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How to get more from your quantitative LibQUAL+ TM dataset: making results practical

How to get more from your quantitative LibQUAL+ TM dataset: making results practical Purpose – The purpose of this paper is to outline three analytic tools utilized in the analysis and interpretation of LibQUAL+™ quantitative data. Design/methodology/approach – D‐M scores, value rankings, and split‐file cross‐tabulations were used to assess the service items from the 2004 LibQUAL+™ quantitative data. The D‐M score is methodologically superior to other methods used in that it is a single score that takes into account all three LibQUAL+™ perception/expectation scores as dictated by the theoretical model LibQUAL+™ is based upon. Findings – The paper finds that these tools provide a way to more easily utilize LibQUAL+™ results in taking actions and developing strategic plans designed to improve patrons' perceptions of service quality. These tools also allow for the continuous evaluation of implemented plans. Practical implications – The paper discusses how these tools helped produce findings that were informative and in a format that decision makers could easily comprehend and utilize. Originality/value – This paper outlines three approaches and offers practical recommendation of how to analyze and interpret LibQUAL+™ quantitative data as well as present findings to strategic stakeholders. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Performance Measurement and Metrics Emerald Publishing

How to get more from your quantitative LibQUAL+ TM dataset: making results practical

Performance Measurement and Metrics , Volume 8 (2): 17 – Jul 10, 2007

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Publisher
Emerald Publishing
Copyright
Copyright © 2007 Emerald Group Publishing Limited. All rights reserved.
ISSN
1467-8047
DOI
10.1108/14678040710760612
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to outline three analytic tools utilized in the analysis and interpretation of LibQUAL+™ quantitative data. Design/methodology/approach – D‐M scores, value rankings, and split‐file cross‐tabulations were used to assess the service items from the 2004 LibQUAL+™ quantitative data. The D‐M score is methodologically superior to other methods used in that it is a single score that takes into account all three LibQUAL+™ perception/expectation scores as dictated by the theoretical model LibQUAL+™ is based upon. Findings – The paper finds that these tools provide a way to more easily utilize LibQUAL+™ results in taking actions and developing strategic plans designed to improve patrons' perceptions of service quality. These tools also allow for the continuous evaluation of implemented plans. Practical implications – The paper discusses how these tools helped produce findings that were informative and in a format that decision makers could easily comprehend and utilize. Originality/value – This paper outlines three approaches and offers practical recommendation of how to analyze and interpret LibQUAL+™ quantitative data as well as present findings to strategic stakeholders.

Journal

Performance Measurement and MetricsEmerald Publishing

Published: Jul 10, 2007

Keywords: Assessment; Computer software; Data analysis; Libraries; Customer satisfaction

References