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Chinese Journal of Management Science ›› 2021, Vol. 29 ›› Issue (11): 55-67.doi: 10.16381/j.cnki.issn1003-207x.2019.0481

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Three-party Evolutionary Game and Simulation Analysis of Drug Quality Supervision under the Government Reward and Punishment Mechanism

ZHU Li-long1, RONG Jun-mei2, Zhang Si-yi1   

  1. 1. School of Business, Shandong Normal University, Ji’nan 250014, China;2. School of Economics and Management, Tongji University, Shanghai 200092, China
  • Received:2019-04-09 Revised:2019-07-10 Online:2021-11-20 Published:2021-11-22
  • Contact: 荣俊美 E-mail:junmeirong@163.com

Abstract: Drug safety concerns the people’s life and health, economic development, social stability and national security. It has always been one of the hot issues that the government and the whole society are focusing on. However, in recent years, various drug safety incidents have been frequently reported, which have revealed many problems such as the lacking of government supervision, imperfect drug testing mechanisms. In recent years, the rapid development of third-party drug testing institutions has not only supplemented government supervision, but also provided technical support for pharmaceutical manufacturers. However, driven by interests, there are phenomena of rent-seeking in drug testing between pharmaceutical manufacturing enterprises and the third-party testing agencies. In order to study how to improve the drug quality supervision mechanism to ensure the quality of drugs and avoid rent-seeking in the process of drug testing, a three-party evolutionary game model among drug manufacturers, third-party drug testing institutions and government regulatory agencies has been constructed. Based on the three-party evolutionary game theory, the evolutionary stability of each participant's strategy choices has been analyzed, the influence of each factor on the choice of three-party strategy has been discussed, and the stability of the equilibrium points in the three-party game system has been further analyzed using Jacobian matrix and Lyapunov’s indirect method. The main results show that: 1) increased incentives and penalties by the government will help enterprises to produce high-efficiency drugs and third-party drug testing institutions to refuse to seek rent, but, increased incentives will not be conducive to the government's own performance of regulatory responsibilities; 2) in order to guarantee the safety of drugs in an evolutionarily stable market environment, the government should set reasonable reward and punishment mechanisms in line with the conditions that the sum of the rewards and punishments of each party is greater than its speculative income, that is the condition that the system has only one evolutionary stable equilibrium point; 3) the accountability of the superior government for the dereliction of duty of the regulatory authorities is of great significance to enhance the stability of enterprises in producing high-efficiency drugs; 4) enhancing the company’s drug sales revenue and increasing the company’s rent-seeking cost are also effective ways to avoid enterprises producing low-efficiency drugs. In addition, the parameters are assigned to numerical values based on the conditions of the evolutionary stability strategies which obtained by the model analysis and combined with the reality. The influence of each element on the evolution of each party’s strategy and the stability of the game system under different conditions has been simulated using the Matlab 2020b software. The simulation analysis verifies the correctness of the model analysis and the effectiveness of the countermeasures and suggestions for improving the government supervision mechanism. In short, this paper puts forward a variety of measures to ensure the stable production of high-effective drugs in enterprises and to eliminate rent-seeking, which is conducive to improving the government’s regulatory strategy to ensure patients’ medication safety.

Key words: drug safety; quality supervision; rent-seeking behavior; three-party evolution game; simulation analysis

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