Vageesh Neelavar Kelkar, Kartikeya Bolar, Valsaraj Payini and Jyothi Mallya
This study aims to identify and validate the different clusters of wine consumers in India based on the wine-related lifestyle (WRL) instrument. It also investigates how the…
Abstract
Purpose
This study aims to identify and validate the different clusters of wine consumers in India based on the wine-related lifestyle (WRL) instrument. It also investigates how the identified clusters differ in terms of socio-demographic characteristics, such as age, gender, income, education, employment and marital status.
Design/methodology/approach
The authors conducted a survey using a structured questionnaire to collect data from wine consumers in India. The number of participants totalled to 432. The authors first identified the clusters using latent profile analysis. The authors then used the decision tree analysis based on a recursive partitioning algorithm to validate the clusters. Finally, the authors analysed the relationship between the identified clusters and socio-demographic characteristics using correspondence analysis.
Findings
Three distinct segments emerged after data were subjected to latent profile analysis, namely, curious, ritualistic and casual. The authors found that the curious cluster had a high mean score for situational and social consumption while the ritualistic cluster had a high mean for ritualistic consumption. The findings also suggest that the casual cluster had more female wine consumers.
Originality/value
This study makes methodological contributions to the wine consumer segmentation approach. First, it adopts a latent profile analysis to profile Indian wine consumers. Second, it validates the obtained clusters using the decision tree analysis method. Third, it analyses the relationship between the identified clusters and socio-demographic variables using correspondence analysis, a technique far superior to the Chi-square methods.
Details
Keywords
Valsaraj Payini, Kartikeya Bolar, Jyothi Mallya and Vasanth Kamath
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…
Abstract
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.