Pharmaceutical enterprises integrity supervision strategy when considering rent-seeking behavior and government reward and punishment mechanism

Abstract

The integrity of pharmaceutical enterprises is crucial to public health, social stability, and national security, consistently garnering attention from both the government and society. The efficiency of pharmaceutical integrity supervision is closely linked to government oversight mechanisms and the behaviors of third-party testing agencies. This study constructs an evolutionary game model that incorporates rent-seeking dynamics and introduces a reward-punishment mechanism, integrating drug production enterprises, third-party testing agencies, government regulators, and drug wholesale enterprises. By solving for the stable equilibrium points of each participant's strategic choices and analyzing the stability of strategy combinations using Lyapunov's first method, the study employs Matlab 2022b for simulation analysis to verify the impact of various decision variables on the strategic choices of different entities. The findings reveal that: 1) The rejection of rent-seeking by third-party testing agencies enhances the incentives for drug production enterprises to operate with integrity, indicating that the government should increase penalties for accepting rent-seeking behavior. 2) Drug wholesale enterprises' reporting likelihood increases production enterprises' integrity and third-party testing agencies' rejection of rent-seeking, inversely tied to reporting costs. 3) Reducing the costs of stringent government supervision and increasing the speculative costs of rent-seeking for third-party testing agencies help prevent dishonest practices among drug production enterprises. 4) A well-designed reward and punishment mechanism facilitates a synergistic environment of government supervision, self-discipline among pharmaceutical enterprises, and social harmony. This paper enriches the theoretical foundation of pharmaceutical integrity supervision and offers pertinent countermeasures and recommendations.

Fig 1. Four-party game relationship.

Fig 1 is a structural diagram of the relationship between drug production enterprises, third-party testing agencies, government regulators and drug wholesale enterprises that introduce government reward and punishment mechanisms under rent-seeking behavior.

Fig 2. Phase diagram of drug production enterprises strategic choices.

Fig 2 is the phase diagram that shows the evolutionary trend of drug production enterprises ‘s strategy obtained by calculating the response function of the probability of drug production enterprises choosing the “integrity management” strategy.

Fig 3. Phase diagram of third-party testing agencies strategic choices.

Fig 3 is the phase diagram that shows the evolutionary trend of third-party testing agencies’ strategy obtained by calculating the response function of the probability of third-party testing agencies choosing the “accept rent-seeking” strategy.

Fig 4. Phase diagram of government regulators strategic choices.

Fig 4 is the phase diagram that shows the evolutionary trend of government regulators’ strategy obtained by calculating the response function of the probability of government regulators choosing the “strict supervision” strategy.

Fig 5. Phase diagram of drug wholesale enterprises strategic choices.

Fig 5 is the phase diagram that shows the evolutionary trend of drug wholesale enterprises’ strategy obtained by calculating the response function of the probability of drug wholesale enterprises choosing the “reporting” strategy.

Fig 6. The impact of fines and incentives on drug wholesale enterprises.

Fig 6 is the simulation diagram that shows the influence of the reward amount brought by drug wholesale enterprises reporting and the fine amount brought by drug wholesale enterprises not reporting on the strategic choices of drug production enterprises, third-party testing agencies, government regulators, and drug wholesale enterprises. (A) When the situation $Fw=0.0$, $Mw=0.0$. (B) When the situation $Fw=3.0$, $Mw=3.0$. (C) When the situation $Fw=7.0$, $Mw=7.0$.

Fig 7. The impact of fines on drug production enterprises and third-party testing agencies.

Fig 7 is the simulation diagram that shows the influence of the fine amount brought by drug production enterprises dishonest management and third-party testing agencies accept rent-seeking on the strategic choices of drug production enterprises, third-party testing agencies, government regulators, and drug wholesale enterprises. (A) When the situation $Fp=0.0$, $Ft=0.0$. (B) When the situation $Fp=5.0$, $Ft=5.0$. (C) When the situation $Fp=10.0$, $Ft=10.0$.

Fig 8. The impact of reporting by drug wholesale enterprises.

Fig 8 is the simulation diagram that shows the influence of the probability of reporting by drug wholesale enterprises on the strategic choices of drug production enterprises, third-party testing agencies, and government regulators. (A) When the situation $z=0.0$. (B) When the situation $z=0.5$. (C) When the situation $z=1.0$.

Fig 9. The impact of strict supervision by government regulators.

Fig 9 is the simulation diagram that shows the influence of the probability of strict supervision by government regulators on the strategic choices of drug production enterprises, third-party testing agencies, and drug wholesale enterprises. (A) When the situation $g=0.0$. (B) When the situation $g=0.5$. (C) When the situation $g=1.0$.

Fig 10. Impact of cost.

Fig 10 is the simulation diagram that shows the influence of various costs on the strategic choices of drug production enterprises, third-party testing agencies, and government regulators. (A) When the situation $Bt=2.9$, $C1-C2=13.0$, $Cr=4.0$. (B) When the situation $Bt=4.9$, $C1-C2=8.0$, $Cr=5.0$. (C) When the situation $Bt=6.9$, $C1-C2=3.0$, $Cr=6.0$.