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+(TM) 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+(TM) 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+(TM) perception/expectation scores as dictated by the theoretical model LibQUAL+(TM) is based upon. Findings - The paper finds that these tools provide a way to more easily utilize LibQUAL+(TM) 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+(TM) quantitative data as well as present findings to strategic stakeholders.