Evolutionary Game Analysis of Firms’ Technological Strategic Choices: A Perspective of the Behavioral Biases

Author:

Zhang Yingqing12ORCID,Fan Ruguo3ORCID,Luo Ming2ORCID,Chen Mingman1ORCID,Sun Jiaqin3ORCID

Affiliation:

1. School of Management Science and Engineering, Guizhou University of Finance and Economics, Guiyang 550025, China

2. Economics and Management School, Guangxi Normal University, Guilin 541000, China

3. Economics and Management School, Wuhan University, Wuhan 430072, China

Abstract

To reveal the mechanisms of firms’ technological strategic choices between innovation and imitation, an evolutionary game model is proposed from the perspective of the behavioral biases. First, behavioral biases such as reference point dependence, loss aversion, and probability weighting can be defined and modeled based on the prospect theory. Second, according to the firm theory, a Cournot or Stackelberg game modeled with a technology spillover effect and intellectual property protection is applied to portray the interaction between firms. Third, an improved evolutionary game model is provided by incorporating behavioral biases into the framework of the decision-making process. Finally, the simulation analysis of some important factors, such as intellectual property protection, patent fees, innovation risks, decision-making attitudes, and consumers’ price preference on firms’ technological strategic choices, is presented. The corresponding results show that (1) innovation risk is an important factor affecting the technological strategic choices of firms, (2) increasing the intellectual property protection and the patent fee for technology transfer can effectively control the spillover effect of technology, (3) there is a partial U-shaped relationship between the consumers’ price preference and innovation, and (4) the behavioral biases such as reference point dependence, loss aversion, and probability weighting will change the perception of payoff and risk and will eventually induce firms to adopt the innovation strategy.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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