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GIS enabled service site selection: Environmental analysis and beyond

Author

Listed:
  • Junjie Wu

    (Beihang University)

  • Jian Chen

    (Tsinghua University)

  • Yili Ren

    (Beihang University)

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.

Suggested Citation

  • Junjie Wu & Jian Chen & Yili Ren, 2011. "GIS enabled service site selection: Environmental analysis and beyond," Information Systems Frontiers, Springer, vol. 13(3), pages 337-348, July.
    • Handle: RePEc:spr:infosf:v:13:y:2011:i:3:d:10.1007_s10796-010-9284-7
    DOI: 10.1007/s10796-010-9284-7
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    References listed on IDEAS

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    1. Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
    2. Aboolian, Robert & Berman, Oded & Krass, Dmitry, 2007. "Competitive facility location and design problem," European Journal of Operational Research, Elsevier, vol. 182(1), pages 40-62, October.
    3. Oded Berman & Dmitry Krass, 2002. "Locating Multiple Competitive Facilities: Spatial Interaction Models with Variable Expenditures," Annals of Operations Research, Springer, vol. 111(1), pages 197-225, March.
    4. ReVelle, C.S. & Eiselt, H.A. & Daskin, M.S., 2008. "A bibliography for some fundamental problem categories in discrete location science," European Journal of Operational Research, Elsevier, vol. 184(3), pages 817-848, February.
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    Cited by:

    1. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    2. Derya Celik Turkoglu & Mujde Erol Genevois, 2020. "A comparative survey of service facility location problems," Annals of Operations Research, Springer, vol. 292(1), pages 399-468, September.

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