摘要
本文构建了不完全信息静态博弈模型,研究基于产品网络效应的垄断企业,面临潜在进入与现实的进入威胁情况下的R&D最优阻挠行为。研究结论表明:在面临潜在进入威胁的情况下,如果R&D行为是一种开创性发现或发明时,垄断企业采用不阻挠战略;如果R&D行为是一种渐进式创新行为时,垄断企业采用提前阻挠战略是最优的;而不同程度的潜在进入威胁引致的阻挠策略是存在区别的,当垄断企业认为进入者进入概率很大时,其最优阻挠行为是快速阻挠;当垄断企业认为进入者进入概率很小时,其最优阻挠行为是慢速阻挠。在现实进入发生的情况下,无论进入者进入市场的推出产品的方式是快还是慢,垄断企业最优阻挠战略是采用慢速阻挠战略。同时,通过数字模拟分析,验证了上述结论;并讨论了产品网络效应强度与垄断企业选择不同R&D阻挠行为的关系。
In this paper, an incomplete information static game theoretical model is set up to do the research of a monopolizer＇s R＆D optimal deterrence strategy when the monopolizer can use pre-emption deterrence strategy and nonce deterrence strategy, and their products have strong network effect on consumer＇s choice behavior. The conclusions of the research are follows： First, at the pre-emption deterrence strategy, if the monopolizer＇s R＆D action is initial discovery or invention, the monopolizer＇s optimal deterrence strategy does not deter the entry of the entrant; otherwise, the monopolizer must use deterrence strategy. The deterrence strategy includes the drastically deterrence strategy and the incrementally deterrence strategy. When the entry probability of the entrant is very high considered by the monopolizer, the monopolizer＇s optimal R＆D strategy is the drastically deterrence strategy. When the entry probability of the entrant is very low considered by the monopolizer, the monopolizer＇s optimal R＆D strategy is the incrementally deter strategy. Second, at the nonce deterrence strategy, whether the entry probability of the entrant is high or not, the monopolizer＇s optimal R＆D strategy is the incrementally deterrence strategy. At the same time, we also test and verify the above conclusions by making some digital simulated experiments, and discuss the network effect has an influence on the monopolizer＇s profits.
出处
《管理工程学报》
CSSCI
2008年第2期90-97,共8页
Journal of Industrial Engineering and Engineering Management
基金
教育部哲学社会科学研究重大课题攻关基金资助项目(04JZD0018)
关键词
静态博弈
R&D
提前阻挠
现时阻挠
网络效应
incomplete information static game
R＆D strategy
pre-emption deterrence strategy
nonce deterrence strategy
network effect
