The assessment of user-perceived web quality: Application of a satisfaction benchmarking approach

Grigoroudis, Evangelos; Litos, Charalambos; Moustakis, Vassilis; Politis, Yannis; Tsironis, Loukas K.

doi:10.1016/j.ejor.2006.09.017

Cited by 104 publications

(46 citation statements)

References 18 publications

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“…These providers need to check the quality of what they are presenting, and users of their websites would give them the most important information. Quality assessment can significantly contribute to develop websites that serve users' need and meet the user expectations to the maximum possible extent (Grigoroudis et al 2008). In order to achieve high-quality websites, designers have to first understand the different quality dimensions that affect users' expectations, and then relate these quality characteristics to specific design features (Zhang and von Dran 2001).…”

Section: Background On Quality Evaluation Of Health-related Websitesmentioning

confidence: 99%

“…To cope with this situation, some initiatives aimed at assessing quality on the Web have been developed. On the other hand, since organisations throughout the world invest time and money in order to develop and maintain user-perceived websites, evaluating their quality is necessary to understand whether websites comply with user needs and expectations (Grigoroudis et al 2008).…”

Section: Introductionmentioning

confidence: 99%

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A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

et al. 2009

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Nowadays, the patients and physicians use the health-related websites as an important information source and, therefore, it is critical the quality evaluation of healthrelated websites. The quality assessment of health-related websites becomes especially relevant because their use imply the existence of a wide range of threats which can affect people's health. Additionally, website quality evaluation can also contribute to maximize the exploitation of invested resources by organizations in the development of user-perceived quality websites. But there is not yet a clear and unambiguous definition of the concept of website quality and the debate about quality evaluation on the Web remains open. In this paper, we present a qualitative and user-oriented methodology for assessing quality of healthrelated websites based on a 2-tuple fuzzy linguistic approach. To identify the quality criteria set, a qualitative research has been carried out using the focus groups technique. The measurement method generates linguistic quality assessments considering the visitors' judgements with respect to those quality criteria. The combination of the linguistic judgements is implemented without a loss of information by applying a 2-tuple linguistic weighted average operator. This methodology means an improvement on quality evaluation of health websites through the commitment to put users first.

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Section: Background On Quality Evaluation Of Health-related Websitesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

et al. 2009

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“…This implies that the customer satisfaction model that considers each customer attribute independently was ignored. Grigoroudis et al (2008) further applied the MUSA method to measure user-perceived web quality. You et al (2006) developed the customer satisfaction models for automotive interior material, using quantification I analysis.…”

Section: Introductionmentioning

confidence: 99%

Modelling customer satisfaction for product development using genetic programming

Chan

Kwong

Wong

2009

Journal of Engineering Design

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Product development involves several processes in which product planning is the first one. Several tasks normally are required to be conducted in the product-planning process and one of them is to determine settings 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

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“…Explicit information for consumer preferences cannot be indicated in the artificial neural networks. To generate explicit models, multivariate regression approaches are commonly used [5,6]. In general, statistical methods are more preferred as more explicit information can be found than using the artificial neural networks.…”

Section: Introductionmentioning

confidence: 99%

A forward selection based fuzzy regression for new product development that correlates engineering characteristics with consumer preferences

Chan

Ling

2016

IFS

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Abstract. Fuzzy regression models have commonly been used to correlate engineering characteristics with consumer preferences regarding a new product. Based on the models, product developers can determine optimal engineering characteristics of the new product in order to satisfy consumer preferences. However, they have a common limitation in that they cannot guarantee to include significant regressors with significant engineering characteristics or significant nonlinear terms. The generalization capability of the model can be reduced, when too few significant regressors are included and too many insignificant regressors are included. In this paper, a forward selection based fuzzy regression (FS-FR) is proposed based on the statistical forward selection to determine significant regressors. After the significant regressors are determined, the fuzzy regression is used to generate the fuzzy coefficients which address the uncertainties due to fuzziness and randomness caused by consumer preference evaluations. The developed model includes only significant regressors which attempt to improve the generalization capability. A case study of a tea maker design demonstrated that the FS-FR was able to generate consumer preference models with better generalization capabilities than the other tested fuzzy regressions. Also simpler consumer preference models can be provided for the new product development.Keywords: fuzzy regression, statistical forward selection, new product development, consumer preferences, engineering characteristics, tea maker design, overfitting, generalization capability * Corresponding author. Kit Yan Chan. E-mail: kit.chan@curtin.edu.au ; Telephone number is 61 8 92662945.

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The assessment of user-perceived web quality: Application of a satisfaction benchmarking approach

Cited by 104 publications

References 18 publications

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

Modelling customer satisfaction for product development using genetic programming

A forward selection based fuzzy regression for new product development that correlates engineering characteristics with consumer preferences

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