Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model

  • Chengcheng Xu Southeast University
  • Chen Wang Southeast University
  • Wei Wang Southeast University
  • Jie Bao Southeast University
  • Menglin Yang Southeast University
DOI: https://doi.org/10.7307/ptt.v29i4.2144
Keywords: e-bike, spatial autocorrelation, spatially autoregressive regression, random-parameter regression, survey data,

Abstract

Increased attention has been given to promoting e-bike usage in recent years. However, the research gap still exists in understanding the effects of spatial interdependence on e-bike choice. This study investigated how spatial interdependence affected the e-bike choice. The Moran’s I statistic test showed that spatial interdependence exists in e-bike choice at aggregated level. Bayesian spatial autoregressive logistic analyses were then used to investigate the spatial interdependence at individual level. Separate models were developed for commuting and non-commuting trips. The factors affecting e-bike choice are different between commuting and non-commuting trips. Spatial interdependence exists at both origin and destination sides of commuting and non-commuting trips. Travellers are more likely to choose e-bikes if their neighbours at the trip origin and destination also travel by e-bikes. And the magnitude of this spatial interdependence is different across various traffic analysis zones. The results suggest that, without considering spatial interdependence, the traditional methods may have biased estimation results and make systematic forecasting errors.

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Chengcheng Xu, Southeast University

Chengcheng Xu is an Assistant Professor at the school of transportation in the Southeast University. Dr. Xu's research interests are transportation planning, traffic safety and intelligent transportation systems.

Chen Wang, Southeast University

Dr. Wang is an Associate Professor at the school of transportation in the Southeast University. Dr. Wang's research interests are traffic safety and intelligent transportation systems.

Wei Wang, Southeast University

Dr. Wang is currently a Professor with the Key Laboratory of Traffic Planning and Management, School of Transportation, Southeast University, Nanjing, China. His research interests are urban transportation and intelligent transportation systems. He is a member of the model traffic technology panel of the National High-tech R&D Program of China (863 Program) and a member of the panel of the National Natural Science Foundation of China. He was the recipient of National Distinguished Teacher Award of China in 2007.

Jie Bao, Southeast University
Mr. Bao is currently working toward the Ph.D. degree with the Key Laboratory of Traffic Planning and Management, School of Transportation, Southeast University, Nanjing, China.
Menglin Yang, Southeast University
Menglin Yang is currently working toward the Ph.D. degree with the Key Laboratory of Traffic Planning and Management, School of Transportation, Southeast University, Nanjing, China.

References

Cherry C, Weinert J, Yang XM. Comparative Environmental Impacts of Electric Bikes in China. Transportation Research Part D: Transportation and Environment. 2009;14(5):281-290. Available from: http://www.sciencedirect.com/science/article/pii/S1361920908001387

Cherry C, Cervero R. Use characteristics and mode choice behavior of electric bike users in China. Transport Policy. 2007;14:247-257. Available from: http://www.sciencedirect.com/science/article/pii/S0967070X07000169

Chiu Y, Tzeng G. The market acceptance of electric motorcycles in Taiwan experience through a stated preference analysis. Transportation Research Part D: Transportation and Environment. 1999;4:127-146. Available from: http://www.sciencedirect.com/science/journal/13619209

Cherry C, Yang H, Jones L, He M. Dynamics of Electric Bike Ownership and Use in Kunming China. Transport Policy. 2016;45:127-135. Available from: http://www.sciencedirect.com/science/article/pii/S0967070X15300524

Jones LR, Cherry C, Vu TA, Nguyen QN. The effect of incentives and technology on the adoption of electric motorcycles: A stated choice experiment in Vietnam. Transportation Research Part A: Policy and Practice. 2013;57:1-11. Available from: http://www.sciencedirect.com/science/article/pii/S0965856413001675

Zhang Y, Li Y, Yang X, Liu Q, Li C. Built Environment and Household Electric Bike Ownership: Insights from Zhongshan Metropolitan Area, China. Transportation Research Record. 2013;2387:102–111. Available from: http://trrjournalonline.trb.org/doi/10.3141/2387-12

Popovich N, Gordon E, Shao Z, Xing Y, Yang Y, Handy S. Experiences of electric bicycle users in the Sacramento, California area. Travel Behaviour and Society. 2014;1:37-44. Available from: http://www.sciencedirect.com/science/article/pii/S2214367X13000185

Heyvaert S, Vanhaverbeke L, Knapen L, Declercq K, Coosemans T, Joeri VM. Choosing an Electric Vehicle as a Travel Mode: Travel Diary Case Study in a Belgian Living Lab Context. Presented at the Transportation Research Board 94th Annual Meeting; 2015.

