Application Of Data Envelopment Analysis Research Articles

Efficiency decomposition in three-stage data envelopment analysis with undesirable and returnable factors

Purpose The purpose of this paper is to evaluate the efficiency of a series network system with undesirable and unreturnable simultaneously. Design/methodology/approach The research was conducted by applying data envelopment analysis (DEA) approach to measure the efficiency score of a system and substages with an undesirable output of the second and third stages separately. For each case, new production technology was introduced, and based on them, novel DEA models were proposed. Findings One of the most important issues in the development of a country is the banking industry. In this study, 51 branches of commercial banks as a three-stage system with undesirable and unreturnable outputs in the second stage are considered. Then, the efficiency of each branch and substages is measured by using proposed models. Originality/value The efficiency of a three-stage network in the presence of undesirable and unreturnable outputs was assessed. In this model, Kousmanen’s technology was used.

Relationship between recycling, circular economy and eco‐innovation in Europe. Application of a dynamic network data envelopment analysis model

AbstractMonitoring of European‐level circular economy (CE) efficiency requires more research than does currently exists in the body of literature on CE. In this regard, this research aims to answer two research questions. Firstly, to be efficient in the implementation of CE at a macroeconomic level, should there be a relationship between the efficiency of the three phases of CE (efficiency in recycling, efficiency in the implementation of CE and efficiency of eco‐innovation)? To answer this question, we use decoupling theory. Secondly, are the three phases of CE related from the point of view of dynamic efficiency? To answer this question, we use dynamic efficiency theory.In accordance with both of these theories, we establish a circular relationship between recycling, CE and eco‐innovation. We test this circular relationship through the application of the dynamic network data envelopment analysis (DNDEA) model of Tone and Tsutsui. The analysis is based on Eurostat data for the period of 2016 to 2022 for 27 European countries.This work contributes to the advancement of the research via (1) the development of a model for measuring the transversal and longitudinal efficiency of the CE and (2) the findings of positive and significant relationships between the efficiency ratios of the three fundamental phases (recycling, CE and eco‐innovation). This leads us to affirm that the countries studied that have managed to be efficient in recycling have also been in the implementation phase of CE and eco‐innovation.

How do environmental, social and governance initiatives and controversies explain the firm efficiency of Chinese energy companies?

PurposeThis study investigates how the initiatives and controversies related to environmental, social and governance (ESG) explain firm efficiency.Design/methodology/approachFirstly, this study applies data envelopment analysis with the epsilon-based measure to estimate the firm efficiency of 80 companies in the Chinese energy sector in 2022. This approach accounts for the diversity and relative importance of inputs and outputs from a multidimensional perspective. Secondly, this study regresses the variables of ESG initiatives and controversies on the estimated firm efficiency scores through a generalised additive model, which can capture nonlinear patterns.FindingsThis study finds that a) the samples have i) about 49% room for improvement in efficiently optimising their resources and business outcomes and ii) the highest scores in governance initiatives, followed by social initiative. b) 69% of them have controversy scores that are greater than the average value. c) A cluster analysis indicates that companies with higher social initiatives have higher firm efficiency than their counterparts. d) ESG initiatives and controversies are nonlinearly related to firm efficiency.Research limitations/implicationsThe findings have practical implications for policy makers and managers who prioritise ESG, particularly regarding (i) the need to examine firm performance from a multidimensional perspective, that is, to measure multiple inputs and outputs simultaneously, (ii) the nonlinearity of the nexus between ESG and efficiency in graphical forms, and (iii) the need to balance ESG initiatives and address ESG controversies.Originality/valueThis study integrates statistical approaches in examining and ensuring sustainable growth and efficiency within the Chinese energy sector and beyond.

