. Res. Board, vol. 2520, no. 1, pp. 100–111, Jan. 2015.
[8] J. A. Hirsch, I. Stewart, S. Ziegler, B. Richter, and S. J. Mooney, "Residents in Seattle, WA Report Differential Use of Free-Floating Bikeshare by Age, Gender, Race, and Location," Front. Built Environ., vol. 5, p. 17, Mar. 2019.
[9] Z. Chen, D. van Lierop, and D. Ettema, "Exploring Dockless Bikeshare Usage: A Case Study of Beijing, China," Sustainability, vol. 12, no. 3, p. 1238, Feb. 2020.
[10] J. Dill and G. Rose, "Electric Bikes and Transportation Policy," Transp. Res. Rec. J. Transp. Res. Board, vol. 2314, no. 1, pp. 1–6, Jan. 2012.
[11] A. A. Campbell, C. R. Cherry, M. S. Ryerson, and X. Yang, "Factors influencing the choice of shared bicycles and shared electric bikes in Beijing," Transp. Res. Part C Emerg. Technol., vol. 67, pp. 399–414, Jun. 2016.
[12] Y. He, Z. Song, Z. Liu, and N. N. Sze, "Factors Influencing Electric Bike Share Ridership: Analysis of Park City, Utah," Transp. Res. Rec. J. Transp. Res. Board, vol. 2673, no. 5, pp. 12–22, May 2019.
[13] F. Heineke, K., Kloss, B., Scurtu, D. and Weig, "Micromobility's 15,000-mile checkup," McKinsey & Company, Jan-2019.
[14] C. S. Smith and J. P. Schwieterman, "E-Scooter Scenarios: Evaluating the Potential Mobility Benefits of Shared Dockless Scooters in Chicago," Dec. 2018.
[15] M. Liu, S. Seeder, H. L.-I. of T. Engineers, and U. 2019, "Analysis of E-Scooter Trips and Their Temporal Usage Patterns," Inst. Transp. Eng. ITE J., vol. 89, no. 6, pp. 44–49, 2019.
[16] R. Clewlow, "The Micro-Mobility Revolution: The Introduction and Adoption of Electric Scooters in the United States," 2019.
[17] O. James, J. Swiderski, J. Hicks, D. Teoman, and R. Buehler, "Pedestrians and E-Scooters: An Initial Look at E-Scooter Parking and Perceptions by Riders and Non-Riders," Sustainability, vol. 11, no. 20, p. 5591, Oct. 2019.
[18] G. McKenzie, "Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, DC," J. Transp. Geogr., vol. 78, pp. 19–28, Jun. 2019.
[19] G. McKenzie, "Docked vs. Dockless bike-sharing: Contrasting spatiotemporal patterns," in Leibniz International Proceedings in Informatics, LIPIcs, 2018, vol. 114.
[20] B. Orr, J. MacArthur, and J. Dill, "The Portland E-Scooter Experience," TREC Friday Semin. Ser., Feb. 2019.
[21] R. L. Sanders, M. Branion-Calles, and T. A. Nelson, "To scoot or not to scoot: Findings from a recent survey about the benefits and barriers of using E-scooters for riders and non-riders," Transp. Res. Part A Policy Pract., vol. 139, pp. 217–227, Sep. 2020.
[22] D. A. Dillman et al., "Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the Internet," Soc. Sci. Res., vol. 38, no. 1, pp. 1–18, Mar. 2009.
[23] J. W. Sakshaug, A. Cernat, and T. E. Raghunathan, "Do Sequential Mixed-Mode Surveys Decrease Nonresponse Bias, Measurement Error Bias, and Total Bias? An Experimental Study," J. Surv. Stat. Methodol., vol. 7, no. 4, pp. 545–571, Dec. 2019.
[24] S. Kaviti, M. Venigalla, and K. Lucas, "Portraying and Differentiating Profiles and Preferences of Casual Users and Registered Members of Capital Bikeshare," 2019.
[25] D. G. Kleinbaum, K. Dietz, M. Gail, M. Klein, and M. Klein, Logistic regression. Springer, 2002.
[26] D. W. Hosmer Jr, S. Lemeshow, and R. X. Sturdivant, Applied logistic regression, vol. 398. John Wiley & Sons, 2013.
[27] M. Szumilas, "Explaining odds ratios," J. Can. Acad. Child Adolesc. Psychiatry, vol. 19, no. 3, pp. 227–229, Aug. 2010.
[1] K. B. Campbell and C. Brakewood, "Sharing riders: How bikesharing impacts bus ridership in New York City," Transp. Res. Part A Policy Pract., vol. 100, pp. 264–282, Jun. 2017.
[2] S. A. Shaheen, S. Guzman, and H. Zhang, "Bikesharing in Europe, the Americas, and Asia," Transp. Res. Rec. J. Transp. Res. Board, vol. 2143, no. 1, pp. 159–167, Jan. 2010.
[3] S. Kaviti, M. M. Venigalla, and K. Lucas, "Travel behavior and price preferences of bikesharing members and casual users: A Capital Bikeshare perspective," Travel Behav. Soc., vol. 15, pp. 133–145, Apr. 2019.
