Chen, Chen YuehChen YuehChenStotlar, David K.David K.StotlarYI-HSIU LIN2022-12-062022-12-062009-01-0114758962https://scholars.lib.ntu.edu.tw/handle/123456789/625896https://www.scopus.com/record/display.uri?eid=2-s2.0-67650151839&origin=resultslistThe primary purpose of this study was to predict types of tickets single-game ticket buyers would purchase to attend the home games of a professional sport team based on their past ticket purchase behaviour using the Multinomial Probit Model. Additionally, the study also sought to identify the factors included in the database that accounted for the prediction model. The research findings included the following: 'Attractive Opponent', 'Late Season', 'Promotion', and 'Value' were the important factors under study that accounted for the prediction model. The correct prediction rates were 60% indicating that this prediction model almost doubled the percentage of correct prediction regarding customers' ticket choice compared to the by-chance guesses. Copyright © 2009, Inderscience Publishers.Data mining | Multinomial Probit Model | Prediction of ticket purchase | Professional sport[SDGs]SDG8journal article10.1504/IJSMM.2009.0267572-s2.0-67650151839https://api.elsevier.com/content/abstract/scopus_id/67650151839