j.1435-5957.2010.00343.x the Impact of Urban Growth on Commuting Patterns in a Restructuring City_Evidence From Beijing

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  The impact of urban growth on commuting patterns in arestructuring city: Evidence from Beijing * Pengjun Zhao 1 , Bin Lu 1 , Gert de Roo 2 1 Department of Urban and Regional Planning, College of Urban and Environmental Sciences, Peking University,5 Yiheyuan Road, Beijing, 100871, China (e-mail:, 2 Department of Urban and Environmental Planning, University of Groningen, Landleven 1, NL-9742 ADGroningen, The Netherlands (e-mail: 21 June 2009 / Accepted: 24 November 2010 Abstract.  Our existing knowledge of the links between urban growth and commuting patternsare dominated by cases from developed countries. This paper examines the impact of urbangrowth on workers’ commutes using the case of Beijing, which is undergoing rapid economicand spatial restructuring. The results of an analysis of household survey data show that clusteredand compact urban development in planned sub-centres is likely to reduce suburban workers’need for a long-distance commute to the city centre when the workers’ socio-economic char-acteristics, the level of transport accessibility and household preferences for residential locationare taken into account. Workers employed in the manufacturing sector tend to have shortercommutes and travel within the planned suburban sub-centres. This reveals that the decentrali-zation of employment in the manufacturing sector provides more opportunities to enhance thespatial matches between household residential and job location choices. Household preferencesfor residential location have an effect on commuting patterns, and high-income workers arelikely to accept longer commutes in order to fulfil their residential preferences. Dramatic urbanrestructuring, in conjunction with changes in lifestyle, is creating new commuting patterns in therapidly growing cities of China. JEL classification:  R14, R23 Key words:  Urban growth, commuting, employment decentralization, Beijing 1 Introduction In recent decades, one of the main arguments in relation to the reduction of energy consumptionand greenhouse gas emissions has focused on passenger transport, as this accounts for over 20 * The travel data used in this study came from a housing survey undertaken in 2006 by Professor Li Si-Ming fromHong Kong Baptist University and Professor John R. Logan from Brown University. The authors would like to thank them for their data support.doi:10.1111/j.1435-5957.2010.00343.x © 2011 the author(s). Papers in Regional Science © 2011 RSAI. Published by Blackwell Publishing, 9600 Garsington Road,Oxford OX4 2DQ, UK and 350 Main Street, Malden MA 02148, USA. Papers in Regional Science , Volume 90 Number 4 November 2011.  percent of the world’s primary energy use and 13 percent of energy-related CO 2  emissions (IEA2006). Of the many factors influencing travel patterns at a city level, urban spatial change isparticularly important. Spatial changes affect travel features through patterns of urban growth(see Crane 2000 for a literature review). In particular, employment decentralization and clus-tered development in the suburbs are often believed to be associated with shorter commutes thanin areas of sprawling development and even monocentric spatial structures (Gordon et al. 1989b;Levinson and Kumar 1994). One major reason for this, according to economics research, is thatpolycentric spatial structures provide more opportunities to enhance spatial matches between theresidential and job location choices of households living in the suburbs (White 1988; Yinger1992).Urban spatial change has been accompanied by changes in individuals’ housing and employ-ment locations, which in turn causes changes in commuting patterns, such as commutingdistance and features of the commuting flow (Anas et al. 1998). Since the SecondWorldWar, thepattern of urban growth in Western countries has been dominated by low density developmentand employment decentralization, which was combined with a rapid increase in car ownershipand use (Glaeser and Kahn 2001; Knight and Stanback 1976). In particular, after the 1980s, ‘newsuburbanization’occurred in NorthAmerican and European countries (Garreau 1991; Stanback 1991; Panebiaco and Kiehl 2003), with several common trends: the decentralization of employ-ment in the service, finance, insurance and real estate sectors, after the decentralization of employment in the manufacturing sector, occurs dramatically in the suburbs and forms newsub-centres; a daily commute at city level is dominated by suburb-to-suburb flow and reversecommuting (centre-to-suburb commuting) grows steadily; most high-income workers choose tolive and work in the suburbs, although some decide to reside in the city centre in order to haveaccess to amenities even if their jobs are located in the suburbs; spatial mismatch is often foundin the city centre with greater urban sprawl believed to be associated with higher spatialmismatch.Due to these new trends in suburbanization and their influence on commuting, manyinitiatives in relation to the management of patterns of urban growth have been introduced inWestern countries in order to mitigate the environmental effects of commuting, such as