A comparison of academic libraries: an analysis using a self‐organizing map
Abstract
Purpose
This paper aims to analyze the relationship among measures of resource and service usage and other features of academic libraries in the USA and Canada.
Design/methodology/approach
Through the use of a self‐organizing map, academic library data were clustered and visualized. Analysis of the library data was conducted through the computation of a “library performance metric” that was applied to the resulting map.
Findings
Two areas of high‐performing academic libraries emerged on the map. One area included libraries with large numbers of resources, while another area included libraries that had low resources but gave greater numbers of presentations to groups, offered greater numbers of public service hours, and had greater numbers of staffed service points.
Research limitations/implications
The metrics chosen as a measure of library performance offer only a partial picture of how libraries are being used. Future research might involve the use of a self‐organizing map to cluster library data within certain parameters and the identification of high‐performing libraries within these clusters.
Practical implications
This study suggests that libraries can improve their performance not only by acquiring greater resources but also by putting greater emphasis on the services that they provide to their users.
Originality/value
This paper demonstrates how a self‐organizing map can be used in the analysis of large data sets to facilitate library comparisons.
Keywords
Citation
Ennis, D., Medaille, A., Lambert, T., Kelley, R. and Harris, F.C. (2013), "A comparison of academic libraries: an analysis using a self‐organizing map", Performance Measurement and Metrics, Vol. 14 No. 2, pp. 118-131. https://doi.org/10.1108/PMM-07-2012-0026
Publisher
:Emerald Group Publishing Limited
Copyright © 2013, Emerald Group Publishing Limited