995 resultados para DEA analysis


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As student numbers in higher education in the UK have expanded during recent years, it has become increasingly important to understand its cost structure. This study applies Data Envelopment Analysis (DEA) to higher education institutions in England to assess their cost structure, efficiency and productivity. The paper complements an earlier study that used parametric methods to analyse the same panel data. Interestingly, DEA provides estimates of subject-specific unit costs that are in the same ballpark as those provided by the parametric methods. The paper then extends the previous analysis and finds that further student number increases of the order of 20–27% are feasible through exploiting operating and scale efficiency gains and also adjusting student mix. Finally the paper uses a Malmquist index approach to assess productivity change in the UK higher education. The results reveal that for a majority of institutions productivity has actually decreased during the study period.

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Seudullinen innovaatio on monimutkainen ilmiö, joka usein sijaitsee paikallisten toimijoiden keskinäisen vuorovaikutuksen kentässä. Täten sitä on perinteisesti pidetty vaikeasti mitattavana ilmiönä. Työssä sovellettiin Data Envelopment Analysis menetelmää, joka on osoittautunut aiemmin menestyksekkääksi tapauksissa, joissa mitattavien syötteiden ja tuotteiden väliset suhteet eivät ole olleet ilmeisiä. Työssä luotiin konseptuaalinen malli seudullisen innovaation syötteistä ja tuotteista, jonka perusteella valittiin 12 tilastollisen muuttujan mittaristo. Käyttäen Eurostat:ia datalähteenä, lähdedata kahdeksaan muuttujsta saatiin seudullisella tasolla, sekä mittaristoa täydennettiin yhdellä kansallisella muuttujalla. Arviointi suoritettiin lopulta 45 eurooppalaiselle seudulle. Tutkimuksen painopiste oli arvioida DEA-menetelmän soveltuvuutta innovaatio-järjestelmän mittaamiseen, sillä menetelmää ei ole aiemmin sovellettu vastaavassa tapauksessa. Ensimmäiset tulokset osoittivat ylipäätään liiallisen korkeita tehok-kuuslukuja. Korjaustoimenpiteitä erottelutarkkuuden parantamiseksi esiteltiin ja sovellettiin, jonka jälkeen saatiin realistisempia tuloksia ja ranking-lista arvioitavista seuduista. DEA-menetelmän todettiin olevan tehokas ja kiinnostava työkalu arviointikäytäntöjen ja innovaatiopolitiikan kehittämiseen, sikäli kun datan saatavuusongelmat saadaan ratkaistua sekä itse mallia tarkennettua.

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Seudullinen innovaatio on monimutkainen ilmiö, joka usein sijaitsee paikallisten toimijoiden keskinäisen vuorovaikutuksen kentässä. Täten sitä on perinteisesti pidetty vaikeasti mitattavana ilmiönä. Työssä sovellettiin Data Envelopment Analysis menetelmää, joka on osoittautunut aiemmin menestyksekkääksi tapauksissa, joissa mitattavien syötteiden ja tuotteiden väliset suhteet eivät ole olleet ilmeisiä. Työssä luotiin konseptuaalinen malli seudullisen innovaation syötteistä ja tuotteista, jonka perusteella valittiin 12 tilastollisen muuttujan mittaristo. Käyttäen Eurostat:ia datalähteenä, lähdedata kahdeksaan muuttujsta saatiin seudullisella tasolla, sekä mittaristoa täydennettiin yhdellä kansallisella muuttujalla. Arviointi suoritettiin lopulta 45 eurooppalaiselle seudulle. Tutkimuksen painopiste oli arvioida DEA-menetelmän soveltuvuutta innovaatiojärjestelmän mittaamiseen, sillä menetelmää ei ole aiemmin sovellettu vastaavassa tapauksessa. Ensimmäiset tulokset osoittivat ylipäätään liiallisen korkeita tehokkuuslukuja. Korjaustoimenpiteitä erottelutarkkuuden parantamiseksi esiteltiin ja sovellettiin, jonka jälkeen saatiin realistisempia tuloksia ja ranking-lista arvioitavista seuduista. DEA-menetelmän todettiin olevan tehokas ja kiinnostava työkalu arviointikäytäntöjen ja innovaatiopolitiikan kehittämiseen, sikäli kun datan saatavuusongelmat saadaan ratkaistua sekä itse mallia tarkennettua.

