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

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.

Citation

Bower, T. and Dennis, B. (2007), "How to get more from your quantitative LibQUAL+^TM dataset: making results practical", Performance Measurement and Metrics, Vol. 8 No. 2, pp. 110-126. https://doi.org/10.1108/14678040710760612