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Lost demand in a competitive environment

Author

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  • T Drezner

    (California State University-Fullerton)

  • Z Drezner

    (California State University-Fullerton)

Abstract

In most analyses performed on consumer behaviour in a competitive environment, it is assumed that discretionary buying power devoted to a certain product category exists in a trade area. The goal is to estimate how this buying power is distributed among competing retail facilities in the area. In this paper, we assume that in many competitive situations not all the buying power is spent at the competing facilities because there are other facilities that offer substitute products. These substitute products are not as desirable as the product in question, but customers will purchase the less desirable substitutes if they are more conveniently available. We construct a model that considers a decline in demand as a function of the distance to competing facilities. If the competing facilities are close to the customers, a larger portion of the buying power will be spent at these facilities. Two objectives are considered. One is the maximization of the buying power spent at all competing facilities, and the second is the maximization of the buying power captured by one's chain of retail facilities. Solution methods for the location of one facility are proposed and computational experiments with these methods are reported.

Suggested Citation

  • T Drezner & Z Drezner, 2008. "Lost demand in a competitive environment," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 362-371, March.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:3:d:10.1057_palgrave.jors.2602330
    DOI: 10.1057/palgrave.jors.2602330
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    References listed on IDEAS

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    1. David L. Huff, 1966. "A Programmed Solution for Approximating an Optimum Retail Location," Land Economics, University of Wisconsin Press, vol. 42(3), pages 293-303.
    2. Drezner, Tammy & Drezner, Zvi & Salhi, Said, 2002. "Solving the multiple competitive facilities location problem," European Journal of Operational Research, Elsevier, vol. 142(1), pages 138-151, October.
    3. Zvi Drezner & Atsuo Suzuki, 2004. "The Big Triangle Small Triangle Method for the Solution of Nonconvex Facility Location Problems," Operations Research, INFORMS, vol. 52(1), pages 128-135, February.
    4. Tammy Drezner & Zvi Drezner, 2004. "Finding the optimal solution to the Huff based competitive location model," Computational Management Science, Springer, vol. 1(2), pages 193-208, July.
    5. Cooper, Lee G & Nakanishi, Masao, 1983. "Standardizing Variables in Multiplicative Choice Models," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(1), pages 96-108, June.
    6. Plastria, Frank, 1992. "GBSSS: The generalized big square small square method for planar single-facility location," European Journal of Operational Research, Elsevier, vol. 62(2), pages 163-174, October.
    7. Ming-Long Lee & R. Kelley Pace, 2005. "Spatial Distribution of Retail Sales," The Journal of Real Estate Finance and Economics, Springer, vol. 31(1), pages 53-69, August.
    8. DeSarbo, Wayne S, et al, 2002. "A Gravity-Based Multidimensional Scaling Model for Deriving Spatial Structures Underlying Consumer Preference/Choice Judgments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 29(1), pages 91-100, June.
    9. Daniel Serra & Charles Revelle, 1994. "Competitive location in discrete space," Economics Working Papers 96, Department of Economics and Business, Universitat Pompeu Fabra.
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    Cited by:

    1. Drezner, Zvi & Eiselt, H.A., 2024. "Competitive location models: A review," European Journal of Operational Research, Elsevier, vol. 316(1), pages 5-18.
    2. H Küçükaydın & N Aras & İ K Altınel, 2011. "A discrete competitive facility location model with variable attractiveness," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1726-1741, September.
    3. Yingru Li & Ting Du & Jian Peng, 2018. "Understanding Out-of-Home Food Environment, Family Restaurant Choices, and Childhood Obesity with an Agent-Based Huff Model," Sustainability, MDPI, vol. 10(5), pages 1-15, May.
    4. Lin, Yunhui & Wang, Yuan & Lee, Loo Hay & Chew, Ek Peng, 2022. "Profit-maximizing parcel locker location problem under threshold Luce model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    5. Tammy Drezner & Zvi Drezner & Atsuo Suzuki, 2019. "A cover based competitive facility location model with continuous demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(7), pages 565-581, October.
    6. T Drezner & Z Drezner & P Kalczynski, 2011. "A cover-based competitive location model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 100-113, January.
    7. Bashiri, Mahdi & Chehrepak, Elaheh & Gomari, Saeed, 2014. "Gradual Covering Location Problem with Stochastic Radius," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Blecker, Thorsten & Kersten, Wolfgang & Ringle, Christian M. (ed.), Innovative Methods in Logistics and Supply Chain Management: Current Issues and Emerging Practices. Proceedings of the Hamburg International Conferenc, volume 19, pages 165-186, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    8. Küçükaydin, Hande & Aras, Necati & Kuban AltInel, I., 2011. "Competitive facility location problem with attractiveness adjustment of the follower: A bilevel programming model and its solution," European Journal of Operational Research, Elsevier, vol. 208(3), pages 206-220, February.

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