Methodological issues in applying Location Models to Rural areas

Kenneth Carling, Mengjie Han and Johan Håkansson ()
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Kenneth Carling: Dalarna University, Postal: Department of Human Geography, SE-791 88 , Falun/Borlänge, Sweden
Mengjie Han: Dalarna University, Postal: Department of Human Geography, SE-791 88 , Falun/Borlänge, Sweden
Johan Håkansson: HUI Research, Postal: Regeringsgatan 60, 103 29 Stockholm, Sweden, Dalarna University, Department of Human Geography, SE-791 88 , Falun/Borlänge, Sweden

No 62, HUI Working Papers from HUI Research

Abstract: Location Models are used for planning the location of multiple service centers in order to serve a geographically distributed population. A cornerstone of such models is the measure of distance between the service center and a set of demand points, viz, the location of the population (customers, pupils, patients and so on). Theoretical as well as empirical evidence support the current practice of using the Euclidian distance in metropolitan areas. In this paper, we argue and provide empirical evidence that such a measure is misleading once the Location Models are applied to rural areas with heterogeneous transport networks. This paper stems from the problem of finding an optimal allocation of a pre-specified number of hospitals in a large Swedish region with a low population density. We conclude that the Euclidian and the network distances based on a homogenous network (equal travel costs in the whole network) give approximately the same optimums. However network distances calculated from a heterogeneous network (different travel costs in different parts of the network) give widely different optimums when the number of hospitals increases. In terms of accessibility we find that the recent closure of hospitals and the in-optimal location of the remaining ones has increased the average travel distance by 75% for the population. Finally, aggregation the population misplaces the hospitals by on average 10 km

Keywords: Multiple service centers; Optimal location; accessibility; network distances; Euclidian distances; spatial aggregation; P-median (search for similar items in EconPapers)
JEL-codes: C18 C61 I10 R50 R53 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2012-04-17
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