A Review on the 40 Years of Existence of Data Envelopment Analysis Models: Historic Development and Current Trends

Panwar, Ankita; Olfati, Maryam; Pant, Millie; Snåšel, Václav

doi:10.1007/s11831-022-09770-3

Cited by 52 publications

(31 citation statements)

References 239 publications

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“…However, there are some limitations and challenges in applying DEA models in this context. For instance, a study by Panwar et al (2022) pointed out that the DEA model that we used this study may not fully capture the complex and multidimensional nature of educational institutions, and there is a need for more advanced methods to measure their efficiency.…”

Section: Discussionmentioning

confidence: 99%

Data Envelopment Analysis for the Efficiency of Higher Education Departments at Sepuluh Nopember Institute of Technology, Indonesia

Wildani¹,

Wibowo²,

Pingit³

et al. 2023

EUROPEAN J ED RES

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<p style="text-align: justify;">The quality of higher education is vital for a country’s future, not only in terms of transferring knowledge to younger generation but also for supporting economic development. This paper applies data envelopment analysis (DEA) to evaluate the relative efficiency of 38 academic departments at Sepuluh Nopember Institute of Technology, Surabaya, Indonesia. The input factors are the number of lecturers, the number of staff and budget allocations, whereas the output is the performance achievement level. The empirical analysis incorporates two traditional DEA models: the Charnes, Cooper and Rhodes (CCR) and the Banker, Charnes and Cooper (BCC) models with input orientation. The results indicate that the CCR model considers five departments efficient while the BCC model considers ten departments efficient, five of which are those considered efficient by the CCR model. It may seem counterintuitive that a department with an output performance achievement below 100% is deemed efficient, and vice versa. However, the underlying principle of efficiency under input-oriented DEA model is resource utilization. Finally, we provide recommendations for the departments with low efficiency scores to improve their performance.</p>

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Section: Discussionmentioning

confidence: 99%

Data Envelopment Analysis for the Efficiency of Higher Education Departments at Sepuluh Nopember Institute of Technology, Indonesia

Wildani¹,

Wibowo²,

Pingit³

et al. 2023

EUROPEAN J ED RES

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“…DEA research is relatively mature, since its inception is widely used in the calculation of financing efficiency. Ali and Lerme, Panwar et al argue that DEA has the following advantages: firstly, DEA is particularly suitable for problems with multiple inputs and multiple outputs; secondly, DEA is a non-statistical and non-parametric method that neither requires a specific functional form nor makes assumptions about the random characteristics of the data; thirdly, there is no requirement for weights, and only the actual input and output data of the decision unit are used to find the optimal weights, which has a strong objectivity [ 19 , 20 ].…”

Section: Methodsmentioning

confidence: 99%

Construction enterprises’ green financing efficiency and its influencing factors including internal and external: Based on four-stage DEA model

Shen

Yan

et al. 2023

PLoS ONE

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Under the background of carbon neutrality, green development is the theme of today’s times. The construction industry is an important part of the green development plan, and it is of great significance to study its green financing efficiency. Based on this, this paper uses the four-stage DEA model to explore the green financing efficiency of listed construction companies from 2019 to 2020. The conclusion shows that: firstly, the green financing efficiency of listed construction companies is low, and the demand for green financing has not been met. It is necessary to strengthen the support of green finance to meet the needs of its expansion. Secondly, the efficiency of green financing is significantly and complexly affected by external influencing factors. It is necessary to dialectically treat external influencing factors such as local industry development support, financial development level, and the number of patent authorizations. Thirdly, among the internal influencing factors, the proportion of independent directors has a significant positive impact on the green financing efficiency of listed construction companies, and the proportion of R&D investment has a significant negative impact. Listed construction companies need to increase the proportion of independent directors and control the proportion of R&D investment.

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“…As a result, researchers use set of variables that varies dramatically and surrogate measures to approximate these influential factors (Mitropoulos, 2021;Ozcan & Khushalani, 2017;Timofeyev et al, 2023). These introduces subjectivity and potential for biases and uncertainty in the analysis, leading to divergent results and varying opinions interpretations of a study results (Panwar et al, 2022;Ratner et al, 2023). 2021) presented findings from 16 countries using DEA, focusing on a 5-week period after identifying the first 100 COVID-19 cases in each country.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Examining previous studies on healthcare efficiency using DEA reveals several gaps in the scientific literature. The primary challenge lies in modeling complex systems like healthcare, leading to differences in assessed models and study outcomes (Panwar et al, 2022;Ratner et al, 2023). This discrepancy often stems from the varied choice of indicators representing inputs, intermediates, and outputs of the healthcare system (Ratner et al, 2023;Zakowska & Godycki-Cwirko, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Analyzing prior literature on healthcare efficiency revealed several research gaps, mainly arising from the complexity of modeling healthcare systems (Panwar et al, 2022;Ratner et al, 2023) and variations in chosen indicators (Ratner et al, 2023;Zakowska & Godycki-Cwirko, 2019). The focus on high-and upper-middle-income countries limits insights into factors that affect efficiency in low and low-middle income countries (Mbau et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Healthcare System Efficiency and Its Drivers in Pre- And Covid-19 Pandemic Settings

Vishniakov,

Kasiev,

Abdrasulova

2023

Business, Management and Economics Engineering

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Purpose – The aim of the study is to assess healthcare system efficiency in both regular circumstances and during the COVID-19 pandemic, with a focus on key factors influencing efficiency, and offer health authorities insights into healthcare system resilience. Research methodology – The analysis was conducted in two stages. The initial stage involved the application of Data Envelopment Analysis output-oriented model with a constant-returnto-scale framework. The second stage employed Tobit regression method to identify factors that influenced countries’ efficiency. Findings – We identified the healthcare system efficiency of 14 CIS and EU countries in Pre and pandemic settings and provided a methodology for results interpretation accounting for the complexity of healthcare systems and temporal variations in pandemic trends. The Tobit regression highlighted the role of the health workforce, emphasizing the caution for the reduction of physicians in the system. Research limitations – The research focused on efficiency in just two regions of Eurasia and only considered medical factors as the primary drivers of efficiency. Additionally, the examination covered the initial year of the pandemic, reflecting only the earlier stages of countries’ performance during the pandemic. Practical implications – This study contributes to the assessment of healthcare resilience on a global scale and provides information for policymakers, aiding in the selection of optimal practices during the pandemic and enhancing preparedness for future crises. Originality/Value – Countries’ efficiency assessment in four models and two settings provides valuable insight into the healthcare systems’ resilience.

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A Review on the 40 Years of Existence of Data Envelopment Analysis Models: Historic Development and Current Trends

Cited by 52 publications

References 239 publications

Data Envelopment Analysis for the Efficiency of Higher Education Departments at Sepuluh Nopember Institute of Technology, Indonesia

Data Envelopment Analysis for the Efficiency of Higher Education Departments at Sepuluh Nopember Institute of Technology, Indonesia

Construction enterprises’ green financing efficiency and its influencing factors including internal and external: Based on four-stage DEA model

Healthcare System Efficiency and Its Drivers in Pre- And Covid-19 Pandemic Settings

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