Investigating technical and scale efficiencies of Australian universities through data envelopment analysis

Performance indicators in the public sector have often been criticised for being inadequate and not conducive to analysing efficiency. The main objective of this study is to use data envelopment analysis (DEA) to examine the relative efficiency of Australian universities. Three performance models are developed, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments. The findings based on 1995 data show that the university sector was performing well on technical and scale efficiency but there was room for improving performance on fee-paying enrolments. There were also small slacks in input utilisation. More universities were operating at decreasing returns to scale, indicating a potential to downsize. DEA helps in identifying the reference sets for inefficient institutions and objectively determines productivity improvements. As such, it can be a valuable benchmarking tool for educational administrators and assist in more efficient allocation of scarce resources. In the absence of market mechanisms to price educational outputs, which renders traditional production or cost functions inappropriate, universities are particularly obliged to seek alternative efficiency analysis methods such as DEA.

Superefficiency and Multiplier Adjustment in Data Envelopment Analysis

Copyright �� 2013 Springer Netherlands.

Multiplier adjustment in data envelopment analysis

V Congreso de Eficiencia y Productividad EFIUCO, C��rdoba, 19-20 Mayo 2011.

Data envelopment analysis: efici��ncia relativa das unidades de tomada de decis��o

A avalia����o das organiza����es e a deterntina����o da performance obtida pelo exerc��cio da gest��o, tem sido uma preocupa����o constante de gestores e accionistas, embora com objectivos diversos. Nos dias de hoje, a quest��o coloca-se com maior acuidade quer pela competitividade acrescida quer pela dimens��o e complexidade actual das empresas. Pretendemos com este trabalho fazer uma descri����o da metodologia DEA - Data Envelopment Analysis - nas suas formula����es iniciais mais simples. A metodologia do DEA, pretende obter uma medida ��nica e simples de avalia����o da efici��ncia, combinando um conjunto de outputs e de inputs relativos ��s diferentes unidades homog��neas que se pretendem avaliar. O m��todo DEA �� um m��todo n��o param��trico que pelas suas caracter��sticas �� particularmente adequado �� avalia����o de unidades homog��neas n��o necessariamente lucrativas. Conclu��mos, em geral, que s��o ��teis e constituem um avan��o importante, as informa����es obtidas atrav��s do DEA mas que outros m��todos, designadamente r��cios e an��lises de regress��o, podem dar um contributo importante para complementar aquela an��lise.

A contabilidade de gest��o e a data envelopment analysis : an��lise de desempenho organizacional

Mestrado em Contabilidade e Gest��o das Institui����es Financeiras

Dynamic network data envelopment analysis for university hospitals evaluation

ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

Avalia����o da efici��ncia das empresas na utiliza����o das redes sociais digitais: data envelopment analysis aplicada ao Facebook

Disserta����o para obten����o do Grau de Mestre em Engenharia e Gest��o Industrial

Aplica����o da Data Envelopment Analysis na determina����o da efici��ncia empresarial em ambientes colaborativos

Disserta����o apresentada na Faculdade de Ci��ncias e Tecnologia da Universidade Nova de Lisboa para obten����o do grau de mestre em Engenharia e Gest��o Industrial

An��lise da efici��ncia na gest��o do risco de fornecedores: aplica����o de um modelo Data Envelopment Analysis

Atualmente a tend��ncia dos neg��cios leva a cadeias de abastecimento complexas e din��micas, que consequentemente levanta quest��es relativas ao aumento do risco de fornecimento em torno dessas mesmas cadeias; pelo que existe cada vez mais uma necessidade dos gestores identificarem e gerirem o risco de um modo mais diversificado. Associado ��s cadeias de abastecimento est��o os fornecedores. A maioria dos riscos relativos a estes, est�� inclu��da no contexto de risco de fornecimento, resultando assim numa problem��tica de sele����o e avalia����o de fornecedores. Riscos como baixa qualidade, atrasos na entrega, falha ou interrup����o de fornecimento, s��o exemplos de fatores de risco associados. Neste contexto, um dos maiores desafios para as organiza����es atualmente �� trabalharem com os melhores fornecedores do mercado, procurando garantir a estabilidade em termos de fornecimento, com as melhores condi����es poss��veis, quer a n��vel de pre��o, qualidade, entre outros, exigindo cada vez mais rela����es comerciais eficientes com os fornecedores. Assim, este trabalho tem como objetivo o desenvolvimento de um modelo baseado no m��todo Data Envelopment Analysis (DEA), que permite ��s organiza����es avaliar e melhorar a efici��ncia das suas rela����es comerciais na gest��o de risco de fornecimento nas suas cadeias de abastecimento. Como tal, o modelo proposto �� divido em dois casos, que diferem pela origem da obten����o dos seus valores. Ou seja, num dos casos �� aplicada uma avalia����o externa �� organiza����o, e no outro �� utilizada uma avalia����o interna, o que permitir�� discutir a sua utiliza����o. Segundo o modelo proposto verificou-se que a efici��ncia m��dia foi de 93% no caso I e 94% no caso II. Concluindo-se ainda ambos os casos necessitam de melhorias nos fornecimentos ao n��vel de: Qualidade, Log��stica e Tecnologia, ou seja, melhorar a qualidade dos servi��os prestados, diminuir os seus prazos de execu����o dos servi��os/fornecimento de material e aumento do conhecimento tecnol��gico.

