Online customer behavior in terms of price elasticity of demand and the effect of time along the booking horizon are key requirements for the price optimization process that allows hotels to maximize their revenues. In this vein, this study adapts the online transient hotel demand functions to deterministic and stochastic dynamic models—two extended optimal pricing methods existing in the literature—in order to determine the prices that maximize the revenues of two resort hotels located in Majorca. The main findings indicate that (1) seasonality, the number of rooms available, the hotel location, and the tourist profile affect dynamic pricing (DP); (2) the booking horizon limitation leads to larger revenue decreases under elastic demand; (3) higher levels in demand elasticities generally produce lower levels of prices; and (4) the distribution of elasticities across the booking horizon and the natural variability of demand have an impact on DP. Implication for industry revenue managers is that they have to consider the booking horizon duration together with the demand price sensitivity in order to maximize the hotel revenues.

中文翻译：

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在线酒店需求的动态定价：马略卡岛的度假酒店

就需求的价格弹性和沿预订期限的时间影响而言，在线客户行为是价格优化过程的关键要求，该过程使酒店能够最大程度地提高收入。因此，本研究将在线暂态酒店需求函数调整为确定性和随机动态模型（文献中存在的两种扩展的最优定价方法），以便确定能够使位于马略卡岛的两家度假酒店收益最大化的价格。主要发现表明：（1）季节性，可用客房数量，酒店位置和游客状况会影响动态定价（DP）；（2）由于弹性需求，预订范围的限制导致更大的收入减少；（3）需求弹性越高，价格水平越低；（4）预订范围内的弹性分布和需求的自然变化都会对DP产生影响。对于行业收入管理者而言，其含义是他们必须考虑预订期限的持续时间以及需求价格敏感性，以使酒店收入最大化。