Study on Relationship between Built Environment and High Income Group Travel Mode

Abstract
Figure/Table
References (0)
Related Citation (2)

Abstract In view of whether the dependence of high income groups on car travel mode can be improved by changing the built environment,based on the survey data of residents' travel in Xiamen in 2015 and multinomial Logit model,the differences of the influence of the built environment on the travel modes of high income groups with/without cars as well as the influence intensity of personal socio-economic attributes and built environment on the travel modes are explored,and the key factors that have significant influence on the travel modes of high income groups and the influence mechanism are analyzed. The results show that (1) After controlling other variables,the increase of the mixing degree of population density and land use in traffic communities inhibited the use of cars by high income groups,but the inhibition effect is weak. Employment density and bus stop density have no significant correlation with the travel mode of high income groups with cars. (2) The improvement of road network density,parking space density and greening rate in traffic communities promoted the use of cars by high income groups with cars. (3) The increase in the density of shopping malls and leisure and entertainment places in the traffic communities promoted the walking level of high income groups. The plot ratio of traffic district has no significant correlation with the travel mode of high income groups. (4) The high income groups inside the island of Xiamen prefer walking and public transport,while the high income groups outside the island prefer cars. (5) The influences of built environment on the travel modes of high income groups with/without cars are significantly different,and its effect is less than that of individual socio-economic attributes. The above conclusions provide a reference for improving residents' travel mode and city planning by optimizing the land use planning of residential communities of different resident groups.

Key words： urban traffic multinomial logit model disaggregate theory high-income groups land use built environment

Received: 23 December 2020

Fund:Supported by the National Natural Science Foundation of China Regional Science Foundation Project (No. 71864008); Guizhou Province Science and Technology Plan Project (Qiankehe Platform Talent No. 5769)

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	HUANG Yong
	ZHAO Hang
	XU Wang-tu
	DUAN Mei-hua
	WEI Wei

Cite this article:

HUANG Yong,ZHAO Hang,XU Wang-tu, et al. Study on Relationship between Built Environment and High Income Group Travel Mode[J]. Journal of Highway and Transportation Research and Development, 2022, 16(1): 71-81.

URL:

http://journal10.magtechjournal.com/Jwk_gljtkj_en/EN/ OR http://journal10.magtechjournal.com/Jwk_gljtkj_en/EN/Y2022/V16/I1/71