[4] M. Venigalla, S. Kaviti, and T. Brennan, "Impact of Bikesharing Pricing Policies on Usage and Revenue: An Evaluation Through Curation of Large Datasets from Revenue Transactions and Trips," J. Big Data Anal. Transp., vol. 2, no. 1, pp. 1–16, Feb. 2020.
[5] E. Fishman, S. Washington, N. Haworth, and A. Mazzei, "Barriers to bikesharing: An analysis from Melbourne and Brisbane," J. Transp. Geogr., 2014.
[6] M. Chen, D. Wang, Y. Sun, E. O. D. Waygood, and W. Yang, "A comparison of users' characteristics between station-based bikesharing system and free-floating bikesharing system: case study in Hangzhou, China," Transportation (Amst)., vol. 47, no. 2, pp. 689–704, Apr. 2020.
[7] R. Buehler and A. Hamre, "Business and Bikeshare User Perceptions of the Economic Benefits of Capital Bikeshare," Transp. Res. Rec. J. Transp. Res. Board, vol. 2520, no. 1, pp. 100–111, Jan. 2015.
[8] J. A. Hirsch, I. Stewart, S. Ziegler, B. Richter, and S. J. Mooney, "Residents in Seattle, WA Report Differential Use of Free-Floating Bikeshare by Age, Gender, Race, and Location," Front. Built Environ., vol. 5, p. 17, Mar. 2019.
[9] Z. Chen, D. van Lierop, and D. Ettema, "Exploring Dockless Bikeshare Usage: A Case Study of Beijing, China," Sustainability, vol. 12, no. 3, p. 1238, Feb. 2020.
[10] J. Dill and G. Rose, "Electric Bikes and Transportation Policy," Transp. Res. Rec. J. Transp. Res. Board, vol. 2314, no. 1, pp. 1–6, Jan. 2012.
[11] A. A. Campbell, C. R. Cherry, M. S. Ryerson, and X. Yang, "Factors influencing the choice of shared bicycles and shared electric bikes in Beijing," Transp. Res. Part C Emerg. Technol., vol. 67, pp. 399–414, Jun. 2016.
[12] Y. He, Z. Song, Z. Liu, and N. N. Sze, "Factors Influencing Electric Bike Share Ridership: Analysis of Park City, Utah," Transp. Res. Rec. J. Transp. Res. Board, vol. 2673, no. 5, pp. 12–22, May 2019.
[13] F. Heineke, K., Kloss, B., Scurtu, D. and Weig, "Micromobility's 15,000-mile checkup," McKinsey & Company, Jan-2019.
[14] C. S. Smith and J. P. Schwieterman, "E-Scooter Scenarios: Evaluating the Potential Mobility Benefits of Shared Dockless Scooters in Chicago," Dec. 2018.
[15] M. Liu, S. Seeder, H. L.-I. of T. Engineers, and U. 2019, "Analysis of E-Scooter Trips and Their Temporal Usage Patterns," Inst. Transp. Eng. ITE J., vol. 89, no. 6, pp. 44–49, 2019.
[16] R. Clewlow, "The Micro-Mobility Revolution: The Introduction and Adoption of Electric Scooters in the United States," 2019.
[17] O. James, J. Swiderski, J. Hicks, D. Teoman, and R. Buehler, "Pedestrians and E-Scooters: An Initial Look at E-Scooter Parking and Perceptions by Riders and Non-Riders," Sustainability, vol. 11, no. 20, p. 5591, Oct. 2019.
[18] G. McKenzie, "Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, DC," J. Transp. Geogr., vol. 78, pp. 19–28, Jun. 2019.
[19] G. McKenzie, "Docked vs. Dockless bike-sharing: Contrasting spatiotemporal patterns," in Leibniz International Proceedings in Informatics, LIPIcs, 2018, vol. 114.
[20] B. Orr, J. MacArthur, and J. Dill, "The Portland E-Scooter Experience," TREC Friday Semin. Ser., Feb. 2019.
[21] R. L. Sanders, M. Branion-Calles, and T. A. Nelson, "To scoot or not to scoot: Findings from a recent survey about the benefits and barriers of using E-scooters for riders and non-riders," Transp. Res. Part A Policy Pract., vol. 139, pp. 217–227, Sep. 2020.
[22] D. A. Dillman et al., "Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the Internet," Soc. Sci. Res., vol. 38, no. 1, pp. 1–18, Mar. 2009.
[23] J. W. Sakshaug, A. Cernat, and T. E. Raghunathan, "Do Sequential Mixed-Mode Surveys Decrease Nonresponse Bias, Measurement Error Bias, and Total Bias? An Experimental Study," J. Surv. Stat. Methodol., vol. 7, no. 4, pp. 545–571, Dec. 2019.
[24] S. Kaviti, M. Venigalla, and K. Lucas, "Portraying and Differentiating Profiles and Preferences of Casual Users and Registered Members of Capital Bikeshare," 2019.
[25] D. G. Kleinbaum, K. Dietz, M. Gail, M. Klein, and M. Klein, Logistic regression. Springer, 2002.
[26] D. W. Hosmer Jr, S. Lemeshow, and R. X. Sturdivant, Applied logistic regression, vol. 398. John Wiley & Sons, 2013.
[27] M. Szumilas, "Explaining odds ratios," J. Can. Acad. Child Adolesc. Psychiatry, vol. 19, no. 3, pp. 227–229, Aug. 2010.