Temporal-spatial analysis of urban education and research efficiency: A case of Yangtze River Delta urban agglomeration, China

Evaluating the efficiency of education and research plays an important role in optimizing resource allocation and promoting sustainable development of science and education. The Yangtze River Delta Urban Agglomeration (YRDUA) is one of the most developed regions in China in terms of economy, science and education, and culture. Quantifying and analyzing its education and research efficiency is of great significance for the development of this urban agglomeration. Therefore, this study applied Data Envelopment Analysis (DEA) to evaluate the education and research efficiency of YRDUA from 2000 to 2021, and applied GIS visualization methods to analyze its spatiotemporal distribution characteristics. The research results indicate that due to the steady implementation of the Yangtze River Delta regional integration strategy, the overall scientific and educational efficiency of the Yangtze River Delta is showing a continuous upward trend. At the same time, the efficiency gap between different cities in the region is showing a narrowing trend,

Efficiency and Performance of Top Indian Pharmaceutical Firms: A Comparative Analysis

The Indian pharmaceutical industry has made significant strides in the past five decades and is an important contributor to the provision of quality healthcare services in any economy. This paper studies the efficiency of selected top ten pharmaceutical companies by applying Data Envelopment Analysis (DEA) under constant return to scale (CRS) model and variable returns t ale (VRS) model. The inputs used in the study are assets, salaries, and wages. The outputs used are Return on Asset, and Net Profits. The study found Divis Laboratories and Sun Pharma to be most efficient under CRS and Sun Pharma was found to be most efficient under VRS models during 2019 – 2023. Seven pharmaceutical companies were working under Increasing returns to scale, two were working under constant returns to scale and one was performing under decreasing returns to scale. Return on assets, Net Profit margin and Return on Capital Employed Ratio were used to study financial performance of the pharmaceutical companies. Abbot India had the highest return on assets (17.948%). Divis Labs had the highest Net Profit Margin (27.76%). Mankind Pharma led in Return on Capital Employed (27.524%), This result further adds to the result provided by DEA. Companies found to be efficient by DEA were found to have high performance standards. Also, through the regression analysis the impact of variables Return on Capital Employed (ROCE) and Net profits margin (NPM) on Return on Asset (ROA) was studied. Returns on Assets (ROA) are 93.6% dependent on Net profits margin and Return on Capital Employed. There is significant (p-value = 0.000) relationship between Return on Asset (ROA), Net profits margin (NPM) and Return on Capital Employed (ROCE).

Technical Efficiency Evaluation of Maize Production in Ghana: An Application of Three-Stage Data Envelopment Analysis

Purpose: In Ghana, maize constitutes the primary source of revenue and food for small-scale farmers, and to attain maize self-sufficiency, appropriate production techniques must be employed, coupled with the scaling up of production efficiency to supplement our food output. The objectives of the study are to estimate the technical efficiency and analyze the trend in total factor productivity of maize production. Method: This study focuses on forty-eight (48) cities in six (6) selected regions of Ghana: Northern, Upper East, Upper West, Central, Eastern, and Volta. Secondary data on maize production was obtained from the Ministry of Food and Agriculture from the 2010/11 to 2020/21 cropping seasons. Environmental variables (amount of rainfall and temperature) were sourced from the Ghana Meteorological Agency (GMA) from 2010/11 to 2020/21. Results and Conclusion: The results displayed a fairly high level of TE, and environmental factors significantly influence production efficiency. The study revealed that the TE of maize cultivation was 0.752 and 0.853 for the first and third stages, respectively. From the findings, the efficiency scores attained after the adjustments to the input in the third stage of the DEA model were greater than those in the first stage. Also, the results indicated the eastern region had the highest TE scores, showed an increment in productivity, and serves as the finest region for maize cultivation. Overall, the technical performance of maize cultivation had shown an upward trend in productivity, and the eastern region recorded the highest efficiency performance and technological progress. Implications of the Research: The research highlights the significance of the maize crop to the Ghanaian economy and how environmental factors impact farmers' production efficiency. It also emphasizes the benefits of resource use efficiency and its implied effects on the total factor productivity of maize cultivation. Policy suggestions include sustainable production practices primarily for farmers living in susceptible areas to enhance productivity and improve their food security status. Originality/Value: The gap discovered in the examined literature was that there exists a substantial deficiency in the usage of the three-stage DEA Malmquist model for analyzing technical efficiency and limited studies on the estimation of the total factor productivity (TFP) changes, specifically focusing on maize farming. This paper adds to the body of the existing literature by utilizing a three-stage DEA model to evaluate the TE of maize production. This is entirely limited both in theory for annual crops and methodologically in the Ghanaian literature on efficiency studies.

