Estimating intergenerational utility distribution preferences

Resource management decisions influence not only the output of the economy but also the distribution of utility between groups within the community. The theory of Benefit Cost Analysis provides a means of incorporating this distributional change through the application of distributional or welfare weights. This paper reports the results of research designed to estimate distributional weights suitable for inclusion in a Benefit Cost Analysis framework. The findings of a choice modelling experiment estimating community preferences with respect to intergenerational utility distribution are presented to illustrate this innovative application of a stated preference technique.

Estimating intergenerational distribution preferences

Resource management decisions influence not only the output of the economy but also the distribution of utility between groups within the community. The theory of cost benefit analysis provides a means of incorporating distributional changes into the decision making calculus through the application of distributional or welfare weights. However, this practice has not been widely adopted in part due to difficulties in the estimation of distributional weights. This paper addresses this problem by using the stated preference method of choice modelling to estimate distributional weights suitable for inclusion in a cost benefit analysis framework. The findings of a choice modelling experiment designed to estimate community preferences with respect to intergenerational utility distribution illustrate the potential of this method in addressing distributional issues.

A bayesian nonparametric joint factor model for learning shared and individual subspaces from multiple data sources

Joint analysis of multiple data sources is becoming increasingly popular in transfer learning, multi-task learning and cross-domain data mining. One promising approach to model the data jointly is through learning the shared and individual factor subspaces. However, performance of this approach depends on the subspace dimensionalities and the level of sharing needs to be specified a priori. To this end, we propose a nonparametric joint factor analysis framework for modeling multiple related data sources. Our model utilizes the hierarchical beta process as a nonparametric prior to automatically infer the number of shared and individual factors. For posterior inference, we provide a Gibbs sampling scheme using auxiliary variables. The effectiveness of the proposed framework is validated through its application on two real world problems - transfer learning in text and image retrieval.

Conceptualising how SMEs incorporate green content in their websites

This paper presents a framework on how Small and Medium Enterprises (SMEs) can proactively incorporate content relating to their ecological responsibility (or green) activities in their websites. SME studies offer limited guidance on, and conceptualisation of, how organisations can incorporate different types of content into their website designs. This paper addresses this problem by presenting the results of an exploratory, qualitative content analysis of Australian SME websites where emergent themes are interpreted using framing and legitimacy theories. It describes three dimensions (location, presentation, and specificity) which comprise the framework, under which the themes are grouped. The paper outlines how scholars can use the framework to develop models and carry out evaluations regarding how SMEs embed green content, and potentially other specific content types, in their websites. It also summarises how the framework can assist SMEs (or website developers serving them) make informed decisions regarding framing their websites as green, or de-emphasising this content, by paying attention to its location (e.g. homepage, navigation bars) and presentation (e.g. how paragraphs, images, etc are used) within webpages. The legitimacy or credibility of the green content can be enhanced using different types of specificity (e.g. statistics, detail of processes and actions, and third-party substantiation).

Measurement invariance across chronic conditions: a systematic review and an empirical investigation of the Health Education Impact Questionnaire (heiQ™).

To examine whether lack of measurement invariance (MI) influences mean comparisons among different disease groups, this paper provides (1) a systematic review of MI in generic constructs across chronic conditions and (2) an empirical analysis of MI in the Health Education Impact Questionnaire (heiQ™).

Implementing novel models of posttreatment care for cancer survivors: Enablers, challenges and recommendations

AIM: The American Society of Clinical Oncology and US Institute of Medicine emphasize the need to trial novel models of posttreatment care, and disseminate findings. In 2011, the Victorian State Government (Australia) established the Victorian Cancer Survivorship Program (VCSP), funding six 2-year demonstration projects, targeting end of initial cancer treatment. Projects considered various models, enrolling people of differing cancer types, age and residential areas. We sought to determine common enablers of success, as well as challenges/barriers. METHODS: Throughout the duration of the projects, a formal "community of practice" met regularly to share experiences. Projects provided regular formal progress reports. An analysis framework was developed to synthesize key themes and identify critical enablers and challenges. Two external reviewers examined final project reports. Discussion with project teams clarified content. RESULTS: Survivors reported interventions to be acceptable, appropriate and effective. Strong clinical leadership was identified as a critical success factor. Workforce education was recognized as important. Partnerships with consumers, primary care and community organizations; risk stratified pathways with rapid re-access to specialist care; and early preparation for survivorship, self-management and shared care models supported positive project outcomes. Tailoring care to individual needs and predicted risks was supported. Challenges included: lack of valid assessment and prediction tools; limited evidence to support novel care models; workforce redesign; and effective engagement with community-based care and issues around survivorship terminology. CONCLUSION: The VCSP project outcomes have added to growing evidence around posttreatment care. Future projects should consider the identified enablers and challenges when designing and implementing survivorship care.

