20231125视频资源：文献与MATLAB代码分享

（1）文献：

https://linkinghub.elsevier.com/retrieve/pii/S1366554521001174.

（2）MATLAB代码：

clear;clc

syms a theta pr ps w c Dr Ds Enc Eprice;                              %0<=theta<1

Enc=0;                                                %0表示不侵占；1表示侵占

U=Ds-(Ds^2)/2+Dr-(Dr^2)/2-theta*Ds*Dr-ps*Ds-pr*Dr;      %消费者效用函数

if Enc==1

  U=Ds-(Ds^2)/2+Dr-(Dr^2)/2-theta*Ds*Dr-ps*Ds-pr*Dr;  

  [Dsx Drx]=solve([diff(U,Ds,1)==0 diff(U,Dr,1)==0],[Ds Dr]);

else

  Ds=0;ps=0;

  U=Ds-(Ds^2)/2+Dr-(Dr^2)/2-theta*Ds*Dr-ps*Ds-pr*Dr;  

  Drx=solve(diff(U,Dr,1)==0,Dr);

  Dsx=0;

end

%% 求解上述优化问题得到需求函数如下

if Enc==1

Dsx =(ps + theta - pr*theta - 1)/(theta^2 - 1);

Drx =(pr + theta - ps*theta - 1)/(theta^2 - 1);

else

  Drx=1 - pr;

  Dsx=0;

end

%% 集中模型

pi=pr*Drx+(ps-c)*Dsx;

if Enc==1

  [psx prx]=solve([diff(pi,ps,1)==0 diff(pi,pr,1)==0],[ps pr])         %CE

else

  prx=solve(diff(pi,pr,1)==0,pr)                                %CN

end

%% 分散模型--等价策略和不等价策略

pir=(pr-w)*Drx;

pim=w*Drx+(ps-c)*Dsx;

Eprice=0                                                   %0表示不采用等价策略

if Enc==1

  if Eprice==1                                              %EP

    pir=(pr-w)*(pr + theta - pr*theta - 1)/(theta^2 - 1);

    prx1=solve(diff(pir,pr,1)==0,pr)

    psx1=prx1

  else

    [prx1 psx1]=solve([diff(pir,pr,1)==0 diff(pim,ps,1)==0],[pr ps])  %NEP

  end

    pimx1=simplify(subs(pim,[ps pr],[psx1 prx1]))

    wx=simplify(solve(diff(pimx1,w,1)==0,w))

    prx=simplify(subs(prx1,w,wx))

    psx=simplify(subs(psx1,w,wx))

else

  prx1=solve(diff(pir,pr,1)==0,pr)                              %N

  pimx1=simplify(subs(pim,pr,prx1))

  wx=simplify(solve(diff(pimx1,w,1)==0,w))

  prx=simplify(subs(prx1,w,wx))

end

%% 直销成本的阈值

% Dsx =subs((ps + theta - pr*theta - 1)/(theta^2 - 1),[pr ps],[prx psx])

% solve(Dsx==0,c)