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Technical and allocative efficiencies of 26 academic departments in the College of Agriculture and Life Sciences at Cornell University are computed using Data Envelopment Analysis over 2004/05. Allocations of faculty time between teaching, research, and extension vary by department and are used as unique prices in calculating allocative efficiencie...
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... Microscopic view: This involves looking at the internal departments or disciplines of a particular university. Some researchers prefer to use the DEA model to collect data on scientific research from colleges of humanities and social sciences to build a super-efficiency model, and the results showed significant differences in their efficiency [8]. In addition, some researchers analyzed expert opinions on the factors influencing scientific research capability in 13 colleges and universities, extracted weights by using the analytical hierarchy process, and established seven factors of a system for evaluating scientific research in colleges and universities [9]. ...
The study takes 10 urban agglomerations in China as the research object, focusing on the Chengdu-Chongqing urban agglomeration, and applies Data Envelopment Analysis (DEA) to measure and compare their scientific input and output efficiency of universities. First, this paper analyzes the input and output of scientific research in universities in major provinces in China in detail. Second, according to the construction principles of the indicator system, using qualitative interview to construct evaluation indicators of university research efficiency. Third, using DEA method, first analyze the input and output profile of some urban agglomeration universities such as Chengdu-Chongqing economic circle, measure and compare their research input and output efficiency, then compare and analyze the research efficiency of research-type sample universities within Chengdu-Chongqing economic circle, and conduct a projection study of non-DEA effective sample universities. The main conclusions are as follows: first, the average efficiency of scientific research in universities in Chengdu-Chongqing and other urban agglomerations in 2020 has slightly increased compared with that in 2016, but the gap between urban agglomerations is prominent, and the innovation level of scientific research in higher education institutions in urban agglomerations needs to be improved. Second, there is a mismatch between the themes of research, funding and human resources in research-oriented universities in the Chengdu-Chongqing economic circle. Third, there is considerable room for improvement in research efficiency, and the influence of scale on overall efficiency is weak. We found that excessive investment in scientific research in universities is the main reason for the non-effect.
... La calidad del servicio educativo se ha convertido en un problema importante en educación en todo el mundo (Zafiropoulos & Vrana 2008). En tal sentido, el interés por medir el desempeño y la eficiencia de los centros educativos de la educación superior no es exclusivo para Chile, sino también mundialmente (Agasisti & Salerno 2007;Agasisti et al., 2011;Agasisti & Johnes 2010), en especial en lo que tiene que ver con análisis de departamentos entre diferentes universidades (Arcelus y Coleman, 1997;Johnes & Johnes 1993;Leitner et al. 2007); Madden et al., 1997;Thursby, 2000; y dentro de la misma universidad (Halkos et al., 2012;Kao & Hung 2008;Tauer et al., 2007;Tyagi et al., 2009). En ambos casos el objetivo ha sido establecer las unidades técnicamente eficientes de aquellas que han hecho un uso ineficiente de los recursos. ...
Introducción.
Actualmente las universidades públicas están siendo objeto de importantes transformaciones educativas en un contexto donde el Estado está exigiendo criterios de racionalidad y eficiencia económica.
Objetivo.
El objetivo de este trabajo es determinar la eficiencia técnica para el total de los 14 Departamentos de la Facultades de Ingeniería, Tecnológica y Humanidades que conforman la Universidad de Atacama para el período lectivo 2020.
Metodología.
La metodología propuesta es un análisis envolvente de datos DEA-CCR orientado inputs con rendimientos constante a escala y un modelo BCC con rendimientos variables a escala. Este tipo de análisis es un aporte de la programación matemática que transforma innumerables inputs y output medidos en una sola suma de productividad eficiente (Coll Serrano & Blasco Blasco, 2006). Como variables inputs se han escogido el presupuesto anual, los gastos operacionales, número de alumnado matriculado, cantidad de personal académico, años de experiencia, carga promedio en docencia y tesis tuteladas y como variables outputs, las publicaciones científicas indexadas y el plan operativo anual.
Resultados.
