Dimensionality of ethnic food fine dining experience: An application of semantic network analysis

Munhyang (Moon) Oh, Seongseop (Sam) Kim

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

This study attempts to find the underlying dimensionality in online reviews of fine-dining ethnic food restaurant experiences in Hong Kong. This research adopted semantic network analysis with Clauset–Newman–Moore clustering. Consequently, diverse and specific dimensionality was explored in this research, including ambiance, service, food, drinks, desserts, view, location, occasions, reputation and price. The content of the reviews on five types of ethnic restaurants was different in some dimensions. Marketers of fine-dining ethnic restaurants can select a particular focus when they promote their restaurants, develop menu plan and train staff members. This study implies that the quality dimensions of traditional restaurants may not accurately represent the factual dimensions, thereby resulting in implications for developing a new index of restaurant quality.

Original languageEnglish
Article number100719
JournalTourism Management Perspectives
Volume35
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Big data
  • Restaurant
  • Semantic network analysis
  • Text analytics

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management

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