[ES] Una vía para conseguir un cambio de modelo de negocio hacia modelos más sostenibles es transformar el modelo empresarial tradicional lineal hacia modelos más circulares, priorizando el aprovechamiento de los recursos y la reducción del consumo de materias primas. De hecho, uno de los diecisiete Objetivos de Desarrollo Sostenible, hace referencia a la producción y al consumo responsables, incluyendo, como una de sus metas, "reducir considerablemente la generación de desechos mediante actividades de prevención, reducción, reciclado y reutilización". En este contexto de expansión del concepto de desarrollo sostenible y de la economía circular, la gestión de los productos recuperados ha convertido la Logística Inversa (LI) en una competencia clave de las Cadenas de Suministro (CdS) modernas. Otra de las causas que sitúan a la LI en la primera línea de las preocupaciones de las empresas son las devoluciones de los productos adquiridos y el elevado flujo inverso que generan, debido al incremento exponencial del comercio electrónico y su permisiva política de devoluciones. Ante este vertiginoso crecimiento de las operaciones de LI, surge la necesidad de actualizar los tradicionales procesos logísticos de las empresas, integrando en ellos el Proceso de Logística Inversa (PLI), lo cual permite controlar todo el ciclo de vida del producto. Sin embargo, debido fundamentalmente a que los flujos inversos son menos predecibles y más variables que los directos, la gestión de la LI no es una tarea fácil. En este contexto, muchas empresas han comenzado a trabajar duramente por estandarizar y formalizar sus PLI, estableciendo una serie de reglas, procedimientos y comunicaciones, que faciliten la comprensión del proceso a todos los interesados y les ayude a saber cómo actuar en cada momento. Disponer de un PLI estandarizado y formalizado permite una mejor comprensión y gestión de los productos devueltos o recuperados y una LI más eficiente, que puede a su vez proporcionar una ventaja competitiva a la empresa. Otro aspecto vital para conseguir una mayor eficiencia y rentabilidad de los PLI es facilitar la toma de decisiones en dicho proceso. En definitiva, una toma de decisiones ágil y acertada aumentará la eficiencia, permitiendo reducir costes, mejorar el servicio al cliente e incrementar los beneficios de la compañía. En este sentido, de entre todas las decisiones relacionadas con el PLI, la decisión sobre la alternativa de disposición (DD) puede destacarse como la más determinante. Precisamente, la importancia del PLI y la complejidad de la DD en el contexto descrito, justifican el desarrollo de herramientas de ayuda a la toma de decisiones. Sin embargo, los trabajos hallados en la literatura, si bien se centran en aportar modelos de ayuda a la toma de decisiones, no trabajan el PLI en su conjunto, y no llegan a estandarizar las operaciones que se realizan a lo largo del proceso, sin mostrar claramente cómo se construyen dichos modelos ni la composición de los distintos elementos del modelo. La presente tesis desarrolla un Marco de Referencia para el Desarrollo Integrado de Modelos de Procesos y Matemáticos en un contexto de LI (MR-DIMPM-LI), aportando una solución integrada que aborde el PLI en su conjunto y facilite la formalización del proceso y la toma de decisiones eficiente y sostenible en cada caso concreto. Mediante el Marco de Referencia planteado se promueve el desarrollo de modelos sostenibles, no solo favoreciendo el entendimiento y la incorporación del PLI en las empresas sino, además, haciendo que este sea realmente sostenible. Este Marco de Referencia se ha aplicado en una red de LI de bucle cerrado de un fabricante de sillones de relax y, por otro lado, en una red de LI de bucle abierto de neumáticos usados. Como resultado, se ha podido comprobar la idoneidad del Marco de Referencia propuesto en cuanto a la formalización del PLI y a la toma de decisiones de la DD, haciéndola más e / [CAT] Una via per aconseguir un canvi de model de negoci cap a models més sostenibles és transformar el model empresarial tradicional lineal cap a models més circulars, prioritzant l'aprofitament dels recursos i la reducció del consum de matèries primeres. De fet, un dels disset Objectius de Desenvolupament Sostenible, fa referència a la producció i al consum responsables, incloent-hi, com un dels seus objectius, "reduir considerablement la generació de residus mitjançant activitats de prevenció, reducció, reciclatge i reutilització". En aquest context d'expansió del concepte de desenvolupament sostenible i de l'economia circular, la gestió dels productes recuperats ha convertit la Logística Inversa (LI) en una competència clau de les Cadenes de Subministrament (CdS) modernes. Una altra