Sediment is a major impairment in many streams and rivers in the drainage basins along the northern Gulf of Mexico. The use of geospatial technologies improves assessment and decision making for the management of environmental resources and conditions for coastal watersheds. This research focuses on the development of a conceptual qualitative model enhanced with expert input for the assessment of soil erosion potential in coastal watersheds. The conceptual model is built upon five layers (slope, precipitation, soil brightness or exposure, Kactor, and stream density) like those in a standard numerical soil loss model such as the Revised Universal Soil Loss Equation (RUSLE). The conceptual model produced a continuous surface to index erosion potential. Pearson’s correlation coefficient was used to identify variable sensitivity. The model was most sensitive to Kactor variable, followed by soil brightness, stream density, and slope. The model was not sensitive to the precipitation variable due to the lack of variability across the watershed. Expert input was added to the conceptual model for erosion potential with the Analytical Hierarchy Process (AHP). The AHP is used to value the importance of criteria, providing a quantitative weight for the qualitative data. The expert input increased the overall importance of topographic features and this increased cell counts in the upper erosion potential classes. The AHP weights were altered in 1% increments ranging from plus to minus 20% producing 201 unique runs. A quartile analysis of the runs was used to define areas of model agreement. The quartile analysis allowed for the application of an analysis mask to identify areas of increased erosion potential for improved management related decisions. The conceptual and AHP erosion potential output data, including watershed management priority rankings, were published as web mapping services for story map development as a transition to a decision support system. The limits of the story map to allow user interactions with model output rendered an unacceptable platform for decision support. The story map does offer an alternative to static reports and could serve to improve dissemination of spatial data as well as technical reports and plans like a watershed management plan.

No description available.

The history of the advancement of the agricultural frontier in Brazil has been closely related to environmental losses. Although environmental losses are sometimes inevitable in the context of agricultural expansion, they should always be minimized. This study seeks to avoid the past pattern of development by proposing a more sustainable way of expanding agriculture. The research tests whether it is possible to expand the cultivation of food and fuel crops in Brazil without compromising natural ecosystems. Brazil has a great agricultural potential considering the significant amount of lands that is suitable for agriculture with a favorable climate and topography. To supply the domestic agricultural market and for Brazil to take on a global food and biofuel export leadership position, actions should be taken to plan for this potential sustainable expansion. This planning would be an alternative means of advancing the agricultural frontier, as opposed to the deforestation previously practiced. A way to accomplish a sustainable pattern of agricultural development could be by the identification of suitable areas to support the expansion without further loss of forestlands. Pasture is a type of land use that occupies large areas in Brazil, and pastures are considered strategic resources for the effectiveness of the proposed expansion, given that they represent areas that have already been deforested and offer some type of existing infrastructure. In addition, from the current biophysical potential production - pasture based beef cattle - may be underused. The goal of this dissertation is to develop a spatial allocation model based on a multicriteria decision making and geographic information systems (GIS) using land suitability analysis to support decision makers with geospatial information about where potential areas for sugarcane and soybean expansion are located in Brazil. The multicriteria decision analysis (MCDA) consists of physical land suitability, infrastructure and socioeconomic data integration to identify suitable pasturelands for crop allocation. To enhance the reliability of the model, a team of specialists in the agricultural crops was selected to establish the criteria priorities in the model for the analysis process. The combination of their judgments gives an overall priority that feeds the multicriteria model. \"What if\" scenarios were also built to show how changes in the criteria priority weights would modify the spatial distribution of suitability classes in relation to the main model. The results yield maps that represent the distribution of suitability classes for sugarcane and soybean expansion. Pasturelands become more or less suitable for sugarcane or soybean allocation according to shifts in the influence of each criterion in the model. The designed models show results that may assist policymakers with geospatial information about priority areas where investments and efforts should be directed for sustainable