Los resultados mostraron que los Departamentos 2 y 3 de la Facultad Tecnológica deben reducir sus inputs en un 77,8% y 85,1% respectivamente para situarse en la frontera eficiente. En la Facultad de Ingeniería hubo un mejor desempeño en términos del uso eficiente de los recursos.
Conclusiones.
Se puede concluir, respecto de la importancia del análisis de eficiencia productiva interdepartamental, que permita mejorar la toma de decisiones de las autoridades universitarias. Se recomienda a las autoridades universitarias llevar a cabo un estudio de la mejora en los años venideros.
... Institution/university level(Abbott & Doucouliagos, 2003; Avkiran, 2001;Breu & Raab, 1994;Kantabutra & Tang, 2010;Kuah & Wong, 2011;Sagarra et al., 2017), -Department/program level(Agasisti et al., 2011;Kao & Hung, 2008;Kounetas et al., 2011;Madden et al., 1997;Mayston, 2014;Tauer et al., 2007),-Teaching efficiency(Agasisti & Bonomi, 2014;Agasisti & Dal Bianco, 2009;Barra & Zotti, 2016a;J. Johnes, 2003;Mikušová, 2017),-Research efficiency (Abramo & D'Angelo, 2009; Chu Ng & Li, 2000; J. Johnes & Li, 2008; Munoz, 2016; Rhaiem, 2017),-Both teaching and research efficiency(Barra & Zotti, 2016b;Beasley, 1995;Kao, 2012;Martín, 2006;Tochkov et al., 2012),-Effects of external factors(Cherchye & Abeele, 2005;Fandel, 2007;Kuo & Ho, 2008;Lee, 2011;Warning, 2004;Wolszczak-Derlacz, 2017), Methodology approaches on the efficiency of HEIs other than DEA (derived from Günay & Dulupçu, 2019); -Malmquist index (Agasisti & Pérez-Esparrells, 2010; Edvardsen et al., 2017; Flegg et al., 2004; Thanassoulis et al., 2011; Worthington & Lee, 2008), -Robust frontiers (Bonaccorsi et al., 2006; Fernández-Santos & Martínez-Campillo, 2015), -Metafrontier (Lu & Chen, 2013), -Stochastic frontier analysis (SFA) (Abbott & Doucouliagos, 2009; G. Johnes & Johnes, 2009; McMillan & Chan, 2006), -Bootstrapping (Lee, 2011; Villano & Tran, 2018). ...
This study determined undergraduate and graduate education efficiency scores using the 2020 data from 20 state research universities in Turkey. The study used input-oriented data envelopment analysis to compare undergraduate and graduate education efficiencies. In the study, the efficiency of the research universities in the prioritized field(s) was compared with the efficiency in the field(s) in which they operate intensively. It also includes suggestions on increasing their effectiveness in the prioritized field(s). In addition, the Tobit regression model, which is a regression model for limited dependent variables, was used to determine the determinants of efficiency scores. The findings show the undergraduate and graduate education performances of research universities comparatively. In addition, based on the results obtained from the Tobit regression model, suggestions were made to increase graduate performance. Five factors (the number of graduate students per faculty member, the number of undergraduate students per academic staff, the number of graduates/undergraduates in the number of students and graduations, and the number of faculty members per program) have a significant effect on graduate performance. Therefore, it is important in terms of strategic management that research universities should be restructured by considering these factors or that they should be considered in plans. The study offers an alternative perspective to performance management in both education and management.
... Most efficiency studies are carried out by mainly considering either a university or an academic department as a unit of measurement. Academic departments within a university or across universities have been compared in the past, as performed by Arcelus and Coleman [11] for Canada; Moreno and Tadepalli [12] and Tauer et al. [13] for the United States; Johnes and Johnes [14,15] for the United Kingdom; Madden et al. [16] for Australia; Kao and Hung [17] for Taiwan; Kounetas et al. [18] for Greece; Agasisti et al. [19,20] for Italy; Leitner et al. [21] for Austria; Koksal and Nalcaci [22] for Turkey; Naderi [23] for Iran; and Ali et al. [24] for India; and Villano and Tran [9] for Vietnam. For instance, Kao and Hung [17] adopted the DEA method with an assurance region to measure the technical efficiency of 41 academic departments at National Cheng Kung University, Taiwan. ...
