Study on the Ownership of Motorized and Non-motorized Vehicles in Suburban Metro Station Areas: A Structural Equation Approach
Tóm tắt
As Chinese megacities are experiencing a large-scale motorization and suburbanization, an ever greater number of households are relocated to suburban towns. The increasing average travel distance surely encourages car growth. China is now the world’s largest car consumer, resulting in a series of unforeseen environmental and public health issues. On the other hand, scooters, electric bikes, and motorcycles become attractive options to substitute non-motorized bicycles. The ongoing demographic changes should also be taken in account. China has a rapidly aging population and a higher birth rate following reforms to the one-child policy allowing couples to have a second child. These changes will lead to a dramatic alteration of the household composition in the near future. Under above emerging contexts, this study aims to understand what implies the ownership of motorized and non-motorized vehicles in suburban metro station areas by means of a structural equation model. The data employed in this study are based on a household survey collected from three neighborhoods in Shanghai suburban metro station areas in 2010. The major findings include: (1) Income is a decisive element in car ownership. Specifically, high-income households have higher propensity to own a car, while middle and poor income families tend to own scooters, electric bikes, motorcycles, or bicycles. (2) Workplace built environment features or mode preferences are not essential to understanding vehicle ownership in Chinese context. (3) Stem families are more likely to own cars; the presence of a child or a senior family member increases the probability of owning a car by enlarging the household. (4) The results estimated for core family and DINK (couple with no child) family are highly consistent, and these families are less likely to own cars. Therefore, transport policies may focus more on households. Providing safe, pleasant, and efficient pedestrian and bicycle paths for children and seniors may decrease the attractiveness of owning cars.
Tài liệu tham khảo
The National Bureau of Statistics of China (2014) China statistical yearbook. China statistics Press, Beijing
Municipality, T.a.P.C.o.S. (2012). Shanghai the 4th Comprehensive Transport Survey Summary Report
Pan H, Shen Q, Zhao T (2013) Travel and car ownership of residents near new suburban metro stations in Shanghai, China. Transp Res Rec 2394:63–69
Qi FJ (2006) Shanghai district rail transit line planning and design concept and application. Urban Rail Transit 11:54–57
Pan HM (2002) Metropolitan rapid transit and urban development-the international experience and the research in Shanghai. Tongji University Press, Shanghai
Pan HJ (2007) Metropolitan rail transit and the spatial structure optimization. Shanghai Urban Plan 6:37–43
Pan HJ (2008) Urban rail transit and the sustainable development. Urban Transp 4:35–39
Municipality, T.a.P.C.o.S.(2015). Shanghai the 5th comprehensive transport survey summary report
Feng J, Zhou Y, Wu F (2008) New trends of suburbanization in Beijing since 1990: from government-led to market-oriented. Reg Stud 42:83–99
Pan H, Zhang M (2008) Rail transit impacts on land use: evidence from Shanghai, China. Transp Res Rec 2048:16–25
Chen X, Zhao J (2013) Bidding to drive: car license auction policy in Shanghai and its public acceptance. Transp Policy 27:39–52
Bento AM, Cropper ML, Mobarak AM, Vinha K (2003) The impact of urban spatial structure on travel demand in the United States. (World Bank policy research working paper #3007)
Bhatia R (2004) Land use: a key to livable transportation. In: Paper presented at the 40th international making cities livable conference, London, UK
Cervero R (2006) Alternative approaches to modeling the traveldemand impacts of smart growth. J Am Plan Assoc 72(3):285–295
Cervero R, Duncan M (2006) Which reduces vehicle travel more: jobs-housing balance or retail-housing mixing? J Am Plan Assoc 72(4):475–490
