Use Of Data Envelopment Analysis Research Articles

Service Innovation Performance in Sierra Leone's Banking Sector: An Empirical Analysis

This study investigates the innovation efficiency of Sierra Leone's banking sector, utilizing Data Envelopment Analysis (DEA) across 14 commercial banks representing 70% of the sector's total assets from 2017 to 2022. By analyzing existing financial and operational data, the study assesses performance variations and identifies disparities in innovation efficiency among these institutions. Findings indicate significant discrepancies in innovation efficiency levels, highlighting the critical role of strategic investment in technology and innovation for enhancing competitiveness and growth. This research contributes theoretically and practically to the literature on service innovation in banking in developing countries. It provides empirical evidence of the efficacy of DEA models in performance evaluation, offering benchmarks and strategic insights that could inform future policy and operational strategies. The study underscores the need for Sierra Leone banks to continually invest in innovative capabilities to maintain and enhance their competitive edge in a dynamic financial environment.

Enhancing pooling levels strengthens the risk resilience of healthcare insurance: a case study of basic medical insurance fund operations data in Gansu, China

BackgroundIn China, enhancing the pooling levels of basic health insurance has consistently been regarded as a pivotal measure to promote the refinement of the healthcare insurance system. From 2020 to 2022, the widespread outbreak of COVID-19 posed new challenges to China’s basic health insurance.MethodsThe research utilizes Data Envelopment Analysis (DEA), Malmquist index assessment, and fixed-effects panel Tobit models to analyze panel data from 2020 to 2022, assessing the efficiency of basic health insurance in Gansu Province.ResultsFrom 2020 to 2022, the average overall efficiency of the municipal pooling of Basic Medical Insurance for Urban and Rural Residents was 0.941, demonstrating a stable trend with a modest increase. The efficiency frontier regions have expanded from 5 (35.71%) to 7 (50%). Operational efficiency exhibited a negative correlation with per capita hospitalization expenses and per capita fund balance but a positive correlation with per capita accumulated fund balance and reimbursement rates for hospitalized patients. In 2021, compared to 2020, the county-pooling Basic Medical Insurance for Urban Employees saw a decline of 0.126 in overall efficiency, reducing the efficiency frontier regions from 8 to 3. However, from 2021 to 2022, the municipal-coordinated Basic Medical Insurance for Urban Employees experienced a 0.069 increase in overall efficiency, with the efficiency frontier regions expanding from 3 to 5. Throughout 2020 to 2022, the operational efficiency of the Urban Employee Basic Medical Insurance showed a consistent negative correlation with per capita fund balance.ConclusionFrom 2020 to 2022, the overall operational performance of basic health insurance in Gansu Province was satisfactory, and enhancing the pooling level is beneficial in addressing the impact of unforeseen events on the health insurance system.

Evaluation of undergraduate academic programs through data envelopment analysis and time-to-degree estimates at Spanish public universities

This article proposes nonparametric and parametric methods for conducting meaningful evaluations of academic programs. In particular, it proposes the use of data envelopment analysis (DEA) along with regression analysis for the evaluation of Spanish public universities' undergraduate curricula. Unlike the radial DEA models, which assume an equiproportional expansion of all outputs to achieve efficiency, the current study also relies on the use of non-radial DEA models for assessing the efficiency of Spanish public universities. A non-radial DEA measure (the so-called Russell measure) allows for unlike proportional augmentations in each positive output. In this study, non-radial DEA measures allow us to identify different levels of inefficiency for each output considered (social sciences and non-social sciences degrees). Specifically, the results show that the inefficiency in the production of scientific and technical degrees is greater than that in the production of humanities and social sciences degrees, although there are differences among institutions. Bachelor's degree production time is also estimated, and a duration analysis explains the time to degree. A worrying result is the "excessive" time it takes for a university to produce four-year undergraduate degree programs. The mean graduation time is 5.7 years. The Cox proportional hazards regression shows that a shorter time to graduation is associated with higher teaching quality as well as a higher faculty-to-student ratio. Parametric survival analysis using a lognormal distribution with gamma frailty also verifies these latter results.

Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: a DEA approach

Container ports play a pivotal role in international trade, facilitating the movement of goods and fostering economic development. While much attention has been given to the efficiency of ports in high-income countries, container ports in lower-middle-income (LMI) countries have received less attention. This paper addresses this research gap by assessing container ports' operational efficiency across diverse LMI countries and determining ways for their efficiency enhancement and management optimization. The cross-sectional data for the year 2012 was collected for 53 container ports in LMI countries. This research utilizes data envelopment analysis, which offers the advantage of considering multiple inputs and outputs. The results show that the overall technical inefficiencies of LMI countries' container ports are mainly due to pure technical inefficiency rather than scale inefficiencies, and the most efficient ports have a combination of large and hub ports. They also reveal that larger ports (as measured by throughput) are not necessarily more efficient than ports with a small production scale. The results of this research can provide government authorities, port authorities, terminal operators, and investors with valuable insights into resource allocation, competitive advantage, and optimization of operating performance.

Use of data envelopment analysis to measure the relative efficiency of the collages Sudan university

Use of data envelopment analysis to measure the relative efficiency of the collages Sudan university

A multidimensional analysis of corporate governance mechanisms and their impact on sustainable economic development: A case study of Ghana’s financial sector

Efficiency remains pivotal to the banking sector, serving as a linchpin for resource allocation and competitive prowess. This study delves into the intricate dynamics between corporate governance and banking efficiency in Ghana, with an analytical lens on cost efficiency (CE) and total efficiency (TE). Utilizing Data Envelopment Analysis (DEA), our investigation spans over a decade (2008–2019) and encompasses a data set of 23 Ghanaian banks.The study findings unveils that rigorous corporate governance mechanisms, as quantified by the Corporate Governance Index (CGI), exert a salutary influence on both cost and total efficiencies. Moreover, a well-defined Risk Management Index (RMI) positively correlates with cost efficiency, albeit without a substantial impact on total efficiency. Conversely, the study identifies a counterintuitive effect: the current make-up of supervisory boards, as gauged by the Supervisory Board Index (SBI), inversely impacts both efficiency metrics, signaling sub-optimal governance structures.Significantly, the research also highlights a pressing concern: the average total efficiency of Ghanaian banks lags behind the global benchmarks prescribed by the World Bank. This discrepancy underscores an exigency for efficiency optimization within the sector.The study thereby offers invaluable insights for multiple stakeholders—including regulatory bodies, investment communities, and policymakers—by delineating the governance variables that can enhance or impede banking efficiency. It also identifies actionable avenues for improvement, specifically in the realms of risk management and board composition, with the potential to catalyze a transformation in Ghana's banking landscape.

Performance of M&A Deals in The Russian Market: Evidence from Oil & Gas and Power Industries

The paper provides a comprehensive investigation of M&A deals on the Russian market, particularly in the Oil and Gas and Power sectors. This research fills the gap in literature by scrutinizing key M&A trends, reviewing M&A activities, and evaluating M&A performance through a combined application of Data Envelopment Analysis (DEA) and case studyanalysis. A critical part of this study involves exploring the influence of geopolitical factors on these transactions. The article presents a novel academic contribution by offering focused insights on M&A activities in two under-researched yet critical sectors of the Russian economy. Furthermore, the innovative use of DEA and case study analysis enhances ourunderstanding of industry trends over a span of 22 years, including the M&A transactions of 2022. Our sample includes 23 deals made by 17 Russian companies in the Energy and Power industries. We selected deals as a result of which the acquirer companies obtained more than 50% of the target company, so the acquirer company gained control over the operationsand performance of the acquired company. The study traces the effects of geopolitical influences on M&A outcomes, a critical consideration given Russia’s unique geopolitical context. This research is of practical significance for domestic and international businesses contemplating M&A decisions within Russia’s Oil & Gas and Power industries, offering valuableinsights to guide future strategies. While this study uncovers promising positive trends, further exploration and long-term data are necessary for a complete assessment of the impact of these M&A activities on company performance.

