Réaction de la concurrence

1.                               # Modèle de Concurrence

2.                               nx1<-seq(6,10.5,0.5)

3.                               nx2<-rep(2,10)

4.                               nattr<-(5*nx1^-2)*(0.3+2*nx2^2/(2^2+nx2^2))

5.                               cx1<-rep(9,10)

6.                               cx2<-rep(2,10)

7.                               cattr<-(5*cx1^-2)*(0.3+2*cx2^2/(2^2+cx2^2))

8.                               npart1<-nattr/(nattr+3*cattr) # notre part - cas de référence

9.                               npart2<-nattr/(nattr+6*cattr) # notre part - marché plus large plus de concurrents

10.                             y<-1600*(cx1+cx2)^-1.5

11.                             profit1<-npart1*y*(nx1-3)-nx2

12.                             profit2<-npart2*y*(nx1-3)-nx2

13.                             df<-data.frame(Effort=nx1, Part1=npart1, Profit1=profit1, Part2=npart2, Profit2=profit2)

14.                             #Politique de pub agressive de la concurence par rapport à notre prix

15.                             cx2<-ifelse(nx1>=9,cx2,cx2+(9-nx1))

16.                             cattr<-(5*cx1^-2)*(0.3+2*cx2^2/(2^2+cx2^2))

17.                             npart3<-nattr/(nattr+6*cattr) # marché large

18.                             profit3<-npart3*y*(nx1-3)-nx2

19.                             df$Part3<-npart3

20.                             df$Profit3<-profit3

21.                             df

22.                             matplot(nx1, df[,c(3,5,7)], pch = 1:3, type = "o", col = 1:3,xlab="Valeurs de x", ylab="Ventes et/ou Profits")

23.                             legend(min(nx1), max(df[,c(3,5,7)]),names(df)[c(3,5,7)], lwd=3, col=1:3, pch=1:3)