Um modelo Data Envelopment Analysis para avalia����o da efici��ncia dos terminais de contentores do grupo TERTIR

O transporte mar��timo tem vindo a adquirir uma consider��vel import��ncia na economia mundial desde o s��culo XV. O transporte mar��timo �� visto como um dos meios de transporte mais vi��veis, que engloba um largo n��mero de destinos no mundo e representa, para uma determinada dist��ncia a percorrer, o menor custo por tonelada. ��, tamb��m, comparativamente com o transporte a��reo e rodovi��rio, o meio de transporte menos poluente, tornando-o, assim, uma alternativa ���amiga do ambiente���. Em particular, o transporte via contentores tem vindo a ser cada vez mais utilizado devido ��s suas in��meras vantagens. O contentor permite o transporte de qualquer tipo de mercadoria em boas condi����es de acondicionamento e permitiu otimizar as opera����es efetuadas atrav��s da redu����o de tempo de trabalho, custos e espa��o. Ademais, com a globaliza����o, a evolu����o do mercado, a constru����o de navios de maiores dimens��es e a maior tecnologia investida no setor, a competi����o entre os portos alcan��ou n��veis que exigem uma maior efici��ncia de toda a estrutura portu��ria. Neste contexto, a presente disserta����o visa avaliar a efici��ncia dos terminais de contentores do grupo TERTIR, nomeadamente os de Lisboa, Leix��es e Set��bal, utilizando o m��todo Data Envelopment Analaysis (DEA). De um modo geral, o m��todo DEA avalia a capacidade dos terminais em converter inputs em outputs. Mais especificamente os inputs selecionados nesta disserta����o dizem respeito ��s infraestruturas e equipamentos dos terminais em estudo, e o output considera a carga movimentada por cada terminal, sendo neste caso representada pelo n��mero de TEUs movimentados. O modelo proposto �� aplicado a um conjunto de 30 terminais de contentores Europeus de 6 pa��ses diferentes, nomeadamente, Alemanha, B��lgica, Espanha, Fran��a, Holanda e Portugal. De um modo geral, os terminais TERTIR apresentam n��veis de efici��ncia baixos quando comparados com outros terminais Europeus. Os resultados contribuem, tamb��m, para auxiliar o grupo TERTIR no debate de algumas quest��es atuais com as autoridades portu��rias, nomeadamente no que se refere �� descida dos tarif��rios praticados aos seus clientes e �� enunciada constru����o do terminal de contentores do Barreiro.

Data Envelopment Analysis (DEA) : A pedagogical guide for decision makers in the public sector

This guide introduces Data Envelopment Analysis (DEA), a performance measurement technique, in such a way as to be appropriate to decision makers with little or no background in economics and operational research. The use of mathematics is kept to a minimum. This guide therefore adopts a strong practical approach in order to allow decision makers to conduct their own efficiency analysis and to easily interpret results. DEA helps decision makers for the following reasons: - By calculating an efficiency score, it indicates if a firm is efficient or has capacity for improvement. - By setting target values for input and output, it calculates how much input must be decreased or output increased in order to become efficient. - By identifying the nature of returns to scale, it indicates if a firm has to decrease or increase its scale (or size) in order to minimize the average cost. - By identifying a set of benchmarks, it specifies which other firms' processes need to be analysed in order to improve its own practices.

