Abstract
In the Gauteng City Region, a substantial number of workers reside far from their place of work, translating into long travel distances and high travel costs and time costs. This study examines the relationship between job-employed ratio, i.e. the percentage of residents that work in the same location in which they live, and average travel times. It also compares the average travel time between internal capture workers, who work and reside in the same area, with employment leakage workers, who work in areas other than those they reside in, and analyses other factors that influence average travel times. The ANOVA results reveal that job-rich and balanced areas are associated with higher average travel times for workers in housing-rich areas. Internal capture workers had the lower average travel time compared employment leakage workers. The regression results indicate that male gender, age and Black African ethnicity are positively associated with higher mean average travel time. Income, education level, informality and private transportation modes are negatively correlated with mean average travel time. This finding implies that land-use planning and public transport policies should be integrated to reduce travel time to work in the Gauteng City Region.
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References
Aguiléra, A., & Grébert, J. (2014). Passenger transport mode share in cities: exploration of actual and future trends with a worldwide survey. International Journal of Automotive Technology and Management, 14(3), 203–216.
Ahmad, P., Chirisa, I., Magwaro-Ndiweni, L., Michundu, M., Ndela, W., Nkonge, M., & Sachs, D. (2010). Urbanising Africa: the city centre revisited. Institute for Housing and Urban Development Studies, Netherland, 26, 1.
Alqhatani, M., Bajwa, S., & Setunge, S. (2013). Modeling the influence of socioeconomic and land-use factors on mode choice. International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering, 7(2), 91–103.
Atkinson, D., & Marais, L. (2006). Urbanisation and the future urban agenda in South Africa. In U. Pillay, R. Tomlinson, & J. Du Toit (Eds.), Democracy and delivery: urban policy in South Africa (pp. 22–49). Cape Town: HSRC Press.
Cao, X., Mokhtarian, L., & Handy, L. (2009). Examining the impacts of residential self-selection on travel behaviour: a focus on empirical findings. Transport Reviews, 29(3), 359–395.
Cervero, R. (1989). Jobs-housing balancing and regional mobility. Journal of the American Planning Association, 55(2), 136–150.
Cervero, R. (1996). Jobs-housing balance revisited: trends and impacts in the San Francisco Bay Area. Journal of the American Planning Association, 62(4), 492–511.
Cervero, R. (2013). Linking urban transport and land use in developing countries. Journal of Transport and Land Use, 6(1), 7–24.
Cervero, R., & Wu, K. L. (1998). Sub-centring and commuting: evidence from the San Francisco Bay area, 1980-90. Urban Studies, 35(7), 1059–1076.
Chakwizira, J., Bikam, P., & Adeboyejo, A. (2014). The impact of rapid urbanisation on public transport systems in the Gauteng Region of South Africa. International Journal of Civil, Environmental, Structural, Construction and Architectural Engineering, 8(5), 564–575.
Corpuz, G. 2007. Public transport or private vehicle: factors that impact on mode choice. 30th Australasian Transport Research Forum.
Department of Transport. (1996). White paper on national transport policy. Pretoria: Department of Transport.
Dubin, R. (1991). Commuting patterns and firm decentralization. Land Economics, 67(1), 15–29.
Ewing, R., & Cervero, R. (2010). Travel and the built environment: a meta-analysis. Journal of the American Planning Association, 76(3), 265–294.
Feng, J., Dijst, M., Prillwitz, J., & Wissink, B. (2013). Travel time and distance in international perspective: a comparison between Nanjing (China) and the Randstad (The Netherlands). Urban Studies, 50(14), 2993–3010.
Giuliano, G., & Small, K. (1993). Is the journey to work explained by urban structure? Urban Studies, 30(9), 1485–1500.
Gordon, P., Richardson, H., & Jun, M. (1991). The commuting paradox: evidence from the top twenty. Journal of the American Planning Association, 57(4), 416–420.
