Influences of built environment characteristics and individual factors on commuting distance: A multilevel mixture hazard modeling approach

Transportation Research Part D: Transport and Environment

Volumn 51, Issue , 2017, Pages 314-325

  Ding, Chuan ^a   Mishra, Sabyasachee ^b   Lu, Guangquan ^a   Yang, Jiawen ^c   Liu, Chao ^d  

^a BEIHANG UNIVERSITY   (China)

^b University of Memphis   (United States)

^c PEKING UNIVERSITY   (China)

^d UNIVERSITY OF MARYLAND   (United States)

Author keywords

Built environment; Commuting distance; Land use; Multilevel hazard model; Spatial heterogeneity

Indexed keywords

ENERGY UTILIZATION; GAS EMISSIONS; GREENHOUSE GASES; LAND USE; MAXIMUM LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATION; REGRESSION ANALYSIS; TRANSPORTATION;

BUILT ENVIRONMENT; COMMUTING DISTANCE; HAZARD MODELING; INDIVIDUAL FACTORS; MAXIMUM LIKELIHOOD ESTIMATION METHOD; SPATIAL HETEROGENEITY; TRAFFIC ANALYSIS ZONES; TRANSPORTATION ENERGY CONSUMPTION;

HAZARDS;

COMMUTING; ENERGY USE; GREENHOUSE GAS; HETEROGENEITY; LAND USE CHANGE; MODELING; RESEARCH; TRAVEL BEHAVIOR; URBAN PLANNING;

DISTRICT OF COLUMBIA; UNITED STATES; WASHINGTON [DISTRICT OF COLUMBIA];

EID: 85013101810     PISSN: 13619209     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trd.2017.02.002     Document Type: Article

References (41)