agricultural expansion in Brazil. / A história do avanço da fronteira agrícola no Brasil tem sido intrinsecamente relacionada ao desmatamento. Embora perdas ambientais sejam, por vezes, inevitáveis no contexto de uma expansão agrícola, elas devem ser reduzidas sempre que possível. Tentando não seguir um padrão de desenvolvimento feito à custa de desmatamentos, e pensando numa forma mais sustentável de expansão da agricultura, nós avaliamos nesse estudo a possibilidade de expansão agrícola, para produção de alimentos e de biocombustíveis, sem o comprometimento do ecossistema natural existente no país. O Brasil tem um grande potencial agrícola atribuído à significativa quantidade de solos aptos para agricultura com clima e topografia favoráveis. Para abastecer o mercado agrícola nacional e assumir uma posição de liderança global na exportação de alimentos e biocombustíveis, ações devem ser tomadas pelo Brasil para o planejamento desse potencial de expansão. Esse planejamento seria um modelo alternativo para o avanço da fronteira agrícola, oposto aos padrões de avanço anteriores diretamente relacionados ao desmatamento. Uma forma de conseguir um padrão de desenvolvimento sustentável poderia ser pela identificação de terras agrícolas aptas à essa expansão sem estimular maiores perdas de florestas. As pastagens ocupam grandes áreas no Brasil e são consideradas recursos estratégicos para a eficácia dessa expansão, uma vez que representam áreas que já foram desmatadas e oferecem algum tipo de infraestrutura. Dado o atual potencial biofísico de produção, estima-se que as áreas de pastagem destinadas à pecuária bovina podem estar sendo subutilizadas. O objetivo desse trabalho é desenvolver um modelo de alocação espacial fundamentado numa análise de decisão multicritério e SIG com base na aptidão agrícola das terras, de forma a fornecer informações geoespaciais estratégicas aos tomadores de decisão sobre a localização das áreas potenciais para a expansão da cana-de-açúcar e soja no Brasil. A análise de decisão multicritério (MCDA) consiste na integração de dados edafoclimáticos, de infraestrutura e socioeconômicos para a identificação das áreas de pastagens aptas para a alocação dessas culturas. Para aumentar a confiabilidade do modelo, uma equipe de especialistas em cana-deaçúcar e soja foi selecionada para julgar a prioridade das variáveis no processo de análise. A combinação dos julgamentos fornece uma prioridade geral das variáveis, as quais alimentam o modelo. \"E se\" cenários foram também elaborados para mostrar como as mudanças nos pesos dos critérios modificariam a distribuição espacial das classes de aptidão com relação ao modelo principal. Os resultados são exibidos através de mapas que representam a distribuição das classes de aptidão agrícola para a alocação dos cultivos da cana-de-açúcar e soja. As pastagens tornam-se tanto mais adequadas para a alocação da cana ou soja de acordo com as mudanças na influência de cada critério no modelo. Os modelos projetados mostram resultados favoráveis que podem ajudar os tomadores de decisão com informações geoespaciais que identificam áreas prioritárias onde investimentos e esforços deveriam ser direcionados para estimular a expansão agrícola sustentável no Brasil.

A seleção de fornecedores é um problema complexo e que vem ganhando importância estratégica nas organizações, principalmente devido à inclusão de diversos atributos que podem ser especificados de acordo com as necessidades da situação, pois o fator custo não é mais o único responsável pela decisão. A relevância da sustentabilidade, em termos econômicos, ambientais e sociais, traz ao tema ainda mais atributos que devem ser mapeados como parte da decisão. Neste trabalho é proposta uma abordagem baseada em otimização combinatória (programação linear inteira) aliada à análise de valor multicriterial que estabelece prioridades e compensações entre os atributos definidos, para seleção de fornecedores de um conjunto de embalagens de cosméticos para uma nova linha de produtos. A solução encontrada é comparada aos métodos de otimização tradicionais (monocriteriais) e à otimização multicriterial sem leilão combinatório. Também são realizadas análises de sensibilidade com o modelo, permitindo que sejam feitas validações de forma a justificar a decisão. / Supplier selection is a complex issue that has gained strategic importance in organizations, mainly due to the consideration of several criteria that can be specified according to the situation, since cost is no longer solely responsible for the decision. The sustainability relevance, in economical, environmental and social terms, brings to the theme even more criteria that should be included as part of the decision. This work proposes an approach based on combinatorial optimization (integer linear programming) combined with multi-criteria value analysis that establishes priorities and trade-offs among the defined criteria, to the supplier selection of a cosmetics packaging set for a new product line. The obtained solution is compared to traditional optimization methods (mono-criteria) and to the multi-criteria optimization without combinatorial auction. Sensitivity analyses are also performed with the model, allowing assessments to be made in order to justify the decision.