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This Master of Science Thesis deals with applying DEA (Data Envelopment Analysis) to the academic performance evaluation of graduate programs in Brazil, exploring it on a Mechanical and Production Engineering Program 2001-2003 data. The data used is that of the national assessment carried by CAPES, the governmental body in charge for graduate program assessment and certification. It is used the CCR output oriented DEA model, the CCR-Output with Assurance Region, and Window Analysis. The main findings are first that the CCR has the concerning problem of zero values of weights of outputs that is not appropriate in a sense that a graduate program has the higher efficiency score zeroing some output (e.g., number of academic papers published). Secondly, the Assurance Region method proved useful. Third, the Window Analysis also gave some light to the consistency of the performance in the time frame analysed. Also, the analysis results in the understanding that the Mechanics and Production Engineering should not be assessed jointly like currently applied by CAPES and rather should be assessed in its own field separately. Finally, the result of the DEA analysis showed some serious inconsistencies with the CAPES method. Graduate programs considered excellent has got low performance score and vice versa. This Thesis provides a strong argument in order to use DEA at least as a complimentary methodology for graduate program performance evaluation in Brazil

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The potential for the use of DEA and simulation in a mutually supporting role in guiding operating units to improved performance is presented. An analysis following a three-stage process is suggested. Stage one involves obtaining the data for the DEA analysis. This can be sourced from historical data, simulated data or a combination of the two. Stage two involves the DEA analysis that identifies benchmark operating units. In the third stage simulation can now be used in order to offer practical guidance to operating units towards improved performance. This can be achieved by the use of sensitivity analysis of the benchmark unit using a simulation model to offer direct support as to the feasibility and efficiency of any variations in operating practices to be tested. Alternatively, the simulation can be used as a mechanism to transmit the practices of the benchmark unit to weaker performing units by building a simulation model of the weaker unit to the process design of the benchmark unit. The model can then compare performance of the current and benchmark process designs. Quantifying improvement in this way provides a useful driver to any process change initiative that is required to bring the performance of weaker units up to the best in class. © 2005 Operational Research Society Ltd. All rights reserved.

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La perdurabilidad y la estrategia son temas que influyen de manera significativa en los sectores productivos. Los grupos de investigación, como eje principal de la ciencia, tecnología e innovación no son ajenos esto. Es así que requieren fortalecer su estructura logrando desempeño superior y entenderse como empresas. Esta investigación busca diseñar, para los factores de talento humano y productividad, un escenario deseado y sus estrategias de dirección para favorecer la perdurabilidad de los grupos privados de investigación en salud. La hipótesis planteada a partir de la cual se realizó el análisis es que los grupos de investigación privados, tienen mayores amenazas para perdurar porque no cuentan con una estructura propia de talento humano financiada o con soporte estructural de procesos para competir por las iniciativas de investigación disponibles. Esta hipótesis se aborda para los grupos privados de investigación que pertenecen al Programa Nacional de Ciencia y Tecnología de la Salud, área del conocimiento en ciencias de la salud y a través de la pregunta: ¿Cuáles pueden ser los escenarios posibles para lograr la perdurabilidad de los grupos privados de investigación en salud, a partir de estrategias relacionadas con los factores de talento humano y productividad? El desarrollo se hizo a través de 2 fases: Un estudio piloto donde se exploró el sector estratégico a través de las herramientas de prospectiva: MICMAC y SMIC y la fase de intervención a través de una metodología conjugada entre aplicación de AESE, un análisis DEA y una simulación de los escenarios encontrados y deseados.

