Technological Advance And Urban Economic Activity: Degree Level Case Studies
Submitted by: Owen Stevens
The effect of ICT advances on the distribution of urban economic activity is a popular topic for undergraduate geographers and economists. This article provides some case studies which can be used to back up arguments surrounding the debate over whether technological advance causes decentralisation or clustering of economic activity. References and suggested reading are provided at the end of the article.
Cheshire (1995 pp.1051) summarises how decentralisation has moved southwards through the EU. From 1975-81 78% of urban cores in Northern European countries experienced decentralisation of population in comparison with just 17% in Southern European countries. This disparity could be due to differences in technological development in cities of Northern and Southern Europe. However, by 1981-91 53% of Northern European urban cores experienced decentralisation compared to 44% in the South. It could be argued that as the South catches up with new technology, so it has caught up in rate of decentralisation.
Ioannides et al. (2007) carry out a study on the effect of an increase in the number of telephone lines per. capita (as a proxy for computer technology) on distribution of city sizes. The assumption is that, as Audirac writes below, decentralisation within cities will lead to decentralisation nationally and a more equal distribution of city sizes, therefore if city sizes are similar decentralization within cities has taken place. Ioannides et al. (2007) show for a set of countries including a significant number of EU countries that, on average, as technology spreads there is a decrease in the variance of the size distribution of cities, in other words decentralisation does occur within the economy in question. In the future it is argued that the internet will have a similar, if not greater, effect.
Turok and Edge (1999) point out that between 1981 and 1996 Britain’s 20 largest cities lost half a million jobs while the rest of the country gained 1.7 million. This is certainly evidence that, on a national scale, decentralisation has taken place and it may be assumed that it is also taking place within cities but is there any evidence specifically relating to cities?
Audirac (2005) writes that firms that locate to take advantage of untraded inter-dependencies are likely to move to secondary hubs as the firms become more mature and the secondary hubs more linked into global technological networks, however, Britton et al. (2004) use the example of Manchester to show how secondary cities may not benefit from IT advances. While IT allows firms in Manchester to have access to the same it also allows their clients to access London firms which may provide a better service, in this sense the impact of IT may be to cause loss of employment in secondary cities.
Similarly, Cheshire (1995 pp.1056) collects data on mean net decentralisation/ recentralisation for countries and groups of countries within the EU taking into account sizes of cities. In each case the largest cities, possibly more likely to be affected by technology developments, experienced greater decentralisation. For example, for the period 1981-91 the largest urban regions in Northern Europe experienced mean net decentralisation of 6.16 in comparison to only 2.5 for medium sized urban areas.
Rather than developments in scientific and technological knowledge being the revolutionary driving force in restructuring urban economies van Winden et al. (2007) argue that so is the use of the knowledge in economic processes and the acquisition of skills to create a knowledge economy. In other words, when considering the effect of advances in computer technology over the last twenty years on urban structure and hence employment location it is important to put the advances into context. This could be factors such as the level of skill of the workforce, government incentives or existing industrial structure. These are factors that enable a city economy to take advantage of IT and will determine to what extent employment location is affected. For example van Winden et al. pick out European cities such as Eindhoven, Munich and Helsinki which have universities which complement and link well to industry in the region as being particularly well placed to take advantage of computer technology developments. However they pick out cities such as Munster, for being too small, and Rotterdam, with a legacy of declining industry, as being less likely to take advantage of technology developments and therefore for employment location to be affected. It is observed that the cities that are well placed to benefit from new technologies are experiencing increased in-migration and business rents, factors which encourage decentralisation.
There are sceptics that argue that decentralisation of employment is not necessarily caused by improvements in ICT. Glaeser and Khan (2003), for example, argue that actually the main driver of decentralization is the car, that edge cities are more relevant to modern economies and are the natural result of a car dominated society.
The location of the financial centres of London and Paris could be confusing in terms of the debate over whether computer technology has caused decentralisation. Stock market trading is highly dependent on computer technology. However, the London financial centre is located in the middle of the city whilst Paris’ is located on the periphery. Financial trading is a brilliant example of an industry which trades entirely virtual goods, what matters in terms of their location choice is access to the best information, this certainly means they need to be in an agglomeration to take advantage of knowledge spillovers but what has made one industry decentralise while the other remains centralised? What appears to have determined their location is not employee’s residential preference or firms’ need for connectivity but government policy. Paris will not build tall offices within the city whereas the city of London has actively encouraged development within the city by ensuring the best possible broadband access for the trading centres among other policies. In this case government policies seem to be the main factor in determining location of employment, not technology.
References and suggested reading
Audirac, I. (2005) Information Technology and Urban Form: Challenges to Smart Growth. International Regional Science Review, 28, 2, pp.119-145
Castells, M. (1996) The Rise of the Network Society, Cambridge, MA: Blackwell
Cheshire, P. (1995) A New Phase of Urban Development in Europe? The Evidence for the 1980s, Urban Studies, Aug. pp.1045-1064
Glaeser, E. and Khan, M. 2003. Sprawl and Urban Form. Working paper 9733. Cambridge MA: National Bureau of Economic Research
Ioannides, Y., Overman, H., Esteban, R. and Schmidheiny, K. (May 30, 2007) The Effect of Information and Communication Technologies on Urban Structure, Preliminary version of a paper prepared for the 46th Panel Meeting of Economic Policy in Lisbon, October 2007
van Winden, W., van den Berg, L. and Pol, P. (2007) European cities in the Knowledge Economy: Towards a Typology. Urban Studies, 44, 3, pp.525-549
About the Author: Owen Stevens is project manager at Skyblu, the
Worcester web design
and digital marketing company.
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