GIS enabled service site selection: Environmental analysis and beyond

JunJie Wu, Jian Chen () and Yili Ren ()
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Jian Chen: Tsinghua University
Yili Ren: Beihang University

Information Systems Frontiers, 2011, vol. 13, issue 3, No 4, 337-348

Abstract: Abstract Given its importance, the problem of selecting the right site for a service entity has attracted great attention in the literature. However, due to its complexity, the quantification of the interrelationships between the service site and its nearby business types is still a challenging task. To this end, in this paper, we propose a novel joint learning scheme for service site selection. This scheme employs both the Probabilistic Latent Semantic Analysis (PLSA) on the Geographical Information System (GIS) data and the partitional clustering on the service performance data. A case study for bank branch selection is provided to demonstrate the usefulness of our method. Finally, based on the joint learning scheme, we present a conceptual framework for the complete procedure of service site selection with a particular emphasis on the GIS enabled network analysis.

Keywords: Site selection; Geographical Information System (GIS); Probabilistic Latent Semantic Analysis (PLSA); Joint learning (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10796-010-9284-7

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