Toward Improving Hotel Prognostications Through the Application of Probabilistic Methodologies. (November 2020)

• Record Type: Journal Article
• Authors: O'Neill, John W.; Bloom, Barry A. N.; Sharma, Amit
• Is Part Of: Cornell hospitality quarterly. Volume 61:Number 4(2020:Nov.)
• Page Start: 373
• Page End: 378
• Publication Date: 2020-11
• Subjects: lodging -- projections -- probabilistic methodologies; Hospitality industry -- Periodicals; Hotel management -- Periodicals; Restaurant management -- Periodicals; 338.4791
• DOI: 10.1177/1938965519899927
• Languages: English
• ISSNs: 1938-9655

Abstract

Existing and generally accepted methodologies for developing projections of future hotel performance have been recently described as "grossly inadequate" and we note they have essentially remained unchanged for decades. Notably, current methodologies result in point estimates of future performance and do not adequately consider the inherent risk in lodging investments. Borrowing from research in other fields, and particularly from the area of finance, we suggest the use of probabilistic, that is, stochastic methodologies. In particular, we recommend hotel investors, operators, and analysts use Monte Carlo simulation. Also, this article provides information regarding why probabilistic methodologies are appropriate and general guidance regarding how to apply such approaches.