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This thesis deals with DEA models (Data envelopment analysis), which are models for measuring the efficiency of peer decision making units (DMUs). First part focus on basic DEA models (CCR model, BCC model) and this part is extended by new CH-CCR model, which considering that the variables (inputs or outputs) are usually strongly correlated. In second part is included description of network-based models, which are afterwards applicated on data of FRS CR (Fire Rescue Service of the Czech Republic). Using this models is solved efficiency of FRS CR through the regions.

The target of this thesis is to compare suitable application methods at intercompany comparison. Used methods are divided into three sections. In the first part, the multiple criteria decision methods are described. Within this part, common used methods (method of simple order, method of standard variables, method of distance from virtual subject) and more advanced methods taught in the class of Theory of decision (WSA, Topsis, ELECTRE III, Mappac and other) are described. As part of these methods the determination preferences are defined. Further Data envelope analyses are introduced. The last method mentioned in the theoretical part is index IN05 method. All of the above described methods are applied to the beer industry. In conclusion the comparison of all used methods is presented.

In today's fiercely competitive environment, not only in the tourism sector, we see a rise in the need to identify the weak and strong sides of the performance of the entire branch network of a travel agency, as well as of its components, the particular branches. This problem can be approached using the process of benchmarking. This method is currently widely used to compare the similarly behaving systems and processes in all areas of human activity. Data envelopment analysis models can be used as one of the methods of benchmarking. This thesis deals first with the theoretical description of the basic models of data envelopment analysis. It then moves on to concentrate on the description of the network-based models, which are then used in the practical part of the thesis. In this last part, it compares selected travel agency branches and identifies the deficiencies in particular areas of their performance.

Diploma thesis describes the problem of quantitative expression of the quality of life. For this purpose is used one of the most widespread indicators of quality of life - Human Development Index. This paper describes its basic characteristics, method of calculation, its advantages and drawbacks. One of the objectives of this paper is the elimination of these shortcomings by alternative method of calculation. The methods of multi-criteria evaluation of alternatives and data envelopment analysis models are applied for these purposes. One part of this paper is a theoretical description of the tasks of multi-criteria decision making and their classification into the methods for multi-criteria evaluation of alternatives and into the methods of multi-criteria linear programming. In this paper are used methods WSA, TOPSIS and PROMETHEE, based on the definition of the theoretical characteristics of the methods of multi-criteria evaluation of alternatives. These methods are applied on the source data, obtained from a model of the human development index. After calculation, the results obtained are analyzed and written into the conclusion. Another alternative approach to obtain the level of human development is to evaluate the degree of efficiency of countries using data envelopment analysis models in comparison with the human development index. For these purposes is written the theoretical background, which defines the basic types of data envelopment analysis models. These theoretical findings serve as the basis for the practical analysis by the BCC output oriented model and by the corresponding model of super efficiency. The results of these calculations are analyzed and subsequently written into the final conclusion.

This study implements radial and non-radial Data Envelopment Analysis (DEA) models to assess eco-efficiency and eco-productivity of the 50 states in the United States in 2018. The models are based on three inputs (capital stock, employment, and energy consumption), a single desirable output (real gross domestic product) and a single undesirable output variable (CO2 emissions). The radial DEA models reveal that at least 32 states are operated efficiently. Five states perform at the most optimal scale size, whereas 17 states have considerable potential to boost their productive efficiencies by enlarging available resources, and 28 states are overinvested in their input variables given their current output levels. The non-radial DEA models show that, overall, the states’ capital efficiency is very high, whereas energy and emission efficiencies are very low. The states’ eco-productivity is relatively higher than the eco-efficiency levels. In the second stage of the analysis, non-parametric statistical tests and Tobit regressions are conducted for further investigation. According to the non-parametric statistical test, high capital stock, labor force, and energy usage do not affect the states’ productive efficiency. However, states with low carbon dioxide emissions have significantly higher eco-efficiency and eco-productivity levels. The Tobit regression results illustrate that nuclear power and renewable energy consumption significantly affect the states’ relative efficiencies.

