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Banking industry has been playing a significant role in the process of economic development of Taiwan. There exists an inseparable relationship between its operation quality and the steady growth of national economy. Nevertheless, the drastically increasing numbers of bank in the recent years have caused a vicious competition in this industry. Meanwhile, the global economic recession also leads to the continuous rise of the percentage of nonperforming loans, ever-reducing profit earning as well as the financial chaos and crisis in the banking industry. This study adopts a more reliable efficiency evaluation method------ Data Envelopment Analysis(DEA) to judge the operation performance of banks. Besides, the CCR model and BCC model in DEA (Data Envelopment Analysis) are employed to explore whether the source of low efficiency comes from pure technical efficiency or from scale efficiency. Through slack variable analysis, this study suggests some room of improvement for the input and output of the low-efficiency banks. In view that the percentage of nonperforming loans is one of the essential factors for evaluating the operation performance of banks, this study puts it in the output variable of DEA so as to overcome the paradoxical isotonicity being caused. After verification is made by the study, the results show that it is really workable.

The following thesis documents application of Data Envelopment Analysis method on the sample of eight banks which were functioning on the Czech banking market during the period 2007 -- 2010 in order to measure their technical efficiency. Thesis consists of two major parts -- theoretical and practical one. The first part includes main principles, areas of application of the method and theoretical base of the DEA which will be used in the practical part. Second part presents brief description of the trends on the Czech banking market and it's development during the period 2007 -- 2010. Practical part also contains results of the measurement, its interpretation and analysis of main reasons of banks' inefficiency.

Paratransit service operators in Canada are under increasing pressure to improve the operational productivity of their services due to increased demand and tightening financial constraints. To achieve this, Paratransit operators need to know their performance as compared to peer systems and the best practices within the industry. This will enable each operator to identify where and how much improvement should be made in order to be on a par with the industry?s best practices. Little research effort, however, has been devoted to the issue of how to measure and compare paratransit efficiency in a consistent and systematic manner. <br /><br /> This research focuses on evaluating the level of efficiency of individual paratransit systems in Canada with the specific objective of identifying the most efficient service agencies and the sources of their efficiency. By identifying the most efficient systems along with the influencing factors, it is possible that new service policies and management and operational strategies could be developed for improved resource utilization and quality of services. To achieve this objective, this research applies the analysis methodology called Data Envelopment Analysis (DEA) approach which is a mathematical programming based technique for determining the efficiency of individual systems as compared their peers involving multiple performance measures. Annual operating data from Canadian Urban Transit Association for Canadian paratransit systems of year 2001, 2002 and 2003 are used in this analysis. Regression analysis is performed to identify the possible relationship between the efficiency of a paratransit system and some measurable operating, managerial and other factors which could have an impact on the performance of paratransit systems. The regression analysis also allows for the calculation of confidence intervals and bias for the efficiency scores in order to assess their precision.

Paratransit service operators in Canada are under increasing pressure to improve the operational productivity of their services due to increased demand and tightening financial constraints. To achieve this, Paratransit operators need to know their performance as compared to peer systems and the best practices within the industry. This will enable each operator to identify where and how much improvement should be made in order to be on a par with the industry?s best practices. Little research effort, however, has been devoted to the issue of how to measure and compare paratransit efficiency in a consistent and systematic manner. <br /><br /> This research focuses on evaluating the level of efficiency of individual paratransit systems in Canada with the specific objective of identifying the most efficient service agencies and the sources of their efficiency. By identifying the most efficient systems along with the influencing factors, it is possible that new service policies and management and operational strategies could be developed for improved resource utilization and quality of services. To achieve this objective, this research applies the analysis methodology called Data Envelopment Analysis (DEA) approach which is a mathematical programming based technique for determining the efficiency of individual systems as compared their peers involving multiple performance measures. Annual operating data from Canadian Urban Transit Association for Canadian paratransit systems of year 2001, 2002 and 2003 are used in this analysis. Regression analysis is performed to identify the possible relationship between the efficiency of a paratransit system and some measurable operating, managerial and other factors which could have an impact on the performance of paratransit systems. The regression analysis also allows for the calculation of confidence intervals and bias for the efficiency scores in order to assess their precision.

