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The Computational Techniques for Optimal Store Placement: A Review

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Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10961))

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Abstract

In today’s world which is subject to an increasing number of stores and level of rivalry on a daily basis, decisions concerning a store’s location are considered highly important. Over the years, researchers and marketers have used a variety of different approaches for solving the optimal store location problem. Like many other research areas, earlier methods for site selection involved the use of statistical data whereas recent methods rely on the rich content which can be extracted from big data via modern data analysis techniques. In this paper, we begin with assessing the historical precedent of the most accepted and applied traditional computational methods for determining a desirable place for a store. We proceed by discussing some of the technological advancements that has led to the advent of more cutting-edge data-driven methods. Finally, we extend a review of some of the most recent, location based social network data-based approaches, to solving the store site selection problem.

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Notes

  1. 1.

    LSBN.

  2. 2.

    Global Positioning System.

  3. 3.

    Radio Frequency Identification.

  4. 4.

    Geospatial Information Systems.

  5. 5.

    VGI.

  6. 6.

    MAUP.

  7. 7.

    www.foursquare.com.

  8. 8.

    Normalized Discounted Cumulative Gain approach.

  9. 9.

    www.Baidu.com.

  10. 10.

    www.Dianping.com.

  11. 11.

    www.Yelp.com.

  12. 12.

    RMSE.

  13. 13.

    MAP.

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Authors and Affiliations

  1. Department of Management, Faculty of Social Science and Economics, Alzahra University, Tehran, Iran

    H. Damavandi & N. Abdolvand

  2. Department of Surveying and Geomatic Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran

    F. Karimipour

Authors
  1. H. Damavandi
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  2. N. Abdolvand
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  3. F. Karimipour
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Corresponding author

Correspondence to N. Abdolvand .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Damavandi, H., Abdolvand, N., Karimipour, F. (2018). The Computational Techniques for Optimal Store Placement: A Review. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10961. Springer, Cham. https://doi.org/10.1007/978-3-319-95165-2_31

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