1. Anastasopoulos, P.C., Islam, B.M., Perperdou, D., Karlaftis, M.G., Hazard-based analysis of travel distance in urban environments: longitudinal data approach. J. Urban Plan. Dev. 138:1 (2012), 53–61, 10.1061/(ASCE)UP.1943-5444.0000102.
2. Antipova, A., Wang, F., Wilmot, C., Urban land uses, socio-demographic attributes and commuting: a multilevel modeling approach. Appl. Geography 31:3 (2011), 1010–1018, 10.1016/j.apgeog.2011.02.001.
3. Bhat, C.R., Guo, J.Y., A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels. Transp. Res. Part B 41:5 (2007), 506–526, 10.1016/j.trb.2005.12.005.
4. Bhat, C.R., Steed, J.L., A continuous-time model of departure time choice for urban shopping trips. Transp. Res. Part B 36:3 (2002), 207–224, 10.1016/S0191-2615(00)00047-3.
5. Bhat, C., Zhao, H., The spatial analysis of activity stop generation. Transp. Res. Part B 36:6 (2002), 557–575, 10.1016/S0191-2615(01)00019-4.
6. Boarnet, M.G., A broader context for land use and travel behavior, and a research agenda. J. Am. Plan. Assoc. 77:3 (2011), 197–213, 10.1080/01944363.2011.593483.
7. Cao, X., Disentangling the influence of neighborhood type and self-selection on driving behavior: an application of sample selection model. Transportation 36:2 (2009), 207–222, 10.1007/s11116-009-9189-9.
8. Cao, X., Examining the impacts of neighborhood design and residential self-selection on active travel: a methodological assessment. Urban Geography 36:2 (2015), 236–255, 10.1080/02723638.2014.956420.
9. Cervero, R., Murakami, J., Effects of built environments on vehicle miles traveled: evidence from 370 US urbanized areas. Environ. Plan. A 42:2 (2010), 400–418, 10.1068/a4236.
10. Chen, C., Gong, H., Robert Paaswell, R., Role of the built environment on mode choice decisions: additional evidence on the impact of density. Transportation 35:3 (2008), 285–299, 10.1007/s11116-007-9153-5.
11. Ding, C., Lin, Y., Liu, C., Exploring the influence of built environment on tour-based commuter mode choice: a cross-classified multilevel modeling approach. Transp. Res. Part D 32 (2014), 230–238, 10.1016/j.trd.2014.08.001.
12. Ding, C., Ma, X., Wang, Y., Wang, Y., Exploring the influential factors in incident clearance time: disentangling causation from self-selection bias. Accid. Anal. Prev. 85 (2015), 58–65, 10.1016/j.aap.2015.08.024.
13. Ding, C., Wang, Y., Xie, B., Liu, C., Understanding the role of built environment in reducing vehicle miles traveled accounting for spatial heterogeneity. Sustainability 6:2 (2014), 589–601, 10.3390/su6020589.
14. Ding, C., Wang, Y., Yang, J., Liu, C., Lin, Y., Spatial heterogeneous impact of built environment on household auto ownership levels: evidence from analysis at traffic analysis zone scales. Transp. Lett.: Int. J. Transp. Res. 8:1 (2016), 26–34, 10.1179/1942787515Y.0000000004.
15. Ewing, R., Cervero, R., Travel and the built environment: a synthesis. J. Transp. Res. Rec.: J. Transp. Res. Board 1780 (2001), 87–114, 10.3141/1780-10.
16. Ewing, R., Cervero, R., Travel and the built environment: a meta-analysis. J. Am. Plan. Assoc. 76:3 (2010), 265–294, 10.1080/01944361003766766.
17. Gadda, S., Kockelman, K.M., Damien, P., Continuous departure time models: a Bayesian approach. J. Transp. Res. Rec.: J. Transp. Res. Board 2132 (2009), 13–24, 10.3141/2132-02.
18. Guo, H., Gao, Z., Yang, X., Zhao, X., Wang, W., Modeling travel time under the influence of on-street parking. J. Transp. Eng. 138:2 (2012), 229–235, 10.1061/(ASCE)TE.1943-5436.0000319.
19. Handy, S., Cao, X., Mokhtarian, P., Correlation or causality between the built environment and travel behavior? Evidence from Northern California. Transp. Res. Part D 10:6 (2005), 427–444, 10.1016/j.trd.2005.05.002.
20. Hojati, A.T., Ferreira, L., Washington, S., Charles, P., Hazard based models for freeway traffic incident duration. Accid. Anal. Prev. 52 (2013), 171–181, 10.1016/j.aap.2012.12.037.
21. Hong, J., Goodchild, A., Land use policies and transport emissions: modeling the impact of trip speed, vehicle characteristics and residential location. Transp. Res. Part D 26 (2014), 47–51, 10.1016/j.trd.2013.10.011.
22. Hong, J., Shen, Q., Residential density and transportation emissions: examining the connection by addressing spatial autocorrelation and self-selection. Transp. Res. Part D 22 (2013), 75–79, 10.1016/j.trd.2013.03.006.
23. Hong, J., Shen, Q., Zhang, L., How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales. Transportation 41:3 (2014), 419–440, 10.1007/s11116-013-9462-9.
24. Hou, L., Lao, Y., Wang, Y., Zhang, Z., Zhang, Y., Li, Z., Time-varying effects of influential factors on incident clearance time using a non-proportional hazard-based model. Transp. Res. Part A 63 (2014), 12–24, 10.1016/j.tra.2014.02.014.
25. Limtanakool, N., Dijst, M., Schwanen, T., The influence of socio-economic characteristics, land use and travel time consideration on mode choice for medium- and longer-distance trips. J. Transp. Geogr. 14:5 (2006), 327–341, 10.1016/j.jtrangeo.2005.06.004.
26. Liu, C., Shen, Q., An empirical analysis of the influence of urban form on household travel and energy consumption. Comput. Environ. Urban Syst. 35:5 (2011), 347–357, 10.1016/j.compenvurbsys.2011.05.006.
27. Liu, X., Survival Analysis: Models and Applications. 2012, John Wiley & Sons, New York.
28. Manaugh, K., Miranda-Moreno, L.F., EI-Geneidy, A.M., The effect of neighbourhood characteristics, accessibility, home-work location, and demographics on commuting distance. Transportation 37:4 (2010), 627–646, 10.1007/s11116-010-9275-z.
29. Mishra, S., Welch, T., Jha, M.K., Performance indicators for public transit connectivity in multi-modal transportation networks. Transp. Res. Part-A: Policy Pract. 46:7 (2012), 1066–1085, 10.1016/j.tra.2012.04.006.
30. Mishra, S., Welch, T., Torrens, P., Fu, C., Zhu, H., Knaap, E., A tool for measuring and visualizing connectivity of transit stop, route and transfer center in a multimodal transportation network. Public Transp. 7:1 (2015), 77–99, 10.1007/s12469-014-0091-2.
31. Mokhtarian, P.L., Cao, X., Examining the impacts of residential self-selection on travel behavior: a focus on methodologies. Transp. Res. Part B 42:3 (2008), 204–228, 10.1016/j.trb.2007.07.006.
32. Nam, D., Mannering, F., An exploratory hazard-based analysis of highway incident duration. Transp. Res. Part A 34:2 (2000), 85–102, 10.1016/S0965-8564(98)00065-2.
33. Nasri, A., Zhang, L., The analysis of transit-oriented development (TOD) in Washington, D.C. and Baltimore metropolitan areas. Transp. Policy 32 (2014), 172–179, 10.1016/j.tranpol.2013.12.009.
34. National Capital Region Transportation Planning Board Metropolitan Washington Council of Governments, 2010. 2007/2008 TPB Household Travel Survey: Technical Documentation. August 27. Available from: < http://www.mwcog.org/uploads/committee-documents/Zl5YWV5W20100903131244.pdf>.
35. Noland, R.B., DiPetrillo, S., Transit-oriented development and the frequency of modal use. J. Transp. Land Use, 2015, 10.5198/jtlu.2015.517 (published online).
36. Pinjari, A.R., Eluru, N., Bhat, C.R., Pendyala, R.M., Spissu, E., Joint model of choice of residential neighborhood and bicycle ownership: accounting for self-selection and unobserved heterogeneity. Transp. Res. Rec.: J. Transp. Res. Board 2082 (2008), 17–26, 10.3141/2082-03.
37. Rubin, J.D., Noland, R.B., Transportation and climate change: developing technologies, policies, and strategies. Transp. Res. News 268 (2010), 3–5 Available from: .
38. Snijders, T.A.B., Bosker, R., Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. second ed., 2012, Sage, Thousand Oaks, California.
39. Van Acker, V., Witlox, F., Commuting trips within tours: how is commuting related to land use?. Transportation 38:3 (2011), 465–486, 10.1007/s11116-010-9309-6.
40. van den Berg, P., Arentze, T., Timmermans, H., A latent class accelerated hazard model of social activity duration. Transp. Res. Part A 46:1 (2012), 12–21, 10.1016/j.tra.2011.09.015.
41. Yang, X., Gao, Z., Guo, H., Huan, M., Survival analysis of car travel time near a bus stop in developing countries. Sci. China Technol. Sci. 55:8 (2012), 2355–2361, 10.1007/s11431-012-4900-z.