Abstract Promoting management efficiency is always a big concern either to profit-making or non-profit-making organizations. An efficient firm indicates that the leader manages well. To a profit-making unit, the term ¡§efficiency¡¨ means ¡§rapid production¡¨, ¡§the offer of distribution¡¨ and ¡§related services¡¨ which could save time and the good use of manpower and resources are also included. Therefore, the promotion of management efficiency becomes an important issue for the organization to survive successfully and to fight with other competitors. This study was to present the evaluation of management efficiency of some commercial banks in Taiwan. Some factors were selected as the ¡§input items¡¨ and ¡§output items¡¨from the financial reports of these commercial banks in Taiwan from 1999 to 2001. It evaluated the efficiency performance of these commercial banks according to the evaluation theory of Farrell and Data Envelopment Analysis. The relative efficiency in the process of the transferring from ¡§input items¡¨ to ¡§output items¡¨ was also concerned. From the changes in ¡§input items¡¨, it could show how efficiency value changes. By these two analyses (Slack Variables Analysis and Scale Efficiency Analysis), the results could show a direction in order to improve the efficiency of all these commercial banks. 38 commercial banks were selected and evaluated in this research. The information collected from financial reports was to construct a model in order to evaluate management efficiency of all subjects. This investigation involved ¡§overall efficiency ¡¨, ¡§overall technical efficiency¡¨, ¡§pure technical efficiency¡¨, ¡§scale efficiency¡¨, and ¡§allocative efficiency ¡¨. Apart from these calculation, all subjects were grouped into three parties: namely ¡§old commercial banks¡¨, ¡§new commercial banks¡¨ and ¡§commercial banks upgraded from credit cooperative¡¨; by cross and vertical analysis the result provided the comparison of management efficiency among these three groups. Using the CCR and BCC models, the overall efficiency value and technical efficiency became available. The Return to Scale was derived by the use of CCR model. The first finding from financial reports in 2001 showed that the top five as the most efficient banks among 38 subjects were Cathy United Bank, Taishin International Bank, Taipei Bank, Fubon Commercial Bank and Bank of Kaohsiung respectively. The bottom five subjects were Chung Shing Bank, Kao Shin Commercial Bank, Cota Commercial Bank, Pan Asia Bank and Union Bank of Taiwan. The Second finding showed that the ¡§old commercial banks¡¨ represented the highest efficiency value in the analysis, which was based on 2001 financial reports. Both the ¡§new commercial banks¡¨ and ¡§commercial banks upgraded from credit cooperative¡¨ had efficiency value, which was below the average efficiency value of all subjects. This was different from the result based on financial report in 2000, which showed that the ¡§new commercial banks¡¨ had the highest efficiency value. This represented the overall efficiency of the ¡§old commercial banks¡¨ was improving and that of the ¡§new commercial banks¡¨ was getting worse. Thirdly, through ¡§Slack Variables Analysis (SVA)¡¨, the result would indicate a direction for these ¡§less-efficient¡¨ subjects for improvement. The decision-maker could follow this direction to restructure or reallocate resources, and refer to the allocation of resources and strategies application of those subjects, which with overall efficiency, in order to improve its management efficiency and reach the optima production. The fourth, using "Analysis of Variance (ANOVA)" to test whether the efficiency values were different between these three groups. The result showed that the efficiency values between these three groups were significantly different in 2001. According to Scheffe's S method, the difference was derived from the scale efficiency between the groups of "new commercial banks" and "commercial banks upgraded from credit cooperative". Finally, according to the regression analysis, the result showed that the overall efficiency measure is negatively related to overdue loans but positively related to BIS ratio. The other items, such as the numbers of branch, the numbers of employee, capital and the numbers of ATM, which were non-related to the overall efficiency.