Knowledge disclosure as a weapon in technological change battles: straight shot or backfire?

This work aims at evaluating how effective is knowledge disclosure in attenuating institutional negative reactions caused by uncertainties brought by firms’ new strategies that respond to novel technologies. The empirical setting is from an era of technological ferment, the period of the introduction of the voice over internet protocol (VoIP) in the USA in the early 2000’s. This technology led to the convergence of the wireline telecommu- nications and cable television industries. The Institutional Brokers’ Estimate System (also known as the I/B/E/S system) was used to capture reactions of securities analysts, a revealed important source of institutional pressure on firms’ strategies. For assessing knowledge disclosure, a coding technique and a established content analysis framework were used to quantitatively measure the non-numerical and unstructured data of transcripts of business events occurred at that time. Eventually, several binary response models were tested in order to assess the effect of knowledge disclosure on the probability of institutional positive reactions. The findings are that the odds of favorable institutional reactions increase when a specific kind of knowledge is disclosed. It can be concluded that knowledge disclosure can be considered as a weapon in technological changes situations, attenuating adverse institutional reactions to the companies’ strategies in environments of technological changes.

A díade saberes e práticas docentes : um estudo de suas inter-relações

This study The Dyad of knowledge and teaching practices: an inter-relational study deals with the relationship between conceptual knowledge on behalf of the teachers and their teaching practices. The research aims to investigate the relations amongst conceptual meanings related to the professor and the practices of three (03) Fundamental Cycle public schools teachers in Natal-Brazil. Thus, a collaborative research of qualitative nature was performed by us. It was based on collaboration and critical reflection, as well as the socialhistorical theoretical methodological principles of Ferreira (2009). This was acknowledged as an analytical support for the reflections that were realized on concepts related to teachers and teaching considering the archeology on these concepts. The methodological procedures and tools we used consisted of Formative Autobiographies, Reflexive Study, Collaborative Observation, as well as some Reflexive Sessions. The analysis framework was based on information obtained by these methodological procedures as well as the critical collaborative and reflexive procedures. The studies permitted us to widen our knowledge related to the conceptual meaning of teaching and teachers. But it was not always possible for us to (re)elaborate these meanings in the conceptual phase. This was only possible to understand once our Formative Autobiographies were analyzed. They reveal that the concept elaboration process is not a part of our own formative path. The time that was dedicated to that proved to not be enough. The concept elaboration process demands time, effort as well as life-long learning skills. This is not always possible to achieve in this part of the study, on the other hand, this was possible to acknowledge that in the different stages of our conceptual elaboration. The teaching practices that we analyzed were predominantly heterogeneous and were fundamented on meanings of concepts related to teachers and teaching, that were internalized beforehand, (re)elaborated according to the conflicted and contradictory situations. The reflexive and collaborative process that we experimented during the Reflexive Sessions pointed out the predominance of technical and practical reflection process. In some moments it was possible for us to critically reflect on teaching practices due to the collaborative mode that we experienced. The importance of collaboration for teaching formation and professional development of behalf of teachers in general is pointed out by this research. Also regarding this research it was possible to see that there was personal and professional growth, experiencing learning together to collaborative reflect, as well as to counter-argument, reformulate concepts and conceptions aiming to transform our teaching practice

Sustentabilidade e gestão ambiental no município de Moju/PA: desafios para a produção do biodiesel

O conceito de desenvolvimento sustentável e sua operacionalização emergem como uma necessidade de pensar em novas formas de mensurar o crescimento, daí o surgimento dos “Indicadores de Sustentabilidade”, criados para medir a sustentabilidade de um sistema, baseado em índices de diversas variáveis que apontam para a sustentabilidade ou não de uma região. Na Amazônia e no Estado do Pará, pouco se tem aplicado ferramentas de análise de sustentabilidade em suas mais diversas dimensões. Recentemente nesta região, foram criados os “Pólos de Produção do Biodiesel” através da Política Nacional de Produção do Biodiesel – PNPB e neste sentido, destaca-se o Município de Moju, no Pará, como um dos maiores produtores de dendê. Apesar da enorme expansão de cultivo de dendezeiro neste município, há dúvidas sobre a capacidade de Moju de receber uma política pública como essa, que se configura em novas territorialidades e novas dinâmicas sociais, econômicas e ambientais e trazem imensos desafios, que requerem uma capacidade de gestão ambiental forte. Dessa forma, o estudo dedica-se a analisar o nível de sustentabilidade do município de Moju e a capacidade de gestão ambiental deste município. Foram realizadas entrevistas e busca de dados secundários e para a análise de sustentabilidade usou-se como ferramenta de avaliação o Barômetro da Sustentabilidade. Observou-se que este município tende a baixa sustentabilidade com poucos avanços socioeconômicos e ambientais, o que denota a fragilidade do município nas questões socioambientais. Em geral, o município possui habilitação para exercer a gestão ambiental plena, ou seja, apresenta uma estrutura administrativa considerada desejável, porém sua estrutura operacional ainda é deficitária ou ineficaz, o que trará certamente problemas para a condução do PNPB.

