Predicting the Expected Waiting Time of Popular Attractions in Walt Disney World




Mendoza, Dayanira
Wu, Wenbo
Leung, Mark T.

Journal Title

Journal ISSN

Volume Title


Office of the Vice President for Research


Waiting lines are inevitable consequence of imbalance in service operations at modern theme parks. Because of that, parks have introduced different approaches to reduce standard waiting time; some of which are at no extra cost to guests whereas some others require a price premium. These approaches usually feature a variety of schemes by which guests can bypass the standard waiting line or enter an express lane featuring a minimal wait. Our current study primarily develops statistical learning models to analyze the empirical data gathered from “,” which encompasses some of Walt Disney World’s (WDW) popular attractions located in Orlando, Florida. Results from data analysis and visualization indicate that each of the four parks had similar patterns throughout the years of 2012 through 2018. The study also examines the time-temporal effect and found out which rides having more popularity is dependent upon the season (period) in the year. Empirical analytics are then conducted on each of the four parks using regression modeling (statistical learning) to predict the waiting times for a particular ride during a specific season. Overall, a sample of 13 rides (attractions) over 17 seasons are used to model the waiting times at each theme park, yielding a total of 13x17x4 = 884 possible combinations.





Management Science and Statistics