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The Long Term Acute Care Hospitals (LTACH), which serve medically complex patients, have grown tremendously in recent years, by expanding the number of Medicare patient admissions and thus increasing Medicare expenditures (Stark 2004). In an attempt to mitigate the rapid growth of the LTACHs and reduce related Medicare expenditures, Congress enacted Section 114 of P.L. 110-173 (§114) of the Medicare, Medicaid and SCHIP Extension Act (MMSEA) in December 29, 2007 to regulate the LTCAHs industry. MMSEA increased the medical necessity reviews for Medicare admissions, imposed a moratorium on new LTCAHs, and allowed the Centers for Medicare and Medicaid Services (CMS) to recoup Medicare overpayments for unnecessary admissions. ^ This study examines whether MMSEA impacted LTACH admissions, operating margins and efficiency. These objectives were analyzed by comparing LTACH data for 2008 (post MMSEA) and data for 2006-2007 (pre-MMSEA). Secondary data were utilized from the American Hospital Association (AHA) database and the American Hospital Directory (AHD).^ This is a longitudinal retrospective study with a total sample of 55 LTACHs, selected from 396 LTACHs facilities that were fully operational during the study period of 2006-2008. The results of the research found no statistically significant change in total Medicare admissions; instead there was a small but not statistically significant reduction of 5% in Medicare admissions for 2008 in comparison to those for 2006. A statistically significant decrease in mean operating margins was confirmed between the years 2006 and 2008. The LTACHs' Technical Efficiency (TE), as computed by Data Envelopment Analysis (DEA), showed significant decrease in efficiency over the same period. Thirteen of the 55 LTACHs in the sample (24%) in 2006 were calculated as “efficient” utilizing the DEA analysis. This dropped to 13% (7/55) in 2008. Longitudinally, the decrease in efficiency using the DEA extension technique (Malmquist Index or MI) indicated a deterioration of 10% in efficiency over the same period. Interestingly, however, when the sample was stratified into high efficient versus low efficient subgroups (approximately 25% in each group), a comparison of the MIs suggested a significant improvement in Efficiency Change (EC) for the least efficient (MI 0.92022) and reduction in efficiency for the most efficient LTACHs (MI = 1.38761) over same period. While a reduction in efficiency for the most efficient is unexpected, it is not particularly surprising, since efficiency measure can vary over time. An improvement in efficiency, however, for the least efficient should be expected as those LTACHs begin to manage expenses (and controllable resources) more carefully to offset the payment/reimbursement pressures on their margins from MMSEA.^

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The Kingdom of Bhutan is a small landlocked country in South Asia, located in the eastern Himalayas, and bordered by India and China. Bhutan is a small and fragile economy with a population of about 687,000. Nevertheless, its banking system plays an essential role in the growth and development of the country. This paper analyzes the financial performance, the development and growth of bank and non-bank financial institutions of Bhutan for the period 1999-2008 using both traditional and data envelopment analysis (DEA). The DEA analysis shows that financial institutions in are efficient and Bhutan National Bank has been the most efficient one. Overall, the paper finds that the ROE of the financial institutions in Bhutan are comparable to the international banks.

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The influence of IT investment on hospital efficiency and quality are of great interest to healthcare executives as well as insurers. Few studies have examined how IT investments influence both efficiency and quality or whether there is an optimal IT investment level that influences both in the desired direction. Decision makers in healthcare wonder if there are tradeoffs between their pursuit of hospital operational efficiency and quality. Our study involving a 2-stage double bootstrap DEA analysis of 187 US hospitals over 2. years found direct effects of IT investment upon service quality and a moderating effect of quality upon operational efficiency. Further, our findings indicate a U-shaped relationship between IT investments and operational efficiency suggesting that IT investments have diminishing returns beyond a certain point.

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Dissertação de Mestrado, Gestão Empresarial, Faculdade de Economia, Universidade do Algarve, 2016

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Benchmarking is an important tool to organisations to improve their productivity, product quality, process efficiency or services. From Benchmarking the organisations could compare their performance with competitors and identify their strengths and weaknesses. This study intends to do a benchmarking analysis on the main Iberian Sea ports with a special focus on their container terminals efficiency. To attain this, the DEA (data envelopment analysis) is used since it is considered by several researchers as the most effective method to quantify a set of key performance indicators. In order to reach a more reliable diagnosis tool the DEA is used together with the data mining in comparing the sea ports operational data of container terminals during 2007.Taking into account that sea ports are global logistics networks the performance evaluation is essential to an effective decision making in order to improve their efficiency and, therefore, their competitiveness.

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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.

