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Points or Discount for Better Retailer Services

Agent-Based Simulation Analysis
  • Yuji Tanaka
  • Takashi Yamada
  • Gaku Yamamoto
  • Atsushi Yoshikawa
  • Takao Terano
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 172)

Abstract

Service management at commodity goods retailers requires various kinds of strategic knowledge. This paper focuses on the (dis)advantages of mileage point and discount services. To uncover the characteristics of the two strategies, we are developing an agent-based simulator to analyze the behaviors of competing retailing stores and their customers. The retailer agents adaptively increase or decrease sales promotion of mileage point service and discounting based on their experiences and strategies to acquire customers. Customer agents, on the other hand, make a decision to choose one of the two retailers to repeatedly purchase daily commodities based on customer types and utilities. To explore the better strategies of retailers, we have conducted intensive simulation experiments. Our computational results have shown that the emergence of retailors’ cooperative behaviors and their stable relations strongly depends on to what extent the retailers decide the discounting rather than mileage point strategy at the very first stages.

Keywords

Mileage points services Discount services Agent-based simulation Sales promotion of commodity goods 

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References

  1. 1.
    Toriyama, M., Kikuchi, T., Yang, C., Yamada, T., Terano, T.: Who is a Key Person to Transfer Knowledge in a Business Firm - Agent-Based Simulation Approach. In: Proc. 5th Knowledge Management in Organizations, KMO 2010, pp. 41–51 (2010)Google Scholar
  2. 2.
    Kobayashi, T., Takahashi, S., Kunigami, M., Yoshikawa, A., Terano, T.: The Effect of Management Style Formalization with Growth of Organization - An Agent-Based Model. In: Proc. 6th Knowledge Management in Organizations, KMO 2011, p. 20 (2011)Google Scholar
  3. 3.
    Chen, S.-H., Terano, T., Yamamoto, R. (eds.): Agent-Based Approaches in Economic and Social Complex Systems. In: VI -Post-Proceedings of the AESCS (2011)Google Scholar
  4. 4.
    International Workshop 2009. ABSS, vol. 8. Springer (2009)Google Scholar
  5. 5.
    Dowling, G.R., Uncles, M.: Do Customer Loyalty Programs Really Work? MIT Sloan Management Review, 16 pages (1997)Google Scholar
  6. 6.
    Berman, B.: Developing an Effective Customer Loyalty Program. California Management Review 49(1), 123–148 (2006)CrossRefGoogle Scholar
  7. 7.
    Liu, Y.: The Long-Term Impact of Loyalty Programs on Consumer Purchase Behavior and Loyalty. Journal of Marketing 71(4), 19–35 (2007)CrossRefGoogle Scholar
  8. 8.
    Humby, C., Hunt, T., Phillips, T.: Scoring Points How Tesco Continues to Win Customer Loyalty. Kogan Page Ltd. (2008)Google Scholar
  9. 9.
    Yi, Y., Jeon, H.: Effects of loyalty programs on value perception, program loyalty, and brand loyalty. Journal of the Academy of Marketing Science 31(3), 229–240 (2003)CrossRefGoogle Scholar
  10. 10.
    Kutschinski, E., Uthmann, T., Polani, D.: Learning Competitive Pricing Strategies by Multi-Agent Reinforcement Learning. Journal of Economic Dynamics and Control 27(11-12), 2207–2218 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    DiMicco, J.M., Greenwald, A., Maes, P.: Learning Curve: A Simulation-Based Approach to Dynamic Pricing. Electronic Commerce Research 3, 245–276 (2003)CrossRefGoogle Scholar
  12. 12.
    Gibbons, R.: Game Theory for Applied Economists. Princeton University Press (1992)Google Scholar
  13. 13.
    Kobayashi, M., Kunigami, M., Yamadera, S., Yamada, T., Terano, T.: How a Major Mileage Point Emerges through Agent Interactions using Doubly Structural Network Model. In: WEIN 2009 (Workshop on Emergent Intelligence on Netwoked Agents) (2009)Google Scholar
  14. 14.
    Doan, R.J., Simon, H.: Power Pricing. Free Press (1997)Google Scholar
  15. 15.
    Taylor, G.A., Neslin, S.A.: The Current and Future Sales Impact of a Retail Frequency Reward Program. Journal of Retailing 81(4), 293–305 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yuji Tanaka
    • 1
  • Takashi Yamada
    • 1
  • Gaku Yamamoto
    • 1
  • Atsushi Yoshikawa
    • 1
  • Takao Terano
    • 1
  1. 1.Department of Computational Intelligence and Systems ScienceTokyo Institute of TechnologyTokyoJapan

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