Eunju Suh, Ph.D., hospitality management professor, recently attended the 20th Asia Pacific Tourism Association (APTA) Conference in Ho Chi Minh City, Vietnam, where she presented a study entitled "Predicting Cross-Gaming Propensity Using CHAID Analysis" (Eunju Suh and Matt Alhaery). Using a data set of 14,120 casino customers, this study aimed to predict a player’s propensity to play different types of casino games. The Exhaustive Chi-squared Automatic Interaction Detector (E-CHAID) method was employed to predict table game players’ slot play propensity and vice versa. The findings of this study will help marketers identify customers that are most likely to cross-play and maximize gaming revenues from more efficient and effective marketing actions. After a rigorous evaluation process of more than 100 papers presented during the conference, the selection committee conferred Dr. Suh with the Best Paper Award. Why was this topic important to you? With the expansion of the casino industry in the global casino market, marketers are looking for opportunities to generate more revenues and improve their player acquisition and retention methods. Hence, customer data to identify, segment and target potential and existing customers have become more important than ever. Analyzing gaming (casino play) data would enable marketers to better understand customer behavior and predict specific behaviors. While casino marketers would agree on the importance of customer data collection and data driven-marketing, in gaming literature, there has been relatively little effort focused on prediction and classification of customer behavior using the actual recorded gaming data of existing casino patrons. What innovative approaches did you employ in this study? Considering the lack of research on the topic of cross-gaming, this study provides a better understanding of players’ cross-gaming behavior while making a meaningful contribution to the pool [...]