Abstract
This paper evaluates the consumer behavior, in the context of the “Essence of Wine” and its impact regarding the intention to return to the event. Data from a random sample of 1080 visitors were collected through face-to-face interviews, during the four days of the event. The data was subjected to clustering analysis. We performed the ANOVA test to describe each cluster taking into account the sociodemographic characteristics in order to evaluate the impact in the intention to return and the global satisfaction with the event. After that, multiple regression analysis was used to identify the factors that influence frequency of participation on fairs and wine workshops. We found out that it is possible to segment the visitors of the Essence of Wine event, according to different consumer behavior variables. The different segments had significant differences with respect to the global level of satisfaction and intention to return. It was proved that both sociodemographic and consumer behavior characteristics had an impact on the frequency of acquisition of wine magazines and frequency of participation on wine fairs. The results allow the segmentation of the public and identify the target audience. The results obtained are a useful framework to the organizers of the event in the process of defining the communication strategies for the next edition of the event.
Original language | English |
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Title of host publication | CIET 2018 Conference Proceedings |
Editors | Bože Plazibat, Silvana Kosanović |
Publisher | University of Split |
Pages | 206-219 |
Number of pages | 14 |
Edition | Split |
ISBN (Print) | 9789537220297 |
Publication status | Published - 1 Jun 2018 |
Externally published | Yes |
Event | Contemporary issues in economy & technology - Split, Croatia Duration: 1 Jun 2018 → 2 Jun 2018 |
Conference
Conference | Contemporary issues in economy & technology |
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Abbreviated title | CIET 2018 |
Country/Territory | Croatia |
City | Split |
Period | 1/06/18 → 2/06/18 |
Keywords
- Wine events
- Consumer behavior
- Clustering