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dc.contributor.authorThompson, Gary M.
dc.contributor.authorSohn, Heeju
dc.description.abstractBy calculating revenue per available seat-hour, or RevPASH, restaurant managers can implement revenue management approaches to build their restaurant’s profitability. The key to making this work is the appropriate calculation of RevPASH, in a way that captures accurately the effects of revenue, time, and capacity. Most RevPASH analyses are based only on the time at which a check is opened. Since the time needed for most meals crosses analysis periods (whether those periods are an hour, a half-hour, or less), assigning the entire RevPASH to the analysis period when the check is opened can create inaccurate analyses. Instead, as demonstrated in this report, a better approach would be to calculate RevPASH according to both check open and close times. The resulting revised RevPASH calculation accounts for the demand that customers place on restaurant capacity for the entire duration of their meals (and the revenue therefrom). Using eight months of data from one restaurant’s POS, we find that the traditional approach works fine when RevPASH is calculated for the entire day part (in this case, the entire lunch period). The approach based only on check-opening times become less accurate, however, as the analysis periods are shortened. Even when the analysis periods are two hours long, the inaccuracy of the traditional approach exceeds 40 percent. Understanding the nature of this inaccuracy (and how to overcome it) is essential for managers who use RevPASH to guide their revenue enhancing decisions.
dc.rightsRequired Publisher Statement: © Cornell University. This report may not be reproduced or distributed without the express permission of the publisher
dc.subjectrevenue per available seat-hour
dc.subjectrestaurant capacity
dc.subjectrestaurant revenue management
dc.titleAccurately Estimating Time-Based Restaurant Revenues Using Revenue per Available Seat-Hour
dc.description.legacydownloadsThompson_202008_20Accurately_20estimating.pdf: 3003 downloads, before Aug. 1, 2020.
local.authorAffiliationThompson, Gary M.: Cornell University

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