Handy, S., Cao, X., & Mokhtarian, P. (2005). Correlation or causality between the built environment and travel behavior? Evidence from Northern California. Transportation Research Part D: Transport and Environment, 10(6), 427–444.
Harrison, P., Todes, A., & Watson, V. (2007). Planning and transformation: learning from the post-apartheid experience. Liverpool: Liverpool University press.
Hitge, G., & Vanderschuren, M. (2015). Comparison of travel time between private car and public transport in Cape Town. Journal of the South African Institution of Civil Engineering, 57(3), 35–43.
Izraeli, O., & McCarthy, R. (1985). Variations in travel distance, travel time and model choice among SMSAs. Journal of Transport Economics and Policy, 1, 139–160.
Jennings, G. (2015). Public transport interventions and transport justice in South Africa: a literature and policy review. In Proceeding of the 34th Annual Southern African Transport Conference 6-8 July 2015. Pretoria: CSIR International Convention Centre.
Kerr, A. 2015. Taxi(i)ing the poor? Commuting costs in South Africa. [online]. 25 September. Available from http://www.redi3x3.org/papers [Accessed on 05 June 2015].
Lee, W. 2005. A spatial analysis of disaggregated commuting data: implications for excess commuting, jobs-housing balance, and accessibility. Doctoral dissertation report. University of the Ohio State, Department of Geography.
Leonard, J. (1987). The interaction of residential segregation and employment discrimination. Journal of Urban Economics, 21(3), 323–346.
Levinson, D. (1998). Accessibility and the journey to work. Journal of Transport Geography, 6(1), 11–21.
Manaugh, K., Miranda-Moreno, L., & El-Geneidy, M. (2010). The effect of neighbourhood characteristics, accessibility, home–work location, and demographics on commuting distances. Transportation, 37(4), 627–646.
Masoumi, E. (2013). Residential self-selection and its effects on urban commute travels in Iranian cities compared to US, UK, and Germany. International Journal of Social Sciences, 7(5), 877–881.
Melia, S., Parkhurst, G., & Barton, H. (2011). The paradox of intensification. Transport Policy, 18(1), 46–52.
Pan, H. & Ge, Y. 2014. Jobs-housing balance and job accessibility in Beijing. In Transportation Research Board 93rd annual meeting (No. 14–5416).
Gauteng Province Roads and Transport [GPRT]. 2016. Gauteng Province household survey 2014. Gauteng: Gauteng Province.
Rospabe, S. & Selod, H. 2006. Does city structure cause unemployment? The case of Cape Town. Poverty and policy in post-apartheid South Africa: 262–287.
Sinclair-Smith, K., & Turok, I. (2012). The changing spatial economy of cities: an exploratory analysis of Cape Town. Development Southern Africa, 29(3), 391–417.
Statistics South Africa. (2015). Measuring household expenditure on public transport: In-depth analysis of the National Household Travel Survey 2013-technical report. Report 03-20-11. Pretoria: Statistics South Africa.
Stoker, P., & Ewing, R. (2014). Job–worker balance and income match in the United States. Housing Policy Debate, 24(2), 485–497.
Vandersmissen, M., Villeneuve, P., & Thériault, M. (2003). Analyzing changes in urban form and commuting time. The Professional Geographer, 55(4), 446–463.
Wang, E., Song, J., & Xu, T. (2011). From “spatial bond” to “spatial mismatch”: an assessment of changing jobs–housing relationship in Beijing. Habitat International, 35(2), 398–409.
Zhao, P., Lü, B., & De Roo, G. (2011). Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era. Journal of Transport Geography, 19(1), 59–69.
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Geyer, H.S., Molayi, R.S.A. Job-Employed Resident Imbalance and Travel Time in Gauteng: Exploring the Determinants of Longer Travel Time. Urban Forum 29, 33–50 (2018). https://doi.org/10.1007/s12132-017-9313-4
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DOI: https://doi.org/10.1007/s12132-017-9313-4