Recommending Rides: Psychometric Profiling in the Theme Park

Authors:
Stefan Rennick Egglestone;Amanda Whitbrook;Julie Greensmith;Brendan Walker;Steve Benford;Joe Marshall;David Kirk;Holger Schnädelbach;Ainoje Irune;Duncan Rowland
Affiliations:
University of Nottingham;BAE Systems;University of Nottingham;Aerial;University of Nottingham;University of Nottingham;University of Nottingham;University of Nottingham;University of Nottingham;University of Nottingham
Venue:
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
Year:
2010

Citing 7
Cited 1

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Abstract

This article presents a study intended to inform the design of a recommender system for theme park rides. It examines the efficacy of psychometric testing for profiling theme park visitors, with the aim of establishing a set of measures to be included in a visitor profile intended for use in a collaborative recommender system. Results presented in this article highlight the predictive value of a number of psychometric measures, including two drawn from the “Big Five” personality inventory, and one drawn from the “Sensation Seeking Scale”. The article discusses general research challenges associated with the integration of psychometric testing into recommender systems, and describes planned future work on a theme park recommender system.