【摘要】 基于微观决策理论 ,分别建立了确定性情况下和不确定性情况下单个潜在用户面对创新时的采纳决策模型 .应用 von Neumann-Morgenstern效用函数 ,给出了不确定性收益的等价确定性收益 ,量化了不确定性对潜在用户决策的影响 ;认为潜在用户对创新性能的判断是一个连续型随机变量 ,给出了基于 Bayes修正法则的潜在用户获得新信息后修正自己以前判断的方法 ;以采纳创新所需要的最少信息数的形式 ,给出了潜在用户采纳创新的先后顺序 .基于单个潜在用户的决策模型以及某些个体特征在潜在用户群中的分布规律建立了宏观层次的创新扩散模型 .更多还原

【Abstract】 An innovation acceptance model at the individual level, considering both certainty and uncertainty, is developed according to decision theory. Through von Neumann-Morgenstern utility function, certain equivalent of uncertain profit is given and the effect of uncertainty on potential user’s decision-making is thus quantified. Potential user’s belief of the profit from using innovation is regarded as a continuous random variable, and a belief updating method based on Bayesian Updating Rule is given. Innovation acceptance sequence of potential users, in the form of the least pieces of information that a potential user needs for adopting innovation, is obtained. Based on decision-making model at the individual level and the distribution of some characteristics of potential users in the whole population, a macrolevel innovation diffusion model is developed.更多还原