Value efficiency analysis of academic research

Korhonen, Pekka; Tainio, Risto; Wallenius, Jyrki

doi:10.1016/s0377-2217(00)00050-3

Cited by 169 publications

(113 citation statements)

References 16 publications

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“…Mean technical efficiencies computed from department level studies vary as follows: 50 to 60% for UK economics departments (Johnes & Johnes 1992;; around 70% in UK departments of chemistry and physics (Beasley 1990); 65 to 82% in Australian departments of economics (Madden et al 1997); 72% in economics research units in Finland (Korhonen et al 2001); and 82 to 87% in the administration sector of Australian universities (Coelli et al 1998). Evidence from HEI level studies suggests that mean technical efficiency varies from around 70 to 80% (Ahn & Seiford 1993;Ng & Li 2000) to well over 90% (Ahn et al 1989;Breu & Raab 1994 with nearly 90% achieving an efficiency score of 1, compared to around 66% of the engineering universities.…”

Section: Methodsmentioning

confidence: 99%

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Johnes

2008

China Economic Review

234

110

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This study uses data envelopment analysis (DEA) to examine the relative efficiency of over 100 selected Chinese regular universities. Various models are developed to measure the research efficiency of these higher education institutions (HEIs) using data for 2003 and 2004. The findings show that the level of efficiency depends on whether or not a subjective measure of research output (based on experts' opinions of the HEIs) is included as an output in the model. Mean efficiency is higher when the reputation variable is included (around 90%) than when it is not (mean efficiency is around 55% in this case). However, the rankings of the universities are remarkably insensitive to whether or not this variable is included. Bootstrapping procedures are used to find the 95% confidence intervals for the efficiencies, and indicate that the best and worst performing institutions are significantly different from each other; only the middle-performing 30% of HEIs cannot be distinguished from each other in terms of their performance. Further investigation suggests that regional location, source of funding and whether the university is comprehensive or specialist may all contribute to the observed differences in performance. The regional differences are consistent but not significant at conventional levels of significance; the efficiencies differ significantly by administrative type when the subjective measure of research output is excluded from the analysis; comprehensive universities consistently and significantly outperform specialist institutions. The possibility of regional differences in performance is particularly worrying since the already economically disadvantaged Western region may suffer a continued lag in development if its HEIs are less efficient than those in the better developed Central and coastal regions. JEL classification:I21, I23, C14

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Section: Methodsmentioning

confidence: 99%

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Johnes

2008

China Economic Review

234

110

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“…On this point, it is found that most of the studies have been conducted in the framework of public research centres, [30][31][32], but few in companies. In the study of [33], the result of the performance of the BSC is evaluated by calculating different ratios of efficiency by means of DEA, but in no case have previous authors validated the content of the BSC employed, nor have they orientated it to university activities.…”

Section: Measuring and Relating Efficiency To The Balanced Scorecardmentioning

confidence: 99%

Balanced Scorecard and Efficiency: Design and Empirical Validation of a Strategic Map in the University by Means of DEA

Valderrama¹,

Cornejo²,

Bordoy³

2013

AJOR

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The principal objective of the research reported in this article is to validate a Balanced Scorecard (BSC) model and a Strategic Map for the University by studying the relationships of efficiency between its dimensions. Subsequently, the validation is completed by establishing hypotheses of efficiency relationships between the perspectives proposed, employing Data Envelopment Analysis (DEA). Empirical evidence has been obtained on the validity of the proposed BSC for a unit of academic management in the university. The first contribution of this work is the establishment of a framework of analysis of the hypothetical cause-effect relationships in the BSC in university institutions. The second contribution is to obtain the determining factors of the performance in this type of institution and, therefore, the Strategic Map. Specifically, these factors are: the participation of teaching staff in innovation activities; the number of doctorate-level staff; the academic subjects and credits in the Virtual Campus; and the scores in the surveys of student satisfaction. With respect to research, the determining factors of the performance are: the research sexennials; the funding obtained from contracts with companies; the number of research projects obtained; their financing; and the participation of teachers in these projects.

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“…A comprehensive list of DEA applications to educational organizations is available in the International Handbook on the Economics of Education ( Johnes, 2004 ) , and an examination of DEA applications to schools at all levels can be found in the Handbook of Data Envelopment Analysis ( Cooper et al , 2004 ). A few examples of its use to evaluate institutions of higher education include ( Beasley, 1990( Beasley, , 1995( Beasley, , 2003Breu and Raab, 1994 ;Athanassopoulos and Shale, 1997 ;Avkiran, 2001 ;Korhonen et al , 2001 ;Abbott and Doucouliagos, ജ 2003 ;Casu and Thanassoulis, 2006 ;Glass et al , 2006 ;Worthington and Lee, 2008 ) .…”

Section: > 0 For Allmentioning

confidence: 99%

HBCU efficiency and endowments: An exploratory analysis

Coupet

Barnum

2010

Int J Educ Adv

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Discussions of effi ciency among Historically Black Colleges andUniversities (HBCUs) are often missing in academic conversations. This article seeks to assess effi ciency of individual HBCUs using Data Envelopment Analysis (DEA), a non-parametric technique that can synthesize multiple inputs and outputs to determine a single effi ciency score for each institution. The authors hypothesized that institutions with higher endowments will have higher effi ciency scores due to an increased ability to acquire more productive capital. To test this hypothesis, effi ciency scores were regressed on endowments and HBCU status, with control variables denoting if institutions are public or religiously affi liated. From DEA, we found that HBCUs were on average slightly more effi cient that Predominantly White Institutions. Endowment levels were found to be signifi cant determinants of effi ciency for both sets of institutions. This suggests (1) that the general perception of HBCUs as ineffi cient requires reconsideration and (2) that schools with the most endowment resources are generally more effi cient. Less effi cient HBCUs should perhaps devote resources to building endowment levels to increase effi ciency. We can also see the importance of methodologies allowing for investigation of both differences among HBCUs and differences in operational contexts among HBCUs and other schools.

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Value efficiency analysis of academic research

Cited by 169 publications

References 16 publications

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Balanced Scorecard and Efficiency: Design and Empirical Validation of a Strategic Map in the University by Means of DEA

HBCU efficiency and endowments: An exploratory analysis

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