Orientador: Orlando Fontes Lima Júnior / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo / Made available in DSpace on 2018-08-17T14:12:02Z (GMT). No. of bitstreams: 1 Carvalho_CarolinaCorreade_M.pdf: 3829740 bytes, checksum: fac7bcc71791eaf9213b18db3929f42a (MD5) Previous issue date: 2010 / Resumo: O uso de plataformas logísticas no mundo vem crescendo consideravelmente, mas no Brasil tal prática ainda é incipiente. Face às particularidades locais, os projetos têm que ser bem adaptados para a realidade brasileira, existindo poucos estudos que auxiliem nesta direção. O objetivo deste trabalho é propor uma metodologia para análise de benchmarking de plataformas logísticas e aplicá-la em um caso na Região Metropolitana de Campinas, São Paulo, Brasil. Como base para o estudo foi selecionado vinte e nove plataformas logísticas espalhadas pelo mundo e, por meio de Análise Envoltória de Dados (DEA), foram identificadas as que constituíram benchmarking Mundial para o projeto da plataforma logística de Campinas (PLC). Para esta analise foi adotado o modelo DEA-BCC (Variable Return to Scale- VRS) com os seguintes indicadores de desempenho; áreas das plataformas logísticas, capital investido, número de empresas atraídas e movimentação anual de carga. Após a avaliação inicial das vinte e nove plataformas pelo DEA foram identificadas sete como benchmarks mundiais e deste conjunto três foram apontadas como referências de melhores práticas para a PLC (Atlantic Gateway-Halifax Logistics Park, Canadá; Raritan Center, USA; e Rickenbacker Global Logistics Park USA). Ao mesmo tempo um estudo qualitativo, utilizando o método de estudo de caso múltiplo, identificou outras cinco plataformas européias como referencias para o projeto; a PLAZA (Espanha); Distrito de Nola (Itália); Rugis (França); Bremen GVZ (Alemanha) e Dallas Logistic Hub (Estados Unidos). A partir de uma analise detalhada das plataformas selecionadas foi possível identificar sugestões de melhoria e diretrizes de concepção para a plataforma brasileira. Esta aplicação demonstrou que a estratégia proposta tem grande aplicabilidade e apresenta bons resultados para avaliação de projetos de concepção de plataformas logísticas / Abstract: The use of logistic Platform in the world has grown considerably, but in Brazil, this practice is still incipient. Given local circumstances, projects need to be well adapted to Brazilian reality, there are few studies that help in this direction. The aim of this paper is to suggest guidelines for strategic planning of the new logistics platform to be installed in Campinas, São Paulo. As a starting point of the study were selected twenty-nine logistics platforms around the world and, through Data Envelopment Analysis (DEA) have been identified that constitute the global benchmarking and were taken as the base platform design logistics of Campinas (PLC). For this analysis we adopted the DEA-BCC model (Variable Return to Scale-VRS) with the following performance indicators, areas of logistics platforms, the capital invested, number of businesses attracted and annual cargo handling. After the initial assessment of the twenty-nine platforms by DEA were identified seven as global benchmarks and this set three references have been identified as best practices for the PLC (Atlantic Gateway-Halifax Logistics Park, Canada, Raritan Center, USA; Rickenbacker Global Logistics Park and USA). At the same time a qualitative study, using the method of multiple case study, identified five more platforms PLAZA (Span), Distrito de Nola (Italy), Rugis (France) Bremen GVZ (German) e Dallas logistic Hub (USA) that could be included as references for the enterprise. From a detailed analysis of selected platforms were able to identify suggestions for improvements and design guidelines for the Brazilian platform. This application demonstrated that the proposed strategy has wide applicability and gives good results for project evaluation design of logistics platforms / Mestrado / Transportes / Mestre em Engenharia Civil

With an increasing number of students enrolling at higher education institutions in South Africa, it has become important to investigate whether these institutions are using their resources adequately. This study uses data envelopment analysis (DEA) to estimate the efficiency of 23 South African tertiary education institutions based on both teaching and research outputs. Using DEA we are able to rank South African universities according to their use of resources in these two areas. These rankings can identify institutions which are performing well and also those which require improvement. The effect that merging institutions has on this efficiency is also determined. Owing to the limited sample size, variable reduction techniques, including the efficiency contribution measure (ECM) and principal components analysis (PCA-DEA), were used to improve the discrimination of the analysis.

