Abstract
One of the great uncertainties of revenue management is estimating total demand for a given date. That estimate is essential to determining which rate classes to open or close on that date. The estimate of total, or unconstrained, demand is the sum of room-nights from guests wanting to arrive on that day plus room-nights generated by guests who would arrive earlier and stay through. The difficulty in making such an estimate is in determining the latent demand—comprising guests who might stay at the property but cannot. Some would-be guests never stay at the hotel because they are denied a room due to a sold-out rate class; others regretfully decline to book when they are told the price. The denied guest is part of latent demand, while the regretful guest is probably not. Another problem in determining latent demand is the potential for double counting reservation requests as a result of customers' behavior (such as shopping for rooms and checking several times for rates). Most operators use computer algorithms to make the complicated calculations to make a reasonable estimate of latent demand.