Determination of Guest Satisfaction by Text Mining

2022 ◽  
pp. 247-269
Author(s):  
Ozan Çatir
Keyword(s):  
Text Mining ◽  
Association Analysis ◽  
Hotel Management ◽  
Mining Method ◽  
Online Comments ◽  
Guest Satisfaction

The satisfaction of guests is of paramount importance to ensure the continuity and profitability of hotels. This study aims to determine guests' satisfaction with hotels by analyzing the online comments of guests. The text mining method has been utilized in this study. 58,193 Turkish comments about 5-star hotels in Turkey have been examined. These comments have been subjected to frequency and association analysis by models with Rapid Miner program. It may be stated that the guests are satisfied with 5-star hotel management in Turkey, and they are also satisfied with hotels in general and the services provided by hotels.

Complaint management model of manufacturing products using text mining and potential failure identification

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ririn Diar Astanti ◽  
Ivana Carissa Sutanto ◽  
The Jin Ai
Keyword(s):  
Quality Management ◽  
Text Mining ◽  
Failure Mode ◽  
Management System ◽  
Main Part ◽  
Mining Method ◽  
Content Type ◽  
Complaint Management ◽  
Potential Failure ◽  
Failure Identification

PurposeThis paper aims to propose a framework on complaint management system for quality management by applying the text mining method and potential failure identification that can support organization learning (OL). Customer complaints in the form of email text is the input of the framework, while the most frequent complaints are visualized using a Pareto diagram. The company can learn from this Pareto diagram and take action to improve their process.Design/methodology/approachThe first main part of the framework is creating a defect database from potential failure identification, which is the initial part of the failure mode and effect analysis technique. The second main part is the text mining of customer email complaints. The last part of the framework is matching the result of text mining with the defect database and presenting in the form of a Pareto diagram. After the framework is proposed, a case study is conducted to illustrate the applicability of the proposed method.FindingsBy using the defect database, the framework can interpret the customer email complaints into the list of most defect complained by customer using a Pareto diagram. The results of the Pareto diagram, based on the results of text mining of consumer complaints via email, can be used by a company to learn from complaint and to analyze the potential failure mode. This analysis helps company to take anticipatory action for avoiding potential failure mode happening in the future.Originality/valueThe framework on complaint management system for quality management by applying the text mining method and potential failure identification is proposed for the first time in this paper.

Sign in / Sign up

Export Citation Format

Share Document