Evaluating sustainable efficiency: A study on transportation systems in South America using data envelopment analysis

The transport sector is pivotal in fostering economic growth and environmental sustainability. Extensive research has scrutinized various transportation modes individually, yet a holistic assessment encompassing all modes while considering CO2 emissions needs to be more conspicuously present. Our study employs Data Envelopment Analysis (DEA) to evaluate the efficacy of transportation policies in South American nations in the context of United Nations-established sustainable development goals. Our overarching objective is to classify the sustainability status of South American countries' transport sectors and to establish benchmark models rooted in the six dimensions of sustainability. Methodologically, our analysis integrates operational transportation metrics, Gross Domestic Product per capita, Human Development Index, and CO2 emissions from transportation systems. Additionally, we draw comparative insights by juxtaposing South American countries against the G8 and BRICS nations. The rigorous application of DEA coupled with bootstrap validation fortifies the reliability of our findings. Our results bring to light these findings, positioning South American countries closer to their developed counterparts. Notably, the sustainable development models of Chile and Uruguay emerge as prominent exemplars. This study underscores the pressing demand for holistic and integrated development strategies to attain more sustainable outcomes across South American nations in a faster way. In conclusion, our research fills a conspicuous void in the extant literature by furnishing a comprehensive evaluation of transportation policy performance in South America. Based on a robust methodology, this empirical evidence offers valuable insights for policymakers striving to advance sustainable regional development.

Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984-2022.

This study reviews scholarly publications on data envelopment analysis (DEA) studies on acute care hospital (ACH) efficiency published between 1984 and 2022 in scholarly peer-reviewed journals.We employ systematic literature review (SLR) method to identify and analyze pertinent past research using predetermined steps. The SLR offers a comprehensive resource that meticulously analyzes DEA methodology for practitioners and researchers focusing on ACH efficiency measurement. The articles reviewed in the SLR are analyzed and synthesized based on the nature of the DEA modelling process and the key findings from the DEA models. The key findings from the DEA models are presented under the following sections: effects of different ownership structures; impacts of specific healthcare reforms or other policy interventions; international and multi-state comparisons; effects of changes in competitive environment; impacts of new technology implementations; effects of hospital location; impacts of quality management interventions; impact of COVID-19 on hospital performance; impact of teaching status, and impact of merger. Furthermore, the nature of DEA modelling process focuses on use of sensitivity analysis; choice of inputs and outputs; comparison with Stochastic Frontier Analysis; use of congestion analysis; use of bootstrapping; imposition of weight restrictions; use of DEA window analysis; and exogenous factors. The findings demonstrate that, despite several innovative DEA extensions and hospital applications, over half of the research used the conventional DEA models. The findings also show that the most often used inputs in the DEA models were labor-oriented inputs and hospital beds, whereas the most frequently used outputs were outpatient visits, followed by surgeries, admissions, and inpatient days. Further research on the impact of healthcare reforms and health information technology (HIT) on hospital performance is required, given the number of reforms being implemented in many countries and the role HIT plays in enhancing care quality and lowering costs. We conclude by offering several new research directions for future studies.

The efficiency analysis of media companies: An application of DEA and Malmquist indices

As the global entertainment and media market is expected to multiply, media companies, such as streaming services, television networks, and broadcasting companies, play critical roles in providing TV and movie content, the industry's fuel. Almost all players of small and large sizes in the industry spend enormous resources on content and expand their investment to retain global and regional content to win the battle of viewership. However, the efficiency of investments varies for media companies. Measuring efficiency has been crucial as all firms strive to achieve better productivity. In particular, estimating the efficiencies and productivities of firms producing and offering intangible assets, such as TV and movie content, and valuing the content on firm performance are challenging. With our longitudinal data about local and global media companies from 2019 to 2022, we first used a Data Envelopment Analysis (DEA) to answer which firms in the media industry have effectively exploited their resources to achieve better firm performance. In addition, with the Malmquist analysis, we show how the efficiencies and productivity of content providers change along with the dynamics of the media industry that the media industry has recently faced. Our understanding of the global media companies' efficiencies from diverse perspectives offers several theoretical and practical implications for the streams of efficiencies and competition in the media industry.

