Applying the fuzzy SERVQUAL method to measure the service quality in certification &amp; inspection industry

Liu, Ru; Cui, Lixin; Zeng, Guangfeng; Wu, Hua; Wang, Chengjie; Yan, Shan; Yan, Bingyan

doi:10.1016/j.asoc.2014.10.014

Cited by 61 publications

(37 citation statements)

References 27 publications

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“…Furthermore, according to the average product perception value and the weight vector of the second-level evaluation index, we can calculate the product perception value of the first-level evaluation indexes using (7). Let [V , V ] be the product perception value of the first-level evaluation index, where V denotes the product perception appropriate value of the first-level evaluation index; V denotes the product perception advantage value of the first-level evaluation index.…”

Section: Calculation Of Product Perception Valuementioning

confidence: 99%

“…Moreover, product quality evaluation is a combination of various attributes; it contains not only objective attributes but also subjective attributes, many of which are intangible and difficult to measure with numerical accuracy and are fuzzy information [7]. For example, the use of "good," "medium," and "bad" language evaluation can be better expressed by the perception of customers for the evaluation of machine tool equipment.…”

Section: Introductionmentioning

confidence: 99%

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An Evaluation Method of Comprehensive Product Quality for Customer Satisfaction Based on Intuitionistic Fuzzy Number

Zhang

2018

Discrete Dynamics in Nature and Society

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How to maximize customer satisfaction is an important research topic in the service quality evaluation. This paper proposes an evaluation method of comprehensive product quality for customer satisfaction based on the intuitionistic fuzzy number. In this method, we design a questionnaire and investigate the customer's language evaluation information of product quality evaluation, including product expectations and product perception at first. And then, the product quality evaluation model is obtained by Delphi method; that is, the first-level evaluation indexes and the second-level evaluation indexes are obtained and the weight vector of each evaluation index is determined. Next, language evaluation information translates into corresponding fuzzy numbers using intuitionistic fuzzy numbers. Therefore, the results of the product quality evaluation of the production system are obtained using the weighted mean method. Finally, an example is used to illustrate the feasibility and effectiveness of the proposed method.

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Section: Calculation Of Product Perception Valuementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Evaluation Method of Comprehensive Product Quality for Customer Satisfaction Based on Intuitionistic Fuzzy Number

Zhang

2018

Discrete Dynamics in Nature and Society

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“…--Fuzzy linguistic scales These scales are frequently considered for different goals as an a posteriori tool to encode data from a discrete (often a Likert) scale by means of fuzzy numbers (see, for instance, Zadeh 1975a, b, c;Tong and Bonissone 1980;Pedrycz 1989;Herrera et al 1998Herrera et al , 2008Lalla et al 2008;Li 2013;Akdag et al 2014;Estrella et al 2014;Massanet et al 2014;Tejeda-Lorente et al 2014Villacorta et al 2014;Wang et al 2014;Garcia-Galán et al 2015;Liu et al 2015a;Tavana et al 2015). --Fuzzy rating scale This scale has been introduced by Hesketh et al (1988).…”

Section: Fuzzy Data: Fuzzy Representation Of Linguistic Terms Ordinamentioning

confidence: 99%

Exploratory multivariate analysis for empirical information affected by uncertainty and modeled in a fuzzy manner: a review

D’Urso

2017

Granul. Comput.

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“…Fuzzy rating scales have been intensively applied in higher education context to measure quality related issues (see e.g. Basaran et al,2011;Lalla et al, 2005;Yu et al, 2016;Lupo, 2013;Liu et al, 2015;Venkatesan and Fragomeni, 2008). Based on the relevant literature the next research issue was addressed by applying a fuzzy-scale in case of student evaluations in the framework of the peer review program and analyze the benefits of fuzzy scales compared to traditional Likert scales.…”

Section: Responsibility Of the Organizing Committee Of The Conferencementioning

confidence: 99%

Enhancing The Reliability Of Measurements And Evaluations Based On Service Quality Models

Tóth¹,

Árva²,

Surman³

2017

European Proceedings of Social and Behavioural Sciences

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Problem statement: The application of different service quality measurements and evaluations in higher educational context and the utilization and reliability of results are examined.Research questions: What are the difficulties in the measurement and evaluation of specific service quality dimensions? How can the reliability of such service quality measurements be enhanced?Purpose of the study: This paper introduces the application and the results of a student satisfaction questionnaire based on fuzzy Likert scale used for evaluating lecturers' performance at the Budapest University of Technology and Economics.Research methods: In order to capture and accurately measure the diversity, subjectivity and imprecision inherent to students' evaluations, a methodology based on fuzzy numbers having sigmoid membership functions has been proposed. By applying the principles of Dombi's Pliant Arithmetics, the evaluations can be aggregated and statistically analysed in a convenient way.Findings: Fuzzy-numbers based questionnaires result in a more precise reflection of human thinking and judgement. The Pliant Arithmetic-based approach allows us to aggregate the parameters of the left and right hand sides of the fuzzy number separately. This property results in a much simpler statistical analysis of the gathered data than the methods previously proposed in the literature.Conclusions: The proposed methodology can be utilized in two ways. It can either be applied to identify lecturers' strengths and weaknesses in order to develop their teaching skills or to compare and analyse various students' evaluations. The results can serve as a base for establishing teaching regulations and discovering best practices as well.

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Applying the fuzzy SERVQUAL method to measure the service quality in certification & inspection industry

Cited by 61 publications

References 27 publications

An Evaluation Method of Comprehensive Product Quality for Customer Satisfaction Based on Intuitionistic Fuzzy Number

An Evaluation Method of Comprehensive Product Quality for Customer Satisfaction Based on Intuitionistic Fuzzy Number

Exploratory multivariate analysis for empirical information affected by uncertainty and modeled in a fuzzy manner: a review

Enhancing The Reliability Of Measurements And Evaluations Based On Service Quality Models

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