Data Envelopment Analysis (DEA) : un guide p��dagogique �� l'intention des d��cideurs dans le secteur public

Ce guide pr��sente la m��thode Data Envelopment Analysis (DEA), une m��thode d'��valuation de la performance . Il est destin�� aux responsables d'organisations publiques qui ne sont pas familiers avec les notions d'optimisation math��matique, autrement dit de recherche op��rationnelle. L'utilisation des math��matiques est par cons��quent r��duite au minimum. Ce guide est fortement orient�� vers la pratique. Il permet aux d��cideurs de r��aliser leurs propres analyses d'efficience et d'interpr��ter facilement les r��sultats obtenus. La m��thode DEA est un outil d'analyse et d'aide �� la d��cision dans les domaines suivants : - en calculant un score d'efficience, elle indique si une organisation dispose d'une marge d'am��lioration ; - en fixant des valeurs-cibles, elle indique de combien les inputs doivent ��tre r��duits et les outputs augment��s pour qu'une organisation devienne efficiente ; - en identifiant le type de rendements d'��chelle, elle indique si une organisation doit augmenter ou au contraire r��duire sa taille pour minimiser son co��t moyen de production ; - en identifiant les pairs de r��f��rence, elle d��signe quelles organisations disposent des best practice �� analyser.

Data Envelopment Analysis and non-discretionary inputs : How to select the most suitable model using multi-criteria decision analysis

Within Data Envelopment Analysis, several alternative models allow for an environmental adjustment. The majority of them deliver divergent results. Decision makers face the difficult task of selecting the most suitable model. This study is performed to overcome this difficulty. By doing so, it fills a research gap. First, a two-step web-based survey is conducted. It aims (1) to identify the selection criteria, (2) to prioritize and weight the selection criteria with respect to the goal of selecting the most suitable model and (3) to collect the preferences about which model is preferable to fulfil each selection criterion. Second, Analytic Hierarchy Process is used to quantify the preferences expressed in the survey. Results show that the understandability, the applicability and the acceptability of the alternative models are valid selection criteria. The selection of the most suitable model depends on the preferences of the decision makers with regards to these criteria.

The Use of Data Envelopment Analysis as Equity Portfolio Selection Criterion in the Finnish Stock Market

This thesis examines the application of data envelopment analysis as an equity portfolio selection criterion in the Finnish stock market during period 2001-2011. A sample of publicly traded firms in the Helsinki Stock Exchange is examined in this thesis. The sample covers the majority of the publicly traded firms in the Helsinki Stock Exchange. Data envelopment analysis is used to determine the efficiency of firms using a set of input and output financial parameters. The set of financial parameters consist of asset utilization, liquidity, capital structure, growth, valuation and profitability measures. The firms are divided into artificial industry categories, because of the industry-specific nature of the input and output parameters. Comparable portfolios are formed inside the industry category according to the efficiency scores given by the DEA and the performance of the portfolios is evaluated with several measures. The empirical evidence of this thesis suggests that with certain limitations, data envelopment analysis can successfully be used as portfolio selection criterion in the Finnish stock market when the portfolios are rebalanced at annual frequency according to the efficiency scores given by the data envelopment analysis. However, when the portfolios were rebalanced every two or three years, the results are mixed and inconclusive.

Green supplier selection via Multiple Criteria Data Envelopment Analysis

An appropriate supplier selection and its profound effects on increasing the competitive advantage of companies has been widely discussed in supply chain management (SCM) literature. By raising environmental awareness among companies and industries they attach more importance to sustainable and green activities in selection procedures of raw material providers. The current thesis benefits from data envelopment analysis (DEA) technique to evaluate the relative efficiency of suppliers in the presence of carbon dioxide (CO2) emission for green supplier selection. We incorporate the pollution of suppliers as an undesirable output into DEA. However, to do so, two conventional DEA model problems arise: the lack of the discrimination power among decision making units (DMUs) and flexibility of the inputs and outputs weights. To overcome these limitations, we use multiple criteria DEA (MCDEA) as one alternative. By applying MCDEA the number of suppliers which are identified as efficient will be decreased and will lead to a better ranking and selection of the suppliers. Besides, in order to compare the performance of the suppliers with an ideal supplier, a ���virtual��� best practice supplier is introduced. The presence of the ideal virtual supplier will also increase the discrimination power of the model for a better ranking of the suppliers. Therefore, a new MCDEA model is proposed to simultaneously handle undesirable outputs and virtual DMU. The developed model is applied for green supplier selection problem. A numerical example illustrates the applicability of the proposed model.