Malmquist Productivity Change of Mutual Funds in Tanzania

This study utilized Data Envelopment Analysis to assess the efficiency of six mutual funds in Tanzania spanning from 2018 to 2022. The analysis explores efficiency changes, technical advancements, scale efficiency, and total factor productivity. The results revealed significant trends of Mutual funds, on average, demonstrate a 3 percent increase in total factor productivity, signifying enhanced output relative to inputs attributed to improved management practices, technology integration, and operational enhancements. Conversely, technical efficiency change experiences by 2.7 percent decline, indicating that certain funds struggle to optimize inputs, potentially due to shifts in management strategies, resource allocation, or market variations. Further differentiation between large and small mutual funds reveals that larger entities exhibit more favorable productivity changes. This disparity is ascribed to economies of scale, improved investment prospects, and reduced transaction costs for larger funds. The study underscores substantial implications for mutual fund managers and the industry. Positive improvements in efficiency change, scale efficiency change, and total factor productivity indicated an overall positive trend in the mutual fund industry. Emphasizing economies of scale can enhance efficiency and overall outcomes, urging regulatory bodies to provide guidance on achieving economies of scale and fostering better practices. This research offers valuable insights into the mutual fund landscape, emphasizing the critical importance of adapting to evolving market dynamics and incorporating technology to maximize efficiency and success.

Enchanting performance measurement and management with data envelopment analysis: Insights from bibliometric data visualization and analysis

While the breadth of applicative uses of data envelopment analysis (DEA) has increased over time, this non-parametric frontier methodology has proven effective for measuring how efficient decision-making units (DMUs) are. One of its uses is performance measurement in various organizations — from universities and banks to investment funds and entrepreneurial small and medium-sized enterprises. Following a search inquiry in the Scopus and Web of Science databases, we found no bibliometric analysis and keyword co-occurrence network visualization of just the use of DEA for performance management. With this study, we attempt to investigate the DEA literature for performance measurement and management, considering articles in scientific peer-reviewed journals, which are indexed in the Web of Science database. The analysis and visualization of the bibliometric data are based on 89 articles from the start of the century onward. We present the annual trends of published articles, journals, authors, and countries leading the scientific discussion and citation analysis. A detailed keyword visualization analysis was performed and is discussed in this article alongside the paths for future hotspots of the use of DEA for performance management. The findings have implications for both the academic community and practitioners, business leaders, managers, and policy-makers.

CO2 Emissions in Air Transport: A Comparative Study Using Data Envelopment Analysis

The international community has been actively addressing the issue of reducing carbon dioxide (CO2) emissions, as evidenced by various initiatives such as Rio 92, Rio +20, the Paris Agreement, and the 2030 Agenda. These endeavors aim to promote sustainability worldwide. While air transport accounts for only 2% of anthropogenic CO2 emissions, its projected growth has spurred the exploration of new technologies to enhance aircraft efficiency. Consequently, further studies are necessary to assess the efficiency and impact of air transport on CO2 emissions in most countries. A methodology utilizing data envelopment analysis (DEA) is proposed in this study for this purpose. This methodology correlates the structure and annual air movement of 21 countries with CO2 production, considering it an undesirable output. The clustering method establishes the relationship between DEA efficiency, the number of airports, air traffic movements (landings and take-offs), and annual economic factors such as gross domestic product in these countries. Additionally, a regression analysis is conducted to examine the influence of air transport on CO2 emissions from transport systems. The findings reveal that the U.S. and China exhibit low efficiency as outliers because of their significant economic disparities. Other countries are grouped based on economic similarities, with South American nations such as Colombia and Chile showing lower air traffic movement efficiency compared with economically powerful European countries such as the UK and Germany. However, the impact of air transportation variables on CO2 emissions remains substantial.

