Modeling hedonic motive–based segments of wine festival visitors using decision tree approach

Purpose: This study aims to identify and validate the different clusters of wine festival visitors based on their hedonic motivation. Further, this study also sought how identified clusters were different in terms of perceived value, satisfaction and loyalty to the wine festival. Design/methodology/approach: A survey was conducted during the International Beach Wine Festival held in Karnataka, India, to collect primary data from 400 visitors. Data were subjected to a two-step cluster analysis. Further, cluster segmentation based on visitors’ demographics, perceived value, satisfaction and loyalty was conducted. Decision tree analysis based on recursive partitioning algorithm was used to validate the clusters. Findings: A two-step cluster analysis identified two distinct segments and named those as elite and informal visitors based on hedonic motivation. The cluster scores show that the elite group had the best ratings on social status, socialization and family harmony. On the other hand, the informal group had top scores for wine tasting, enjoyment, change from routine and the festival atmosphere. Decision tree analysis results indicate that social status enjoyment and taste motives differentiate an informal group from the elite group. Research limitations/implications: This study was conducted in a wine festival held in a single location. To assess the strength of the results, case studies in other regions will be of importance. Originality/value: This study extended the knowledge of the wine festival by adapting hedonic motivation as a basis for wine festival segmentation. Besides, this study’s empirical findings would greatly benefit wine festival organizers to formulate an appropriate marketing strategy to target each wine festival visitors’ cluster based on the differentiating factors obtained from the decision tree modelling.