Modèles de la Valeur Espérée

  • Politique de produit - Modèles de valeur espérée [ 4.1-3]

1.                               # Modèles de valeur espérée

2.                               K=2 # no critères

3.                               I=10 # no individus

4.                               # Perception produit echelle 1-7

5.                               # input (1)

6.                               x<-round(runif(I*K, min=1, max=7))

7.                               dim(x)<-c(I,K)

8.                               colnames(x)<-colnames(x, do.NULL=F, prefix="Percp.")

9.                               # Importance des critères par individu

10.                             # input (2)

11.                             w<-round(runif(I*K, min=1, max=5))

12.                             dim(w)<-c(I,K)

13.                             colnames(w)<-colnames(w, do.NULL=F, prefix="Import.")

14.                             # Scores Individuels proportionnels aux probabilités dachat

15.                             p<-(x*w)%*%c(1,1)

16.                             dim(p)<-c(I,1)

17.                             maxp=max(p)

18.                             maxprob=0.3

19.                             p<-maxprob*p/maxp

20.                             colnames(p)<-"Prob.achat"

21.                             rownames(p)<-rownames(p, do.NULL=F, prefix="Obs.")

22.                             df<-data.frame(cbind(p,x,w))

23.                             df

24.                             cat("Ventes")

25.                             (sum(df[,"Prob.achat"]))

26.                             # Effets de la modification des caractéristiques dun produit

27.                             # input (3)

28.                             deltax=c(0,2)

29.                             deltaVentes=sum(((w%*%diag(deltax))%*%c(1,1))%*%(maxprob/maxp))

Michel Calciu calciu@iae.univ-lille1.fr; - Cours IAE de Lille 2004 - -