con-tainment strategies, smart growth, compact city, new urbanism, transit-oriented development(TOD). A recent report, ‘Growing Cooler’, based on a summary of a large body of literature,concludes that “it is realistic to assume a 30 percent cut in VMT [through] compact develop-ment” (Ewing et al. 2008, p. 9). However, current policies designed to manage urban growth onthe fringes of the city are often criticized for their limitations in terms of altering the course of commuting patterns (Gordon and Richardson 1997; Giuliano 1999; Rodriguez et al. 2006). Onemajor reason for this is that there is still considerable uncertainty about the links betweenpatterns of urban growth and the travel behaviour of individuals.In addition, our existing knowledge about the links between urban growth and commutingis largely based on cases from NorthAmerican and European countries. Cases from developingcountries are scarce. Research into the dynamics of urban growth in rapidly growing cities indeveloping countries would enhance and expand our knowledge of the relationship betweenurban growth and commuting. In the case of China, since the 1980s its large cities have beenundergoing rapid urban spatial change, which has been so dramatic that it is often called‘restructuring’(Ma 2004; Ma and Wu 2005; Lu and McCarthy 2008; Zacharias and Tang 2010).Several main new trends in urban development can be described as follows: rapid expansion of the urban space as a consequence of housing and industrial development on the fringes of thecity; suburbanization caused by the outward movement of the urban population and industriesfrom the city centre; and polynucleation in large cities, resulting from the growth of sub-centresand industrial zones in the suburbs. Consequently, new relationships between jobs and housingand new commuting patterns have developed in the suburbs of China’s large cities during the 736 P. Zhao et al. Papers in Regional Science , Volume 90 Number 4 November 2011.  urban restructuring process (Gaubatz 1999a; Zhao et al. 2009c; Zhao et al. 2011). In particular,a great deal of the new urban development on the fringes of the city has diverged quitedramatically from the traditional compact urban form. Urban sprawl has already been identifiedas one of the major traits of suburban development (Deng and Huang 2004; Wong and Tang2005). Sprawling development, combined with an increase in car ownership, tends to worsen theenvironmental effects of urban growth by promoting the need for long-distance commuting(Shen 1997; Wu 2002). These new trends in urban spatial change and their effects on travelpatterns in China’s cities are likely to develop in a similar way toWestern countries in the 1950s.However, in the restructuring of China’s cities, the relationship between urban growth andcommuting is more complex than in other countries (Zhao and Lu 2010). First, urban growth inChina has been fundamentally driven by the transformation from a centrally planned system toa market system. The country has witnessed dramatic political decentralization, globalizationand marketization since the 1980s (Wei 2001). Market-oriented real estate and commercialdevelopment, following government-led industrial development, is shaping the suburbanizationof China (Zhao et al. 2009a). Compared with employment decentralization inWestern countries,China’s current suburbanization is characterized by residential decentralization due to old cityregeneration and the development of housing in the suburbs (Zhou 1997). Employment decen-tralization develops slowly and is dominated by the manufacturing and construction sectors,while the finance, insurance and real estate sectors are still concentrated and growing rapidly inthe central areas of cities. Second, compared to Western cities, most high-income households inChina are likely to choose to live in central areas of the city, where jobs for those who are highlyqualified and high-price housing are located (Zheng et al. 2005). Traditional cultural factors arean important reason for this, as well as the high level of accessibility to urban services andamenities in central areas. For example, living in the city centre, where the ‘privilegentsia’traditionally lived, usually indicates higher social status in China (Gaubatz 1999b). While somehigh-income households move to the suburbs because of changes in their lifestyle (Wang and Li2004), most low-income workers reside in the suburbs because they cannot afford the high-pricehousing in the central urban areas, even if their job is located in the city centre. That means thatemployment decentralization and urban sprawl would bring benefits to low-income households.Third, in terms of policy-making, the supply of various types of housing and residential land usein China is still more centrally planned and tightly regulated in the present reform era than inWestern countries (Zhao et al. 2009b).As a result, the role of residential preference in the actualchoice of residential location may be weaker than in Western countries where there is a higherdegree of market-oriented housing.Therefore, an investigation into urban growth in China is of great importance to freshen andenhance our understanding of the impact it may have on an individual’s travel behaviour.However, relatively few studies