Efficiency analysis of non-homogeneous parallel sub-unit systems for the performance measurement of higher education

Singh, Sanjeet; Ranjan, Prabhat

doi:10.1007/s10479-017-2586-0

Cited by 15 publications

(5 citation statements)

References 74 publications

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“…The results suggested that the employability issue was the main reason constraining the growth of institutional efficiency. Singh and Ranjan (2017) proposed a single stage DEA approach, which can measure the efficiency of DMUs and their parallel sub-units simultaneously.…”

Section: Previous Studies On Higher Education Efficiencymentioning

confidence: 99%

Measuring Scientific Productivity in China Using Malmquist Productivity Index

Song

Schubert

Liu

et al. 2019

Journal of Data and Information Science

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Purpose: This paper aims to investigate the scientific productivity of China's science system.Design/methodology/approach: This paper employs the Malmquist productivity index (MPI) based on Data Envelopment Analysis (DEA). Findings:The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities. Research limitations:As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research. Practical implications:The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities.Originality/value: This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009-2016. Three main functional activities of universities (i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively.

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Section: Previous Studies On Higher Education Efficiencymentioning

confidence: 99%

Measuring Scientific Productivity in China Using Malmquist Productivity Index

Song

Schubert

Liu

et al. 2019

Journal of Data and Information Science

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“…Thus, when there is no common efficient DMU between the two stages, none of the generic systems become efficient. Although rare, such results can be found in the DEA literature (Gong et al, 2018 ; Singh & Ranjan, 2018 ).…”

Section: Theoretical Backgoundmentioning

confidence: 99%

“…As a result, there is no DMU that is overall efficient. Though such kinds of instances are not very common (Moreno & Lozano, 2014 ), they can be found in the DEA literature (Gong et al, 2018 ; Singh & Ranjan, 2018 ). Each of the stages has its own PPS.…”

Section: Theoretical Backgoundmentioning

confidence: 99%

Examining operational efficiency with prudent risks of Covid-19: a contextual DEA analysis with an undesirable intermediate measure

2023

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In the wake of the losses of human lives and disruption to the world economy caused by the spread of the COVID-19 pandemic, it has become imperative to assess the effectiveness of containment strategies adopted by countries. The success of any containment strategy of achieving low mortality and high recovery rate depends on the efficient utilization of available but limited resources, such as number of hospital beds and healthcare workers. While the spreading pattern of the pandemic has been researched heavily, there is limited research that comprehensively focuses on the efficient utilization of available resources to achieve the desired aims of low mortality and high recovery. In order to close this research gap, we employ a two-stage network data envelopment analysis (DEA) to identify the inefficiency in the process and resolve the resource constraints by considering medical and non-medical (administrative) interventions as two serial stages. The number of infected people is treated as the intermediate product, which is an undesirable output of the first stage and subsequently enters the second stage as an input. This network DEA model successfully addresses the conflict between the two stages over the handling of infected people and assesses the vulnerabilities of the countries against the transmission rates of the disease in the respective countries. Thus, the objective of this study is to develop a well-coordinated plan for different government agencies to jointly mitigate the risk under constrained resources. The findings reveal that almost of the Organization for Economic Cooperation and Development (OECD) countries have used their resources suboptimally and are producing, on average, almost half the amount of the maximum possible outputs. As a sizeable amount of inefficiency can be explained by varying economic and demographic factors, such as health expenditure and the proportion of the aged population, the efficiency evaluation has been revisited with adjustments for unfavorable externalities. The analysis and its implications can help policymakers formulate optimal resource plans and identify potential areas for improvement.

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“…Over the past 39 years, DEA has been applied to a variety of application areas that include banks, hospitals, sports, manufacturing, finance, education, airlines, social welfare, crews, insurance, supply chain, etc. see [3][4][5][6][7][8]. As an extension to the classical CCR [1] and BCC models [9], researchers have proposed various models [3,10] to handle diverse nature of practical problems.…”

Section: Introductionmentioning

confidence: 99%

Intuitionistic fuzzy DEA/AR and its application to flexible manufacturing systems

Singh

2018

RAIRO-Oper. Res.

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The concept of assurance region (AR) was proposed in Data Envelopment Analysis (DEA) literature to restrict the ratio of any two weights within a given lower and upper bounds so as to overcome the difficulty of ignoring or relying too much on any of the input or output while calculating the efficiency. Further, AR approach was extended to handle fuzzy input/output data. But, available information is not always sufficient to define the impreciseness in the input/output data using classical fuzzy sets. Intuitionistic Fuzzy Set (IFS) is a generalized fuzzy set to characterize the impreciseness by taking into account degree of hesitation also. In this paper, intuitionistic fuzzy DEA/AR approach has been proposed to evaluate the efficiency where input/output data are represented as intuitionistic fuzzy. Based on the expected value approach, classical cross efficiency has also been generalized to rank the DMUs for the case of intuitionistic fuzzy data. To the best of my knowledge, this is the first attempt to propose assurance region approach (DEA/AR) in DEA with intuitionistic fuzzy input/output data. This approach is useful for the experts and decision makers when they are hesitant about defining the degree of membership/non-membership of fuzzy data. Results have been illustrated and validated using a case of flexible manufacturing systems (FMS).

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Efficiency analysis of non-homogeneous parallel sub-unit systems for the performance measurement of higher education

Cited by 15 publications

References 74 publications

Measuring Scientific Productivity in China Using Malmquist Productivity Index

Measuring Scientific Productivity in China Using Malmquist Productivity Index

Examining operational efficiency with prudent risks of Covid-19: a contextual DEA analysis with an undesirable intermediate measure

Intuitionistic fuzzy DEA/AR and its application to flexible manufacturing systems

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