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Herd Behavior Analysis Based on Evolutionary Game Theory in the Decision-Making of Innovation Adoption

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Social Media Retrieval and Mining

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 387))

Abstract

Information Cascades are fairly important to individual decision making, however, it of lead to adoption of inferior products. Many researches on herd behavior have limited their scope on the phenomenon in capital markets and the behavior of investors, but few of them focus on the herd behavior of agents. This paper aims to employ the evolutionary game theory to explain the cause of the herd behavior of agents in their decision-making process for innovation adoption. Furthermore, the effects of herd behavior on innovation adoption and diffusion are analyzed. A kind of remuneration incentives mechanism is then presented in order to circumvent the herd behavior of agents. Last but not the least, a case study on the innovation adoption of e-business enterprises in China has been conducted to demonstrate the effectiveness of the proposed methods.

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Author information

Authors and Affiliations

  1. School of Information Management, Wuhan University, Wuhan, People’s Republic of China

    Mao Yan-ni & Zhou Lei

  2. School of International Economics and Business, Nanjing University of Finance and Economics, Nanjing, People’s Republic of China

    Mao Yan-ni

Authors
  1. Mao Yan-ni
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  2. Zhou Lei
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Corresponding author

Correspondence to Mao Yan-ni .

Editor information

Editors and Affiliations

  1. Fudan University School of Computer Science, Shanghai, People's Republic of China

    Shuigeng Zhou

  2. University of Finance and Economics, Nanjing, People's Republic of China

    Zhiang Wu

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Yan-ni, M., Lei, Z. (2013). Herd Behavior Analysis Based on Evolutionary Game Theory in the Decision-Making of Innovation Adoption. In: Zhou, S., Wu, Z. (eds) Social Media Retrieval and Mining. Communications in Computer and Information Science, vol 387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41629-3_9

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  • DOI: https://doi.org/10.1007/978-3-642-41629-3_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41628-6

  • Online ISBN: 978-3-642-41629-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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