Em meio às crises, surgem as ameaças e as oportunidades na Rede Mundial de Computadores. A Internet, âncora do Comércio Eletrônico, apresenta estas duas situações implícitas. Um grande acumulo de situações que se tornam ameaçadoras, as quais quando tratadas utilizando um embasamento científico, aprovado experimentalmente; são consideradas favoráveis, transformando-as em uma grande oportunidade de sucesso em uma próspera empresa, participante desse mundo virtual do comércio eletrônico na Internet. Com o intuito de colaborar com esta situação que envolve decisões importantes e estratégicas, grande volume de recursos, cujas soluções têm influência no futuro das organizações, esta dissertação propõe um modelo de avaliação para empresas de comércio eletrônico, visando sua melhoria contínua, através da aplicação recursiva desta avaliação. Tal modelo informado pelos juízos de valores daqueles responsáveis pelo site, objetiva identificar as limitações e potencialidades da empresa, diante dos cenários ameaçadores e oportunistas que se apresentam no momento de sua aplicação. Para a construção do modelo, foi eleita a metodologia Multicritério de Apoio à Decisão - MCDA, fundamentada cientificamente e com comprovada eficiência em aplicações práticas, considerada a mais adequada, por sua capacidade de gerar conhecimento aos participantes, através de um processo construtivista, e por sua capacidade de integrar tanto elementos objetivos quanto subjetivos. A partir da aplicação do modelo, será observado o perfil de desempenho de um site de comércio eletrônico mediante as ameaças e oportunidades existentes, sendo possível elaborar as recomendações e análises das ações, objetivando a melhoria da empresa de forma progressiva e contínua, servindo de referencial para aplicações futuras. / During times of crises, threats and opportunities will certainly arise in the computer World Wide Web. The Internet, an e-commerce anchor, presents both aforementioned situations. Many of these situations may become threatening, however, when treated by means of an experimentally proven scientific process, they can be changed into great opportunities for a company which participates in the Internet e-commerce virtual world. This situation involves important and strategic decisions, and a great amount of resources, which can lead to solutions that will have a great influence in the future of the organizations. In this way, this thesis proposes an evaluation model for e-commerce companies seeking continuous improvement by the recursive application of it. This evaluation model, that requires information provided by the site management, has as a goal to identify the company limitations and potentialities, in the presence of the threatening and opportunistic scenario existing at the moment of its application. For the development of the evaluation model, the MCDA - Multicriteria Decision Aid has been selected, as it is regarded as a scientifically well-founded methodology. Having its efficiency proven by practical applications, this methodology has been considered the most appropriate, because it generates knowledge to the participants, through a constructive process and for its capability of integrating both objective and subjective elements. Through the application of this model, the performance profile of the e-commerce sites will be observed, in face of the existing threats and opportunities. Thus, it becomes possible to elaborate the recommendations and analyses of actions to be taken, in order to improve the enterprise in a progressive and continuous way. Furthermore, this research can be used as a reference for future applications.

