Efficiency assessment in university libraries

Tavares, R.; Drumond, Geisa Meirelles; Meza, Lídia Ângulo; Méxas, Mírian Picinini

doi:10.1590/2318-08892018000100006

Cited by 7 publications

(3 citation statements)

References 29 publications

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“…The selection of the correct and adequate number of input and output variables is very important in this type of study. There are, however, no standard variables to be applied in all studies; nevertheless, several variables have been repeated in a large number of studies (Tavares et al, 2018). Different variables have been used according to the type of libraries under study, time of studies, authors of articles, and type of information resources in libraries (electronic or paper).…”

Section: Discussionmentioning

confidence: 99%

DEA-based Performance Evaluation of Libraries: A Systematic Mapping study

Najafi

Sefiddashti

Sheikhshoaei

et al. 2020

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Este estudio emplea un estudio de mapeo sistemático para analizar publicaciones sobre evaluación del desempeño de la biblioteca con análisis por envoltura de datos (DEA, por sus siglas en inglés). La revisión se basa en una búsqueda exhaustiva en la literatura académica que incluye bases de datos científicas de Scopus y Web of Science. Se seleccionaron 44 artículos publicados entre 1997 y 2018 como el núcleo del estudio. Los resultados muestran que los estudios publicados son realizados principalmente por especialistas en economía, administración, ingeniería y apenas por especialistas en bibliotecología y ciencias de la información. Curiosamente, una gran cantidad de los estudios se llevan a cabo en Taiwán y los Estados Unidos con un enfoque específico en la evaluación del desempeño de las bibliotecas universitarias. Los resultados de este estudio identifican lagunas en términos de técnicas, métodos y procesos utilizados para evaluar el rendimiento de las bibliotecas. Identificar estas brechas puede ayudar a los investigadores de las Ciencias de la Información y Bibliotecología a prestar más atención a la investigación sobre la evaluación del desempeño de las bibliotecas. Además, el estudio identifica las variables clave de entrada y salida en la evaluación del desempeño de las bibliotecas.

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Section: Discussionmentioning

confidence: 99%

DEA-based Performance Evaluation of Libraries: A Systematic Mapping study

Najafi

Sefiddashti

Sheikhshoaei

et al. 2020

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“…In addition to these studies on the efficiency of higher education in countries, some of the studies in the literature focus on specific units within universities, like academic units (Anastasiou et al, 2007), students (Chen & Soo, 2010), and libraries (Tavares et al, 2018). Additionally, other studies have specifically examined the efficiency of either public universities (Visbal-Cadavid et al, 2017) or private universities (Brzezicki, 2020).…”

Section: Introductionmentioning

confidence: 99%

Teaching, research, and third mission efficiency of universities: A data envelopment analysis and hybrid multi‐criteria decision‐making approach

Maral,

Çetin

2024

Manage Decis Econ

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Previous studies on the efficiency of higher education institutions have generally approached the functions of higher education from a limited perspective, and the studies have followed traditional methods. The aim of this study is to determine the teaching, research, and third mission technical efficiency of universities, to rank efficient universities, to identify potential areas for improvement, and to examine the determinants of efficiency scores and the differences in scores in terms of various variables. In this study, the efficiency of 187 universities was measured by data envelopment analysis. Efficiency criteria were weighted by both objective and subjective multi‐criteria decision‐making (MCDM) methods and ranked by different MCDM methods. Beta and Linear regression were performed to determine the factors on efficiency scores. According to the results of the study, the most efficient universities are in the fields of research, teaching, and third mission, respectively. Budget criterion is the most important input criterion. Number of graduates, number of publications, and number of social responsibility projects are the most important output criteria. Having an older history positively predicts teaching and research efficiency. The size of universities and being located in developed regions negatively predict research and third mission efficiency. There is a positive relationship between rankings in teaching, research, and third mission. This research provides more comprehensive information to universities by considering teaching, research, and third mission efficiency separately. Second, this research proposes a new methodology for higher education efficiency measurement by integrating DEA and hybrid MCDM. Finally, this research provides new insights by analyzing factors related to teaching, research, and tertiary mission efficiency.

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“…DEA model has been employed to evaluate the resources being used and the outputs being produced to provide good quality services to the users. The evaluation of the efficiency of multiple outputs and inputs has encouraged researchers to apply this approach compared to other tools (Tavares et al, 2018). Tian and Zhang (2018) determined library efficiency based on a library's ability to transform its input into outputs.…”

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confidence: 99%

Improving the Efficiency of University Libraries in Malaysia Using Zero-Sum Gains Dea Model

Saliman¹,

Ramli²,

Salleh³

2022

MJoC

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Measuring the efficiency and optimizing available resources are vital for library management. This research empirically examines the measurement of efficiency of 10 public university libraries in Malaysia and provides an opportunity for inefficient libraries to improve their efficiency by proposing the appropriate number of resources. Data encompassing the number of staff, materials availability, and material circulation were gathered between 2016 and 2019. This study implements the zero-sum gains data envelopment analysis (ZSG-DEA) model to improve the efficiency. The findings show that in the early stage, five libraries were efficient in 2016 and 2018 while six libraries were efficient in 2017 and 2019. Comparable efficiency scores between conventional DEA and ZSG-DEA can be seen as all the inefficient libraries manage to attain better efficiency scores. Overall, all inefficient libraries can increase their efficiency rates. Despite the scores still not achieving the highest rate of efficiency, this study may assist librarians on managing library operations efficiently.

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Efficiency assessment in university libraries

Cited by 7 publications

References 29 publications

DEA-based Performance Evaluation of Libraries: A Systematic Mapping study

DEA-based Performance Evaluation of Libraries: A Systematic Mapping study

Teaching, research, and third mission efficiency of universities: A data envelopment analysis and hybrid multi‐criteria decision‐making approach

Improving the Efficiency of University Libraries in Malaysia Using Zero-Sum Gains Dea Model

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