de les causes que situen la LI en la primera línia de les preocupacions de les empreses són les devolucions dels productes adquirits i l'elevat flux invers que generen, a causa de l'increment exponencial del comerç electrònic i la seua permissiva política de devolucions. Davant d'aquest vertiginós creixement de les operacions de LI, sorgeix la necessitat d'actualitzar els tradicionals processos logístics de les empreses, integrant en ells el Procés de Logística Inversa (PLI), la qual cosa permet controlar tot el cicle de vida del producte. Tanmateix, a causa del fet que els fluxos inversos són menys predictibles i més variables que els directes, la gestió de la LI no és una tasca fàcil. En aquest context, moltes empreses han començat a treballar durament per estandarditzar i formalitzar els seus PLI, establint una sèrie de regles, procediments i comunicacions, que faciliten la comprensió del procés a tots els interessats i els ajude a saber com actuar en cada moment.Un altre aspecte vital per tal d'aconseguir una major eficiència i rendibilitat dels PLI és facilitar la presa de decisions en aquest procés. La identificació, estudi, descripció i modelatge de les decisions ajudarà els gestors o decisors a tenir una visió integrada de les mateixes i a entendre millor els aspectes a considerar en aquestes decisions i el seu impacte. En definitiva, una presa de decisions àgil i encertada augmentarà l'eficiència, permetent reduir costos, millorar el servei al client i incrementar els beneficis de la companyia. En aquest sentit, d'entre totes les decisions relacionades amb el PLI, la decisió sobre l'alternativa de disposició (DD) pot destacar-se com la més determinant, pel fet que ha de ser única per cada producte, condiciona a la resta de decisions, està influenciada per una elevada incertesa, repercuteix en el grau de sostenibilitat de l'empresa, està condicionada per molts factors la condicionen i generalment precisa d'agilitat i rapidesa per proporcionar una resposta a client. Precisament, la importància del PLI i la complexitat de la DD en el context descrit, justifiquen el desenvolupament d'eines d'ajuda a la presa de decisions. No obstant això, els treballs trobats a la literatura, tot i que se centren en aportar models d'ajuda a la presa de decisions, no treballen el PLI en el seu conjunt, i no arriben a estandarditzar les operacions que es realitzen al llarg de el procés. La present tesi desenvolupa un Marc de Referència (MR) per al Desenvolupament Integrat de Models de Processos i Matemàtics en un context de LI, aportant una solució integrada que aborde el PLI en el seu conjunt i facilite la formalització del procés i la presa de decisions eficient i sostenible en cada cas concret. El MR plantejat promou els models sostenibles, no només afavorint l'enteniment i la incorporació del PLI a les empreses sinó, a més, fent que aquest siga realment sostenible. Aquest MR s'ha aplicat a una xarxa de LI d'un fabricant de butaques de relax i a una xarxa de LI de pneumàtics usats. Com a resultat, s'ha pogut comprovar la idoneïtat del MR proposat pel que fa a la formalització del PLI i a la presa / [EN] One way to achieve a change in the business model towards more sustainable ones is to transform the traditional linear business models to more circular ones, prioritizing the use of resources and reducing the consumption of raw materials. In fact, one of the seventeen Sustainable Development Goals, refers to responsible production and consumption, including, as one of its goals, "considerably reduce the generation of waste through prevention, reduction, recycling and reuse activities". In this context of expanding the sustainable development and the circular economy concepts, recovered product's management has made Reverse Logistics (RL) a key competence of modern Supply Chains (SC). Another reason why RL is a major concern for companies is the returns of purchased products and the high reverse flow generated, due to the exponential e-commerce increase and its permissive return policy. Because of this vertiginous growth of RL operations, the companies must update the traditional logistics processes, integrating the Reverse Logistics Process (RLP) into them, which allows controlling the entire life cycle of the product. However, RL management is not an easy task, mainly because reverse flows are less predictable and more variable than direct ones. In this context, many companies have begun to work hard to standardize and formalize their RLP, establishing a set of rules, procedures and communications, which facilitate the understanding of the process for all interested stakeholders and help them to know how to act at any time. Having a standardized and formalized RLP enables better