Submitted by Secretaria Pós de Produção (tpp@vm.uff.br) on 2017-07-27T19:24:17Z No. of bitstreams: 1 D2016 - Glauco Barbosa da Silva.pdf: 5776264 bytes, checksum: d50812d465487f52e8c02b7f636435ab (MD5) / Made available in DSpace on 2017-07-27T19:24:17Z (GMT). No. of bitstreams: 1 D2016 - Glauco Barbosa da Silva.pdf: 5776264 bytes, checksum: d50812d465487f52e8c02b7f636435ab (MD5) / Problem: From Modeling decision maker preferences, the Multicriteria Decision Aid (MCDA) is a field dedicated to the study of real-world decision-making problems that are, usually, too complex and not so well-structured to be considered through the examination of a single point of view (criteria). This feature of MCDA implies that a comprehensive model of a decision maker situation cannot be “created”, but instead, the model should be developed to meet the requirements of the Decision Maker (DM). In general, the development of such a model can only be achieved through an iterative and interactive process, until the preferences of the decision maker are consistently represented in the model. However, an interactive method is a procedure that consists of an alternation of calculation and discussion stages, which presumes that the decision maker is willing to answer a large number of relatively difficult questions. For instance, one of the main difficulties to be faced when interacting with a Decision Maker in order to build a decision aid procedure is the various parameters’ elicitation of the preference model. Methodology: In this thesis, as an alternative to interactive process, among the main streams of MCDA, a Preference Disaggregation Analysis method was used, which is considered to assess or to infer preference models from the given preferential structures and to address decision-aiding activities to elicit preferential information and to construct decision models from decision examples. Combining Composition Probabilistic of Preference with Data Mining techniques, a proposal of a three-step process is presented: attribute selection; clustering; and classification. The first and the second ones are data mining tasks and the last one is a multicriteria task. Purpose: This thesis aims to present a new approach with a Data Mining Layer (attribute selection and/or clustering) in Composition Probabilistic of Preferences in Trichotomic procedure (CPP-TRI), which combines data mining techniques with a Multicriteria Decision Aid method in classification (sorting) problems. Findings: The decision maker ability to comprehend without powerful tools has been exceeded. Therefore, important decisions are often made based not on the information-rich data stored in data repositories, but rather, on intuition of the decision maker. Involved in similar problems, the connections between disaggregation methods and data mining (identifying patterns, extracting knowledge from data, eliciting preferential information and constructing decision models from decision examples) are explored to combine and improve the CPP-TRI Method from Attribute Selection Techniques. / Problem: From Modeling decision maker preferences, the Multicriteria Decision Aid (MCDA) is a field dedicated to the study of real-world decision-making problems that are, usually, too complex and not so well-structured to be considered through the examination of a single point of view (criteria). This feature of MCDA implies that a comprehensive model of a decision maker situation cannot be “created”, but instead, the model should be developed to meet the requirements of the Decision Maker (DM). In general, the development of such a model can only be achieved through an iterative and interactive process, until the preferences of the decision maker are consistently represented in the model. However, an interactive method is a procedure that consists of an alternation of calculation and discussion stages, which presumes that the decision maker is willing to answer a large number of relatively difficult questions. For instance, one of the main difficulties to be faced when interacting with a Decision Maker in order to build a decision aid procedure is the various parameters’ elicitation of the preference model. Methodology: In this thesis, as an alternative to interactive process, among the main streams of MCDA, a Preference Disaggregation Analysis method was used, which is considered to assess or to infer preference models from the given preferential structures and to address decision-aiding activities to elicit preferential information and to construct decision models from decision examples. Combining Composition Probabilistic of Preference with Data Mining techniques, a proposal of a three-step process is presented: attribute selection; clustering; and classification. The first and the second ones are data mining tasks and the last one is a multicriteria task. Purpose: This thesis aims to present a new approach with a Data Mining Layer (attribute selection and/or clustering) in Composition Probabilistic of Preferences in Trichotomic procedure (CPP-TRI), which combines data mining techniques with a Multicriteria Decision Aid method in classification (sorting) problems. Findings: The decision maker ability to comprehend without powerful tools has been exceeded. Therefore, important decisions are often made based not on the information-rich data stored in data repositories, but rather, on intuition of the decision maker. Involved in similar problems, the connections between disaggregation methods and data mining (identifying patterns, extracting knowledge from data, eliciting preferential information and constructing decision models from decision examples) are explored to combine and improve the CPP-TRI Method from Attribute Selection Techniques.

