EFFECT OF MOTOR VEHICLE CONGESTION ON THE ECONOMIC PERFORMANCE OF KENYA: A CASE OF NAIROBI CITY COUNTY

RAJESH GEOFREY MOSOTI

Abstract


Transport is a key variable in the growth of the Kenyan economy. With such a rapid increase in urban population, there has been an increase in demand for mobility, and with it, an increase in motorized vehicle ownership. Much of the developing world is experiencing rapid economic growth. Motor vehicle fleet is increasing at a rapid pace in many cities around the world creating an infrastructure backlog and imposing constraint on economic development. The general objective of this study was to assess the effect of the motor vehicle congestion on the economy of Kenya. A case study was  made of Nairobi City County. The objectives of the study was to establish the effect of transport infrastructure and Government Policy on the economy as influenced by traffic congestion in Nairobi County. The study was limited to the residents of Nairobi County. The study targeted city county planners, city county traffic office and city economic and finance office. The study was targeting the years between 2011 and 2013.The Study used the descriptive research design.The study population were respondents from city county planner’s office, city county traffic office and city economic and finance office which had 108 respondents and sample size of 54 which is 50% of the total target population. Stratified random sampling was used as a sampling design then simple random sampling to ensure that all the subgroups were included in the study. The data collection instrumentused was the questionnaire. Then data wasanalysed by use of the tables, and pie charts, that are qualitative in nature.The study concluded that motor vehicle congestion has a direct effect on the economy of Kenya. The research concluded that the lost man-hours due to people sitting in traffic was causing a slowdown in the economy’s growth and that investors are relocating because of the high cost of labour in Kenya. The study re affirmed the importance on public transport to the Kenyan economy and that it is the nerve center that holds it together, however it is poorly managed and governed and thus the stakeholders need to come up with better strategies to make it viable.

Key Words: Motor Vehicle, Congestion, Economic Performance


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References


Brockmeyer, E. (1948).The life and works of A.K. Erlang.København: Akademiet for de TekniskeVidenskaber.

Calhoun, C. (2002). Dictionary of the social sciences. New York: Oxford University Press.

Cosgrove, D., & Gargett, D. (2007). Estimating urban traffic and congestion cost trends for Australian cities. Canberra, ACT: Bureau of Transport and Regional Economics.

Dachis, B. (2013). Cars, congestion and costs: A new approach to evaluating government infrastructure investment. Toronto, ON: C.D. Howe Institute.

Dimitriou, H. (2011). Urban transport in the developing world: A handbook of policy and practice. Cheltenham, UK: Edward Elgar.

Duranton G., and TurnerM. 2009. The fundamental law of road congestion: evidence form U.S. cities. NBER Working paper 15376

Fundamental law of road congestion. (2011). The American Economic Review.

Hardin, G. (1968). The tragedy of the commons

Henley, Jon (2005-03-15). "Paris drive to cut traffic in centre by 75%". The Guardian(London: Guardian Media Group) (closing off areas to other users except public transport)

Kant Rao, William L. Grenoble IV, (1991) "Modelling the Effects of Traffic Congestion on JIT", International Journal of Physical Distribution & Logistics Management, Vol. 21 Iss: 2, pp.3 – 9

Kenya Gazette Notice No. 720, Transport and Urban De-Congestion Committee . Retrieved September 12, 2014:

Kerner, B. (2009). Introduction to modern traffic flow theory and control the long road to three-phase traffic theory. Heidelberg: Springer.

Kothari C. (2009). Research Methodology: An Introduction. New Age International Publishers New Delhi.

Litman T (2014) Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Strategies: Victoria Transport Policy Institute

Lomax, T. (2011).Real-timing the 2010 Urban Mobility Report. College Station, TX: University Transportation Center for Mobility, Texas Transportation Institute, Texas A&M University System.

Macmillan, H., & Schumacher, S. (2006). Research in education: evidence-based inquiry. 6th Edition. Boston: Pearson Education Inc.

Managing urban traffic congestion. (2007). Paris: OECD :.

Mugenda, A. & O. Mugenda (1999). Research Methods: Qualitative and Quantitative Approaches. Nairobi: Acts Press.

Mugenda, M.O. (2003) Research methods, qualitative and Quantitative Aprroaches. Africa Center for technology Nairobi-Kenya.

Murashige, Y. (1995). Drivers' evaluation of advanced traveller information systems for inter-city expressways in Japan

Neuman, W.L (2000). Social Research Methods: Qualitative and Quantitative Approaches. Boston: Allyn and Bacon Publishers.

News Archive: Top News from March 25, 2014. (n.d.).Retrieved September 16, 2014.

Parkinson, T., & Phillips, M. (2006). Kenya (6th ed.). Footscray, Vic.: Lonely Planet.

Parry, I., &Timilsina, G. (2009). Pricing externalities from passenger transportation in Mexico city. Washington, D.C.: World Bank

Rao, A., &Rao, K. (2012).MEASURING URBAN TRAFFIC CONGESTION.International Journal for Traffic and Transport Engineering, 2(4), 286 – 305-286 – 305.

Roger L. Mackett (2012), Reducing Car Use in Urban Areas, in Roger L. Mackett, Anthony D. May, Masanobu Kii, Haixiao Pan (ed.) Sustainable Transport for Chinese Cities (Transport and Sustainability, Volume 3)Emerald Group Publishing Limited, pp.211 – 230

Sundarapandian, V. (2009). Probability, statistics and queuing theory (Eastern economy ed.). New Delhi: PHI Learning.

Traffic clogs emerging economies 2011 commuter pain index finds technolgy might help alleviate the problem. (2011, september 27). States News Service. Retrieved September 12, 2014, from http://www.highbeam.com/doc/1G1-268195989.html?

WardsAuto | Automotive Industry News, Data and Statistics.(n.d.).Retrieved September 13, 2014.

Winston, C., & Langer, A. (2006). The effect of government highway spending on road users' congestion costs. Washington, D.C.: AEI-Brookings Joint Center for Regulatory Studies.

www.inrix.com/economic-environment-cost-congestion/, accessed on November 5th 2014

www.Kenya national bureau of statistics.Org, accessed on November 5th 2014

www.vision2030.go.ke, accessed on November 5th 2014




DOI: http://dx.doi.org/10.61426/sjbcm.v2i1.96

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