understanding and management of returned or recovered products and a more efficient RL, which can in turn provide a competitive advantage to the company. Another vital aspect to achieve greater efficiency and profitability of the RLP is to facilitate decision making in this process. The identification, study, description and modeling of decisions will help managers or decision-makers to have an integrated vision of them and to better understand the aspects to be considered in such decisions and their impact. In fact, agile and accurate decision making will increase efficiency, reducing costs, improving customer service and increasing company profits. In this sense, among all the decisions related to the RLP, the disposition decision (DD) can be highlighted as the most decisive, since it must be unique for each product, it determines the rest of the decisions, it is influenced by high uncertainty and affects the degree of sustainability of the company, it is conditioned by multiple factors and generally requires agility and speed to respond to the costumer. Precisely, the importance of RLP and the complexity of DD in the context described, justify the development of tools as an aid to decision-making. However, the studies found in the literature, although they focus on providing models for decision-making, do not work on the PLI as a whole, and do not come to standardize the operations carried out throughout the process, hardly showing how these models are built or the composition of the different elements of the model.This thesis develops a Reference Framework for the Integrated Development of Mathematical and Process Models in an RL context, providing an integrated solution that addresses the RLP as a whole and facilitates the formalization of the process and the efficient and sustainable decision making in each specific case. Through this, the development of sustainable models is promoted, not only favoring the understanding and incorporation of the RLP in companies but also making it truly sustainable. This framework has been applied to two real examples: a RL network of the manufacturer of relaxing chairs and a network of used tires. As a result, it has been possible to verify the suitability of the proposed Reference Framework regarding the formalization of the RLP and the decision-making of the DD, making it more efficient and sustainable. / Cortés Pellicer, P. (2020). Marco de Referencia para el Desarrollo Integrado de Modelos de Procesos y Matemáticos de Ayuda a la Toma de Decisiones en un Contexto de Logística Inversa [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/159265

The growing volume of opinion data presents a significant challenge for policymakers striving to distill public sentiment into actionable decisions. This study aims to explore the capability of large language models (LLMs) to synthesize public opinion data into coherent policy recommendations. We specifically leverage Mistral 7B and Mixtral 8x7B models for text generation and have developed an architecture to process vast amounts of unstructured information, integrate diverse viewpoints, and extract actionable insights aligned with public opinion. Using a retrospective data analysis of the Polis platform debates published by the Computational Democracy Project, this study examines multiple datasets that span local and national issues with 1600 statements posted and voted upon by over 3400 participants. Through content moderation, topic modeling, semantic structure extraction, insight generation, and argument mapping, we dissect and interpret the comments, leveraging voting data and LLMs for both quantitative and qualitative insights. A key contribution of this thesis is demonstrating how LLM reasoning techniques can enhance content moderation. Our content moderation approach shows performance improvements using comment deconstruction in multi-class classification, underscoring the trade-offs between moderation strategies and emphasizing a balance between precision and cautious moderation. Using comment clustering, we establish a hierarchy of semantically linked topics, facilitating an understanding of thematic structures and the generation of actionable insights. The generated argument maps visually represent the relationships between topics and insights, and highlight popular opinions. Future work will leverage advanced semantic extraction and reasoning techniques to enhance insight generation further. We also plan to generalize our techniques to other major discussion platforms, including Kialo. Our work contributes to the understanding of using LLMs for policymaking and offers a novel approach to structuring complex debates and translating public opinion into actionable policy insights.