The history of the advancement of the agricultural frontier in Brazil has been closely related to environmental losses. Although environmental losses are sometimes inevitable in the context of agricultural expansion, they should always be minimized. This study seeks to avoid the past pattern of development by proposing a more sustainable way of expanding agriculture. The research tests whether it is possible to expand the cultivation of food and fuel crops in Brazil without compromising natural ecosystems. Brazil has a great agricultural potential considering the significant amount of lands that is suitable for agriculture with a favorable climate and topography. To supply the domestic agricultural market and for Brazil to take on a global food and biofuel export leadership position, actions should be taken to plan for this potential sustainable expansion. This planning would be an alternative means of advancing the agricultural frontier, as opposed to the deforestation previously practiced. A way to accomplish a sustainable pattern of agricultural development could be by the identification of suitable areas to support the expansion without further loss of forestlands. Pasture is a type of land use that occupies large areas in Brazil, and pastures are considered strategic resources for the effectiveness of the proposed expansion, given that they represent areas that have already been deforested and offer some type of existing infrastructure. In addition, from the current biophysical potential production - pasture based beef cattle - may be underused. The goal of this dissertation is to develop a spatial allocation model based on a multicriteria decision making and geographic information systems (GIS) using land suitability analysis to support decision makers with geospatial information about where potential areas for sugarcane and soybean expansion are located in Brazil. The multicriteria decision analysis (MCDA) consists of physical land suitability, infrastructure and socioeconomic data integration to identify suitable pasturelands for crop allocation. To enhance the reliability of the model, a team of specialists in the agricultural crops was selected to establish the criteria priorities in the model for the analysis process. The combination of their judgments gives an overall priority that feeds the multicriteria model. \"What if\" scenarios were also built to show how changes in the criteria priority weights would modify the spatial distribution of suitability classes in relation to the main model. The results yield maps that represent the distribution of suitability classes for sugarcane and soybean expansion. Pasturelands become more or less suitable for sugarcane or soybean allocation according to shifts in the influence of each criterion in the model. The designed models show results that may assist policymakers with geospatial information about priority areas where investments and efforts should be directed for sustainable agricultural expansion in Brazil. / A história do avanço da fronteira agrícola no Brasil tem sido intrinsecamente relacionada ao desmatamento. Embora perdas ambientais sejam, por vezes, inevitáveis no contexto de uma expansão agrícola, elas devem ser reduzidas sempre que possível. Tentando não seguir um padrão de desenvolvimento feito à custa de desmatamentos, e pensando numa forma mais sustentável de expansão da agricultura, nós avaliamos nesse estudo a possibilidade de expansão agrícola, para produção de alimentos e de biocombustíveis, sem o comprometimento do ecossistema natural existente no país. O Brasil tem um grande potencial agrícola atribuído à significativa quantidade de solos aptos para agricultura com clima e topografia favoráveis. Para abastecer o mercado agrícola nacional e assumir uma posição de liderança global na exportação de alimentos e biocombustíveis, ações devem ser tomadas pelo Brasil para o planejamento desse potencial de expansão. Esse planejamento seria um modelo alternativo para o avanço da fronteira agrícola, oposto aos padrões de avanço anteriores diretamente relacionados ao desmatamento. Uma forma de conseguir um padrão de desenvolvimento sustentável poderia ser pela identificação de terras agrícolas aptas à essa expansão sem estimular maiores perdas de florestas. As pastagens ocupam grandes áreas no Brasil e são consideradas recursos estratégicos para a eficácia dessa expansão, uma vez que representam áreas que já foram desmatadas e oferecem algum tipo de infraestrutura. Dado o atual potencial biofísico de produção, estima-se que as áreas de pastagem destinadas à pecuária bovina podem estar sendo subutilizadas. O objetivo desse trabalho é desenvolver um modelo de alocação espacial fundamentado numa análise de decisão multicritério e SIG com base na aptidão agrícola das terras, de forma a fornecer informações geoespaciais estratégicas aos tomadores de decisão sobre a localização das áreas potenciais para a expansão da cana-de-açúcar e soja no Brasil. A análise de decisão multicritério (MCDA) consiste na integração de dados edafoclimáticos, de infraestrutura e socioeconômicos para a identificação das áreas de pastagens aptas para a alocação dessas culturas. Para aumentar a confiabilidade do modelo, uma equipe de especialistas em cana-deaçúcar e soja foi selecionada para julgar a prioridade das variáveis no processo de análise. A combinação dos julgamentos fornece uma prioridade geral das variáveis, as quais alimentam o modelo. \"E se\" cenários foram também elaborados para mostrar como as mudanças nos pesos dos critérios modificariam a distribuição espacial das classes de aptidão com relação ao modelo principal. Os resultados são exibidos através de mapas que representam a distribuição das classes de aptidão agrícola para a alocação dos cultivos da cana-de-açúcar e soja. As pastagens tornam-se tanto mais adequadas para a alocação da cana ou soja de acordo com as mudanças na influência de cada critério no modelo. Os modelos projetados mostram resultados favoráveis que podem ajudar os tomadores de decisão com informações geoespaciais que identificam áreas prioritárias onde investimentos e esforços deveriam ser direcionados para estimular a expansão agrícola sustentável no Brasil.

