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Geo-Fencing or Geo-Conquesting? a strategic analysis of Location-Based coupon under different market structures

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Listed:
  • Ding, Long
  • Liu, Peng
  • Hu, Sen

Abstract

Location-based technology enables firms to target consumers with personalized coupons based on their real-time locations, making location-based coupons (LBC) an innovative marketing tool. In this paper, we consider two types of LBC strategies, namely defensive geo-fencing versus offensive geo-conquesting. With a defensive LBC strategy, a company sets a virtual geo-fence by offering coupons with deeper discounts to consumers located closer to the focal firm. Using a spatial model, we examine how two competing companies choose between defensive and offensive LBC strategies, as well as the impact of LBC strategies on company profits, consumer surplus, and social welfare. The results show that the defensive LBC strategy lowers revenue in a monopoly market but increases it under duopoly conditions. In a duopoly market, both firms adopting the defensive LBC strategy is the Nash equilibrium outcome, leading to the highest profits but lowest consumer surplus. The misalignment of interests among firms and consumers requires policymakers to regulate firms’ LBC strategies for the sake of customers.

Suggested Citation

  • Ding, Long & Liu, Peng & Hu, Sen, 2023. "Geo-Fencing or Geo-Conquesting? a strategic analysis of Location-Based coupon under different market structures," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:transe:v:174:y:2023:i:c:s1366554523001047
    DOI: 10.1016/j.tre.2023.103116
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    as
    1. Du, Shaofu & Sheng, Jianchao & Peng, Jing & Zhu, Yangguang, 2022. "Competitive implications of personalized pricing with a dominant retailer," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    2. Luo, Meiling & Li, Gang & Chen, Xudong, 2021. "Competitive location-based mobile coupon targeting strategy," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    3. Daniel Leithold, 2014. "Defractionalisation in Different Electoral Systems," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 12(1), pages 50-54, 04.
    4. Wang, Jing & Cai, Jianping & Yue, Xiaohang & Suresh, Nallan C., 2021. "Pre-positioning and real-time disaster response operations: Optimization with mobile phone location data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    5. Ahmad, Baseer & Ali, Syed Babar, 2012. "Do Individual Investors in Pakistan Prefer Dividends?," MPRA Paper 64205, University Library of Munich, Germany.
    6. Liu, Weihua & Yan, Xiaoyu & Li, Xiang & Wei, Wanying, 2020. "The impacts of market size and data-driven marketing on the sales mode selection in an Internet platform based supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    7. repec:ces:ifodic:v:12:y:2014:i:1:p:19108861 is not listed on IDEAS
    8. Zhijun Chen & Chongwoo Choe & Noriaki Matsushima, 2020. "Competitive Personalized Pricing," Management Science, INFORMS, vol. 66(9), pages 4003-4023, September.
    9. Greg Shaffer & Z. John Zhang, 1995. "Competitive Coupon Targeting," Marketing Science, INFORMS, vol. 14(4), pages 395-416.
    10. Juanjuan Zhang, 2011. "The Perils of Behavior-Based Personalization," Marketing Science, INFORMS, vol. 30(1), pages 170-186, 01-02.
    11. Drew Fudenberg & Jean Tirole, 2000. "Customer Poaching and Brand Switching," RAND Journal of Economics, The RAND Corporation, vol. 31(4), pages 634-657, Winter.
    12. Yuxin Chen & Ganesh Iyer, 2002. "Research Note Consumer Addressability and Customized Pricing," Marketing Science, INFORMS, vol. 21(2), pages 197-208, November.
    13. Chongwoo Choe & Stephen King & Noriaki Matsushima, 2018. "Pricing with Cookies: Behavior-Based Price Discrimination and Spatial Competition," Management Science, INFORMS, vol. 64(12), pages 5669-5687, December.
    14. Souiden, Nizar & Chaouali, Walid & Baccouche, Mona, 2019. "Consumers’ attitude and adoption of location-based coupons: The case of the retail fast food sector," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 116-132.
    15. J. Yannis Bakos, 1997. "Reducing Buyer Search Costs: Implications for Electronic Marketplaces," Management Science, INFORMS, vol. 43(12), pages 1676-1692, December.
    16. Krista J. Li & Sanjay Jain, 2016. "Behavior-Based Pricing: An Analysis of the Impact of Peer-Induced Fairness," Management Science, INFORMS, vol. 62(9), pages 2705-2721, September.
    17. Jiwoong Shin & K. Sudhir, 2010. "A Customer Management Dilemma: When Is It Profitable to Reward One's Own Customers?," Marketing Science, INFORMS, vol. 29(4), pages 671-689, 07-08.
    18. Han, Chirok & Phillips, Peter C. B. & Sul, Donggyu, 2014. "X-Differencing And Dynamic Panel Model Estimation," Econometric Theory, Cambridge University Press, vol. 30(1), pages 201-251, February.
    19. Yuxin Chen & Xinxin Li & Monic Sun, 2017. "Competitive Mobile Geo Targeting," Marketing Science, INFORMS, vol. 36(5), pages 666-682, September.
    20. Daniel Leithold, 2014. "Defractionalisation in Different Electoral Systems," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 12(01), pages 50-54, April.
    21. Ping Han, 2014. "Effects of Fiscal Policy under Different Capital Mobility," Accounting and Finance Research, Sciedu Press, vol. 3(1), pages 111-111, February.
    22. Gao, Hongyan & Liu, Fasheng, 2013. "Estimating freeway traffic measures from mobile phone location data," European Journal of Operational Research, Elsevier, vol. 229(1), pages 252-260.
    23. Yi-Jen (Ian) Ho & Sanjeev Dewan & Yi-Chun (Chad) Ho, 2020. "Distance and Local Competition in Mobile Geofencing," Information Systems Research, INFORMS, vol. 31(4), pages 1421-1442, December.
    24. Krista J. Li, 2018. "Behavior-Based Pricing in Marketing Channels," Marketing Science, INFORMS, vol. 37(2), pages 310-326, March.
    25. Stefan F. Bernritter & Paul E. Ketelaar & Francesca Sotgiu, 2021. "Behaviorally targeted location-based mobile marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 677-702, July.
    26. Anindya Ghose & Beibei Li & Siyuan Liu, 2019. "Mobile Targeting Using Customer Trajectory Patterns," Management Science, INFORMS, vol. 65(11), pages 5027-5049, November.
    27. Siliang Tong & Xueming Luo & Bo Xu, 2020. "Personalized mobile marketing strategies," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 64-78, January.
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