Much of the confusion about the effectiveness of information security programs concerns not only how to measure, but also what to measure — an issue of equivocality. Thus, to lower uncertainty for improved decision-making, it is first essential to reduce equivocality by defining, expanding, and clarifying risk factors so that metrics, the "necessary measures," can be unambiguously applied. We formulate a system that (1) allows threats to be accurately measured and tracked, (2) enables the impacts and costs of successful threats to be determined, and (3) aids in evaluating the effectiveness and return on investment of countermeasures. We then examine the quality of controls implemented to mitigate cyber risk and study how effectively they reduce the likelihood of security incidents. Improved control quality was shown to reduce the likelihood of security incidents, yet the results indicate that investing in maximum quality is not necessarily the most efficient use of resources. The next manuscript expands the discussion of cyber risk management beyond single organizations by surveying perceptions and experiences of risk factors related to 3rd parties. To validate and these findings, we undertake in an in-depth investigation of nearly 1000 real-world data breaches occurring over a ten-year period. It provides a robust data model and rich database required by a decision support system for cyber risk in the extended enterprise. To our knowledge, it is the most comprehensive field study ever conducted on the subject. Finally, we incorporate these insights, data, and factors into a simulation model that enables us study the transfer of cyber risk across different supply chain configurations and draw important managerial implications. / Ph. D. / This dissertation comprises several manuscripts exploring various topics under the overall theme of cybersecurity risk in supply chains. The first topic presents the difficulties involved in measuring risk in the cybersecurity domain and discusses how this hinders firms in making justified decisions and taking appropriate actions to manage risk. We then examine the quality of controls implemented to mitigate cyber risk and study how effectively they reduce the likelihood of security incidents. Next, we survey firms to explore perspectives and experiences related to security incidents involving their supply chain partners. To validate these perspectives, we then analyze data collected from over 900 forensic investigations of real-world breaches. This provides excellent visibility into how 3rd parties cause and contribute to incidents in supply chains and key risk factors. Finally, we incorporate these insights, data, and factors into a simulation model that enables us study the transfer of cyber risk across different supply chain configurations and draw important managerial implications.

Yes / Blockchain operates on a highly secured framework, and its decentralized consensus has benefits for supply chain sustainability. Scholars have recognized the growing importance of sustainability in supply chains and studied the potential of blockchain for sustainable supply chain management. However, no study has taken stock of high-quality research in this area. To address this gap, this paper aims to provide a state-of-the-art overview of high-quality research on blockchain for sustainable supply chain management. To do so, this paper conducts a systematic literature review using a bibliometric analysis of 146 high-quality articles on blockchain for sustainable supply chain management that have been published in journals ranked “A*”, “A”, and “B” by the Australian Business Deans Council and retrieved from the Scopus database. In doing so, this paper unpacks the most prominent journals, authors, institutions, and countries that have contributed to three major themes in the field, namely blockchain for sustainable business activities, decision support systems using blockchain, and blockchain for intelligent transportation system. This paper also reveals the use of blockchain for sustainable supply chain management across four major sectors, namely food, healthcare, manufacturing, and infrastructure, and concludes with suggestions for future research in each sector.

