Two-Phase Network Data Envelopment Analysis: An Example of Bank Performance Assessment

Data envelopment analysis (DEA) models assess decision-making units (DMUs), which directly convert multiple inputs into multiple outputs. Network DEA models have been studied extensively. However, the performance indices that link the two stages are assumed to be fixed or non-discretionary; their values are not adjustable. These models only assumed that the reductions on the inputs and additions on the outputs would improve the overall efficiency. But in the real world, the link is always adjustable. “Free links” means that the intermediate items are adjustable or discretionary, and each DMU can be increased or decreased from the observed one. The current chapter introduces a two-phase procedure with free links to assess system performance, Phase-I is a proposed slack-based measurement (SBM) model to partition the links into two sets: as-input and as-output. Phase-II is a modified SBM model to determine the slack of each input, as-input link, output and as-output link. This proposed model counts the slacks associated with the intermediate items in the efficiency scores and determines the entire system performance by the directional distance function. It is validated using network procedure and assesses the performance of supply chain management system

A novel multilevel network slacks-based measure with an application in electric utility companies

In this paper, we developed an alternative Network Slacks-Based Data Envelopment Analysis Measure (NSBM) wherein the overall efficiency is expressed as a weighted average of the efficiencies of the individual processes. The advantage of this new model is that both overall efficiency and multi-divisional efficiencies have been calculated with a unified framework. The major merits of the proposed model are its ability to provide appropriate measure of efficiency, obtaining weight of processes from model, simultaneous assessment of intermediate variables considering them as both input and output. Finally, an application in electric power companies shows the practicality of the proposed model

Technical progress and efficiency changes in football teams participating in the UEFA Champions League

This paper commits to calculate and analyze productivity levels and its components for teams that participated in the UEFA Champions League between 2003 and 2012. It will pursue three objectives: 1) evaluate resources usage, 2) analyze the productivity levels of the football teams and the sports results, and 3) see the influence of participation experience in reference to productivity and sports results. Using Malmquist Productivity Index, the results reflect a lack of consistent progression of efficiency, productivity, and technical change. This competition does not reward the efficient usage of resources and there is not a conclusive relationship between permanence in the competition and productivity. Este arti´culo pretende calcular y analizar los niveles de productividad y de sus componentes para los equipos que participaron en la Liga de Campeones de la UEFA entre 2003 y 2012. Se persiguen tres objetivos: 1) evaluar la utilizacio´n de los recursos, 2) analizar los niveles de productividad de los equipos de fu´tbol y los resultados deportivos y 3) ver si la experiencia que da la participacio´n influye en la productividad y los resultados deportivos. Usando el i´ndice de productividad de Malmquist, los resultados reflejan una ausencia de evolucio´n constante para la eficiencia, la productividad y el cambio te´cnico. Esta competicio´n no premia el uso eficiente de los recursos y no hay una relacio´n concluyente entre productividad y permanencia en la competicio´n

Environmental Efficiency Assessment of Dublin Port Using Two-Stage Non-Radial DEA Model

Global maritime trade has reached 11 billion tons and accounts for more than 80% of global merchandise trade (United Nations Conference on Trade & Development (UNCTAD), 2019). As a result, there is a wide range of vessels, from very large bulk carriers (coal, ores, grains, etc., and crude oil/refinery carriers) to container ships to various cruise ships and naval vessels. To efficiently accommodate these various vessels, ports have had to evolve from wharves to efficient logistical hubs within the larger supply chain that move vessels deeper into the hinterland. Port development is critical to managing the growing volume of cargo (European Commission (EC), 2011)

Team improvement in the UEFA Champions League: an application of data envelopment analysis

Football teams, when considered as economic organisations, are expected to achieve their objectives without consuming excess resources. Put another way, they must produce their products and services efficiently. In this study, we calculate efficiency on the playing field for teams in the UEFA Champions League between 2003 and 2012. We do this not only with an aim of separating the efficient and inefficient teams, but also to propose a way for inefficient teams to become more efficient. To this end, we use data envelopment analysis to calculate efficiency ratios. From those results, we calculate improvement percentages that we then use as a basis for team management recommendations. We find that no single input is to blame for inefficiency. The general recommendation for inefficient teams is to use fewer attacking plays