Den här studien använder sig av en Multimodal Kritisk Diskursanalys (MCDA) för att undersöka hur reality-showen Biggest Loser Sverige 2018 framställer överviktiga. Syftet med studien är att analysera hur seriens finalister framställs när dem är överviktiga respektive när dem är normalviktiga, samt undersöka ifall viktstigmatiserade attityder kommer till uttryck i programmet. Studiens teoretiska ramverk utgår från fältet hälsokommunikation, med fokus på stigmatiseringsteorin och stigmatiseringsprocessen. I analysen undersöks utvalda delar av Biggest Loser Sverige 2018 utifrån olika analysbegrepp hämtade från MCDA. Analysresultatet visar att programmet innehåller viktstigmatiserade attityder genom att finalisterna som överviktiga framställs som olyckliga och lata, iklädda för tighta kläder och ätandes ohälsosam mat. Dessutom filmas de utifrån kameravinklar som gör att deras kroppar ser större ut, samtidigt som ljussättningen är mörk och dyster. När finalisterna är normalviktiga framställs dem som lyckliga, självsäkra och iklädda figursydda kläder. De filmas dessutom utifrån kameravinklar som gör att deras kroppar ser mindre ut, tillsammans med en ljus ljussättning som framhäver deras kroppar på ett exklusivt sätt. Avslutningsvis i studien diskuteras hur den stora skillnaden i framställandet av finalisterna skapar viktstigmatiserade attityder genom att ge en diskriminerande bild av överviktiga människor. / This study uses a Multimodal Critical Discourse Analysis (MCDA) to investigate how the reality-show Biggest Loser Sweden 2018 presents obesity. The purpose of the study is to analyze how the finalists of the series are presented as obese and non-obese, as well as investigate if weight-stigmatized attitudes are being expressed in the program. The theoretical framework of the study is based on the field of health communication, focusing on the stigmatization theory and the stigmatization process. The analysis examines selected parts of Biggest Loser Sweden 2018 based on various analytical concepts. The analysis results shows that the program contains weith stigmatized attitudes, by portaying the finalists as miserable and lazy, dressed in inappropriately fitting clothing and eating unhealthy food. Additionally, they are being filmed from unflattering wiews that makes their bodys look bigger, with a dark lightning. When the finalists are normalweighted, they are being presented as happy, confident and with close-fitting clothes. They are also being filmed from angles that make their bodys look smaller, and with a lightning that emphasizes their bodies in an exclusive way. In conclusion, the study discusses how the big difference in the presentation of the finalists may promote weight-stigmatized attitudes by giving a discriminatory picture of overweight people.

