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Competitive Targeted Marketing

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  • Hang-Hyun Jo
  • Jeoung-Yoo Kim

Abstract

In this paper, we consider two firms diffusing incompatible technologies and their decision of consumer targeting. The technology adoption is made in two steps. First, once the firms sell their products to their respective targeted consumer, the technology is diffused successively by word-of-mouth communication from the initial consumer to other consumers linked along the network. Then, in the second step, each consumer imitates the technology distribution keeps evolving until it reaches the long-run steady state. We demonstrate that the early entrant chooses the minmax location when firms are myopic in the sense that they do not take the imitation possibility into account. If firms consider the possibility of imitation, the best target will tend towards a hub, although the minmax principle in general keeps valid in the sense that it should be the minmax location after considering imitation.

Suggested Citation

  • Hang-Hyun Jo & Jeoung-Yoo Kim, 2012. "Competitive Targeted Marketing," ISER Discussion Paper 0834, Institute of Social and Economic Research, Osaka University.
    • Handle: RePEc:dpr:wpaper:0834
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    File URL: https://www.iser.osaka-u.ac.jp/library/dp/2012/DP0834.pdf
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    References listed on IDEAS

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    1. Kim, Beom Jun & Jun, Tackseung & Kim, Jeong-Yoo & Choi, M.Y., 2006. "Network marketing on a small-world network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 493-504.
    2. Jun, Tackseung & Kim, Jeong-Yoo, 2008. "A theory of consumer referral," International Journal of Industrial Organization, Elsevier, vol. 26(3), pages 662-678, May.
    3. F. Schweitzer & L. Behera, 2009. "Nonlinear voter models: the transition from invasion to coexistence," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 301-318, February.
    4. Hołyst, Janusz A. & Kacperski, Krzysztof & Schweitzer, Frank, 2000. "Phase transitions in social impact models of opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 199-210.
    5. Goyal, Sanjeev & Galeotti, Andrea, 2007. "A Theory of Strategic Diffusion," Coalition Theory Network Working Papers 9096, Fondazione Eni Enrico Mattei (FEEM).
    6. Jo, Hang-Hyun & Ki Baek, Seung & Moon, Hie-Tae, 2006. "Immunization dynamics on a two-layer network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(2), pages 534-542.
    7. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    8. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
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    Cited by:

    1. František Pollák & Peter Markovič, 2021. "Economic Activity as a Determinant for Customer Adoption of Social Media Marketing," Sustainability, MDPI, vol. 13(7), pages 1-12, April.
    2. Pejman Ebrahimi & Datis Khajeheian & Maria Fekete-Farkas, 2021. "A SEM-NCA Approach towards Social Networks Marketing: Evaluating Consumers’ Sustainable Purchase Behavior with the Moderating Role of Eco-Friendly Attitude," IJERPH, MDPI, vol. 18(24), pages 1-21, December.

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