Identifying an Efficiency Productivity Model for Faculties with DEA Benchmarking Technique

Sasarose Jaijit, P. Piamsa-nga, Nalina Phisanbut, J. Pichitlamken
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Abstract

Purpose: Many universities in Thailand aim to raise their ranking; thus, university administrators set the target outputs for their institutions. However, the university-level targets may differ from those at the faculty levels because the inherent nature of academic fields and faculty capacity to produce outputs may not be considered. Therefore, we propose a model to determine possible target values for faculty outputs with weak efficiency by benchmarking the university under study with one of the leading universities in Thailand. As a result, the evidence-based target values allow inefficient faculties to know what outputs they need to improve under the assumption that "if each faculty improves their productivity to reach a target value, the university can rank higher." This can lead to a more realistic and achievable target instead of a single target across all faculties. Study design/methodology/approach: Due to inherent differences among faculties, they are clustered by subject areas with the hierarchical cluster analysis to reduce bias. Then an efficiency score of each faculty is computed via the Data Envelopment Analysis. Findings: The faculties of the university under study are clustered into three subject areas: 1) agricultural science and technology management, 2) engineering and ecology, and 3) social sciences and humanities. The DEA technique provides the slack values to be used in target settings that mitigate the bias from different capabilities on producing outputs across subject areas. For the faculties in agricultural science and technology management, social sciences, and humanities, the inadequacy of performed research and teaching operations are essential indicators, i.e., the percentage of the sum of slack values in both aspects is more than 80%. In engineering and ecology, the essential indicators (i.e., the percentage of the sum of slack values in both aspects is 91.10%) are related to teaching and international outlook operations. However, the teaching operation is the most critical aspect (i.e., the maximum value of the percentage sum of each subject area's slack values is 42.23%) that all subject areas should be focused on for improvement. Originality/value: Our approach can provide a quantitative decision support tool that allows university administrators to set realistic operational policies according to evidence-based target values tailored for each subject area.
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用DEA标杆技术确定学院的效率生产力模型
目的:泰国许多大学的目标是提高自己的排名;因此,大学管理者为他们的机构设定目标产出。然而,大学一级的目标可能与学院一级的目标不同,因为学术领域的固有性质和教师生产产出的能力可能没有被考虑在内。因此,我们提出了一个模型,通过将所研究的大学与泰国一所顶尖大学进行比较,来确定效率较低的教师产出的可能目标值。因此,基于证据的目标值让效率低下的院系知道他们需要改进哪些产出,前提是“如果每个院系都提高生产率以达到目标值,大学的排名就会更高”。这可以导致一个更现实和可实现的目标,而不是所有院系的单一目标。研究设计/方法/方法:由于各院系之间存在固有差异,因此采用分层聚类分析将其按学科领域聚类,以减少偏倚。然后通过数据包络分析计算每个学院的效率得分。研究发现:研究对象大学的院系主要集中在三个学科领域:1)农业科技管理,2)工程与生态,3)社会科学与人文。DEA技术提供了用于目标设置的松弛值,以减轻不同能力对跨主题领域产生输出的偏差。对于农业科技管理、社会科学和人文学科的教师来说,进行的科研和教学操作的不足是必不可少的指标,即这两个方面的松弛值之和的百分比大于80%。在工程学和生态学中,基本指标(即两方面的松弛值之和的百分比为91.10%)与教学和国际视野操作有关。而教学操作是各学科领域需要重点改进的最关键的方面(即各学科领域的松弛值百分比总和的最大值为42.23%)。原创性/价值:我们的方法可以提供定量的决策支持工具,使大学管理者能够根据为每个学科领域量身定制的循证目标值制定现实的操作政策。
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来源期刊
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发文量
27
审稿时长
24 weeks
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