IDEAS home Printed from https://ideas.repec.org/a/bla/ijethy/v19y2023i4p855-878.html
   My bibliography  Save this article

Location choice with asymmetric data in the Hotelling model

Author

Listed:
  • Shuaicheng Liu

Abstract

This paper analyzes the location choices of firms in the Hotelling model, in which one firm has consumer data and can practice price discrimination, while the other firm without data can only set uniform price. The equilibrium results show medium differentiation. The location choices of firms can alleviate the inhibition of data asymmetry on competition and increase consumer surplus. And we consider the consumers' transportation costs as an exponential function of distance. When this exponent increases, horizontal differentiation increases, but market prices fall, benefiting consumers.

Suggested Citation

  • Shuaicheng Liu, 2023. "Location choice with asymmetric data in the Hotelling model," International Journal of Economic Theory, The International Society for Economic Theory, vol. 19(4), pages 855-878, December.
  • Handle: RePEc:bla:ijethy:v:19:y:2023:i:4:p:855-878
    DOI: 10.1111/ijet.12382
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ijet.12382
    Download Restriction: no

    File URL: https://libkey.io/10.1111/ijet.12382?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Valletti, Tommaso M., 2002. "Location choice and price discrimination in a duopoly," Regional Science and Urban Economics, Elsevier, vol. 32(3), pages 339-358, May.
    2. Alberto Cavallo, 2018. "More Amazon Effects: Online Competition and Pricing Behaviors," NBER Working Papers 25138, National Bureau of Economic Research, Inc.
    3. Hanaki, Nobuyuki & Tanimura, Emily & Vriend, Nicolaas J., 2019. "The Principle of Minimum Differentiation revisited: Return of the median voter," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 145-170.
    4. Rodrigo Montes & Wilfried Sand-Zantman & Tommaso Valletti, 2019. "The Value of Personal Information in Online Markets with Endogenous Privacy," Management Science, INFORMS, vol. 65(3), pages 1342-1362, March.
    5. Hehenkamp, Burkhard & Wambach, Achim, 2010. "Survival at the center--The stability of minimum differentiation," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 853-858, December.
    6. Zhijun Chen & Chongwoo Choe & Noriaki Matsushima, 2020. "Competitive Personalized Pricing," Management Science, INFORMS, vol. 66(9), pages 4003-4023, September.
    7. Choe, Chongwoo & Matsushima, Noriaki & Tremblay, Mark J., 2022. "Behavior-based personalized pricing: When firms can share customer information," International Journal of Industrial Organization, Elsevier, vol. 82(C).
    8. Thisse, Jacques-Francois & Vives, Xavier, 1988. "On the Strategic Choice of Spatial Price Policy," American Economic Review, American Economic Association, vol. 78(1), pages 122-137, March.
    9. Byong‐Duk Rhee & André de Palma & Claes Fornell & Jacques‐François Thisse, 1992. "Restoring The Principle Of Minimum Differentiation In Product Positioning," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 1(3), pages 475-505, September.
    10. d'Aspremont, C & Gabszewicz, Jean Jaskold & Thisse, J-F, 1979. "On Hotelling's "Stability in Competition"," Econometrica, Econometric Society, vol. 47(5), pages 1145-1150, September.
    11. Qihong Liu & Konstantinos Serfes, 2004. "Quality of Information and Oligopolistic Price Discrimination," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 13(4), pages 671-702, December.
    12. Neven, Damien, 1985. "Two Stage (Perfect) Equilibrium in Hotelling's Model," Journal of Industrial Economics, Wiley Blackwell, vol. 33(3), pages 317-325, March.
    13. Jentzsch, Nicola & Sapi, Geza & Suleymanova, Irina, 2013. "Targeted pricing and customer data sharing among rivals," International Journal of Industrial Organization, Elsevier, vol. 31(2), pages 131-144.
    14. Didier Laussel & Joana Resende, 2022. "When Is Product Personalization Profit-Enhancing? A Behavior-Based Discrimination Model," Management Science, INFORMS, vol. 68(12), pages 8872-8888, December.
    15. Rosa Branca Esteves & Francisco Carballo-Cruz, 2021. "Can data openness unlock competition when the incumbent has exclusive data access for personalized pricing?," NIPE Working Papers 16/2021, NIPE - Universidade do Minho.
    16. Greg Shaffer & Z. John Zhang, 1995. "Competitive Coupon Targeting," Marketing Science, INFORMS, vol. 14(4), pages 395-416.
    17. Jakub Kastl & Marco Pagnozzi & Salvatore Piccolo, 2018. "Selling information to competitive firms," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 254-282, March.
    18. Economides, Nicholas, 1984. "The principle of minimum differentiation revisited," European Economic Review, Elsevier, vol. 24(3), pages 345-368, April.
