Performance Measurement of Hawaii State Public Libraries: An Application of Data Envelopment Analysis (DEA)

Author:

Sharma Khem R.,Leung PingSun,Zane Lynn

Abstract

In view of continuing economic stagnation and consequent budgetary constraints facing the state, Hawaii public libraries have been concerned with their operational efficiency and library managers have been seeking better methods in allocating limited resources among the libraries. This paper employed data envelopment analysis (DEA) technique to assess the performance and resource utilization efficiency of 47 public libraries in Hawaii. Three output measures—circulation, reader visits, and reference transactions and four input categories—collection, library staff, days open, and nonpersonal expenditures were used in the analysis. For fiscal year 1996/97, the estimated technical efficiency scores for Hawaii State public library branches ranged from 0.45 to 1.00, with an average of 0.84. The results showed that 14 of the 47 libraries are technically efficient. The estimated efficiency scores were related to relevant library-specific factors and community characteristics, such as total floor space, size of collection, population density, and location to identify factors influencing library performance. Only floor space and volume of collection did show moderate positive effects on library performance. The resulting information can be mainly useful in improving the performance of inefficient libraries. With special consideration to factors uncontrollable by the libraries the results may also be useful in allocating limited resources among them.

Publisher

Cambridge University Press (CUP)

Subject

Economics and Econometrics,Agronomy and Crop Science

Reference23 articles.

1. Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis

2. The educational attainment and income level of the population the library serves can also be important, but could not be considered because of the data constraint.

3. The output measures defined here are mainly quantitative in nature. Despite the importance of qualitative measures, such as user's satisfaction, no qualitative output measure is considered because of the lack of such information.

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