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Surviving in a competitive spatial market: The threshold capture model

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Abstract

Most facility location decision models ignore the fact that for a facility to survive it needs a minimum demand level to cover costs. In this paper we present a decision model for a firm that wishes to enter a spatial market where there are several competitors already located. This market is such that for each outlet there is a demand threshold level that has to be achieved in order to survive. The firm wishes to know where to locate its outlets so as to maximize its market share taking into account the threshold level. It may happen that due to this new entrance, some competitors will not be able to meet the threshold and therefore will disappear. A formulation is presented together with a heuristic solution method and computational experience.

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  • Daniel Serra & Charles Revelle & Ken Rosing, 1999. "Surviving in a competitive spatial market: The threshold capture model," Economics Working Papers 359, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:359
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    6. ReVelle, Charles, 1993. "Facility siting and integer-friendly programming," European Journal of Operational Research, Elsevier, vol. 65(2), pages 147-158, March.
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    Cited by:

    1. Diego Ruiz-Hernández & Javier Elizalde & David Delgado-Gómez, 2017. "Cournot–Stackelberg games in competitive delocation," Annals of Operations Research, Springer, vol. 256(1), pages 149-170, September.
    2. Rosa Colomé & Helena Lourenço & Daniel Serra, 2003. "A New Chance-Constrained Maximum Capture Location Problem," Annals of Operations Research, Springer, vol. 122(1), pages 121-139, September.
    3. Martin Carree & Marcus Dejardin, 2007. "‘Entry Thresholds and Actual Entry and Exit in Local Markets’," Small Business Economics, Springer, vol. 29(1), pages 203-212, June.
    4. Marcus Dejardin & Martin Carree, 2011. "Firm Entry and Exit in Local Markets: Market Pull and Unemployment Push," Working Papers 1114, University of Namur, Department of Economics.
    5. Jiang, Yuanchun & Liu, Yezheng & Shang, Jennifer & Yildirim, Pinar & Zhang, Qingfu, 2018. "Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives," European Journal of Operational Research, Elsevier, vol. 267(2), pages 612-627.
    6. Benjamin Spaulding & Robert Cromley, 2007. "Integrating the maximum capture problem into a GIS framework," Journal of Geographical Systems, Springer, vol. 9(3), pages 267-288, September.
    7. Francisco Silva & Daniel Serra, 2007. "Incorporating Waiting Time in Competitive Location Models," Networks and Spatial Economics, Springer, vol. 7(1), pages 63-76, March.
    8. Rafael Blanquero & Emilio Carrizosa & Amaya Nogales-Gómez & Frank Plastria, 2014. "Single-facility huff location problems on networks," Annals of Operations Research, Springer, vol. 222(1), pages 175-195, November.
    9. Robert Cromley & Dean Hanink, 2008. "Population growth and the development of a central place system," Journal of Geographical Systems, Springer, vol. 10(4), pages 383-405, December.
    10. Rosing, K. E. & ReVelle, C. S. & Schilling, D. A., 1999. "A gamma heuristic for the p-median problem," European Journal of Operational Research, Elsevier, vol. 117(3), pages 522-532, September.
    11. Papathanasiou, Jason & Manos, Basil D., 2007. "An approximation algorithm for the location of dairy enterprises under time constraints," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1479-1487, November.
    12. Francisco Silva & Daniel Serra, 2008. "Incorporating waiting time in competitive location models: Formulations and heuristics," Economics Working Papers 1091, Department of Economics and Business, Universitat Pompeu Fabra.
    13. Martin Carree & Marcus Dejardin, 2020. "Firm Entry and Exit in Local Markets: 'Market Pull' or 'Unemployment Push' Effects, or Both?," Post-Print halshs-03220690, HAL.

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    More about this item

    Keywords

    Discrete facility location; threshold; competitive location;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock

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