Firms or organisations implement performance assessment to improve productivity but evaluating the performance of firms or organisations may be complex and complicated due to the existence of conflicting objectives. Data Envelopment Analysis (DEA) is a non-parametric approach utilized to evaluate the relative efficiencies of decision making units (DMUs) within firms or organizations that perform similar tasks. Although DEA measures the relative efficiency of a set of DMUs the efficiency scores generated do not consider the decision maker’s (DM’s) or expert preferences. DEA is used to measure efficiency and can be extended to include DM’s and expert preferences by incorporating value judgements. Value judgements can be implemented by two techniques: weight restrictions or constructing an equivalence Multiple Objective Linear Programming (MOLP) model. Weight restrictions require prior knowledge to be provided by the DM and moreover the DM cannot interfere during the assessment analysis. On the other hand, the second approach enables the DM to interfere during performance assessment without prior knowledge whilst providing alternative objectives that allow the DM to reach the most preferred decision subject to available resources. The main focus of this research was to establish interactive frameworks to allow the DM to set targets, according to his preferences, and to test alternatives that can realistically be measured through an interactive procedure. These frameworks are based on building an equivalence model between extended DEA and MOLP minimax formulation incorporating an interactive procedure. In this study two frameworks were established. The first is based on an equivalence model between DEA trade-off approach and MOLP minimax formulation which allows for incorporating DM’s and expert preferences. The second is based on an equivalence model between DEA bounded model and MOLP minimax formulation. This allows for integrating DM’s preferences through interactive steps to measure the whole efficiency score (i.e. best and worst efficiency) of individual DMU. In both approaches a gradient projection interactive approach is implemented to estimate, regionally, the most preferred solution along the efficient frontier. The second framework was further extended by including ranking based on the geometric average. All the frameworks developed and presented were tested through implementation on two real case studies.

An airport is an important piece of infrastructure in air transportation system. This project focuses on measuring and ranking the efficiency of airports in the United States using the basic DEA, Ranking DEA, Goal programming and DEA and TOPSIS. In general, airport authorities of relatively inefficient airports are trying to benchmark the operational strategies of efficient airports. This project focuses on evaluating hub airports in the United States. ATL, LAX, and MEM airports are relatively efficient among forty four hub airports in the United States based on the performances and airport facilities of the 2000 year when the results of all applied methods in this project, the basic DEA ranking, the Cross Efficiency ranking, the Andersen-Petersen ranking and TOPSIS ranking method, are compared. The implication of this project is that airport authorities in the United States would benchmark these three airports to maximize operation and management efficiency for their airports. In general, most of the airports are handling passengers and freight. Therefore, ATL and LAX would be the most efficient hub airports in the United States. The capacities of airport facilities and more appropriate input data like financial data should be considered in the follow up research. / Master of Science

About 75% of human food in the 21st century consists of just 12 crops, though specific crops vary among nations. Modern technology has allowed development of innovative food and non-food uses for these commodities. For instance, corn (maize (Zea mays L.)) is produced for many purposes, including food, livestock feed, biofuels, fiber for clothing, etcetera. Scientists project the human population will reach 9.2 billion in next 20 years—an 18% increase from the 2020 population of 7.8 billion—resulting in increased demand for corn and other crops. Hence, farmers must increase total crop production to meet demand; however, local agricultural resource endowments such as climate, land and water availability, and soil attributes constrain production. Perhaps the quickest yield and efficiency improvements will result from farm management practices that tailor input applications to match accurate seasonal weather forecasts. Regional seasonal weather forecasts would enable farmers to optimize yields by reducing yield risk from extreme weather events, as well as from less extreme inter-annual weather variability. Improved productive efficiency is also critical to reducing environmental harms, e.g. contaminated runoff from excessive agricultural input use. The objective of this dissertation is to estimate the corn yield frontier and efficiency measures based on agricultural input management and weather. This research contributes to an enhanced understanding of how the corn yield frontier responds to inter-annual weather variations, and how it may shift with climate change. The first chapter summarizes three main topics—farm technology, climate change and weather variability, and methods for evaluating production efficiency. The second presents estimated corn yield frontiers and efficiency measures based on stochastic frontier and data envelopment analyses for nine North Dakota Agricultural Statistics Districts from 1994 to 2018. The third presents corn yield efficiency measures for five states: Minnesota, North Dakota, Nebraska, South Dakota, and Wisconsin from 1994 to 2018. The results reveal the major causes of inter-annual yield variation are variability of rainfall and temperature. Development of accurate growing-season weather forecasts is likely to result in high value-added for farmers and downstream agribusinesses. Federal, state, and private research funding in seasonal weather forecasting would probably be well invested.

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Toda organización necesita, medir su desempeño como requisito previo para mejorar. Este trabajo propone un modelo para evaluar el sector asegurador argentino, analizando la eficiencia y productividad relativa de las compañías de seguros durante el periodo 2002 - 2011, utilizando la técnica de frontera eficiente conocida como Análisis Envolvente de Datos y el Índice de Malmquist. Los resultados indican que en los últimos diez años el mercado no ha mejorado su productividad. Una de las causas se atribuye al deterioro tecnológico sufrido en el periodo. Las empresas necesitaron más recursos para seguir produciendo lo mismo, no han invertido en pos de mejorar sus prácticas administrativas y tecnológicas, o bien sus inversiones no se han traducido en un aumento en el nivel de primas negociadas. Palabras clave: Mercado asegurador, Eficiencia, Productividad, Data Envelopment Analysis, Índice de Malmquist. / All organizations need to measure their performance as a prerequisite for improvement. This thesis proposes a model to evaluate the Argentine insurance sector, analyzing efficiency and relative productivity during the period 2002-2011, using a technique of efficient frontier known as Data Envelopment Analysis and Malmquist Index. The results indicate that in the last ten years the market has not improved its productivity. One of the causes is attributed to the technological decline suffered in the period. Companies needed more resources to continue producing at the same level, they have not invested in pursuit of improving its administrative and technological practices, or investments have not translated into an increase in the level of negotiated premiums. Key words: Insurance market, Efficiency, Productivity, Data Envelopment Analysis, Malmquist Index.

