In order to gain maximum profit, retail can make policy close to market through observing real sale situation of last period and updating demand forecasting using Bayesian rule. This paper applies Bass extended diffusion model and constructs an optimal policy model for perishable hi-tech products with demand updating and substitutable successive generation products coming into the market at random time. After analyzing and discussing a two-period special example this paper draws some significant conclusion: retail can increase significantly profit when forecast is not correct and the variance of the forecast is large.%以获得最大期望利润为目标,零售商观察前期产品的实际销售情况,使用贝叶斯更新法则更新对需求的预测,更好地接近市场实际状况制定价格策略.引入Bass扩展扩散模型建立了考虑需求更新并且后续产品随机时间进入市场且对老产品需求有替代影响下的易逝性高科技产品收益管理定价策略模型,对建立的模型以两阶段特例进行了算例分析和讨论,结论表明预测不准确时,预测方差偏大能显著提高零售商利润.
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