Healthcare Service Efficiency: An Empirical Study on Healthcare Capacity in Various Counties and Cities in Taiwan.

As human lifespan increases and the need for elderly care grows, the demand for healthcare services and its associated costs have surged, causing a decline in the operational efficiency of universal healthcare. This has created an imbalance in medical services across different regions, posing a long-standing challenge for the public. To address this issue, strategies to enhance the capacity, efficiency, and quality of healthcare services in various regions must be developed. The appropriate allocation of medical resources is a fundamental requirement for countries to establish a robust healthcare system. This empirical study utilized data envelopment analysis (DEA) to evaluate the efficiency of medical service capacity and identify potential improvement strategies for counties and cities in Taiwan during the period from 2015 to 2020. The results of this study show that (1) the annual average efficiency of medical service capacity in Taiwan is approximately 90%, indicating that there is still room for a 10% improvement; (2) among the six municipalities, only Taipei City has sufficient healthcare capacity, whereas the efficiency of the remaining municipalities needs improvement; and (3) most counties and cities demonstrated increasing returns to scale, indicating a need to scale up the capacity of medical services as appropriate. Based on the findings of this study, it is recommended that medical personnel be increased accordingly to balance the workload, a favorable working environment be provided to stabilize the medical workforce, and urban-rural medical disparities be balanced to improve service quality and reduce cross-regional health services. These recommendations are expected to provide a reference for society as a whole to promote and enhance public health policies, leading to a continual improvement of the quality of medical services.

Involvement, leadership and social practice to the development of postgraduate attributes: evidence from extracurricular education with Chinese characteristics.

Limited by students' time and energy, participation in extracurricular activities is not necessarily beneficial to the development of postgraduate attributes. Thus, it is necessary to explore the impact path of extracurricular activities and education outcomes on the development of postgraduate attributes. From a configuration perspective, this study identifies the asymmetric causal effects of engagement and extracurricular education on postgraduate attributes. First, this study proposes a theoretical framework for postgraduate attribute development in extracurricular education with Chinese characteristics based on the input-environment-output (IEO) theory. Second, 166 academic scholarship applications submitted by the whole third-grade postgraduates who are from a science and engineering school at a double first-class university in China are taken as the sample. Finally, utilizing data envelopment analysis (DEA) and fuzzy set qualitative comparative analysis (fsQCA), this study conducts the effect of the combination of causal conditions on the development of postgraduate attributes. Results are as follows: (1) the development efficiency of postgraduate attribute in extracurricular education with Chinese characteristics is practical but still insufficient; (2) four configurations consistently linked to high development efficiency of postgraduate attributes. Specifically, in context with outstanding academic research achievement and excellent moral character, participating in extracurricular education or not consistently linked to high development efficiency. In contrast, in a context characterized by academic achievement or moral award not outstanding enough, involvement in extracurricular activities or social practice is consistently linked to high development efficiency. In addition, no configuration links student leadership to high development efficiency, and non-scientific research ability is consistently linked to low development efficiency; (3) there is an asymmetric causal relationship between the high and low development efficiency paths, indicating that the conditions affecting the development of postgraduate attributes have multiple concurrencies. These findings provide a new practical path and perspective for promoting the development of postgraduate attributes through extracurricular education with Chinese characteristics.

Green supplier selection problems with data scaling and production frontier estimations in a DEA model

AbstractConsidering ecological issues in supplier evaluation and management alongside business considerations is getting more recognition among firms. Data envelopment analysis (DEA) is one of those methods, which is frequently suggested by the literature to support management decisions. However, the data requirements of the method should be an important consideration. The literature often addresses the issue of desirable outputs and undesirable input as an important data related problem in case of the ecological use of DEA. This paper will present a new solution to manage these data problems along with connecting the evaluation of management criteria, environmental criteria and total cost aspects. The proposed environmental supplier selection problem is an extension of a former paper. The new model examines the effect of inventory related costs, such as EOQ costs of inventory holding or ordering costs on the selected supplier, extended with newly introduced scaled values of input and output indicators. The usage of scaled values is motivated by the problem of invariance to data alteration. In addition to the uncertainty of the data, the paper looks for a functional relationship between the input and output criterion values and the efficiency that can be assigned to them using DEA.

