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Effects of ability difference and strategy imitation on cooperation network formation: A study with game theoretic modeling and multi-agent simulation

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  • Nishino, Nariaki
  • Okazaki, Miki
  • Akai, Kenju

Abstract

Using game theoretic modeling and multi-agent simulation, this study examines cooperation networks in business ecosystems. Business ecosystems generally involve various stakeholders, which develop complex and interdependent relations. Many related studies qualitatively assess these issues from actual case studies, but it is difficult to clarify the general mechanism that forms an ecosystem. In this study, particularly addressing cooperative behavior between agents in business ecosystems, we construct a game theoretic model of cooperation network formation based on Nowak's model of indirect reciprocity and Heider's balance theory. Multi-agent simulation demonstrates that in case agents have different abilities, a cooperation network is likely to collapse because low-ability agents leave the cooperative network. Furthermore, if the agents are able to imitate strategies, then simulation similarly demonstrates that cooperation is insufficiently constructed because of a delay of increasing evaluation values. However, the surviving cooperation network under the conditions of ability difference and strategy imitation forms strong cooperative relations. This result can be regarded as a strong coupling, whereas loosely coupled relations, as demonstrated by Iansiti and Levien, are desirable in terms of the health of ecosystems. Finally, we present discussion of how to form business ecosystems in terms of ability differences and strategy imitation.

Suggested Citation

  • Nishino, Nariaki & Okazaki, Miki & Akai, Kenju, 2018. "Effects of ability difference and strategy imitation on cooperation network formation: A study with game theoretic modeling and multi-agent simulation," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 145-156.
  • Handle: RePEc:eee:tefoso:v:136:y:2018:i:c:p:145-156
    DOI: 10.1016/j.techfore.2017.02.008
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    References listed on IDEAS

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