Attractive Vicinity Wenjuan Li, Einar Holm, Urban Lindgren Spatial Modelling Centre (SMC), P.O. Box 839, SE-981 28 Kiruna Sweden Department of Social and Economic Geography, Umeå University, SE-901 87Umeå Sweden
Background of the research question: Regional growth, employment, labour market • Labour market—demand of labour and supply of labour • Supply of labour—population distribution & redistributionplace attractiveness
Literatures related to place attractiveness: • Economic condition and performance — Thompson et al. 1964; Champion and Green 1987; Coombes and Raybould 1988; • Indicators of quality of life — Boyer & Savageau 1981; Rogerson et al. 1989; • Population redistributiontrend— Kontuly 1998; • Relative intrinsic attractivity (RIA) —Fotheringham et al. 2000; • Driving forces of migration — Kontuly and Schön 1994; Westlund 2002; Lundholm et al. 2004; • Place marketing—Niedomysl 2004; • etc.
Among the existed studies, place is often related to administration regions. It is difficult to view administration zones as a place with homogeneous intrinsic site attributes. ************************************* Floating grid anda from within model • the fundamental spatial unit of analysis should be the immediate surrounding of the individual—kilometre square(vicinity). • The surrounding properties of each vicinity can be regarded as intrinsic attributes of the vicinity itself.
Vicinity, local area (vicinity-5km), hinterland (5-50km) (108 000 vicinities) Figure 1.
Data Sources: • Astrid--an individual longitude database that is collected by Statistics Sweden (SCB). • the SwedishRed Map—1: 250 000 Swedish national general maps by Swedish Land Survey (Lantmäteriet).
Two dimensions of attractiveness attributes • four categories • three spatialscales • Each vicinity has its unique attributes Figure 2.
Two indicators of place attractiveness: • Migration model Y = the change of individuals at age 20-64 in vicinity level within two years (2000-2001) • Income model Y = the average vicinity earning income
OLS models (Full models)Y=a+b1x1 +…+bixi • Partial F test – to test if a single X variable (or X variables in a group) gives a significant contribution in the model • η2-- the explanatory power of X variable (s) to the Y variable • Totally 84 partial models were constructed for the Partial F test and η2 calculation
Figure 3. The total explanatory power of the two models and the composition of the explanatory power in the four categories
Conclusions: • The explanatory power of physical, demographic, socio-economic factors to place attractiveness vary considerably, and the effects of the factors differ across different spatial scales. • For the four categories, demographic factors play dominant role in place attractiveness. Demographic factors, labour market factors, service factors, physical factors • For the three spatial scales, vicinity is the most important scale for place attractiveness. Vicinity,hinterland, local area