The traditional linear economy, using a take-make-dispose model is resourceintense and comes with adverse environmental impacts. Circular economy (CE) is regenerative and restorative by design and intention and is recommended as the business model for efficient use of resources. Despite the push for businesses and organisations to switch from linear to CE, there are several barriers/challenges that need solving such as business models and the criticism of CE projects often being small scale. Technology can be an enabler toward scaling up CE; however, the prime challenge is to identify technologies that can allow predicting, tracking and proactive monitoring of product's residual value, that can potentially motivate businesses to pursue circularity decisions. In this thesis, an Internet of Things (IoT)-enabled decision support system (DSS) for CE business model is proposed. The aim is to effectively enable tracking, monitoring, and analysis of products in real time with focus on residual value. The business model is implemented using an ontological model. This model is complemented by a semantic DSS. The semantic ontological model, first of its kind, is evaluated for technical compliance, quality of modelling and domain coverage, for final reengineering and re-evaluations. The DSS and the ontological model is applied in a real-world use case and demonstrate viability and applicability of the approach to businesses and sustainability via Sustainable Development Goals (SDGs) lens. The results of the comparison of this novel model to the linear economy is promising with the novel model proving more profitable and resource efficient. / Petroleum Development Technology Fund (PTDF) Nigeria

An average of 3 million deaths occurs each year in high-income countries due to unsafe care, with causes including diagnostic and communication failures. These failures are related to clinical information overload, the extraction of essential unstructured data, and complex health data analytics for deriving insights. The use case of this dissertation focuses on emergency room (ER) physicians, as they are the initial point of contact for patients, and time-sensitive situations occur frequently in the ER. The goal is to develop an intelligent clinical information platform (ICIP) for ER physicians, assisting patients’ care pathways using machine learning (ML). This platform provides a new, multidimensional view to represent patients’ medical conditions, focused on heart diseases. To achieve the platform’s implementation, three technical components are developed and published within this dissertation: first, a component for data extraction from remote video consultations via WebRTC; second, a data classification component using a Faster Region-Based Convolutional Neural Network (R-CNN) model together with active learning (AL); and third, a data search component with an implemented Elasticsearch pipeline and data storage unified in the FHIR standard. The research for a newly developed clinical platform is practically and industrially based on building a future clinical product. For this product, ML models are developed to analyze data from past clinical treatments using an R-CNN model for text classification and to access verbal audio data through a speech-to-text (STT) engine employing an RNN TensorFlow model and a large language model (LLM) from NLP.js. Additionally, JSON object-based rule-based reasoning from FHIR is used. It has been demonstrated that a three-tier architecture (AngularJS, Java Spring Boot, and PostgreSQL), consisting of components involving neural networks such as R-CNN, RNN (recurrent neural network), and LLM, can be implemented as a data platform for assisting heart disease care pathways. This allows physicians to interpret patients’ vital parameters, pathways, and timelines via diagrams presented in widgets on the AngularJS frontend.

Entscheidungsunterstützungssysteme in der Finanzwirtschaft sind nicht nur für die Wis-senschaft, sondern auch für die Praxis von großem Interesse. Um die Finanzmarktüber-wachung zu gewährleisten, sehen sich die Finanzaufsichtsbehörden auf der einen Seite, mit der steigenden Anzahl von onlineverfügbaren Informationen, wie z.B. den Finanz-Blogs und -Nachrichten konfrontiert. Auf der anderen Seite stellen schnell aufkommen-de Trends, wie z.B. die stetig wachsende Menge an online verfügbaren Daten sowie die Entwicklung von Data-Mining-Methoden, Herausforderungen für die Wissenschaft dar. Entscheidungsunterstützungssysteme in der Finanzwirtschaft bieten die Möglichkeit rechtzeitig relevante Informationen für Finanzaufsichtsbehörden und Compliance-Beauftragte von Finanzinstituten zur Verfügung zu stellen. In dieser Arbeit werden IT-Artefakte vorgestellt, welche die Entscheidungsfindung der Finanzmarktüberwachung unterstützen. Darüber hinaus wird eine erklärende Designtheorie vorgestellt, welche die Anforderungen der Regulierungsbehörden und der Compliance-Beauftragten in Finan-zinstituten aufgreift.

