Pharmaceutical enterprises drug quality strategy Moran analysis considering government supervision and new media participation

Abstract

The improvement of drug quality requires not only the supervision of government, but also the participation of new media. Therefore, this paper considers the impact of government regulation and new media reports on pharmaceutical enterprises, constructs a Moran Process evolutionary game model, and analyzes the evolution trajectory of pharmaceutical enterprises' choice of drug quality improvement strategy and drug cost reduction strategy. We obtain the conditions for the two strategies to achieve evolutionary stability under the dominance of external factors and the dominance of expected returns. To verify the theoretical results, we conduct a numerical simulation by the software MATLAB 2021b. The results show that, first of all, when the government penalty is high, the drug quality improvement strategy tends to become an evolutionary stable solution, increasing the penalty amount will help promote the improvement of drug quality. What's more, when the government penalty is low and the new media influence is low, the drug cost reduction strategy is easier to dominate. The higher the new media influence, the higher the probability that pharmaceutical enterprises choose the drug quality improvement strategy. Thirdly, when the number of pharmaceutical enterprises is lower than a threshold, the drug quality improvement strategy is easier to dominate. Finally, the drug quality improvement strategy is dominant when the quality cost factor is low and the government penalty is high, the drug cost reduction strategy is dominant when the quality cost factor is high and the government penalty is low. Above all, this paper provides countermeasures and suggestions for the drug quality improvement of pharmaceutical enterprises in practice.

Keywords: Moran process; drug cost reduction strategy; drug quality improvement strategy; government supervision; new media participation.

Figure 1

Effect of the number of pharmaceutical enterprises on fixed point probability. This figure shows that under the dominance of external factors, the effect of the number of pharmaceutical enterprises on fixed point probability when considering different government penalty. (A) When F = 10.66, (B) When F = 1.066.

Figure 2

Effect of new media influence on fixed point probability. This figure shows that under the influence of external factors, the effect of new media influence on fixed point probability when considering different government penalty. (A) When F = 10.66, (B) When F = 1.066.

Figure 3

Effect of government penalty and new media influence. This figure shows the effect of the government penalty and the new media influence on the fixed-point probability under the dominance of external factors. (A) Fixed point probability N×ρ_Q, (B) Fixed point probability N×ρ_L.

Figure 4

Effect of the number of pharmaceutical enterprises on strategic choice. This figure shows that under the dominance of expected returns the effect of the number of pharmaceutical enterprises on the strategic choice when considering different government penalty. (A) When F = 5, (B) When F = 2.5, (C) When F = 1.

Figure 5

Effect of government penalty and new media influence on strategic choice. This figure shows the effect of government penalty and the new media influence on the choice of drug quality improvement strategy under the dominance of expected returns. (A) When q = 0.7, (B) When q = 0.4.