Performance of Emergency Department (ED) physicians (MDs) is multi-faceted since it impacts multiple dimensions such as health outcomes of patients, utilization of resources, throughput of patients and timeliness of care. Therefore, the assessment of their performance demands the use of a tool that allows considering multiple evaluation criteria. However, commonly used multi-criteria evaluation methods often require assigning weights to dimensions in order to define their relative importance on a final performance score. This feature introduces subjectivity in the development of weights and has the potential to produce biased results. The purpose of this thesis research is to develop a multi-dimensional evaluation tool for evaluating performance of ED MDs. The proposed evaluation tool relies on a mathematical programming model known as Data Envelopment Analysis (DEA). The use of DEA does not ask for subjective weighting assignments for each dimension that describe the ED MDs’ performance. It is capable of considering multiple heterogeneous performance measures to identify benchmark practice and the individual improvements leading to best practice of each evaluated unit. The DEA model described here was developed from real data to assess the performance of 20 PED MDs from the Children’s Hospital of Eastern Ontario (CHEO). Multiple evaluations were run on stratified data in order to identify benchmark practice in each of seven categories of patients’ complaints and to determine the impact of accompanying MD trainees on PED MDs’ performance. For each PED MD, performance scores and improvements in each category of patients’ complaints (i.e. respiratory, trauma, abdominal, fever, gastroenterology, allergy and Ear-Nose-Throat complaints) were determined. This helped identifying the required improvements that would lead PED MDs to achieve benchmark performance. Regarding the influence of MD trainees on PED MDs’ performance, results show that most PED MDs (15 out of 20) perform better when they are not accompanied by a trainee which motivates further research to assess trade-offs between teaching and clinical performance. In summary, DEA proved to be an appropriate tool for performance evaluation of PED MDs because it helped to identify benchmark performers and provided information for performance improvements under a multi dimensional performance evaluation framework.

This thesis examines farm-level efficiency of rice farmers in the High Barind region of Bangladesh by estimating technical, allocative and economic efficiency using farm level cross section survey data. Two contrasting methods for measuring efficiency are applied: the stochastic econometric frontier and Data Envelopment Analysis (DEA). These measures are used to investigate the factors associated with technical, allocative and economic inefficiency. First, technical efficiency is computed by estimating the translog stochastic frontier in which technical inefficiency effects are modelled as a function of socioeconomic, infrastructure and environmental degradation factors in a single stage estimation technique using maximum likelihood method. Technical and scale efficiency are calculated by solving output- and input-oriented constant returns to scale (CRS) and variable returns to scale (VRS) DEA frontiers. A Tobit model is used to evaluate factors associated with technical and scale inefficiency from both input-oriented and output-oriented CRS and VRS frontiers. Same factors are analyzed as in the translog stochastic frontier. The translog stochastic frontier results show that farm households are, on average, 79 per cent technically efficient. The output-oriented DEA frontier results show that the average technical efficiency estimates are 79 and 86 per cent under CRS and VRS assumptions and the average scale efficiency is 92 per cent. The average values for technical efficiency measures and scale efficiency from the input-oriented CRS and VRS frontiers are 79, 85 and 93 per cent respectively. The translog stochastic frontier exhibits decreasing returns to scale, whereas the DEA frontier exhibits decreasing, constant and increasing returns to scale. The technical inefficiency effects model in the translog stochastic frontier and Tobit analysis for DEA frontier show that irrigation infrastructure and environmental degradation are significant factors in determining technical inefficiency. We then measure technical, allocative and economic efficiency by estimating the Cobb- Douglas stochastic frontier following the Kopp and Diewert cost decomposition technique and by running input-oriented CRS and VRS DEA frontier models. We estimate the Tobit model to analyze the factors associated with technical, allocative and economic inefficiency from the DEA frontiers. In addition, we compare the results obtained from both the Cobb- Douglas stochastic frontier and DEA frontiers. The results from the Cobb-Douglas stochastic frontier shows that the average technical, allocative and economic efficiency of farm households are 80, 77, and 61 per cent respectively. The input-oriented CRS frontier results show that farm households have, on average, 86, 91 and 78 per cent technical, allocative and economic efficiency and the corresponding VRS frontier shows that farm households are, on average, 91, 87 and 79 per cent technically, allocatively and economically efficient. An evaluation of factors associated with technical, allocative and economic inefficiency from both the Cobb-Douglas stochastic frontier and DEA frontier reveals that irrigation infrastructure and environmental degradation are the most statistically significant factors affecting technical, allocative and economic inefficiency. This implies that diesel-operated pumps and environmental degradation are not only reducing output from given inputs but are also causing sub-optimal cost-minimizing input decisions. Assessing efficiency suggests that there is a considerable amount of inefficiency among farm households and there is room for enhancing rice production through the improvement of technical, allocative and economic efficiency without resort to technical improvements. Farm households could reduce their variable production costs, on average, between 21 - 31 per cent if they could utilize their inputs in a technically and allocatively efficient manner. An evaluation of factors associated with inefficiency concludes that government electrification programmes which convert diesel pumps into electricity-operated pumps for irrigation in rural areas and policies which lead to reduced environmental degradation would reduce inefficiency, thereby increasing rice production and the welfare of farm households.