An evaluation of blood collection efficiency at the regional level: the case of Turkey

PurposeThe aim of this study is to analyze Turkey's blood collection efficiency at the regional level between 2018 and 2021 and discuss managerial implications.Design/methodology/approachThe authors utilize data envelopment analysis (DEA) to evaluate the efficiency scores of the 18 regions for which the Turkish Red Crescent is responsible. The data set is obtained from the General Directorate of Blood Services in the Turkish Red Crescent.FindingsThe results reveal that the efficient regions over the years did not substantially change, and regions that were consistently efficient for a four-year period are identified. Another finding is that COVID-19 did not affect the blood collection efficiency of the regions. Moreover, the findings illustrate that concentrating on the operations would contribute more to the blood collection efficiency than changing the scale size. Furthermore, the authors observe that the service population is by far the most important variable in determining the efficiency of the regions.Originality/valueIn this study, the authors present a multi-dimensional perspective on the performance evaluation of blood collection operations. In addition, the authors present blood bank managers' feedback on the performance evaluation model, outlining managerial implications. Furthermore, the authors explore the effects of the pandemic on blood collection in Turkey and illustrate the changes in efficiency throughout a distinct period that incorporates the pandemic. The study would provide a guide for blood bank managers to improve the performance of their organizations.

Bibliometric Analysis of Data Envelopment Analysis in Supply Chain Management

A bibliometric analysis is presented in this paper to examine the use of Data Envelopment Analysis (DEA) in the domain of Supply Chain Management (SCM). The research trends on DEA in SCM from 2000 to 2023 are explored, using data obtained from the Web of Science database (WoS) and VOS viewer software for detailed mapping of the articles. The numerous articles that use DEA in SCM worldwide are analyzed and summarized in this bibliometric study, producing a complete assessment of DEA in the field from 352 academic papers published in high-ranking publications. The articles are classified according to the year of publication, countries of the author(s), working areas, journals, and content of studies. Based on the findings of this research, tremendous potential is shown for DEA as a suitable evaluation instrument for future studies on sustainability concerns in SCM.

The Assessment of Specific, Economic and Technical, Allocative Efficiency in Calfs Fatting Fields in Nineveh (Gogjali as a model) Using DEA Method

Calf fattening fields in Nineveh and particularly in Gogjali village occupy a very significant position in providing the area of the beef meet for the whole community. The present study aims at investigating the technical efficiency utilizing Data Envelopment Analysis method. The study is conducted with the hypothesis of variable return scale taking into consideration the input-oriented method. The study covered filed data of sample consisting of 151 field with a percentage estimated at 47% of the total of the studied fields. The study divided into two groups. The first includes 100 fields with imported calf class. The second includes 51 fields with local calf. The averages of TE, AE and EE amounted to 87.8% , 71.3% and 62.8% respectively for the first group of sample of TE , AE ,EE As for the second, the averages amounted to 94.6% , 78.6% and 62.8% respectively. The researcher suggests conducting experiments and studies in order to improve the genetic strains fodder, veterinary treatments and providing loans to breeders without interest.
  