Traditionally, data envelopment analysis (DEA) requires all decision-making units (DMUs) to have similar characteristics and experiences within the same external conditions. In many cases, this assumption fails to hold, and thus, difficulties will be encountered to some extent when measuring efficiency with a standard DEA model. Ideally, the performance of DMUs with different characteristics could be examined using the DEA meta-frontier framework. However, some of these DMUs are mixed-type DMUs that may affiliate with more than one group. Furthermore, the total number of observations of this mixed-type DMUs is limited. This is one of common problems when studies focus on faculty research performance in higher education institutions. In general, a faculty member is affiliated with a certain department, and if the departmental assessment policy is not suitable for faculty members who are involved in interdisciplinary research, their performance could be underestimated. Therefore, the proposed model is an extension of the DEA meta-frontier framework that can assess the performance of mixed-type DMUs by constructing the reference set without the same type of DMUs. In this paper, the scientific research efficiency of faculty members at the Inner Mongolia University is used as an example to provide a better understanding of the proposed model. The proposed model is intended to provide a fair and balanced performance assessment method to reflect the actual performance, especially for mixed-type DMUs.
... For example, in the Kao and Hung (2008) study, the Liberal Arts department might have had difficulty in obtaining more grant dollars (an output); however, the department may be able to improve in the teaching performance area (a different output) (Kao and Hung, 2008). Tauer et al. (2007) also addressed the efficiencies of academic departments and the need for improvement given the reduction of governmental funding and the acute awareness of the increase of college tuition. They conducted their study at the College of Agricultural and Life Sciences at Cornell University and found that some departments were considered to have the correct mix of outputs and, thereby, considered efficient. ...
... They conducted their study at the College of Agricultural and Life Sciences at Cornell University and found that some departments were considered to have the correct mix of outputs and, thereby, considered efficient. They also found that some departments were considered technically efficient but not creating the correct amount of each specific output (Tauer et al., 2007). They further found departments that were considered inefficient and not aligned with the mission of the college and needed to be addressed by administration (Tauer et al., 2007). ...
... They also found that some departments were considered technically efficient but not creating the correct amount of each specific output (Tauer et al., 2007). They further found departments that were considered inefficient and not aligned with the mission of the college and needed to be addressed by administration (Tauer et al., 2007). ...
... For example, in the Kao and Hung (2008) study, the Liberal Arts department might have had difficulty in obtaining more grant dollars (an output); however, the department may be able to improve in the teaching performance area (a different output) (Kao and Hung, 2008). Tauer et al. (2007) also addressed the efficiencies of academic departments and the need for improvement given the reduction of governmental funding and the acute awareness of the increase of college tuition. They conducted their study at the College of Agricultural and Life Sciences at Cornell University and found that some departments were considered to have the correct mix of outputs and, thereby, considered efficient. ...
... They conducted their study at the College of Agricultural and Life Sciences at Cornell University and found that some departments were considered to have the correct mix of outputs and, thereby, considered efficient. They also found that some departments were considered technically efficient but not creating the correct amount of each specific output (Tauer et al., 2007). They further found departments that were considered inefficient and not aligned with the mission of the college and needed to be addressed by administration (Tauer et al., 2007). ...
... They also found that some departments were considered technically efficient but not creating the correct amount of each specific output (Tauer et al., 2007). They further found departments that were considered inefficient and not aligned with the mission of the college and needed to be addressed by administration (Tauer et al., 2007). ...
Higher education costs are rising. The literature points to varying factors for the increases: the lack of efficiency on the instructional side, the growth in administrative expenses as well as the decrease in state appropriations. But do these items impact average net price at four-year public and private not-for-profit institutions? This study looks at the relationship between average net price and these factors considering the fixed effects by state.
... The results of DEA in the dimensions of teaching, research, service and quality are modelled under fuzzy environment and then a single index of performance for each department is generated. Tauer et al. (2007) study for technical and allocative efficiencies of academic departments in the College of Agriculture and Life Sciences at Cornell University using DEA. They use various specifications of outputs and inputs to determine sensitivity of results to specification. ...