have examined China’s situation. By looking at the case of Beijing, this paper examines the relationships between patterns of urban growth and commutingin China’s cities. Two research questions will be answered. One is how patterns of urban growthaffect a worker commuting on the fringes of the city of Beijing. The other is whether existingregional policies designed to form a polycentric spatial structure in order to reduce crowding inthe city centre also have implications for the reduction of long-distance suburb-to-centre com-muting. Two aspects of commuting patterns are studied: commuting destination choice andcommuting trip length. This paper also takes into account the individual worker’s socio-economic features, household characteristics and household preference for residential location.The remainder of this paper is organized as follows: Section 2 introduces the theory andreviews the existing literature concerning the relationship between urban growth and commut-ing; Section 3 presents an analysis of the city context of Beijing; Section 4 presents the data andmethodology used in this study; Section 5 explores the impact of patterns of urban growth onindividual workers’ commuting features and Section 6 presents the conclusions reached. 737The impact of urban growth on commuting patterns Papers in Regional Science , Volume 90 Number 4 November 2011.  2 The relationship between urban growth and commuting patterns 2.1 Theory Search theory has been widely used to explain individual travel behaviour (see reviews byMcFadden 2001; Waddell 2001). According to search theory, a worker’s choice of residentialand job location determines their commuting distance, and a worker will make a location choicewhich has a maximum degree of utility. A worker’s commute length is therefore understood asa function of the utility of their home and job location choice. In a monocentric city model, allemployment is located in the central business district (CBD), and workers are often only facedwith a choice in terms of housing location (Alonso 1964; Muth 1969). However, in a polycentriccity model, employment is located throughout the city, for example, in the CBD, at sub-centresand in rural areas; workers are facing not only a set of alternative housing locations but alsoemployment locations (White 1988). A worker’s commuting distance is determined by thecombination of housing and workplace location choice (Anas et al. 1998; Van Ommeren et al.2000). The utility of a worker’s choice of location is constrained by various factors such as theworker’s personal characteristics, household characteristics, housing and job features as well asaspects of the zone in which the worker resides and works (Richardson 1977). A worker’scommuting distance in a polycentric city model can be expressed as:  D f U P F H L W S  ij i i i i j j =  ( ) [ ] , , , , , , ε   (1)where,  D ij  is the worker’s commuting distance between residential location  i  and workplace  j ,  P i is a vector representing the worker’s personal characteristics, such as age and gender,  F  i  is avector in which the worker’s family characteristics, such as income and the number of employedfamily members, are represented,  H  i  is a vector that shows the features of the housing, such assize and price,  L i  is a vector that represents the characteristics of the location in which the workerresides, such as neighbourhood land use and transport services,  W   j  is a vector that represents thefeatures of the location in which the worker works, such as proximity to the CBD or sub-centres,land use pattern and transport accessibility,  S   j  is a vector that indicates the characteristics of the job, such as employment sector, and  e   is random utility. A worker’s commuting distance is alsosubject to household budget constraints and his/her time constraints.However, traditional explanations from the above model usually ignore the influence of household attitudes to location on the choice of residential location. Location attitudes, meaninghousehold preferences for certain attributes of housing, location and neighbourhood, may affectindividuals’ residential location and thus commuting patterns (Handy et al. 2005; Scheiner andHolz-Rau 2007). When the variable  N  i , representing a household’s preferences for residentiallocation is added, Equation (1) can be rewritten as:  D g U P F H L N W S  ij i i i i i j j =  ( ) [ ] , , , , , , , ε   (2)Ahypothesis can be derived from the theory above: for workers residing on the fringes of thecity, a polycentric model would entail a shorter commute than a monocentric model. The mainreason for this is that the polycentric model permits workers to choose between several joblocations within a given metropolitan area, allowing greater average proximity between homeand work (White 1988; Yinger 1992).Aworker’s commute length can be indicated by the degree of spatial separation between thelocation of the commuting destination (workplace) and the location of its origin (housinglocation). Therefore, a discrete variable can be used to reflect a worker’s choice of commutelength and direction if the worker’s housing location is fixed. 738 P. Zhao et al. Papers in Regional Science , Volume 90 Number 4 November 2011.
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