Revenue collection agencies across the world aim to maximise revenue collection by minimising tax noncompliance. The different types of tax noncompliance are collectively referred to as the tax gap phenomenon, which revenue collection agencies address by means of various enforcement approaches and capabilities. Much like any organisation, the resources required to execute these capabilities are finite and require accurate organisational decision-making in order to make optimal use thereof. Information technology, and specifically decision support systems (DSS), is critical in enabling this decision-making process. Using the Structuration Model of Technology, the information needs, demand and offerings of revenue collection agencies are explored given their objective of narrowing the tax gap phenomenon using DSS. Emphasis is placed on the manner in which IT is used to address taxpayer noncompliance, the way in which IT supports knowledge creation and subsequently also facilitate the decision-making process of tax practitioners, and also the different types of IT offerings made available to decision-makers in the form of DSS. In doing so, this research presents the results of a case study on the South African Revenue Service in which a conceptual decision support system framework is developed aimed at minimising the tax gap phenomenon. The research is conducted as a qualitative single case study and presented through a narrative analysis. The framework is systematically constructed as the research findings emerge and concluded by means of a framework validation and transfer ability test. The research result is a conceptual DSS framework acting as a reference point to other revenue collection agencies with the objective of addressing taxpayer noncompliance through DSS. / Jurisprudence / D. Phil. (Information Systems)

Thesis (PhD (Logistics))--University of Stellenbosch, 2006. / Conventional supply chain integration concepts focus primarily on the internal and external integration of individual supply chains (can be viewed as intra-supply chain integration). Due to the highly integrated nature of petrochemical value chains, related supply chains should also be integrated by taking account of enterprise/industry-wide synergies and interdependencies (can be viewed as inter-supply chain integration). Inter-supply chain integration can typically develop along three dimensions: - Upstream feed clusters (upstream in the chemical value chain) - Downstream product clusters (downstream in the chemical value chain) - Macro logistics network clusters (within and across related logistics networks for liquid bulk, dry bulk, packaged goods and gases) This dissertation presents a generic framework of applicable intra- and inter-supply chain planning processes that supports related long- (strategic), medium- (tactical) and short-term (operational) supply chain decisions for large-scale petrochemical companies. This type of companies has to manage relative complex supply chains. Highly complex supply chains (due to an extensive product portfolio, supplier base, customer base, manufacturing processes, transportation, and management processes and systems) require far more advanced planning processes than simple supply chains. Advanced supply chain planning processes cover an extended supply chain scope, deal with longer time horizons, and utilize more sophisticated analytical techniques and decision support systems. An extensive literature study, supplemented by empirical research in the South African petrochemical industry, provided the foundation for the advanced supply chain planning framework concluded in this dissertation. Semi-structured interviews and a questionnaire presented to an informed audience constitute the empirical research conducted. The related best practices, concepts, approaches followed, and level of advancement in three supply chain planning dimensions were derived. To guide petrochemical companies along the planning advancement journey, the roadmap developed can be utilized for the application and implementation of the advanced supply chain planning framework. This roadmap articulates the advancement stages, dimensions, characteristics, and triggers to advance. Typical characteristics associated with the advancement stages and dimensions provide the means for a company to assess their level of progression. The essential mechanisms that can enable interventions are also articulated.