Chapman J, Frank L (2004) Integrating travel behavior and urban form data to address transportation and air quality problems in Atlanta, Georgia (Research Project No. 9819, Task Order 97–13). Washington, DC: U.S. Department of Transportation
Hess PM, Moudon AV, Snyder MC, Stanilov K (1999) Site design and pedestrian travel. Transp Res Rec 1674:9–19
Naess P (2005) Residential location affects travel behavior—but how and why? The case of Copenhagen metropolitan area. Prog Plan 63(1):167–257
Cervero R (2002) Built environments and mode choice: toward a normative framework. Transp Res D 7(4):265–284
Frank LD, Bradley M, Kavage S, Chapman J, Lawton K (2008) Urban form, travel time, and cost relationships with tour complexity and mode choice. Transportation 35(1):37–54
Lee C, Moudon AV (2006) Correlates of walking for transportation or recreation purposes. J Phys Activity Health 3(1):77–98
Rodriguez DA, Joo J (2004) The relationship between nonmotorized mode choice and the local physical environment. Transp Res D 9(2):151–173
Handy SL, Cao X, Mokhtarian PL (2006) Self-selection in the relationship between the built environment and walking—empirical evidence from Northern California. J Am Plan Assoc 72(1):55–74
Khattak AJ, Rodriquez D (2005) Travel behavior in neotraditional neighborhood developments: a case study in USA. Transp Res A 39(6):481–500
Shay E, Fan Y, Rodriguez DA, Khattak AJ (2006) Drive or walk? Utilitarian trips within a neo-traditional neighborhood. Transp Res Rec 1985:154–161
Boarnet MG, Nesamani KS, Smith CS (2004) Comparing the influence of land use on nonwork trip generation and vehicle distance traveled: An analysis using travel diary data. In: Paper presented at the 83rd annual meeting of the Transportation Research Board, Washington, DC
Hedel R, Vance C (2007) Impact of urban form on automobile travel: Disentangling causation from correlation. In: Paper presented at the 86th annual meeting of the Transportation Research Board, Washington, DC
Boer R, Zheng Y, Overton A, Ridgeway GK, Cohen DA (2007) Neighborhood design and walking trips in ten U.S. metropolitan areas. Am J Prev Med 32(4):298–304
Cao X, Mokhtarian PL, Handy SL (2009) Examining the impacts of residential self selection on travel behaviour: a focus on empirical findings. Transp Rev 29:359–395
Golob TF (2003) Structural equation modeling for travel behavior research. Transp Res B 37:1–25
Simma A (2000) Verkehrsverhalten als eine Funktion soziodemografischer und r€aumlicher Faktoren. Working Paper 55, Institute of Transportation, Traffic, Highway- and Railway-Engineering (IVT), Swiss Federal Institute of Technology (ETHZ), Zurich
Simma A, Axhausen KW (2001a). Within-household allocation of travel: the case of Upper Austria. In: Presented at the annual meeting of the Transportation Research Board, 7–11 Jan, Washington
Axhausen KW, Simma A, Golob TF (2001) Pre-commitment and usage: season tickets, cars and travel. Eur Res Region Sci 11:101–110
Simma A, Axhausen KW (2001) Structures of commitment in mode use: a comparison of Switzerland, Germany and Great Britain. Transp Policy 8:279–288
Liu C, Shen Q (2011) An empirical analysis of the influence of urban form on household travel and energy consumption. Comput Environ Urban Syst 35(2011):347–357
Aditjandra PT, Cao XJ, Mulley C (2011) Understanding neighbourhood design impact on travel behaviour: An application of structural equations model to a British metropolitan data. Transp Res A 46(2012):22–32
Yang L (2011) The relationship between urban form and residential carbon emission, a case study in Pearl River Delta. Peking University, Beijing
Bagley M, Mokhtarian P (2002) The impact of residential neighborhood type on travel behavior: a structural equations modeling approach. Ann Region Sci 36(2):279–297
Cao X, Mokhtarian PL, Handy SL (2007) Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach. Transportation 34(5):535–556
Cervero R, Murakami J (2010) Effects of built environments on vehicle miles traveled: evidence from 370 U.S. metropolitan areas. Environ Plan A 42(2):400–418
Thakuriah P, Liao Y (2005) Analysis of variations in vehicle ownership expenditures. Transp Res Rec 1926:1–9