The ginger industry is one of the key industries identified by the Fiji government in its diversification strategy to accommodate the remnants of the withdrawal of the European Union’s sugar preferences. There is considerable pressure on small industries such as ginger in search of ways in which they can be made to operate efficiently and sustain the economy. Expansion of commercial agriculture into marginal land which is unsustainable adds enormous pressure on land causing soil erosion. Coupled with this is the quality issue which is a serious problem of ginger production and has reduced its competitiveness over the years. This study focuses on two types of losses in ginger production to provide an integrated approach to policy making and computing production losses. One is the observable output loss at the farm site that is not sold due to sub-standard quality related to disease and the other is the unobserved output loss due to inefficient production. The research attempts to answer the question of whether the Fiji ginger farmers are producing efficiently, and at what levels. The relative importance of each input in ginger production is examined. The study undertakes to determine the effects of key variables on farm efficiency. Also examined is the overall farm profiles based on the efficiency rankings of the ginger producers. Furthermore, this research attempts to determine factors that influence soil erosion, and those that influence the observed ginger loss. Using cross-sectional data from a ginger farm survey conducted in June 2007, this research estimates a stochastic production frontier which incorporates soil erosion as an input in the framework. Very few studies have looked at the impact of soil erosion in this context; hence, this study fills the gap by incorporating land quality in the analysis. Farms were found to produce at 69% of their maximum potential output and soil erosion resulted in 6.8% loss in ginger output. This also implies that using the same resources, technology and farming techniques efficiently can lead to a 31% increase in output. While unobserved loss to farm income is a 27% (F$4.6m) increase over the observable loss at farm site, the revenue loss to the whole industry is at least 30% (F$5.07m). Profit was a key determinant of both losses, but staying on farm, slope of land, manure use and hot water treatment affected the observed but not unobserved loss. Although farmer education had no effect on both losses, it was important for undertaking soil conservation. Fiji is in a good position to increase production as education, age and experience of farmers were not significant determinants of efficiency. Thus, displaced farmers from sugar cane farming (given serious concerns of the viability of that industry) can be encouraged to move with ease into ginger as an alternative livelihood. Lastly, the study highlights some practical implication which calls for an integrated package of policies related to use of best farming techniques, land tenure and, agricultural extension and support services for sustainable agricultural growth.

The aim of this study is to measure Swedish district courts’ technical efficiency for the period between 2000 and 2016 by applying the stochastic distance function approach. Although a very important issue from a policy perspective, a few studies have measured the efficiency of the courts. The narrow literature is also limited to using nonparametric methods, such as the DEA. The stochastic distance function has not been used for this purpose before and hence this is the first study to do so. The estimated mean score of technical efficiency is 93%. However, this study observes that efficiency levels increase throughout the studied period. Large variations between efficiency levels of different courts are also observed. Policy recommendations are to learn from courts with higher efficiency levels.