Um dos problemas que afetam as cidades brasileiras é a falta de uma metodologia adequada para a implantação de equipamentos coletivos públicos (escolas, postos de saúde, entre outros), e da utilização de modo racional desses equipamentos. Esse foi o ponto de partida para esse trabalho, cujo objetivo principal foi desenvolver uma ferramenta de análise espacial para auxiliar o poder público no planejamento e na gestão dos serviços públicos de educação e saúde, no que concerne basicamente à melhor localização das unidades básicas de atendimento e à melhor distribuição dos usuários por essas unidades, buscando reduzir os custos de transporte. Após uma avaliação da atual política de distribuição e utilização dos equipamentos coletivos de educação e saúde no Brasil e no mundo, foi realizada uma análise dos conceitos relativos às ferramentas de apoio a problemas de decisão de caráter espacial, particularmente os Sistemas de Apoio à Decisão Espacial (SADE). De posse dessa base conceitual, buscou-se formular as bases de um sistema (ou uma metodologia) que apoiasse a implantação de novos equipamentos coletivos e uma utilização eficiente dos equipamentos já existentes, tendo como parâmetro principal de comparação o custo de deslocamento dos usuários. Esse sistema deveria ser adequado à realidade das cidades médias brasileiras, de maneira geral hoje inseridas num cenário de falta de planejamento e de ausência de bases de dados estruturadas (e atualizadas). Ainda, como proposta adicional, procurou-se incorporar como ferramentas de apoio ao sistema algumas técnicas emergentes que, embora relativamente pouco utilizadas no planejamento urbano até o presente momento, apresentam grande potencial para tal. São elas: os Autômatos Celulares (ou CA, Cellular Automata) e as Redes Neurais Artificiais (RNA). Os fundamentos do sistema concebido foram transpostos para uma aplicação prática desenvolvida em um Sistema de Informações Geográficas (SIG) através de um estudo de caso conduzido na cidade de São Carlos (SP), cujos resultados demonstraram que quando se pensa em otimizar os custos de deslocamento, a principal ação a ser empreendida é a redistribuição da demanda às unidades de oferta, antes de se pensar na abertura de novas unidades. Mais importante do que os resultados numéricos obtidos, foi a confirmação de que é possível se utilizar as diversas ferramentas de planejamento e gestão de modo integrado. A partir dessa metodologia, um investimento em desenvolvimento de software pode levar à construção de um efetivo Sistema de Apoio à Decisão Espacial. De maneira mais geral, pode-se afirmar que a obtenção de dados é o grande obstáculo para pesquisas dessa natureza. A montagem de uma base de dados sólida e confiável é, sem dúvida, o ponto crucial para a execução de projetos potencialmente bem sucedidos / One of the main problems faced by brazilian cities is the lack of adequate methodologies for the implementation and rational use of public service facilities (such as schools and health care centers). That was the starting point in the definition of the main objective of the present work, which is the development of a spatial analysis tool for seeking an optimal arrangement of primary health and education facilities, in order to reduce transportation costs. The use of such a tool in the public administration is important not only for planning but also for management purposes. The study starts with an investigation of approaches that have been used in real cases, in cities of different countries, to define health and education facility types and their distribution. A careful analysis of location-allocation concepts and analysis tools for the solution of spatial problems, with particular emphasis on the Spatial Decision Support Systems (SDSS), was also conducted. The system (or methodology) proposed, which was meant to support the process of location of new facilities and also an efficient use of the existing ones while reducing transportation costs, was based on that conceptual framework. The system was directed to the context of brazilian medium-sized cities, where planning concepts are not widely applied and even the databases available are sometimes very limited and frequently outdated. The system design looked for both traditional and innovative approaches and computer-based techniques, such as Cellular Automata (CA) and Artificial Neural Networks (ANN). These techniques, although not yet extensively applied in urban planning and management, seem to be promising alternatives for those activities. The integration of the different tools and techniques was tested in a practical application carried out in the city of São Carlos (SP) and developed in a Geographic Information System (GIS) environment. The results drawn from the application are clear: the main action to reduce the transportation costs in the case studied was a re-distribution of the demand. It was considerable, despite the fact that not a single facility has been added. Another important outcome of the research was the confirmation of the hypothesis that the distinct planning and management tools tested could be used in an integrated approach. Therefore, the methodology discussed here could effectively become a Spatial Decision Support System only by means of software development for building the system interfaces. As a general conclusion, the data gathering problems still seem to be the main barrier for research development in this area. Consequently, the construction of solid and reliable databases is undoubtedly a key point to start any potentially successful project