Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195637
Authors: 
Abing, Stephen Lloyd N.
Barton, Mercie Grace L.
Dumdum, Michael Gerard M.
Bongo, Miriam F.
Ocampo, Lanndon A.
Year of Publication: 
2018
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 14 [Year:] 2018 [Issue:] 4 [Pages:] 733-746
Abstract: 
This paper adopts a modified approach of data envelopment analysis (DEA) to measure the academic efficiency of university departments. In real-world case studies, conventional DEA models often identify too many decision-making units (DMUs) as efficient. This occurs when the number of DMUs under evaluation is not large enough compared to the total number of decision variables. To overcome this limitation and reduce the number of decision variables, multi-objective data envelopment analysis (MODEA) approach previously presented in the literature is applied. The MODEA approach applies Shapley value as a cooperative game to determine the appropriate weights and efficiency score of each category of inputs. To illustrate the performance of the adopted approach, a case study is conducted in a university in the Philippines. The input variables are academic staff, non-academic staff, classrooms, laboratories, research grants, and department expenditures, while the output variables are the number of graduates and publications. The results of the case study revealed that all DMUs are inefficient. DMUs with efficiency scores close to the ideal efficiency score may be emulated by other DMUs with least efficiency scores.
Subjects: 
Academic efficiency
Data envelopment analysis
Multi-objective data envelopment analysis
University departments
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

Files in This Item:
File
Size
481.99 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.