Lee A, Molin E, Maat K, Sierzchula W. Electric Bicycle Use and Mode Choice in the Netherlands. Presented at the Transportation Research Board 94th Annual Meeting; 2015.

Montgomery BN. Cycling Trends and Fate in the Face of Bus Rapid Transit: Case Study of Jinan, Shandong Province, China. Transportation Research Record. 2000;2193:28-36. Available from: http://trrjournalonline.trb.org/doi/ref/10.3141/2193-04

Dill J. Rose G. Electric bikes and transportation policy insights from early adopters. Transportation Research Record. 2012;2314:1-6. Available from: http://trrjournalonline.trb.org/doi/10.3141/2314-01

Fyhri A, Sundfør HB. Ebikes-who wants to buy them, and what effect do they have? TØI Report 1325/2014. Institute of Transport Economics, Oslo; 2014. Available from: https://www.toi.no/getfile.php/Publikasjoner/T%C3%98I%20rapporter/2014/1325-2014/sum-1325-2014.pdf

Fyhri A, Fearnley A. Effects of e-bikes on bicycle use and mode share. Transportation Research Part D: Transportation and Environment. 2015;36:45-52. Available from: http://www.sciencedirect.com/science/article/pii/S1361920915000140

Goetzke F. Network effects in public transit use: evidence from a spatially autoregressive mode choice model for New York. Urban Studies. 2008;45:407-417. Available from: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.2358

Adjemian MC, Williams LJ. Estimating spatial interdependence in automobile type choice with survey data. Transportation Research Part A. 2010;44:661-675. Available from: http://www.sciencedirect.com/science/article/pii/S0965856410000911

Li Q, Lam WHK, Tam M L. Vehicle Travel Time Prediction in Spatio-Temporal Space. Applied Mechanics and Materials. 2013;253:1662-1665. Available from: http://www.scientific.net/AMM.253-255.1645

Lawson A. Bayesian Disease Mapping Hierarchical Modeling in Spatial Epidemiology. CRC; 2009.

Gelman A, Carlin J, Stern H, Rubin D. Bayesian Data Analysis. 2nd ed. London: Chapman and Hall; 2004.

Ntzoufras I. Bayesian Modeling Using WinBUGS. Wiley; 2009.

Washington SP, Karlaftis MG, Mannering FL. Statistical and Econometric Methods for Transportation Data Analysis. Boca Raton, FL: Chapman & Hall/CRC; 2003.

Weiss GM, Provost F. Learning when training data are costly: The effect of class distribution on tree induction. Journal of Artificial Intelligence Research. 2003;19:315-354. Available from: http://citeseerx.ist.psu.edu/viewdoc/summary?-doi=10.1.1.60.8100

Li Z, Wang W, Liu P, Ragland D. Physical environments influencing bicyclists’ perception of comfort on separated and on-street bicycle facilities. Transportation Research Part D: Transportation and Environment. 2012;17:256-261. Available from: http://www.sciencedirect.com/science/article/pii/S1361920911001556

Li Z, Wang W, Shan XF, Jin J, Lu J, Yang C. Analysis of bicycle passing events for LOS evaluation on physically separated bicycle roadways in China. Presented at 89th Annual Meeting of the Transportation Research Board. Washington, DC; 2010. Available from: https://trid.trb.org/view/2010/C/910355

Published
2017-08-28
How to Cite
1.
Xu C, Wang C, Wang W, Bao J, Yang M. Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model. Promet [Internet]. 2017Aug.28 [cited 2024Nov.21];29(4):351-62. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/2144
Issue
Vol 29 No 4 (2017)
Section
Articles

Copyright (c) 2017 Chengcheng Xu, Chen Wang, Wei Wang, Jie Bao, Menglin Yang

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