Modelling customer satisfaction for product development using genetic programming

Product development involves several processes in which product planning is the first one. Several tasksnormally are required to be conducted in the product-planning process and one of them is to determinesettings of design attributes for products. Facing with fierce competition in marketplaces, com...

Full description

Bibliographic Details
Main Authors: Chan, Kit Yan, Kwong, C., Wong, T.
Format: Journal Article
Published: Taylor & Francis 2009
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/6161
_version_ 1848744997005819904
author Chan, Kit Yan
Kwong, C.
Wong, T.
author_facet Chan, Kit Yan
Kwong, C.
Wong, T.
author_sort Chan, Kit Yan
building Curtin Institutional Repository
collection Online Access
description Product development involves several processes in which product planning is the first one. Several tasksnormally are required to be conducted in the product-planning process and one of them is to determinesettings of design attributes for products. Facing with fierce competition in marketplaces, companies try to determine the settings such that the best customer satisfaction of products could be obtained.To achieve this, models that relate customer satisfaction to design attributes need to be developed first. Previous research has adopted various modelling techniques to develop the models, but those models are not able to address interaction terms or higher-order terms in relating customer satisfaction to design attributes, or they are the black-box type models. In this paper, a method based on genetic programming (GP) is presented to generate models for relating customer satisfaction to design attributes. The GP is first used to construct branches of a tree representing structures of a model where interaction terms and higher-order terms can be addressed. Then an orthogonal least-squares algorithm is used to determine the coefficients of the model. The models thus developed are explicit and consist of interaction terms and higher-order terms in relating customer satisfaction to design attributes. A case study of a digital camera design is used to illustrate the proposed method.
first_indexed 2025-11-14T06:10:21Z
format Journal Article
id curtin-20.500.11937-6161
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T06:10:21Z
publishDate 2009
publisher Taylor & Francis
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-61612017-09-13T16:06:25Z Modelling customer satisfaction for product development using genetic programming Chan, Kit Yan Kwong, C. Wong, T. interaction terms design attributes customer satisfaction genetic programming higher-order terms Product development involves several processes in which product planning is the first one. Several tasksnormally are required to be conducted in the product-planning process and one of them is to determinesettings of design attributes for products. Facing with fierce competition in marketplaces, companies try to determine the settings such that the best customer satisfaction of products could be obtained.To achieve this, models that relate customer satisfaction to design attributes need to be developed first. Previous research has adopted various modelling techniques to develop the models, but those models are not able to address interaction terms or higher-order terms in relating customer satisfaction to design attributes, or they are the black-box type models. In this paper, a method based on genetic programming (GP) is presented to generate models for relating customer satisfaction to design attributes. The GP is first used to construct branches of a tree representing structures of a model where interaction terms and higher-order terms can be addressed. Then an orthogonal least-squares algorithm is used to determine the coefficients of the model. The models thus developed are explicit and consist of interaction terms and higher-order terms in relating customer satisfaction to design attributes. A case study of a digital camera design is used to illustrate the proposed method. 2009 Journal Article http://hdl.handle.net/20.500.11937/6161 10.1080/09544820902911374 Taylor & Francis fulltext
spellingShingle interaction terms
design attributes
customer satisfaction
genetic programming
higher-order terms
Chan, Kit Yan
Kwong, C.
Wong, T.
Modelling customer satisfaction for product development using genetic programming
title Modelling customer satisfaction for product development using genetic programming
title_full Modelling customer satisfaction for product development using genetic programming
title_fullStr Modelling customer satisfaction for product development using genetic programming
title_full_unstemmed Modelling customer satisfaction for product development using genetic programming
title_short Modelling customer satisfaction for product development using genetic programming
title_sort modelling customer satisfaction for product development using genetic programming
topic interaction terms
design attributes
customer satisfaction
genetic programming
higher-order terms
url http://hdl.handle.net/20.500.11937/6161