Research on the Scientific Research Efficiency of Provincial Universities Based on the DEA Model

Wang, Lifeng; Tan, Wenjun

doi:10.1155/2021/7929084

Cited by 6 publications

(13 citation statements)

References 11 publications

(9 reference statements)

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“…When the literature is examined, it is seen that different inputs are used in the measurement of research efficiency. The number of academicians is generally used as human resource input (Canal et al, 2015;Cherchye and Abeele, 2005;Jimenez-Saez et al, 2011;Li et al, 2023;Munoz, 2016;Shi et al, 2022;Su et al, 2020;Wang and Wang, 2021). However, it is also seen that the number of R&D personnel (Jiang et al, 2020) and doctoral students (Cherchye and Abeele, 2005) are also used.…”

Section: Inputs and Outputsmentioning

confidence: 99%

“…One of the most frequently used inputs in measuring research efficiency is financial resources. Tuition fees (Munoz, 2016), research funds (Amara et al, 2020;Jimenez-Saez et al, 2011), science and technology funding expenditures (Wang and Wang, 2021), administrative expenses (Canal et al, 2015), investment costs (Jiang et al, 2020), scientific research funds (Liao et al, 2016), total research funding (Rhaiem and Amara, 2020) and annual budget (Li et al, 2023) were used as financial resource inputs. Although academic staff and financial resources are frequently used in the evaluation of research efficiency, various inputs other than these two inputs are also used.…”

Section: Inputs and Outputsmentioning

confidence: 99%

“…These differences in inputs also apply to outputs in research efficiency measurement: number of publications (Amara et al, 2020;Canal et al, 2015;Cherchye and Abeele, 2005;Jiang et al, 2020;Jimenez-Saez et al, 2011;Ma et al, 2021;Munoz, 2016;Su et al, 2020;Wang and Wang, 2021), research grants (Ma et al, 2021;Munoz, 2016), R&D contracts (Jimenez-Saez et al, 2011), technology transfer income (Wang and Wang, 2021), number of science awards (Jiang et al, 2020), number of research awards (Liao et al, 2016), number of citations (Amara et al, 2020;Rhaiem and Amara, 2020), number of citations per article (Li et al, 2023;Su et al, 2020), impact factor of articles (Liao et al, 2016) and number of highly cited papers (Li et al, 2023). As can be seen, there is no standard output criterion in the studies.…”

Section: Inputs and Outputsmentioning

confidence: 99%

“…When the literature is examined, it is seen that research efficiency is measured for different units and with different methods. Research programs (Cherchye and Abeele, 2005), researchers (Amara et al, 2020), higher education institutions (Dimyati and Hermanu, 2022;Jiang et al, 2020;Munoz, 2016), universities (Canal et al, 2015;Li et al, 2023;Shi et al, 2022;Wang and Wang, 2021), R&D programs (Jimenez-Saez et al, 2011), academic disciplines (Su et al, 2020), a specific field (Zhang et al, 2022), institute (Amara et al, 2020;Liao et al, 2016) IJEM 37,6/7 1162…”

Section: Introductionmentioning

confidence: 99%

“…, 2023; Shi et al. , 2022; Wang and Wang, 2021), R&D programs (Jimenez-Saez et al. , 2011), academic disciplines (Su et al.…”

Section: Introductionmentioning

confidence: 99%

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Examination of research efficiency of research universities in Türkiye by data envelopment analysis

Maral

2023

IJEM

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PurposeThe purpose of this study is to examine the research efficiency of the research universities in Türkiye and to identify potential areas for improvement and to examine the factors affecting efficiency.Design/methodology/approachFor this purpose, data envelopment analysis was conducted with the output-oriented Banker, Charnes and Cooper (BCC) model with five-year article and citation counts data of 23 universities which were obtained from the Web of Science Core Collection.FindingsThe findings of the study show that only eight research universities are efficient. There are areas of development for universities to be effective. In addition, the findings of the regression analysis conducted to reveal the determinants of efficiency revealed significant results.Research limitations/implicationsResearch universities in Türkiye should allocate their resources in a way to increase research performance. Policies should be developed to increase the number of publications and, more importantly, the quality of publications.Originality/valuePotential areas for improvement were identified for the universities to become efficient. The results revealed that both publication quality and productivity need to be improved, but there is more room for improvement in publication quality. Regression analysis with the determinants of efficiency scores shows that the development level of the region where the universities are located has a positive effect on the research efficiency of universities. In addition, it is concluded that smaller universities have better efficiency scores.

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Section: Inputs and Outputsmentioning

confidence: 99%

Section: Inputs and Outputsmentioning

confidence: 99%

Section: Inputs and Outputsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…, 2023; Shi et al. , 2022; Wang and Wang, 2021), R&D programs (Jimenez-Saez et al. , 2011), academic disciplines (Su et al.…”

Section: Introductionmentioning

confidence: 99%

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Examination of research efficiency of research universities in Türkiye by data envelopment analysis

Maral

2023

IJEM

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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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Topic based quality indexes assessment through sentiment

Frigau

Contu

2022

Comput Stat

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This paper proposes a new methodology called TOpic modeling Based Index Assessment through Sentiment (TOBIAS). This method aims at modeling the effects of the topics, moods, and sentiments of the comments describing a phenomenon upon its overall rating. TOBIAS is built combining different techniques and methodologies. Firstly, Sentiment Analysis identifies sentiments, emotions, and moods, and Topic Modeling finds the main relevant topics inside comments. Then, Partial Least Square Path Modeling estimates how they affect an overall rating that summarizes the performance of the analyzed phenomenon. We carried out TOBIAS on a real case study on the university courses’ quality evaluated by the University of Cagliari (Italy) students. We found TOBIAS able to provide interpretable results on the impact of discussed topics by students with their expressed sentiments, emotions, and moods and with the overall rating.

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Research on the Scientific Research Efficiency of Provincial Universities Based on the DEA Model

Cited by 6 publications

References 11 publications

Examination of research efficiency of research universities in Türkiye by data envelopment analysis

Examination of research efficiency of research universities in Türkiye by data envelopment analysis

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

Topic based quality indexes assessment through sentiment

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