The efficiency of hospitals: Platform for sustainable healthcaresystem

Hospitals and other providers of health services are facing enormous pressure to reduce costs while providing better services for patients without lowering their quality. By utilising a two-stage dynamic Data Envelopment Analysis (DEA) approach, we explore whether there is a compromise between the production of services and the quality of services in the process of providing health care at the level of hospitals in Slovakia. While the first stage deals with the production efficiency of the hospitals, the second stage deals with the quality of service using patient-reported safety and satisfaction measures. The efficiency of hospitals in Slovakia is assessed, using hospital-level data from the database of INEKO for the years 2015 and 2018. In order to dynamically analyse the efficiency changes during the analysed period, the Malmquist index was used. The results revealed that overall technical efficiency increased over the analysed period. We can also see an increase within the service production division as well as service quality division. The results obtained represent a significant platform for the creators of health policy at the national level, and for the creators of the strategic regional health plans as a basis of continuous creation of mechanisms that are inevitable for providing a sustainable system of the Slovak health care at the regional level. The global threats of epidemics, such as COVID-19 pandemic, address the question of public health systems’ sustainability, which enormously increases. © 2020 by author(s) and VsI Entrepreneurship and Sustainability Center.Internal Grant Agency of FaME Tomas Bata University in Zli

Selection of Guided Surgery Dental Implant Systems Using Network Data Envelopment Analysis

[[abstract]]All dental implant system suppliers typically claim the advantages and superiority of their product’s specific attributes and functions. However, as assessment criteria are often inconsistent and conflicting, clinical dentists find it difficult to choose the most appropriate dental implant system. The present study used two-stage data envelopment analysis to measure the overall efficiency of individual dental implant systems and the relative efficiency of each phase of the selection process. The results of the present study can not only provide decision-making information for users, such as medical organizations, dentists, and patients, but may also inform guidelines for system producers to improve dental implant performance.[[notice]]補正完

Benchmarking with network DEA in a fuzzy environment

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Benchmarking is a powerful and thriving tool to enhance the performance and profitabilities of organizations in business engineering. Though performance benchmarking has practically and theoretically developed in distinct fields such as banking, education, health and so on, supply chain benchmarking across multiple echelons that includes certain characteristics such as intermediate measure differs from other fields. In spite of incremental benchmarking activities in practice, there is the dearth of a unified and effective guideline for benchmarking in organizations. Amongst the benchmarking tools, data envelopment analysis (DEA) as a non-parametric technique has been widely used to measure the relative efficiency of firms. However, the conventional DEA models that are bearing out precise input and output data turn out to be incapable of dealing with uncertainty, particularly when the gathered data encompasses natural language expressions and human judgements. In this paper, we present an imprecise network benchmarking for the purpose of reflecting the human judgments with the fuzzy values rather than precise numbers. In doing so, we propose the fuzzy network DEA models to compute the overall system scale and technical efficiency of those organizations whose internal structure is known. A classification scheme is presented based upon their fuzzy efficiencies with the aim of classifying the organizations. We finally provide a case study of the airport and travel sector to elucidate the details of the proposed method in this study

Eficiência do setor bancário brasileiro : modelo DEA dois estágios com regressão truncada bootstrapped

