TY - GEN
T1 - How Restaurant Attributes Affect Customer Satisfaction
T2 - 22nd Wuhan International Conference on E-Business, WHICEB 2023
AU - Lu, Huijin
AU - Tan, Huidan
AU - Li, Chenwei
AU - Xu, Xiaobo
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/5
Y1 - 2023/5
N2 - The study aims to understand how the various attributes of restaurant affect its customer satisfaction. Different with prior literature with heavy reliance on self-reported data, we investigated 17 representative restaurant attributes extracted from online reviews, modeled the relationship between restaurant attributes and customer satisfaction leveraging neural network, and classified the attributes into five categories based on kano model. The findings show that, among the 17 attributes, waiter’s attitude and taste of food are most important for a high customer satisfaction. This study could help restaurant allocate its resources with greater efficiency and improve customer satisfaction.
AB - The study aims to understand how the various attributes of restaurant affect its customer satisfaction. Different with prior literature with heavy reliance on self-reported data, we investigated 17 representative restaurant attributes extracted from online reviews, modeled the relationship between restaurant attributes and customer satisfaction leveraging neural network, and classified the attributes into five categories based on kano model. The findings show that, among the 17 attributes, waiter’s attitude and taste of food are most important for a high customer satisfaction. This study could help restaurant allocate its resources with greater efficiency and improve customer satisfaction.
KW - Customer Satisfaction
KW - Kano Model Classification
KW - Neural Network Modelling
KW - Restaurant Attributes
KW - Sentiment Analysis
UR - https://link.springer.com/chapter/10.1007/978-3-031-32299-0_20
U2 - 10.1007/978-3-031-32299-0_20
DO - 10.1007/978-3-031-32299-0_20
M3 - Conference Proceeding
AN - SCOPUS:85192934867
SN - 9783031322983
T3 - Lecture Notes in Business Information Processing
SP - 233
EP - 241
BT - E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings
A2 - Tu, Yiliu
A2 - Chi, Maomao
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 26 May 2023 through 28 May 2023
ER -