| Yazarlar |
Mehmet Bahri Saydam
Türkiye |
Doç. Dr. Hasan Evrim ARICI
Kastamonu Üniversitesi, Türkiye |
|
Victor Oluwafemi Olorunsola
|
| Özet |
| Consumers can share User Generated Content on social media sites like TripAdvisor, which allows customers to track their contentment and displeasure. These activities are an important form of electronic word-of-mouth that might affect other customers' purchasing decisions. Hence, utilizing User Generated Content from an online platform, this study attempts to investigate guest' experiences in Michelin 3-star restaurants in the United States. Broadly speaking goal of the study was to identify the key aspects of Michelin 3-star restaurant experiences and see if they differed depending on the age and nationality of the travelers. Content analysis approaches were used to examine a sample of 1,032 customer online reviews. After computer-assisted qualitative data analysis identified the dominant themes, subsequent qualitative analysis identified the important narratives connected with Michelin 3-star restaurant experiences using Leximancer software. The findings show that customers are exceedingly pleased with their Michelin 3-star dining experiences. "Food," "chefs," "restaurant," "wine," "staff," and "price" are the major motives that run across the dominant narratives. The findings provide valuable perspectives into guests' overall experiences based on social media data and make it easier to identify the primary themes associated with the guests' gender and nationality. |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayımlanan tam makale |
| Dergi Adı | Journal of Tourism and Gastronomy Studies |
| Dergi ISSN | 2147-8775 |
| Dergi Tarandığı Indeksler | TR DİZİN |
| Makale Dili | İngilizce |
| Basım Tarihi | 03-2022 |
| Cilt No | 10 |
| Sayı | 1 |
| Sayfalar | 62 / 74 |
| Doi Numarası | 10.21325/jotags.2022.978 |
| Makale Linki | http://dx.doi.org/10.21325/jotags.2022.978 |
| Atıf Sayıları | |
| TRDizin | 3 |
| Google Scholar | 9 |
