ISPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25. 2001 
295 
First, among areas with mean wage rates below $30,000, 
the higher the mean wage rate in a residential area, the 
farther the area is away from the jobs (i.e., workers trade 
better housing or more space for longer commutes). In areas 
above $30,000, the trend is reversed. That is to say, low- 
wage workers are indeed located in proximity to their 
suitable jobs. Porter (1995) characterizes this as the 
competitive advantage of inner-city low-income residents. 
Public policies should be directed to help them utilize not 
abandon their locational advantage (Shen, 1998, p.358). 
Second, although low-wage workers enjoy better job 
proximity in general, many of the inner-city residents have 
the worst job accessibility. Policies for improving the job 
accessibility of these residents should focus on removing the 
nonspatial barriers that handicap their mobility, such as 
enhancing vehicle ownership and availability, and improving 
the road network, traffic conditions and public transit 
services near their residences. Attempts such as relocating 
them to suburban housing or similar settings may receive 
disappointed results. 
Third, the mean commute time varies little among areas with 
different mean wage rates. But workers of high-wage 
residential areas have far better mobility than those of low- 
wage areas. In other words, high-wage workers are able to 
travel faster probably because of their easy access to 
highways and less congestion in low-density areas. But the 
time saved through faster travel is not translated into non 
travel activities but into greater distance traveled (Bieber et 
al., 1994). Better mobility means larger search ranges and 
more choices of jobs and housing opportunities. The 
literature tends to pay more attention to explanations and 
policy implications of commute time. Mobility (i.e., commute 
range) deserves more attention. 
Finally, jobs are scattered regionwide with several significant 
suburban job concentrations. However, downtown Cleveland 
exerts the dominant effect on forming the concentric patterns 
of job proximity (to a less degree, job accessibility). Since 
workers with various wages respond differently to job 
access, the mean wage distribution is hardly monocentric. 
The urban classic monocentric model assumes the CBD as 
the only employment location, and considers income as the 
driving force shaping the residential concentric patterns. This 
research lends support to the monocentric model in terms of 
job access (the cause), not the spatial pattern of income 
distribution (the consequence). The complicated urban 
mosaic is, at least partially, explainable by the nonlinear 
response of commute ranges to increasing wages. 
For the reasons discussed in the introduction section 
(particularly the focus of classic urban economic models on 
income to explain residential locations), this research 
examines on the job proximity and accessibility for workers 
of various wage groups. Perhaps the major weakness of the 
research is its failure to consider other socioeconomic 
factors such as race, education and family structure. Future 
research will be pursued in those directions. 
RERERENCE9 
Bieber, A., M. H. Massot and J. P. Orfeuil. 1994. Prospects 
for daily urban mobility. Transport Reviews 14, 
321-339. 
Bureau of Transportation Statistics, U.S. Department of 
Transportation. 1996. The 1990 Census for 
Transportation Planning Package (Urban 
Element), BTS-CD-15-08. 
Cervero R., K. L. Wu. 1998. Sub-centring and commuting: 
Evidence from the San Francisco Bay Area, 1980- 
90. Urban Studies 35, 1059-1076. 
Environmental Systems Research Institute, Inc. (ESRI) 
2000. 
http://vvww.esri com 'dataonline/tiaer.'index.html. 
Ellwood, D. T. 1986. The spatial mismatch hypothesis: are 
there teenage jobs missing in the ghetto? In R. B. 
Freeman and H. J. Holer (eds), The Black Youth 
Employment Crisis, Chicago: University of 
Chicago Press, 147-185. 
Freeman, R. B. 1996. Why do so many young American 
men commit crimes and what might we do about 
it? Journal of Economic Perspectives 10, 25-43. 
Gordon P., H. Richardson, M. Jun. 1991. The commuting 
paradox: evidence from the top twenty. Journal of 
American Planning Association 57, 416-420. 
Hansen, W. G. 1959. How accessibility shapes land use. 
Journal of the American Institute of Planners 25, 
73-76. 
Huff, D. L. 1963. A probabilistic analysis of shopping center 
trade areas. Land Economics 39, 81 -90. 
Ihlanfeldt K. R. and D. L. Sjoquist. 1990. Job accessibility 
and racial differences in youth employment rates. 
The American Economic Review 80, 267-276. 
Immergluck, D. 1998. Job proximity and the urban 
employment problem: Do suitable nearby jobs 
improve neighborhood employment rates? Urban 
Studies 35, 7-23. 
Kain, J. 1968. Housing segregation, Negro employment, and 
metropolitan decentralization. Quarterly Journal of 
Economics 82, 175-197. 
Leete, L, N. Bania and C. Coulton. 2000. Updated estimates 
of entry-level job openings in the eight-county 
Cleveland Akron Metropolitan Area. Briefing 
Report No. 9910, Center on Urban Poverty and 
Social Change, Case Western Reserve University. 
Porter, M. 1995. The competitive advantage of the inner city. 
Harvard Business Review (May-June), 
Cambridge, MA: Harvard University Press, 55-71. 
Salomon, I. and P. L. Mokhtarian. 1998. What happens 
when mobility-inclined market segments face 
accessibility-enhancing policies? Transportation 
Research 03,129-140. 
Sawicki, D. S. and M. Moody. 2000. Developing 
transportation alternatives for welfare recipients 
moving to work. Journal of the American Planning 
Association 66, 306-318. 
Sen, A., P. Metaxatos, S. Soot and V. Thakyriah, 1999. 
Welfare reform and spatial matching between 
clients and jobs. Papers in Regional Science 78, 
195-211. 
Shen, Q. 1998. Location characteristics of inner-city 
neighborhoods and employment accessibility of 
low-income workers. Environment and Planning B: 
Planning and Design 25, 345-365. 
Shen, Q. 1999. Transportation, telecommunications, and the 
changing geography of opportunity. Urban 
Geography 20, 334-355. 
Shen, Q. 2000. Spatial and social dimensions of commuting. 
Journal of the American Planning Association 66, 
68-82. 
Taylor, B. and P. Ong. 1995. Spatial mismatch or automobile 
mismatch? An examination of race, residence and 
commuting in U.S. metropolitan areas. Urban 
Studies 32, 1453-1473. 
Wang, F. and W. Minor. 2000. Is job accessibility relevant to 
crime patterns?: A GIS approach. Final Report to 
the National Institute of Justice (NIJ) [available 
upon request from the NIJ]. 
Wang, F. 2000. Modeling commute patterns in Chicago in a 
GIS environment: a job accessibility perspective. 
Professional Geographer 52,120-133. 
Wang, F. 2001. Explaining Intraurban Variations of 
Commuting by Job Accessibility and Workers’ 
Characteristics, Environment and Planning B, in 
press. 
Wilson, W. J. 1996. When Work Disappears. New York: 
Alfred A Knopf.