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Article
Publication date: 3 July 2009

Yahia Zare Mehrjerdi, Hossein Sayyadi Toranlo and Reza Jamali

The purpose of this paper is to present the perception of service quality. The measurement of service quality has grown significantly in importance over recent years. However…

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Abstract

Purpose

The purpose of this paper is to present the perception of service quality. The measurement of service quality has grown significantly in importance over recent years. However, since customers' perceptions of service quality are expressed subjectively in vague linguistic terms therefore, a fuzzy approach to service quality of an academic library is applied and the gap between the student's expectations and perceptions analyzed.

Design/methodology/approach

The LibQUAL method is applied to identify the gap between customer expectation and perceptions of the actual service received. The linguistic procedure is developed considering four dimensions of LibQUAL. The quality analyses are based on the non‐parametric rank‐based statistics (Wilcoxon's two‐sample rank sum statistic) and extended to fuzzy data which consequently reinforces results in comparison with crisp data.

Findings

It is found that there is no gap between the students' expectations and perceptions in three dimensions of “affect of service”, “library as a place”, and “personal control”. But, from the students' point of view, regarding the “access to information” dimension, there is a significant difference between the students' expectations and perceptions.

Research limitations/implications

The instrument that is administered is a paper questionnaire version based on the 2002 model of LibQUAL.

Practical implications

It is felt that application of this fuzzy procedure has implications on possible constraints on the statistics of interest, as well as on the p‐value of any associated significance tests.

Originality/value

This paper is possibly the first to demonstrate the application of fuzzy logic to the LibQUAL model. This fuzzy procedure persuades possibility constraints on the statistic of interest, as well as on the p‐value of an associated significance test. This fuzzy procedure persuades possibility constraints on the statistic of interest, as well as on the p‐value of an associated significance test.

Details

Performance Measurement and Metrics, vol. 10 no. 2
Type: Research Article
ISSN: 1467-8047

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Article
Publication date: 3 July 2009

Steve Thornton

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Abstract

Details

Performance Measurement and Metrics, vol. 10 no. 2
Type: Research Article
ISSN: 1467-8047

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