TY - JOUR
T1 - Dimensionality of ethnic food fine dining experience
T2 - An application of semantic network analysis
AU - Oh, Munhyang (Moon)
AU - Kim, Seongseop (Sam)
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - 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.
AB - 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.
KW - Big data
KW - Restaurant
KW - Semantic network analysis
KW - Text analytics
UR - http://www.scopus.com/inward/record.url?scp=85088403579&partnerID=8YFLogxK
U2 - 10.1016/j.tmp.2020.100719
DO - 10.1016/j.tmp.2020.100719
M3 - Journal article
AN - SCOPUS:85088403579
SN - 2211-9736
VL - 35
JO - Tourism Management Perspectives
JF - Tourism Management Perspectives
M1 - 100719
ER -