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Programa de Pós-Graduação em Administração, 2019.Tendo em vista a importância e a complexidade do setor bancário, esse setor tem sido foco de muitos estudos de eficiência. Nesse sentido, dentre as técnicas existentes para mensuração do desempenho, a Análise Envoltória de Dados (DEA) tem se destacado por necessitar de poucas informações prévias e a possibilidade de lidar com processos produtivos complexos, como é o caso do setor bancário. Entretanto, os modelos Data Envelopment Analisys (DEA) tradicionais são frequentemente criticados por não reconhecerem que fatores ambientais, exógenos, podem influenciar os índices de eficiência. Diante desse contexto, os modelos dois estágios externos têm ganhado notoriedade por justamente possibilitar superar tais limitações. O presente estudo utilizou um modelo dois estágios DEA com regressão truncada bootstrapped com o objetivo de mensurar a eficiência do setor bancário brasileiro no ano de 2018, considerando tanto a abordagem de intermediação quanto a de produção na seleção das variáveis. Além disso, buscou-se verificar se variáveis não discricionárias como o controle estatal, o fato de ser estrangeiro, risco de crédito, capitalização e lucratividade impactam na eficiência dos bancos, tanto em seu papel de intermediador financeiro, quanto na função de ofertar serviços aos clientes. Cinco amostras foram utilizadas, em que o maior valor de eficiência média no modelo de intermediação foi 62,13% na Eficiência Puramente Técnica (EPT) e 46,75% na Eficiência Técnica (ET), enquanto que o maior valor médio da eficiência livre de viés foi de 45,20% e 36,49%, respectivamente. Para o modelo de produção, o maior valor da eficiência média foi de 79,94% em EPT e 67,41% em ET, ao passo que após a correção de viés essa eficiência foi de 66,53% e 57,46%, respectivamente. As hipóteses em relação a lucratividade e capitalização foram confirmadas, enquanto que para a variável controle estatal o impacto se alterou de acordo com o escopo considerado, confirmando a hipótese no que tange ao modelo de produção e rejeitando para o modelo de intermediação. O controle estrangeiro apresentou relação negativa com a eficiência, indicando a rejeição da hipótese, e a variável risco de crédito não foi significativa no modelo de produção e teve, em sua maioria, relação positiva com a eficiência no modelo de intermediação, sugerindo também a rejeição da hipótese proposta. Implicações dos resultados foram discutidas e medidas para impulsionar a eficiência do setor foram indicadas.Given the importance and complexity of the banking sector, this sector has been the focus of many efficiency studies. In this sense, among the techniques for measuring performance, Data Envelopment Analisys (DEA) has been highlighted because it requires few prior information and enables to deal with complex production processes, such as the banking sector. However, traditional DEA models are often criticized for not recognizing that exogenous, environmental factors can influence efficiency. Given this context, the external two-stage DEA models have gained notoriety for precisely making it possible to overcome such limitations. The present study used a two-stage DEA model with Bootstrap Truncated Regression with the objective of measuring the efficiency of the Brazilian banking sector in 2018, considering both the intermediation approach and the production approach in the selection of variables. In addition, this study sought to verify whether non-discretionary variables such as state control, the fact of being foreign, credit risk, capitalization and profitability impacts on banks’ efficiency, both in their role of financial intermediary and in the function of offering services to clients. Five samples were used, in which the highest average value of efficiency in the intermediation model was 62.13% in PTE and 46.75% in TE, while the highest average bias corrected efficiency value was 45.20% and 36.49%, respectively. For the production model, the average efficiency was 79.94% in PTE and 67.41% TE, while after the bias correction this efficiency was 66.53% and 57.46%, respectively. The hypotheses regarding profitability and capitalization were confirmed, while for the variable state control the impact changed according to the scope considered, confirming the hypothesis regarding the production model and rejecting it for the intermediation model. Foreign control presented a negative relation with efficiency, indicating the rejection of the hypothesis, and the credit risk variable was not significant in the production model and presented, in most cases, positive relation with the efficiency in the intermediation model, also suggesting the rejection of the hypothesis proposed. Implications of the results were discussed and measures to boost the efficiency of the sector were indicated

Profitability and marketability efficiencies of manufacturers in the association of Southeast Asian Nations: A multi-stage empirical study : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University

The Association of Southeast Asian Nations (ASEAN) is developing as an attractive, promising destination for manufacturing operations in Asia. Since the 2015 establishment of ASEAN Economic Community, which aims to become a resilient manufacturing and business centre, it has fostered the growth of manufacturers in ASEAN. The manufacturing sector has contributed extensively to the economic development of ASEAN nations. Notable recent positive statistics report the impressive performance and continuous development of manufacturing in most ASEAN countries. Despite the acknowledged contribution and potential growth of manufacturing in ASEAN nations, the profit-generating and market-value efficiencies of manufacturing enterprises in ASEAN are still debatable. This study applies the bootstrap two-stage data envelopment analysis (DEA) to investigate the profitability and marketability efficiencies of 899 listed manufacturers in six selected ASEAN countries (ASEAN-6): Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam from 2007 to 2018. The study uses panel-data fractional and Tobit regression models to examine the effects of corporate factors on the listed manufacturers’ profitability and marketability efficiencies across the ASEAN-6 countries. Though the fractional regression model is the most advantageous method for fractional response variables, the Tobit regression model is most widely used for evaluating efficiency determinants. The bootstrap two-stage DEA results show that Indonesian and Singaporean listed manufacturing attains relatively high average profitability efficiency. Conversely, Malaysia, the Philippines, Thailand, and Vietnam listed manufacturers’ profitability efficiency has considerable room for improvement. Marketability efficiency levels are significantly lower than profitability efficiency for most ASEAN-6 countries (exception, Malaysia). Singaporean listed manufacturers have the highest marketability efficiency scores, followed by Indonesia, Malaysia, Thailand, the Philippines, and Vietnam listed manufacturers. The empirical results from the regression models show diverse, significant impacts of corporate financial and non-financial factors on the profitability and marketability efficiencies of the listed firms in the ASEAN-6 countries’ manufacturing sector and sub-sectors (high-technology and traditional production sub-sectors)