Zegras C (2010) The built environment and motor vehicle ownership and use: evidence from Santiago de Chile. Urban Stud 47:1793–1817
Schimek P (1996) Household motor vehicle ownership and use: how much does residential density matter? Transp Res Rec 1552:120–125
Buehler R (2011) Determinants of transport mode choice: a comparison of Germany and the USA. J Transp Geogr 19:644–657
Han S, Zhang H, Chen X (2014) Intervention policies for private car ownership in megacities of developing countries. Transp Res Rec 2451:68–76
Koh WT (2003) Control of vehicle ownership and market competition: theory and Singapore’s experience with the vehicle quota system. Transp Res A 37:749–770
Zhang M (2004) The role of land use in travel mode choice: evidence from Boston and Hong Kong. J Am Plan Assoc 70:344–360
Klincevicius M, Morency C, Trépanier M (2014) Assessing impact of carsharing on household car ownership in Montreal, Quebec, Canada. Transp Res Rec 2416:48–55
Chen X, Zhang H (2012) Evaluation of effects of car ownership policies in Chinese megacities. Transp Res Rec 2317:32–39
Dargay J, Gately D (1999) Income’s effect on car and vehicle ownership, worldwide: 1960–2015. Transp Res A 33:101–138
Dargay J, Gately D, Sommer M (2007) Vehicle ownership and income growth, worldwide: 1960–2030. Energy J 28(4):143–170
Dargay JM (2001) The effect of income on car ownership: evidence of asymmetry. Transp Res A 35:807–821
Gómez-Gélvez J, Obando C (2014) Joint disaggregate modeling of car and motorcycle ownership. Transp Res Rec 2451:149–156
Nolan A (2010) A dynamic analysis of household car ownership. Transp Res A 44:446–455
Alsnih R, Hensher DA (2003) The mobility and accessibility expectations of seniors in an aging population. Transp Res A 37:903–916
Newbold KB, Scott DM, Spinney JEL, Kanaroglou P, Páez A (2005) Travel behavior within Canada’s older population: a cohort analysis. J Transp Geogr 13:340–351
Pinjari AR, Pendyala RM, Bhat CR, Waddell PA (2011) Modeling the choice continuum: an integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions. Transportation 38:933–958
Cao X, Xu Z, Fan Y (2009) Exploring the connections among residential location, self-selection, and driving behavior: a case study of Raleigh, NC. In: Paper presented at the 89th annual meeting of the Transportation Research Board
Yamamoto T (2009) Comparative analysis of household car, motorcycle and bicycle ownership between Osaka metropolitan area, Japan and Kuala Lumpur, Malaysia. Transportation 36:351–366
Handy SL, Xing Y, Buehler TJ (2010) Factors associated with bicycle ownership and use: a study of six small US cities. Transportation 37:967–985
Pinjari A, Eluru N, Bhat C, Pendyala R, Spissu E (2008) Joint model of choice of residential neighborhood and bicycle ownership: accounting for self-selection and unobserved heterogeneity. Transp Res Rec 2082:17–26
Weinert J, Ma C, Cherry C (2007) The transition to electric bikes in China: history and key reasons for rapid growth. Transportation 34:301–318
Burge P, Fox J, Kouwenhoven M, Rohr C, Wigan M (2007) Modeling of motorcycle ownership and commuter usage: a UK study. Transp Res Rec 2031:59–68
Anastasopoulos P, Karlaftis M, Haddock J, Mannering F (2012) Household automobile and motorcycle ownership analyzed with random parameters bivariate ordered probit model. Transp Res Rec 2279:12–20
Rose G (2012) E-bikes and urban transportation: emerging issues and unresolved questions. Transportation 39:81–96
Zhang Y, Li Y, Yang X, Liu Q, Li C (2013) Built environment and household electric bike ownership: insights from Zhongshan metropolitan area, China. Transp Res Rec 2387:102–111
Shanghai Municipal Statistics Bureau (2011) Shanghai statistical year book. China Statistics Press, Beijing
Maat K, van Wee B, Stead D (2005) Land use and travel behaviour: expected effects from the perspective of utility theory and activity-based theories. Environ Plan 32:33–46
Prillwitz J, Harms S, Lanzendorf M (2007) Interactions between residential relocations, life course events, and daily commute distances. Transp Res Rec 2021:64–69
Cullinane S (2003) Hong Kong’s low car dependence: lessons and prospects. J Transp Geogr 11:25–35