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / It aims to analyze the socioeconomic profile of producers of irrigated fruit in the Cariri and measure the technological level, identifying the factors that influence each level. The measurement of technological index of fruit growers allows you to identify the level of technology used by producers. Have the technical efficiency scores of caririenses fruit growers and the identification of the effects of socioeconomic variables on efficiency levels allowed capture the impact of these determinants along different points of the conditional distribution of technical efficiency. In preparing the technological index was used factor analysis, and to measure the index of efficiency scores were applied in determining the analysis of data envelopment analysis (DEA) models and quantile regression. Came indicators of primary sources, collected in 2014, directly, with 86 growers located in six municipalities of the Cariri. The results show that in most cases, the growers (53.49%) have only to primary education, and only 16.28% can only sign his name. You can still see that 31.40% of producers have secondary education and that is down the number of illiterate farmers (3.49%) and they have 30-50 years of age (66.67%) and also that 75 , 68% of growers have over five years experience in the activity. The results also show that 42.66% of the fruit growers of the region not participating unions have no access to any type of credit; 72.73% of these already, participating cooperatives or associations, hold some kind of credit. For the technological indexes classified as very low, there were two growers, 30 of them were considered low-tech, 53 fruit growers have considered average index and fruit grower demonstrated considered high index, 0.62 to 0.78, with relative frequency of 1, 16%. There were no fruit growers with very high rates for technology adoption. The variables that contributed most to indicate adoption of technological improvements in that index were Total Area, Gross Income and Total Production, result justified by the increased variance indicated by the data, a total of 24.058%, represented by the factor 1 (intensive Productivity) technology. The quantile regression was estimated, considering the technical efficiency scores obtained in the constant returns to scale model, the results show that the explanatory factors of technical efficiency for the group of more efficient producers are important in explaining the efficiency of this group. For the less efficient growers group, it is observed that among the six explanatory variables, only management index, credit and education played irrelevant role in explaining variations in technical efficiency level, since the coefficients of these variables were not statistically significant, in this case, there is no difference between fruit growers with access to credit and those without and between grade levels, ie, if the producer has secondary or higher education or do not have that level of education. / Objetiva analisar o perfil socioeconÃmico dos produtores de fruticultura irrigada na regiÃo do Cariri e mensurar o nÃvel tecnolÃgico, identificando os fatores que mais influenciam cada nÃvel. A mensuraÃÃo do Ãndice tecnolÃgico dos fruticultores permite que se identifique o nÃvel de tecnologia utilizado pelos produtores. Jà os escores de eficiÃncia tÃcnica dos fruticultores caririenses e a identificaÃÃo dos efeitos das variÃveis socioeconÃmicas sobre os nÃveis de eficiÃncia permitiram captar os impactos desses determinantes ao longo de pontos distintos da distribuiÃÃo condicional da eficiÃncia tÃcnica. Para a elaboraÃÃo do Ãndice tecnolÃgico foi empregada a anÃlise fatorial, e para mensurar o Ãndice dos escores de eficiÃncia foram aplicados na anÃlise determinante os modelos de anÃlise envoltÃria dos dados (DEA) e de regressÃo quantÃlica. Os indicadores provieram de fontes primÃrias, colhidas em 2014, diretamente, com 86 fruticultores, localizados em seis municÃpios da regiÃo do Cariri. Os resultados mostram que em sua maioria, os fruticultores (53,49%) sà possuem atà o ensino primÃrio, sendo que apenas 16,28% conseguem assinar somente o nome. Ainda se pode perceber que 31,40% dos produtores possuem ensino secundÃrio e que à baixo o nÃmero de produtores analfabetos (3,49%) e eles tÃm de 30 a 50 anos de idade (66,67%) e ainda, que 75,68% dos fruticultores tÃm mais de cinco anos de experiÃncia na atividade. Os resultados tambÃm mostram que 42,66% dos fruticultores da regiÃo que nÃo participam de cooperativas nÃo tÃm acesso a algum tipo de crÃdito; jà 72,73% destes, que participam de cooperativas ou associaÃÃes, detÃm algum tipo de crÃdito. Para os Ãndices tecnolÃgicos classificados como muito baixo, houve dois fruticultores, 30 deles foram considerados de baixa tecnologia, 53 fruticultores apresentam Ãndice considerado mÃdio e um fruticultor demonstrou Ãndice considerado alto, de 0,62 a 0,78, com frequÃncia relativa de 1,16%. NÃo foram encontrados fruticultores com Ãndices muito altos para adoÃÃo de tecnologia. As variÃveis que mais contribuÃram para indicar melhorias de adoÃÃo do nÃvel tecnolÃgico do referido Ãndice foram: Ãrea Total, Renda Bruta e a ProduÃÃo Total, resultado justificado pela maior variÃncia apontada pelos dados, num total de 24,058%, representadas pelo fator 1 (uso intensivo da tecnologia Produtividade). A regressÃo quantÃlica foi estimada, considerando os escores de eficiÃncia tÃcnica obtidos no modelo de retornos constantes de escala, cujos resultados mostram que os fatores explicativos da eficiÃncia tÃcnica para o grupo de produtores mais eficientes sÃo importantes para explicar a eficiÃncia desse grupo. Para o grupo de fruticultores menos eficientes, observa-se que dentre as 6 variÃveis explicativas, apenas Ãndice de gestÃo, crÃdito e escolaridade desempenharam papel irrelevante para explicar variaÃÃes no nÃvel de eficiÃncia tÃcnica, jà que os coeficientes destas variÃveis nÃo se mostraram estatisticamente significantes, neste caso, nÃo hà diferenÃa entre os fruticultores com acesso ao crÃdito e os que nÃo possuem e entre os nÃveis de escolaridade, ou seja, se o produtor possui ensino secundÃrio ou superior ou nÃo tem esse grau de instruÃÃo.