Kansei engineering with online review mining methodology for robust service design

Hartono, Markus and Prayogo, Dina Natalia and Ronyastra, I Made and Baredwan, Abdullah (2023) Kansei engineering with online review mining methodology for robust service design. Theoretical Issues in Ergonomics Science. ISSN 1463-922X; E-ISSN: 1464-536X

PDF Markus Hartono_Kansei engineering with online review mining methodology.pdf Download (4MB)

Abstract

Kansei Engineering (KE) has shown its prominent applicability in service design and development, focusing on translating and interpreting customers’ emotional needs (Kansei) into service characteristics. It is critical and promising as the services sector has grown faster than the manufacturing sector in developing economies in the past three decades. It accounted for an average of 55% of GDP in some developing economies. KE’s flexibility in collaborating with other methods and covering various service settings shows its unique superiority. However, there is criticism of the collected Kansei’s validity and the proposed solution’s robustness. It might be potentially caused by the dynamics of customer emotional needs and various service settings. As a result, Kansei is found to be somewhat fuzzy, unclear, and ambiguous. Hence, a more structured KE methodology incorporating the Kansei text mining process for robust service design is proposed. Kansei text mining approach will extract and summarize service attributes and their corresponding affective responses based on the online product descriptions and customer reviews. The Taguchi method will support the robustness of the proposed improvement strategy. An empirical study of a zoo as a tourism attraction service and its practical implication is discussed and validated in the proposed integrative framework.

Item Type:	Article
Uncontrolled Keywords:	Kansei engineering; robust design; mining methodology; service innovation
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Engineering > Department of Industrial Engineering
Depositing User:	Markus Hartono 61124
Date Deposited:	29 Sep 2023 03:42
Last Modified:	24 Oct 2023 04:25
URI:	http://repository.ubaya.ac.id/id/eprint/45012

Actions (login required)

View Item