How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification

Huijin Lu; Huidan Tan; Chenwei Li; Xiaobo Xu

doi:10.1007/978-3-031-32299-0_20

How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification

Huijin Lu, Huidan Tan, Chenwei Li, Xiaobo Xu^*

^*Corresponding author for this work

Department of Intelligent Operations and Marketing

Duke University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings
Editors	Yiliu Tu, Maomao Chi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	233-241
Number of pages	9
ISBN (Print)	9783031322983
DOIs	https://doi.org/10.1007/978-3-031-32299-0_20
Publication status	Published - 2023
Event	22nd Wuhan International Conference on E-Business, WHICEB 2023 - Wuhan, China Duration: 26 May 2023 → 28 May 2023

Publication series

Name	Lecture Notes in Business Information Processing
Volume	480 LNBIP
ISSN (Print)	1865-1348
ISSN (Electronic)	1865-1356

Conference

Conference	22nd Wuhan International Conference on E-Business, WHICEB 2023
Country/Territory	China
City	Wuhan
Period	26/05/23 → 28/05/23

Keywords

Customer Satisfaction
Kano Model Classification
Neural Network Modelling
Restaurant Attributes
Sentiment Analysis

Access to Document

10.1007/978-3-031-32299-0_20

Cite this

Lu, H., Tan, H., Li, C., & Xu, X. (2023). How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification. In Y. Tu, & M. Chi (Eds.), E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings (pp. 233-241). (Lecture Notes in Business Information Processing; Vol. 480 LNBIP). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-32299-0_20

Lu, Huijin ; Tan, Huidan ; Li, Chenwei et al. / How Restaurant Attributes Affect Customer Satisfaction : A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification. E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings. editor / Yiliu Tu ; Maomao Chi. Springer Science and Business Media Deutschland GmbH, 2023. pp. 233-241 (Lecture Notes in Business Information Processing).

@inproceedings{2944c74a8bb2401fa568117375d496d9,

title = "How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification",

abstract = "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{\textquoteright}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.",

keywords = "Customer Satisfaction, Kano Model Classification, Neural Network Modelling, Restaurant Attributes, Sentiment Analysis",

author = "Huijin Lu and Huidan Tan and Chenwei Li and Xiaobo Xu",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 22nd Wuhan International Conference on E-Business, WHICEB 2023 ; Conference date: 26-05-2023 Through 28-05-2023",

year = "2023",

doi = "10.1007/978-3-031-32299-0_20",

language = "English",

isbn = "9783031322983",

series = "Lecture Notes in Business Information Processing",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "233--241",

editor = "Yiliu Tu and Maomao Chi",

booktitle = "E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings",

}

Lu, H, Tan, H, Li, C & Xu, X 2023, How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification. in Y Tu & M Chi (eds), E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings. Lecture Notes in Business Information Processing, vol. 480 LNBIP, Springer Science and Business Media Deutschland GmbH, pp. 233-241, 22nd Wuhan International Conference on E-Business, WHICEB 2023, Wuhan, China, 26/05/23. https://doi.org/10.1007/978-3-031-32299-0_20

How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification. / Lu, Huijin; Tan, Huidan; Li, Chenwei et al.
E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings. ed. / Yiliu Tu; Maomao Chi. Springer Science and Business Media Deutschland GmbH, 2023. p. 233-241 (Lecture Notes in Business Information Processing; Vol. 480 LNBIP).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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

PY - 2023

Y1 - 2023

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 - http://www.scopus.com/inward/record.url?scp=85161561385&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-32299-0_20

DO - 10.1007/978-3-031-32299-0_20

M3 - Conference Proceeding

AN - SCOPUS:85161561385

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 -

Lu H, Tan H, Li C , Xu X. How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification. In Tu Y, Chi M, editors, E-Business. Digital Empowerment for an Intelligent Future - 22nd Wuhan International Conference, WHICEB 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 233-241. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-031-32299-0_20

How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this