[1] BOARNET M G, BOSTIC R W, RODNYANSKY S, et al. Do High Income Households Reduce Driving More When Living Near Rail Transit?[J]. Transportation Research Part D:Transport and Environment, 2020, 80:102244.
[2] YANG Chao, PU Yi-chao, WANG Chao. Excess Commuting Model with a Consideration Resident Income Difference[J]. Journal of Tongji University:Natural Science, 2014, 42(4):564-569. (in Chinese)
[3] CUI B, BOISJOLY G, MIRANDA-M L, et al. Accessibility Matters:Exploring The Determinants of Public Transport Mode Share Across Income Groups in Canadian Cities[J]. Transportation Research Part D:Transport and Environment, 2019, 80:102276.
[4] HEDAU L, SANGHAI S. Development of Trip Generation Model Using Activity Based Approach[J]. International Journal of Civil, Structural, Environmental and Infrastructure Engineering Research and Development, 2014, 4(3):61-77.
[5] DING Chuan, LIN Yao-yu, WANG Yao-wu. Interactive Relationship Between Urban Spatial Expansion and Mobility Growth in China[J]. Journal of Transportation Systems Engineering & Information Technology, 2014, 14(3):9-15. (in Chinese)
[6] LIU Yu-feng, QIAN Yi-zhi, HU Da-wei, et al. Correlation Analysis of Travel Mode Choice for Urban Residents in Different Urban Size Based on Structural Equation Model[J]. Journal of Chang'an University:Natural Science Edition, 2018, 38(5):87-95. (in Chinese)
[7] CERVERO R, KOCKELMAN K. Travel Demand and The 3Ds:Density, Diversity, and Design[J]. Transportation Research Part D:Transport and Environment, 1997, 2(3):199-219.
[8] YIN Chao-ying, SHAO Chu-fu, WANG Xiao-quan. Influence of Urban Built Environment on Car Commuting Considering Parking Availability[J]. Journal of Jilin University:Engineering and Technology Edition, 2019, 49(3):714-719. (in Chinese)
[9] HUANG Xiao-yan, CAO Xiao-shu, YIN Jiangbin, et al. The Influence of Urban Transit and Built Environment on Walking[J]. Acta Geographica Sinica, 2020, 75(6):1256-1271. (in Chinese)
[10] EWING R, CERVERO R. Travel and the Built Environment:A Meta-Analysis[J]. Journal of the American Planning Association, 2010, 76(3):265-294.
[11] ZHANG Ying-jie, ZHENG Si-qi, WANG Rui. Can Rail Transit Really Promote "Green" Travel?-An Empirical Study Based on Beijing Micro Survey Samples[J]. World Economic Journal, 2015, (3):77-88. (in Chinese)
[12] LI Wan, DAN Bo, SUN Bin-dong, et al. Research on The Influence of Rail Transit on Travel Mode Selection-An Empirical Analysis Based on The Micro Survey Samples of Post-80s Generation in Shanghai[J]. Geographic Research, 2017, 36(5):945-956. (in Chinese)
[13] MISRA R, BHAT C R. Activity-Travel Patterns of Non-Workers in The San Francisco Bay Area:Exploratory Analysis[J]. Transportation Research Record. 2000, 1718(1):43-51.
[14] WALLACE B, BARNES J, RUTHERFORD G S. Evaluating The Effects of Traveler and Trip Characteristics on Trip Chaining, with Implications for Transportation Demand Management Strategies[J]. Transportation Research Record:Journal of The Transportation Research Board, 2000, 1718:97-106.
[15] MANOJA M, VERMA A. Activity-travel Behavior of Non-workers Belonging to Different Income Group Households in Bangalore, India[J]. Journal of Transport Geography, 2015, 49:99-109.
[16] WANG Feng-long, WANG Dong-gen. Characteristics and Determinants of Car Use in Beijing[J]. Acta Geographica Sinica, 2014, 69(6):771-781. (in Chinese)
[17] TA Na, CHAI Yan-wei, Guan Mei-Po. The Relationship Between the Built Environment and Car Travel Distance on Weekdays in Beijing[J]. Acta Geographica Sinica, 2015, 70(10):1675-1685.
[18] LI Shan-shan. Research on Urban Vehicle Parking Charge Rate Based on Traffic Demand Management[D]. Kunming:Kunming University of Science and Technology, 2008. (in Chinese)
[19] YIN Chao-ying, SHAO Chun-fu, WANG Xiao-quan, et al. Influence of Built Environment on Commuting Mode Choice Considering Spatial Heterogeneity[J]. Journal of Jilin University:Engineering and Technology Edition. 2020, 50(2):543-548. (in Chinese)
[20] LIMANOND T, NIEMEIER D A. Effect of Land Use on Decisions of Shopping Tour Generation:A Case Study of Three Traditional Neighborhoods in WA[J]. Transportation, 2004, 31(2):153-181.
[21] WEE V, BERT. Self-selection:A Key to a Better Understanding of Location Choices, Travel Behavior and Transport Externalities?[J]. Transport Reviews, 2009, 29(3):279-292.
[22] JIANG Nan, LI Sai, CAO Su-zhen, et al. Transportation Activity Patterns of Chinese Population During the COVID-19 Epidemic[J]. Research of Environmental Sciences, 2020, 33(7):1675-1682. (in Chinese)
[23] CHEN Jian, LI He-ping, ZHONG Yi-ying, et al. Housing and Travel Choice Behavior of Low and Middle Income Group[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(4):19-26. (in Chinese)
[24] FENG Jian-xi, YANG Zhen-shan. Factors Influencing Travel Behavior of Urban Elderly People in Nanjing[J]. Progress in Geography 2015, 34(12):1598-1608. (in Chinese)
[25] SHANG Shan-shan. Research on The Impact of Urban Built Environment on General School Travel Under The Guidance of Child Friendliness[D]. Suzhou:Suzhou University of Science And Technology, 2019. (in Chinese)
[26] LIU Ji-xiang, XIAO Long-zhu, YANG Lin-chuan, et al. A Tale of Two Social Groups in Xiamen, China:Trip Frequency of Migrants and Locals and Its Determinants[J]. Travel Behavior and Society, 2020, 20:213-224.
[27] ZHOU Zheng-long, SHA Jin-ming, FAN Yue-xin, et al. Spatiotemporal Changes and Driving Forces of Impervious Landscape Pattern in Xiamen City[J]. Journal of Applied Ecology, 2020, 31(1):230-238. (in Chinese)
[28] Xiamen Special Economic Zone Year Book[EB/OL]. (2006-12-05)[2019-09-23] http://202.109.255.156:8130/files_pub/publish/2016/2016main().htm. (in Chinese)
[29] ANJUKE. Fujian Housing Prices in 2015[EB/OL].(1999-04-13)[2019-10-02] https://www.anjuke.com/fangjia/fujian2015. (in Chinese)
[30] WANG Lin. Research on Housing Security of Middle Income Groups in Xiamen[D]. Xiamen:Jimei University, 2013. (in Chinese)
[31] CAO Xiao-shu, YANG Wen-yue. Examining The Effects of The Built Environment and Residential Self-Selection on Commuting Trips and The Related CO₂, Emissions:An Empirical Study in Guangzhou, China[J]. Transportation Research Part D:Transport & Environment, 2017, 52:480-494.
[32] FOX M. Transport Planning and The Human Activity Approach[J]. Journal of Transport Geography, 1995, 3(2):105-116.
[33] SUN Bin-dong, DAN Bo. Impact of Urban Built Environment on Residential Choice of Commuting Mode in Shanghai[J]. Acta Geographica Sinica, 2015, 70(10):1664-1674. (in Chinese)
[34] THI M CN, HIRONORI K, LE B P. Is Built Environment Associated with Travel Mode Choice in Developing Cities? Evidence from Hanoi[J]. Sustainability, 2020, 12(14):5773.
[35] DALUMPINES R, SCOTT D M. Making Mode Detection Transferable:Extracting Activity and Travel Episodes from GPS Data Using The Multinomial Logit Model and Python[J]. Transportation Planning & Technology, 2017, 40(5):523-539.
[36] YANG L, HIPP J A, ADLAKHA D, et al. Choice of Commuting Mode Among Employees:Do Home Neighborhood Environment, Worksite Neighborhood Environment, And Worksite Policy and Supports Matter?[J] Journal of Transport & Health, 2015, 2(2):212-218.
[37] COLE-HUNTER T, DONAIRE-GONZALEZ D, CURTOA, et al. Objective Correlates and Determinants of Bicycle Commuting Propensity in an Urban Environment[J]. Transportation Research Part D, 2015, 40:132-143.