... The aim of the paper is to estimate and analyse the efficiency of faculties of a leading university for the year 2014 using DEA. Although there are numerous studies focused on the efficiency of universities, university departments and so on in different countries around the world using various parametric and non-parametric methods (Kokkelenberg et al. 2008;Al-Shayea and Battal, 2013;Izadi et al. 2002;Glass et al. 2006;McMillan and Chan, 2006;Worthington and Lee, 2008;Abbott and Doucouliagos, 2003;Tzeremes and Halkos, 2010;Johnes and Johnes, 1993;Tauer et al. 2007;Kao and Hung, 2008;Colbert et al. 2000;Agha et al. 2011), it is limited in Turkey. Therefore, we aim at contributing the current literature by this way considering efficiency analysis of faculties of a Turkish university. ...
Data envelopment analysis (DEA) is a linear programming based data analytic
method for measuring the relative efficiency of organisational units where the presence
of multiple inputs and outputs makes comparisons difficult. Academic departments have
critical importance for a university so we agree to research and compare about academic
faculties in a leading university in Turkey. The aim of the study is to measure the
relative efficiency of the academic faculties and determine the efficient/inefficient ones
in the studied university. 12 faculties of the university are investigated within the scope
of this study. The input variables are considered as total number of academic staff, total
number of non-academic staff, number of students and the output variables are as
number of publications, number of projects and the percentage of budget used. While
results of CCR model show an average of 90.5% relative efficiency value, five faculties
are found 100% efficient according to the CCR model. According to BCC model, the
results have an average of 93.7% and 6 faculties are 100% efficient. In terms of the
potential improvements evaluated for each inefficient faculty, it is seen that faculty of
mechanical engineering and faculty of civil engineering are the ones requiring the most
improvement. This paper contributes to the literature a lot however it is a new and
proper study on efficiency analysis of faculties of a Turkish university. On conclusion
of the DEA efficiency scores, the existence of misallocation of resources or/and
inefficient applications to the faculties’ academic development are uncovered.
... A large number of these studies have been predominantly undertaken in developed countries (e.g. Tomkins & Green, 1988;Beasley, 1990;Johnes & Johnes, 1993;Kao, 1994;Sinuany-Stern, Mehrez, & Barboy, 1994;Beasley, 1995;Johnes & Johnes, 1995;Athanassapoulos & Shale, 1997;Madden & Savage, 1997;Sarrico, Hogan, Dyson, & Athanassopoulos, 1997;Haksever & Muragishi, 1998;Hanke & Leopoldseder, 1998;Post & Spronk, 1999;Colbert, Levary, & Shaner, 2000;Sarrico & Dyson, 2000;Korhonen, Tainio, & Wallenius, 2001;Abbott & Doucouliagos, 2003;Warning, 2004;Carrington, Coelli, & Rao, 2005;Emrouznejad & Thanassoulis, 2005;Joumady & Ris, 2005;Johnes, 2006a;Johnes, 2006b;McMillan, & Chan, 2006;Tauer, Fried, & Fry, 2007;Tajnikar & Debevec, 2008;Abbott & Doucouliagos, 2009;Johnes & Schwarzenberger, 2010;Kempkes & Pohl, 2010). Only a few efficiency studies on universities were related to developing countries. ...
This study is focused on conceptual paper and the purpose of this study is to conduct an empirical investigation into the Malaysian Preschool institutions, focusing on measuring their technical efficiency and productivity changes. This study is to examine the nature of productivity changes by means of bootstrapped Malmquist TFP indices. The study use a Three-year set of panel data (2009–2012) for analyzing the performance of 8307 KEMAS Preschools classes during the implementation of the (Government Transformation Program) GTP 1.0. The study considered all KEMAS Preschools classes operating in the sector. The input and output data were manually extracted from the Malaysia's Ministry of Rural and Regional Development (MRRD) and all KEMAS Preschools. Non-parametric DEA models are employed to estimate efficiency and productivity changes of the institutions. Thus, this study is expected makes significant contributions to the literature of efficiency and productivity changes in Early Childhood Care and education institutions.