  

An analysis of the positive effect of real earnings management on financial performance

PurposeREM models infer abnormal levels of cashflow from operations (AbCFO), selling, general and admin (AbSGA) and production expenses (AbProd) are opportunistic, based on the supposition that engaging in real activities to meet current earnings targets (t) will negatively influence future performance (t+1). However, from a firm productivity perspective, cost reduction (via AbCFO, AbProd and AbSGA) is interpreted as an efficiency enhancing business strategy. This study therefore differentiates between (1) firms with ineffective management that have engaged in AbCFO, AbProd and AbSGA to achieve an optimal resource-cost mix to generate sales (REMF) and (2) firms with effective management that have not (OEF).Design/methodology/approachUsing a sample of Korean listed firms over the 2000–2016 sample period, the study utilizes data envelopment analysis to capture the capability of management to generate sales from resources that are directly under their control. The study then compares the incremental effect that managerial decision making can have on real earnings management (REM) and future firm performance (period t+1 to t+5).FindingsThe study makes two important contributions. First, consistent with the efficiency/productivity literature, but contrary to seminal REM studies, empirical results shows that AbCFO, AbProd and AbSGA improve firm performance in period t and t+1 (to t+5), demonstrating “REM” is not opportunistic by default. Second, OEF have higher financial performance compared to REMF, in periods t and t+1.Originality/valueThe study therefore invokes resource-based theory and data envelopment analysis to integrate managerial effectiveness (human capital) into REM modelling. The study therefore extends the basic REM residual model.

Use of Data Envelopment Analysis (DEA) to assess management alternatives in the presence of multiple objectives

Marine ecosystem-based management often aims to satisfy a wide range of economic, social and environmental objectives. These are often measured in non-commensurable units, making identification of a preferred option difficult when outcomes and measures vary considerably. In this paper, we examine the potential for data envelopment analysis (DEA) as an alternative approach to traditional multi-criteria decision analysis (MCDA). We derive multi-output composite indicator scores for three case study examples. The management alternatives are assessed both with and without exogenously determined objective preference weights. The frontier-based analysis does not require weights to be assigned to each objective, instead generating flexible “benefit of the doubt” weights that allow for different objectives to be influencing each management option. Applying stakeholder objective importance weights allows the assessment of the objective alignment of the different stakeholder groups, providing additional information on management option performance. The DEA results were found to be consistent with those from an earlier study that used a more traditional MCDA approach. DEA has the additional advantage of not requiring measures to be commensurable and can also directly incorporate undesirable outcomes into the analysis.

Can environmental regulation promote the green output bias in China's mariculture?

The green output bias of technological progress is the key factor driving the green transformation of mariculture. This study considers whether environmental regulation can promote the green output bias. Utilizing data envelopment analysis (DEA), we decomposed the green output biased technological progress index (OBTC) and constructed the index to measure the output bias between output value and pollutant emissions. The results show spatial and temporal differences in the green output bias, with different bias values for three major Chinese coastal regions during the study period. As the bias value mainly fluctuates around the zero value, the degree of green output bias must be enhanced. Considering the heterogeneity of environmental regulation, we empirically study the relation that exists between environmental regulation and green output bias. Our findings indicate a U-shaped relation between two categories of environmental regulation and the green output bias. Green technology partially intermediates the mechanisms by which these environmental regulations influence green output bias. Our results have implications for policymakers and other stakeholders for strengthening environmental regulation, promoting green technological innovation, and the scientific planning of the species and scale of mariculture to promote sustainable development.

Data-Driven Robust Data Envelopment Analysis for Evaluating the Carbon Emissions Efficiency of Provinces in China

To combat global warming, China proposed the “dual carbon” policy in 2020. In this context, it becomes crucial to improve carbon emissions efficiency. Currently, some scholars have utilized data envelopment analysis (DEA) to study carbon emissions efficiency. However, uncertainty about climate and government economic policy is ignored. This paper establishes a robust DEA model to reduce uncertainty and improve robustness. First, robust optimization theory is combined with DEA to establish the robust DEA model. Second, considering three uncertainty sets (box set, ellipsoid set, and polyhedron set), a robust DEA model for different situations is considered. Finally, to address the problem of over-conservatism in robust optimization, this paper applies the data-driven robust DEA model to further analyze the carbon emissions efficiency of China. The results of the data-driven robust DEA model suggest that the government should focus on coordinated regional development, promote the transformation and upgrading of the energy structure, innovate in green technology, and advocate for people to live a green and low-carbon lifestyle.