The concept of efficiency measurement is based on the definition of a frontier that envelopes observed production plans. The effect of pollution on productive efficiency is typically studied by considering pollution as not freely disposable (i.e., there is a cost incurred to dispose of pollution) or by assigning shadow prices to pollution outputs. However, the frontier along with the required technological assumptions (such as convexity) needed for a definition of a frontier may be replaced with the concept of pair-wise dominance. With data from a manufacturing facility, the use of pair-wise dominance allows one to consider a wide spectrum of inputs and outputs. Pair-wise dominance can also be applied to segregate production plans into sets according to their relative environmental performance and productive efficiency. These sets are used to identify reference production plans upon which distance-based measures of performance are defined. This research applies pair-wise dominance to time series data from a printed circuit board manufacturing facility to illustrate the approach. The proposed approach is compared to the Data Envelopment Analysis (DEA) approach. It was observed that for detailed production data the proposed approach was more informative concerning the measurement of productive efficiency than the standard methods. / Ph. D.

This dissertation explores the use of the efficiency performance measurement paradigm (EM), in terms of its concepts and applications, as an ex-ante mechanism to evaluate enterprise performance and inform enterprise design. The design of an enterprise is driven by decisions that include, but not limit to, which strategies to implement, how to allocate resources, how to shift operating patterns, and how to boost coordination among enterprises, among others. Up to date, EM has been mainly used as a descriptive mechanism, but the fundamental reason for measuring performance in an ex-post fashion, i.e., how well an enterprise does, is also valid in the context of design decisions, i.e., ex-ante evaluation. The contrast between the ex-post and ex-ante use of EM relates to the measurement purpose, i.e., why to measure. Ex-post measurement focuses on evaluating 'what happened' (non-disruptive) while ex-ante measurement emphasizes in informing design decisions exploring changes in current settings (more disruptive). Within this context and to achieve the purpose above, this dissertation is supported by theoretical insights and complemented with three empirical studies. The theoretical insights relate to facts that support, connect to, and challenge (i.e., facilitate or impede) the ex-ante use of EM for enterprise evaluation and informing enterprise design. Those insights are based on the efficiency performance measurement, organizational design and enterprise systems engineering literature. Meanwhile, the three empirical studies situate the application of EM as an ex-ante mechanism to inform evacuation management, bank branch management, and power plants. The theoretical and empirical results indicate that EM is well suited for both evaluating enterprise performance and informing design decisions. The main contribution of this dissertation to enterprise stakeholders is that EM can be not only used to answer how well the enterprise did, but also how well it could do if certain design decisions are taken. / Ph. D.

Data envelopment analysis (DEA) is a relative technical efficiency measurement tool, which uses operations research techniques to automatically calculate the weights assigned to the inputs and outputs of the production units being assessed. The actual input/output data values are then multiplied with the calculated weights to determine the efficiency scores. Recent variants of the DEA model impose upper and lower bounds on the weights to eliminate certain drawbacks associated with unrestricted weights. These variants are called weight restriction DEA models. Most weight restriction DEA models suffer from a drawback that the weight bound values are uncertain because they are determined based on either incomplete information or the subjective opinion of the decision-makers. Since the efficiency scores calculated by the DEA model are sensitive to the values of the bounds, the uncertainty of the bounds gets passed onto the efficiency scores. The uncertainty in the efficiency scores becomes unacceptable when we consider the fact that the DEA results are used for making important decisions like allocating funds and taking action against inefficient units. In order to minimize the effect of the uncertainty in bound values on the decision-making process, we propose to explicitly incorporate the uncertainty in the modeling process using the concepts of fuzzy set theory. Modeling the imprecision involves replacing the bound values by fuzzy numbers because fuzzy numbers can capture the intuitive conception of approximate numbers very well. Amongst the numerous types of weight restriction DEA models developed in the research, two are more commonly used in real-life applications compared to the others. Therefore, in this research, we focus on these two types of models for modeling the uncertainty in bound values. These are the absolute weight restriction DEA models and the Assurance Region (AR) DEA models. After developing the fuzzy models, we provide implementation roadmaps for illustrating the development and solution methodology of those models. We apply the fuzzy weight restriction models to the same data sets as those used by the corresponding crisp weight restriction models in the literature and compare the results using the two-sample paired t-test for means. We also use the fuzzy AR model developed in the research to measure the performance of a newspaper preprint insertion line. / Master of Science