... A large number of these studies have been predominantly undertaken in developed countries (e.g. Tomkins & Green, 1988;Beasley, 1990;Johnes & Johnes, 1993;Kao, 1994;Sinuany-Stern, Mehrez, & Barboy, 1994;Beasley, 1995;Johnes & Johnes, 1995;Athanassapoulos & Shale, 1997;Madden & Savage, 1997;Sarrico, Hogan, Dyson, & Athanassopoulos, 1997;Haksever & Muragishi, 1998;Hanke & Leopoldseder, 1998;Post & Spronk, 1999;Colbert, Levary, & Shaner, 2000;Sarrico & Dyson, 2000;Korhonen, Tainio, & Wallenius, 2001;Abbott & Doucouliagos, 2003;Warning, 2004;Carrington, Coelli, & Rao, 2005;Emrouznejad & Thanassoulis, 2005;Joumady & Ris, 2005;Johnes, 2006a;Johnes, 2006b;McMillan, & Chan, 2006;Tauer, Fried, & Fry, 2007;Tajnikar & Debevec, 2008;Abbott & Doucouliagos, 2009;Johnes & Schwarzenberger, 2010;Kempkes & Pohl, 2010). Only a few efficiency studies on universities were related to developing countries. ...
This study is focused on conceptual paper and the purpose of this study is to conduct an empirical investigation into the Malaysian Preschool institutions, focusing on measuring their technical efficiency and productivity changes. This study is to examine the nature of productivity changes by means of bootstrapped Malmquist TFP indices. The study use a Three-year set of panel data (2009–2012) for analyzing the performance of 8307 KEMAS Preschools classes during the implementation of the (Government Transformation Program) GTP 1.0. The study considered all KEMAS Preschools classes operating in the sector. The input and output data were manually extracted from the Malaysia’s Ministry of Rural and Regional Development (MRRD) and all KEMAS Preschools. Non-parametric DEA models are employed to estimate efficiency and productivity changes of the institutions. Thus, this study is expected makes significant contributions to the literature of efficiency and productivity changes in Early Childhood Care and education institutions.
... Data envelopment analysis applies linear programming to maximise each entity's efficiency with reference to a nonparametric efficient frontier over the available input and output factors. Following Bessent and Bessent (1980), and as noted by Johnes et al. (2005), Johnes (2006) and Liu et al. (2013a and, this methodology has been widely applied in higher education, including in the United States (Bougnol andDulá, 2006 andTauer et al., 2007), Australia (Hanke and Leopoldseder, 1998, Avkiran, 2001, Abbott and Doucouliagos, 2003, Carrington et al., 2005and Worthington and Lee, 2008 and ...
In this thesis, an analytical framework is developed for the assessment of the financial condition of South African public universities.
Foundational constructs of nonprofit economics are applied in the consideration of financial theories of nonprofit organisations in general, and public universities in particular. From this review, a number of hypotheses are developed. Each of these specifies a positive or negative association between a university's financial condition and a particular dimension of its assets, liabilities, equity, revenues, expenses and surplus. From the nonprofit financial analysis literature, ratios and indicators relevant to these hypotheses are selected. Audited data from the annual financial statements of the universities for the seven year period 2007 to 2013 are substantially transformed in mitigation of failures in accounting, auditing and accountability. The adjusted accounting numbers are used to calculate the financial indicators applicable to each university. Exploratory factor analysis is implemented to categorise and organise this large indicator set on the basis of identified associations with a smaller number of factors.
It is found that the financial condition of South African public universities is defined by two broad financial characteristics, capital and revenue. Assessment of the capital dimension is informed by a focus on institutional equity, with particular emphasis on expendable equity and its proportionate relationships with surplus, total capital, and total expenses. The revenue dimension is appropriately evaluated in the context of a comparative and interactive consideration of the three main components of South African public university revenue, as well as the proportionate relationship between non-staff operating expenses and total expenses. The framework displays considerable levels of stability and consistency over the seven year review period, and its constructs are, in addition, robust to the application of multiple alternative confirmatory tests involving financial data that are independent of the factor solutions.
The financial condition assessment framework developed in this thesis offers a contribution to a broader discourse in nonprofit finance and accounting, with a focus on public university finances.
Key words: nonprofit financial analysis, South African public universities