Em meio às crises, surgem as ameaças e as oportunidades na Rede Mundial de Computadores. A Internet, âncora do Comércio Eletrônico, apresenta estas duas situações implícitas. Um grande acumulo de situações que se tornam ameaçadoras, as quais quando tratadas utilizando um embasamento científico, aprovado experimentalmente; são consideradas favoráveis, transformando-as em uma grande oportunidade de sucesso em uma próspera empresa, participante desse mundo virtual do comércio eletrônico na Internet. Com o intuito de colaborar com esta situação que envolve decisões importantes e estratégicas, grande volume de recursos, cujas soluções têm influência no futuro das organizações, esta dissertação propõe um modelo de avaliação para empresas de comércio eletrônico, visando sua melhoria contínua, através da aplicação recursiva desta avaliação. Tal modelo informado pelos juízos de valores daqueles responsáveis pelo site, objetiva identificar as limitações e potencialidades da empresa, diante dos cenários ameaçadores e oportunistas que se apresentam no momento de sua aplicação. Para a construção do modelo, foi eleita a metodologia Multicritério de Apoio à Decisão - MCDA, fundamentada cientificamente e com comprovada eficiência em aplicações práticas, considerada a mais adequada, por sua capacidade de gerar conhecimento aos participantes, através de um processo construtivista, e por sua capacidade de integrar tanto elementos objetivos quanto subjetivos. A partir da aplicação do modelo, será observado o perfil de desempenho de um site de comércio eletrônico mediante as ameaças e oportunidades existentes, sendo possível elaborar as recomendações e análises das ações, objetivando a melhoria da empresa de forma progressiva e contínua, servindo de referencial para aplicações futuras. / During times of crises, threats and opportunities will certainly arise in the computer World Wide Web. The Internet, an e-commerce anchor, presents both aforementioned situations. Many of these situations may become threatening, however, when treated by means of an experimentally proven scientific process, they can be changed into great opportunities for a company which participates in the Internet e-commerce virtual world. This situation involves important and strategic decisions, and a great amount of resources, which can lead to solutions that will have a great influence in the future of the organizations. In this way, this thesis proposes an evaluation model for e-commerce companies seeking continuous improvement by the recursive application of it. This evaluation model, that requires information provided by the site management, has as a goal to identify the company limitations and potentialities, in the presence of the threatening and opportunistic scenario existing at the moment of its application. For the development of the evaluation model, the MCDA - Multicriteria Decision Aid has been selected, as it is regarded as a scientifically well-founded methodology. Having its efficiency proven by practical applications, this methodology has been considered the most appropriate, because it generates knowledge to the participants, through a constructive process and for its capability of integrating both objective and subjective elements. Through the application of this model, the performance profile of the e-commerce sites will be observed, in face of the existing threats and opportunities. Thus, it becomes possible to elaborate the recommendations and analyses of actions to be taken, in order to improve the enterprise in a progressive and continuous way. Furthermore, this research can be used as a reference for future applications.

A seleção de fornecedores é um problema complexo e que vem ganhando importância estratégica nas organizações, principalmente devido à inclusão de diversos atributos que podem ser especificados de acordo com as necessidades da situação, pois o fator custo não é mais o único responsável pela decisão. A relevância da sustentabilidade, em termos econômicos, ambientais e sociais, traz ao tema ainda mais atributos que devem ser mapeados como parte da decisão. Neste trabalho é proposta uma abordagem baseada em otimização combinatória (programação linear inteira) aliada à análise de valor multicriterial que estabelece prioridades e compensações entre os atributos definidos, para seleção de fornecedores de um conjunto de embalagens de cosméticos para uma nova linha de produtos. A solução encontrada é comparada aos métodos de otimização tradicionais (monocriteriais) e à otimização multicriterial sem leilão combinatório. Também são realizadas análises de sensibilidade com o modelo, permitindo que sejam feitas validações de forma a justificar a decisão. / Supplier selection is a complex issue that has gained strategic importance in organizations, mainly due to the consideration of several criteria that can be specified according to the situation, since cost is no longer solely responsible for the decision. The sustainability relevance, in economical, environmental and social terms, brings to the theme even more criteria that should be included as part of the decision. This work proposes an approach based on combinatorial optimization (integer linear programming) combined with multi-criteria value analysis that establishes priorities and trade-offs among the defined criteria, to the supplier selection of a cosmetics packaging set for a new product line. The obtained solution is compared to traditional optimization methods (mono-criteria) and to the multi-criteria optimization without combinatorial auction. Sensitivity analyses are also performed with the model, allowing assessments to be made in order to justify the decision.