Economic Development, Industrialization, and Poverty Eradication: A Benchmarking Analysis of Developing, Emerging, and Developed Countries

This study utilizes benchmarking techniques to monitor productivity change in relation to Sustainable Development Goals (SDGs) 1, 8, and 9, addressing the challenges faced by countries in interpreting measures. The first SDG 1, “No Poverty”, aims to completely eliminate poverty. The objective of SDG 8, “Decent Work and Economic Growth”, is to foster comprehensive economic advancement. Finally, SDG 9, “Industry, Innovation, and Infrastructure”, focuses on the creation of durable and sustainable infrastructure, as well as promoting innovation to drive economic progress. Economic development, job creation, wealth creation, and poverty eradication are crucial for sustainable development. However, there is no other study estimating the evolution of countries’ performance in terms of these SDGs, whether countries have converged or not, and how each of these SDGs contributes to this performance development. This is the main goal of the present study, which compares 85 countries (2010–2020) from different profiles (developing, emerging, and developed) in terms of several SDG indicators. We applied data envelopment analysis (DEA) and Malmquist productivity indices that quantify changes in efficiency and technology over time to assess productivity dynamics and improvements. Results showed that emerging countries showed the highest productivity development, followed by developing countries and finally developed countries. The slower productivity development in developed countries indicates stagnation, allowing emerging countries to converge in terms of wealth creation, distribution, and poverty reduction.

Measuring Efficiency of Tea Retail Chain Stores: Application of Data Envelopment Analysis

Measuring Efficiency of Tea Retail Chain Stores: Application of Data Envelopment Analysis

Has the efficiency and productivity of the health system in India improved during post-policy period? Application of the bootstrap data envelopment analysis and Malmquist productivity index

ABSTRACT The efficiency and productivity of the health system are assessed using bootstrap data envelopment analysis and the bootstrap Malmquist productivity index across 21 states of India against the backdrop of the National Health Policy (NHP-2017). We took two child outcomes and three maternal outcomes as outputs and four inputs. A technical efficiency score of 0.760 suggests that the outputs could be increased by 24% without any additional inputs in the health system. A productivity of 0.993 indicates a decline at an average rate of 0.7% per year attributable to technological regress. Deducing from the statistical tests conducted, a significant change in the efficiency of the health system over the years was observed, particularly between the pre- and post-policy periods. In contrast, no significant change in productivity was observed. Despite having relatively better outcomes, Tamil Nadu lies farther away from the frontier, which indicates the inefficient utilization of public health resources. In contrast, Bihar, which has poor health outcomes, has better efficiency and witnessed significant productivity growth, indicating the efficient utilization of limited resources.

A unified framework for nonperforming loan modeling in bank production: An application of data envelopment analysis

The aim of this paper is to conduct a comparative analysis of three environmental approaches in the context of a bank production framework, considering the presence of nonperforming loans (NPLs). Specifically, we examine banks' inefficiency levels using the "by-production technology," "joint-weak disposable technology," and "material balanced technology." To ensure comparability within a directional slack inefficiency framework, we propose a two-step procedure. The study is based on a sample of 379 prominent banks operating in the United States from 2003 to 2017. Our findings reveal that the material balance and by-production technologies result in estimated inefficiency measures with higher sensitivity compared to the estimator utilizing the joint-weak disposable technology. Additionally, we identify distinct properties among the estimators, emphasizing their unique characteristics for modeling nonperforming loans. Finally, our paper sheds light on the differences between the three estimators in relation to banks' inefficiency levels, considering the incorporation of nonperforming loans in the production process.

Determinants of Technical Efficiency in Cow Milk Production in Kurunegala District: An Application of Data Envelopment Analysis

The aim of this study was to determine the level of technical efficiency scores under the assumptions of both constant returns and variable returns to scales on a sample of 150 cow milk producers in Kurunegala District, Sri Lanka. A structured questionnaire was used to gather the data during 2022 in the study and those data were analysed by Data Envelopment Analysis and Tobit regression model. Results of the data envelopment analysis based on input - oriented reveal that, mean technical efficiency scores estimated for constant returns and variable returns to scales were 0.782 and 0.887, respectively, indicating that substantial inefficiencies occurred in operations among the sample farmers. Further, with respect to returns to scale, out of the 150 dairy farmers, 21 were found to be operating at the constant returns to scale while, 122 and 7 were operating at an increasing return to scale and decreasing returns to scale respectively. Tobit regression model was applied to examine the factors influencing the technical efficiency under the specifications of constant returns to scale, variable returns to scale, and scale effects. The study found that age, sex, family size, credit accessibility, and milking frequency were significantly influence the technical efficiencies in dairy farming. These findings could help to increase the milk production and technical efficiency of cow milk production in the study area.