    19. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021. "Selling strategic information in digital competitive markets," RAND Journal of Economics, RAND Corporation, vol. 52(2), pages 283-313, June.
    20. Rhee, Byong-Duk, et al, 1992. "Restoring the Principle of Minimum Differentiation in Product Positioning," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 1(3), pages 475-505, Fall.
    21. Liu, Qihong & Serfes, Konstantinos, 2006. "Customer information sharing among rival firms," European Economic Review, Elsevier, vol. 50(6), pages 1571-1600, August.
    22. Christian Ahlin & Peter D. Ahlin, 2013. "Product Differentiation Under Congestion: Hotelling Was Right," Economic Inquiry, Western Economic Association International, vol. 51(3), pages 1750-1763, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Choe, Chongwoo & Matsushima, Noriaki & Tremblay, Mark J., 2022. "Behavior-based personalized pricing: When firms can share customer information," International Journal of Industrial Organization, Elsevier, vol. 82(C).
    2. Flavio Pino, 2022. "The microeconomics of data – a survey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 635-665, September.
    3. Chongwoo Choe & Noriaki Matsushima & Mark J. Tremblay, 2020. "Behavior-Based Personalized Pricing: When Firms Can Share Customer Information," ISER Discussion Paper 1083, Institute of Social and Economic Research, Osaka University.
    4. Rhodes, Andrew & Zhou, Jidong, 2022. "Personalized Pricing and Competition," MPRA Paper 112988, University Library of Munich, Germany.
    5. Bruno Jullien & Markus Reisinger & Patrick Rey, 2023. "Personalized Pricing and Distribution Strategies," Management Science, INFORMS, vol. 69(3), pages 1687-1702, March.
    6. Irina Baye & Irina Hasnas, 2017. "Consumer flexibility, data quality and location choice," Journal of Economics, Springer, vol. 120(2), pages 135-169, March.
    7. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2022. "Market for Information and Selling Mechanisms," CER-ETH Economics working paper series 22/367, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    8. Clavorà Braulin, Francesco, 2023. "The effects of personal information on competition: Consumer privacy and partial price discrimination," International Journal of Industrial Organization, Elsevier, vol. 87(C).
    9. Ronen Gradwohl & Moshe Tennenholtz, 2022. "Pareto-Improving Data-Sharing," Papers 2205.11295, arXiv.org.
    10. Jentzsch, Nicola & Sapi, Geza & Suleymanova, Irina, 2013. "Targeted pricing and customer data sharing among rivals," International Journal of Industrial Organization, Elsevier, vol. 31(2), pages 131-144.
    11. Irina Baye & Geza Sapi, 2020. "Consumer foresight, customer data, and investment in targeting technology," Scottish Journal of Political Economy, Scottish Economic Society, vol. 67(4), pages 363-386, September.
    12. Chongwoo Choe & Jiajia Cong & Chengsi Wang, 2024. "Softening Competition Through Unilateral Sharing of Customer Data," Management Science, INFORMS, vol. 70(1), pages 526-543, January.
    13. Sapi, Geza & Suleymanova, Irina, 2013. "Consumer flexibility, data quality and targeted pricing," DICE Discussion Papers 117, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    14. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2018. "Selling Strategic Information in Digital Competitive Markets," CESifo Working Paper Series 7078, CESifo.
    15. Aguirre, Inaki & Paz Espinosa, Maria, 2004. "Product differentiation with consumer arbitrage," International Journal of Industrial Organization, Elsevier, vol. 22(2), pages 219-239, February.
    16. Paul Belleflamme & Wing Man Wynne Lam, & Wouter Vergote, 2020. "Competitive Imperfect Price Discrimination and Market Power," Marketing Science, INFORMS, vol. 39(5), pages 996-1015, September.
    17. Noriaki Matsushima & Tomomichi Mizuno & Cong Pan, 2023. "Personalized pricing with heterogeneous mismatch costs," Southern Economic Journal, John Wiley & Sons, vol. 90(2), pages 369-388, October.
    18. Axel Gautier & Ashwin Ittoo & Pieter Cleynenbreugel, 2020. "AI algorithms, price discrimination and collusion: a technological, economic and legal perspective," European Journal of Law and Economics, Springer, vol. 50(3), pages 405-435, December.
    19. Baye, Irina & Sapi, Geza, 2014. "Targeted pricing, consumer myopia and investment in customer-tracking technology," DICE Discussion Papers 131, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    20. Shy, Oz & Stenbacka, Rune, 2013. "Investment in customer recognition and information exchange," Information Economics and Policy, Elsevier, vol. 25(2), pages 92-106.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:ijethy:v:19:y:2023:i:4:p:855-878. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1742-7355 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.