Since 2008, the world has been in recession. As daily news outlets report, this crisis has prompted many small businesses and large corporations to file for bankruptcy, which has grave global social implications. Despite government intervention and incentives to stimulate the economy that have put nations in hundreds of billions of dollars of debt, and have reduced the prime rates to almost zero, efforts to combat the increase in unemployment rate as well as the decrease in discretionary income have been troublesome. It is a vicious cycle: consumers are apprehensive of spending due to the instability of their jobs and ensuing personal financial problems; businesses are weary from the lack of revenue and are forced to tighten their operations which likely translates to layoffs; and so on. Cautious movement of cash flows are rooted in and influenced by the psychology of the players (stakeholders) of the game (society). Understandably, the complexity of this economic fallout is the subject of much attention. And while the markets have recovered much of the lost ground as of late, there is still great opportunity to learn about all the possible factors of this recession, in anticipation of and bracing for one more downturn before we emerge from this crisis. In fact, there is no time like today more appropriate for research in bankruptcy prediction because of its relevance, and in an age where documentation is highly encouraged and often mandated by law, the amount and accessibility of data is paramount – an academic’s paradise! The main objective of this thesis was to develop a model supported by Data Envelopment Analysis (DEA) to predict the likelihood of failure of US companies in the retail-apparel industry based on information available from annual reports – specifically from financial statements and their corresponding Notes, Management’s Discussion and Analysis, and Auditor’s Report. It was hypothesized that the inclusion of variables which reflect managerial decision-making and economic factors would enhance the predictive power of current mathematical models that consider financial data exclusively. With a unique and comprehensive dataset of 85 companies, new metrics based on different aspects of the annual reports were created then combined with a slacks-based measure of efficiency DEA model and modified layering classification technique to capture the multidimensional complexity of bankruptcy. This approach proved to be an effective prediction tool, separating companies with a high risk of bankruptcy from those that were healthy, with a reliable accuracy of 80% – an improvement over the widely-used Altman bankruptcy model having 70%, 58% and 50% accuracy when predicting cases today, from one year back and from two years back, respectively. It also provides a probability of bankruptcy based on a second order polynomial function in addition to targets for improvement, and was designed to be easily adapted for analysis of other industries. Finally, the contributions of this thesis benefit creditors with better risk assessment, owners with time to improve current operations as to avoid failure altogether, as well as investors with information on which healthy companies to invest in and which unhealthy companies to short.

Zugl.: Stuttgart, Univ., Diss., 2005

Zugl.: Berlin, Freie Univ., Diss., 2008

Zugl.: Frankfurt (Main), Frankfurt School of Finance & Management, Diss.

Thesis (M.S.)--University of Central Florida, 2008. / Adviser: Charles Reilly. Includes bibliographical references (p. 71-73).

Thesis (M.S.)--University of Delaware, 2006. / Principal faculty advisor: Scott A. Malcolm, Dept. of Food and Resource Economics. Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 228-234).

Dissertação (mestrado)—Universidade de Brasília, Departamento de Economia, 2006. / Submitted by Diogo Trindade Fóis (diogo_fois@hotmail.com) on 2009-10-20T10:42:12Z No. of bitstreams: 1 2006_Antonio de Lara Resende Neto.pdf: 467210 bytes, checksum: d19b51d9a0df8c71d4d656b3ec47427a (MD5) / Approved for entry into archive by Gomes Neide(nagomes2005@gmail.com) on 2010-06-08T20:00:46Z (GMT) No. of bitstreams: 1 2006_Antonio de Lara Resende Neto.pdf: 467210 bytes, checksum: d19b51d9a0df8c71d4d656b3ec47427a (MD5) / Made available in DSpace on 2010-06-08T20:00:46Z (GMT). No. of bitstreams: 1 2006_Antonio de Lara Resende Neto.pdf: 467210 bytes, checksum: d19b51d9a0df8c71d4d656b3ec47427a (MD5) Previous issue date: 2006 / Vários indicadores numéricos de performance, como os índices de Sharpe e de Sortino, são utilizados para avaliar fundos de investimento. Esses indicadores descrevem características quantitativas desses fundos permitindo dessa forma uma análise comparativa entre seus resultados. Esse estudo desenvolve um novo indicador de performance de fundos de investimento por meio de uma análise DEA (data envelopment analysis). Esse indicador é mais aconselhável quando os retornos dos fundos não têm distribuição normal e não é possível caracterizá-los corretamente usando apenas os primeiros dois momentos da distribuição de probabilidades de retorno. _________________________________________________________________________________________ ABSTRACT / Several measures of performance, like Sharpe and Sortino measures, are used to evaluate investment funds. These measures embody quantitative characteristics of funds that allow a comparative analysis between their results. This paper develops a new measure of performance for investment funds by using a DEA program. This measure is better suited for returns that are not normally distributed and therefore it is not possible to correctly characterize them using only the first two moments of their distribuitions.