To date, police organizations have not been rigorously analyzed by organizational scholars and most analysis of these organizations has been captured through a single construct. The purpose of this study is to develop confirmatory police organizational analysis by validating a multi-dimensional conceptual framework that explains the relationships among three constructs: environmental constraints, the design structures of police organizations, and organizational performance indicators. The modeling is deeply rooted in contingency theory, and the influence of isomorphism and institutional theory on the covariance structure model are investigated. One hundred and thirteen local police organizations from the State of Florida are included in this non-experimental, cross-sectional study to determine the direct effect of the environmental constraints on the performance of police organizations, the indirect effect of environmental constraints on the performance of police organizations via the organizational design structure of police organizations, and the direct affect of organizational design structure on performance of police organizations. For the first time, structural equation modeling and data envelopment analysis are used together to confirm the effects of the environment on police organization structure and performance. The results indicate that environmental social economic disparity indicators have a large positive effect on police resources and a medium effect on police efficiency. Propensity of crime indicators has a large negative effect on police resources, and population density has a small to medium negative effect on crime clearance. Structure has a much smaller effect on performance than the environment. The results of the efficiency analysis revealed unexpected findings. Three of the top five largest police organizations in the study scored maximum efficiency. The cause of this unexpected result is explained and confirmed in the covariance model. The study methodology and results enhances the understanding of the relationship among the constructs while subjecting environmental and police organizational data to two comprehensive analytical techniques. The policy implications and practical contributions of the study provide new knowledge and information to organizational management of police organizations. Furthermore, the study establishes a new approach to police organizational analysis and police services management research called Police Services Management Research (PSMR) that encompasses a variety of disciplines with a primary responsibility of theory building and the selection of theoretical framework.

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En el presente estudio doctoral se aborda el tema de la Gestión de los Residuos Sólidos Urbanos (GIRSU) con el objetivo de describir los sistemas y analizar la eficiencia en la gestión táctica de los mismos. Para ello, se seleccionaron dos regiones de interés, el Sudodeste de la Provincia de Buenos Aires (SOBA) y Cataluña, a partir de los cuales se recolectaron los datos necesarios de 18 y 19 municipios respectivamente, para evaluar la eficiencia relativa de los mismos mediante el análisis DEA. Se realizaron diferentes modelos DEA, con rendimientos constantes y variables, para obtener distintos resultados, así como las recomendaciones necesarias para llevar los municipios hacia la eficiencia. Los resultados indican a Bahía Blanca como la única localidad del SOBA que registra la máxima eficiencia en todos los análisis, y a Terrasa en la región de Cataluña. Posteriormente, se utilizan los resultados obtenidos en DEA para entrenar Redes Neuronales Artificiales y formular modelos de Regresión Lineal, que ayuden en la toma de decisiones de largo plazo, respecto a la proyección de aumento de generación de RSU así como la planificación inicial de recursos para que los municipios del SOBA migren a un sistema de GIRSU que valorice los RSU, como el instalado en Cataluña. Los resultados muestran que sólo las localidades de Bahía Blanca, Carmen de Patagones, Laprida, Monte Hermoso y Villalonga, necesitarían ampliar su capacidad actual de camiones para migrar a un sistema por contenedores (además de adaptarlos con la tecnología necesaria), mientras que, en cuestión de disponibilidad de personal, todas las localidades muestran estar sobradas y preparadas para migrar a dicho sistema. / In the present thesis, the tactical management of Municipal Solid Waste Management (MSW) is addressed with the aim of describing the system and analyzing its efficiency. For this, two regions of interest were selected, the Southeast of the Province of Buenos Aires of Argentina (SOBA) and Catalonia, Spain. For this purpose, data from 18 and 19 municipalities respectively for each region was collected to evaluate the relative efficiency through the DEA analysis. Different DEA models were applied with constant and variable yields to obtain different efficiency results as well as the recommendations to enhance the efficiency of the municipalities. The results indicate that Bahia Blanca is the only SOBA locality that registers maximum efficiency in all the performed analyses. Similarly, Terrasa is the efficient locality in the region of Catalonia. Later, the results obtained in DEA were used to train Artificial Neural Networks and to formulate models of Linear Regression that support the decision-making process in the long run, considering the expected increment in the MSW generation waste. In order to migrate to a system that recovers the resources from waste, as it is performed in Catalonia), the municipalities from the SOBA Bahía Blanca, Carmen de Patagones, Laprida, Monte Hermoso, and Villalonga need to expand the current capacity of trucks to migrate to a system by containers (in addition to adapting them with the necessary technology). However, in regard to the availability of personnel, the localities do not require to make any adjustment.