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Ce guide présente la méthode Data Envelopment Analysis (DEA), une méthode d'évaluation de la performance . Il est destiné aux responsables d'organisations publiques qui ne sont pas familiers avec les notions d'optimisation mathématique, autrement dit de recherche opérationnelle. L'utilisation des mathématiques est par conséquent réduite au minimum. Ce guide est fortement orienté vers la pratique. Il permet aux décideurs de réaliser leurs propres analyses d'efficience et d'interpréter facilement les résultats obtenus. La méthode DEA est un outil d'analyse et d'aide à la décision dans les domaines suivants : - en calculant un score d'efficience, elle indique si une organisation dispose d'une marge d'amélioration ; - en fixant des valeurs-cibles, elle indique de combien les inputs doivent être réduits et les outputs augmentés pour qu'une organisation devienne efficiente ; - en identifiant le type de rendements d'échelle, elle indique si une organisation doit augmenter ou au contraire réduire sa taille pour minimiser son coût moyen de production ; - en identifiant les pairs de référence, elle désigne quelles organisations disposent des best practice à analyser.

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This article explores how data envelopment analysis (DEA), along with a smoothed bootstrap method, can be used in applied analysis to obtain more reliable efficiency rankings for farms. The main focus is the smoothed homogeneous bootstrap procedure introduced by Simar and Wilson (1998) to implement statistical inference for the original efficiency point estimates. Two main model specifications, constant and variable returns to scale, are investigated along with various choices regarding data aggregation. The coefficient of separation (CoS), a statistic that indicates the degree of statistical differentiation within the sample, is used to demonstrate the findings. The CoS suggests a substantive dependency of the results on the methodology and assumptions employed. Accordingly, some observations are made on how to conduct DEA in order to get more reliable efficiency rankings, depending on the purpose for which they are to be used. In addition, attention is drawn to the ability of the SLICE MODEL, implemented in GAMS, to enable researchers to overcome the computational burdens of conducting DEA (with bootstrapping).

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The increasing use of fossil fuels in line with cities demographic explosion carries out to huge environmental impact in society. For mitigate these social impacts, regulatory requirements have positively influenced the environmental consciousness of society, as well as, the strategic behavior of businesses. Along with this environmental awareness, the regulatory organs have conquered and formulated new laws to control potentially polluting activities, mostly in the gas stations sector. Seeking for increasing market competitiveness, this sector needs to quickly respond to internal and external pressures, adapting to the new standards required in a strategic way to get the Green Badge . Gas stations have incorporated new strategies to attract and retain new customers whom present increasingly social demand. In the social dimension, these projects help the local economy by generating jobs and income distribution. In this survey, the present research aims to align the social, economic and environmental dimensions to set the sustainable performance indicators at Gas Stations sector in the city of Natal/RN. The Sustainable Balanced Scorecard (SBSC) framework was create with a set of indicators for mapping the production process of gas stations. This mapping aimed at identifying operational inefficiencies through multidimensional indicators. To carry out this research, was developed a system for evaluating the sustainability performance with application of Data Envelopment Analysis (DEA) through a quantitative method approach to detect system s efficiency level. In order to understand the systemic complexity, sub organizational processes were analyzed by the technique Network Data Envelopment Analysis (NDEA) figuring their micro activities to identify and diagnose the real causes of overall inefficiency. The sample size comprised 33 Gas stations and the conceptual model included 15 indicators distributed in the three dimensions of sustainability: social, environmental and economic. These three dimensions were measured by means of classical models DEA-CCR input oriented. To unify performance score of individual dimensions, was designed a unique grouping index based upon two means: arithmetic and weighted. After this, another analysis was performed to measure the four perspectives of SBSC: learning and growth, internal processes, customers, and financial, unifying, by averaging the performance scores. NDEA results showed that no company was assessed with excellence in sustainability performance. Some NDEA higher efficiency Gas Stations proved to be inefficient under certain perspectives of SBSC. In the sequence, a comparative sustainable performance and assessment analyzes among the gas station was done, enabling entrepreneurs evaluate their performance in the market competitors. Diagnoses were also obtained to support the decision making of entrepreneurs in improving the management of organizational resources and promote guidelines the regulators. Finally, the average index of sustainable performance was 69.42%, representing the efforts of the environmental suitability of the Gas station. This results point out a significant awareness of this segment, but it still needs further action to enhance sustainability in the long term