On the Use of Data Envelopment Analysis for Multi-Criteria Decision Analysis

Data envelopment analysis (DEA) has been proposed as a means of assessing alternative management options when there are multiple criteria with multiple indicators each. While the method has been widely applied, the implications of how the method is applied on the resultant management alternative ranking have not been previously considered. We consider the impact on option ranking of ignoring an implicit hierarchical structure when there are different numbers of indicators associated with potential higher-order objectives. We also consider the implications of the use of radial or slacks-based approaches on option ranking with and without a hierarchical structure. We use an artificial data set as well as data from a previous study to assess the implications of the approach adopted, with the aim to provide guidance for future applications of DEA for multi-criteria decision making. We find substantial benefits in applying a hierarchical approach in the evaluation of the management alternatives. We also find that slacks-based approaches are better able to differentiate between management alternatives given multiple objectives and indicators.

Measuring healthcare efficiency in Kazakhstan: an application of data envelopment analysis

The study aims to evaluate the efficiency of the Republic of Kazakhstan's healthcare sector over the period 2014-2021 using the non-parametric method of data envelope analysis. The analysis was carried out based on quantitative indicators of the medical statistics of the Republic of Kazakhstan. The study's results prove that efficiency tends to change over the medium term. Simultaneously, implementing digital technologies based on the computerisation and digitalisation of the healthcare sector in the short term is revealed to reduce overall efficiency, but that efficiency increases in the long term. The events of the COVID-19 pandemic did not reduce the overall efficiency of the healthcare sector in the Republic of Kazakhstan.

PENINGKATAN PELAYANAN BISNIS PADA IKM KOMPONEN OTOMOTIF DI CIKARANG KABUPATEN BEKASI

PT Nikko Teknik Indonesia is a tier-3 Small and Medium Industry company which operates in the field of manufacturing automotive components in the city of Bekasi. Tier-3 companies are automotive component manufacturing companies at the lowest level, such as PT Nikko Teknik Indonesia which focuses on making jigs, dies and welding from automotive components. The urgency of this research, there are many obstacles faced by tier-3 companies such as lack of use of technology information to support business, marketing aspects. It often managed conventionally (so it difficult to get new buyers/vendors) and also problems with automation of tracking components which deliver to customer. So, implementing comprehensive supply chain management e-dashboard is very helpful for tier-3 automotive component SME’s businesses. The research methods used are Data Envelopment Analysis (DEA) and Rapid Development Application (RAD) methods in automotive component production companies. The results of this research are that it has succeeded in building an e-Dashboard system for Supply Chain Management recording information, which provides facilities: statistics and indicators starting from raw materials, work-in-process and finished goods that are ready to be sent to buyers. .
 
 Keywords: Automotive Components SMEs, Business Services, E-Supply Chain Management

Evaluating the resource management and profitability efficiencies of US commercial banks from a dynamic network perspective

The central concept of strategic benchmarking is resource management efficiency, which ultimately results in profitability. However, little is known about performance measurement from resource-based perspectives. This study uses the data envelopment analysis (DEA) model with a dynamic network structure to measure the resource management and profitability efficiencies of 287 US commercial banks from 2010 to 2020. Furthermore, we provide frontier projections and incorporate five variables, namely capital adequacy, asset quality, management quality, earning ability, and liquidity (i.e., the CAMEL ratings). The results revealed that the room for improvement in bank performance is 55.4%. In addition, we found that the CAMEL ratings of efficient banks are generally higher than those of inefficient banks, and management quality, earnings quality, and liquidity ratios positively contribute to bank performance. Moreover, big banks are generally more efficient than small banks. Overall, this study continues the current heated debate on performance measurement in the banking industry, with a particular focus on the DEA application to answer the fundamental question of why resource management efficiency reflects benchmark firms and provides insights into how efficient management of CAMEL ratings would help in improving their performance.

A study on the application of data envelopment analysis in evaluating the quality of physical education teaching in universities

A study on the application of data envelopment analysis in evaluating the quality of physical education teaching in universities

A study on the application of data envelopment analysis in evaluating the quality of physical education teaching in universities

A study on the application of data envelopment analysis in evaluating the quality of physical education teaching in universities