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An Analysis of Food Tourists' Behavior Among Unobserved Heterogeneous Groups

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This study assessed key factors that influence food tourists' intention to consume local cuisine while traveling. This study also aimed to determine if there was any underlying heterogeneity in food tourists for market segmentation purposes. Food tourists were surveyed at four restaurants in the southeastern US and 450 responses were obtained. Overall, frequency of past behavior had the strongest positive influence on food tourists' intentions to consume local cuisine. A partial least squares prediction-orientated segmentation analysis revealed two segments among food tourists. The first group is more influenced by factors related to tourists' previous travel experiences, including the positive effects of frequency of past behavior and self-identity, and the negative effects of familiarity. The second group is more influenced by factors related to tourists' daily experiences including the positive effects of food involvement, motivation and novelty. Implications for academics and practitioners are discussed in detail.

Keywords: BEHAVIORAL INTENTION; FOOD TOURISTS; LOCAL CUISINE; PARTIAL LEAST SQUARES; PREDICTION-ORIENTED SEGMENTATION

Document Type: Research Article

Publication date: 15 May 2019

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  • Established in 1996, Tourism Analysis is an interdisciplinary journal that provides a platform for exchanging ideas and research in tourism and related fields. The journal aims to publish articles that explore a broad range of research subjects, including, but not limited to, the social, economic, cultural, environmental, and psychological aspects of tourism, consumer behavior in tourism, sustainable and responsible tourism, and effective operations, marketing, and management.

    Tourism Analysis focuses on both theoretical and applied research and strives to promote innovative approaches to understanding the complex and dynamic nature of tourism, its stakeholders, businesses, and its effects on society. The journal welcomes articles on innovative research topics and methodologies beyond the traditional theory-testing sciences, such as robotics, computational sciences, and data analytics.

    Our primary goal is to contribute to the development and advancement of new knowledge in tourism while fostering critical reflections and debates on the radical changes and evolution in tourism among scholars, practitioners, policymakers, and other stakeholders.
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