Present bounds on new neutral vector resonances from electroweak gauge boson pair production at the LHC

Several extensions of the standard model predict the existence of new neutral spin-1 resonances associated with the electroweak symmetry breaking sector. Using the data from ATLAS (with integrated luminosity of L = 1.02 fb(-1)) and CMS (with integrated luminosity of L = 1.55 fb(-1)) on the production of W+W- pairs through the process pp --> l(+)l(-)' is not an element of(T), we place model independent bounds on these new vector resonances masses, couplings, and widths. Our analyses show that the present data exclude new neutral vector resonances with masses up to 1-2.3 TeV depending on their couplings and widths. We also demonstrate how to extend our analysis framework to different models with a specific example.

Trade-offs between voice and silence: a qualitative exploration of oncology staff's decisions to speak up about safety concerns

BACKGROUND Research suggests that "silence", i.e., not voicing safety concerns, is common among health care professionals (HCPs). Speaking up about patient safety is vital to avoid errors reaching the patient and thus to prevent harm and also to improve a culture of teamwork and safety. The aim of our study was to explore factors that affect oncology staff's decision to voice safety concerns or to remain silent and to describe the trade-offs they make. METHODS In a qualitative interview study with 32 doctors and nurses from 7 oncology units we investigated motivations and barriers to speaking up towards co-workers and supervisors. An inductive thematic content analysis framework was applied to the transcripts. Based on the individual experiences of participants, we conceptualize the choice to voice concerns and the trade-offs involved. RESULTS Preventing patients from serious harm constitutes a strong motivation to speaking up but competes with anticipated negative outcomes. Decisions whether and how to voice concerns involved complex considerations and trade-offs. Many respondents reflected on whether the level of risk for a patient "justifies" the costs of speaking up. Various barriers for voicing concerns were reported, e.g., damaging relationships. Contextual factors, such as the presence of patients and co-workers in the alarming situation, affect the likelihood of anticipated negative outcomes. Speaking up to well-known co-workers was described as considerably easier whereas "not knowing the actor well" increases risks and potential costs of speaking up. CONCLUSIONS While doctors and nurses felt strong obligation to prevent errors reaching individual patients, they were not engaged in voicing concerns beyond this immediacy. Our results offer in-depth insight into fears and conditions conducive of silence and voicing and can be used for educational interventions and leader reinforcement.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Linear global instability of non-orthogonal incompressible swept attachment-line boundary layer flow

Instability of the orthogonal swept attachment line boundary layer has received attention by local1, 2 and global3–5 analysis methods over several decades, owing to the significance of this model to transition to turbulence on the surface of swept wings. However, substantially less attention has been paid to the problem of laminar flow instability in the non-orthogonal swept attachment-line boundary layer; only a local analysis framework has been employed to-date.6 The present contribution addresses this issue from a linear global (BiGlobal) instability analysis point of view in the incompressible regime. Direct numerical simulations have also been performed in order to verify the analysis results and unravel the limits of validity of the Dorrepaal basic flow7 model analyzed. Cross-validated results document the effect of the angle _ on the critical conditions identified by Hall et al.1 and show linear destabilization of the flow with decreasing AoA, up to a limit at which the assumptions of the Dorrepaal model become questionable. Finally, a simple extension of the extended G¨ortler-H¨ammerlin ODE-based polynomial model proposed by Theofilis et al.4 is presented for the non-orthogonal flow. In this model, the symmetries of the three-dimensional disturbances are broken by the non-orthogonal flow conditions. Temporal and spatial one-dimensional linear eigenvalue codes were developed, obtaining consistent results with BiGlobal stability analysis and DNS. Beyond the computational advantages presented by the ODE-based model, it allows us to understand the functional dependence of the three-dimensional disturbances in the non-orthogonal case as well as their connections with the disturbances of the orthogonal stability problem.

Gestión óptima de embalses en avenidas incorporando al concepto de incertidumbre : aplicación a embalses con central hidroeléctrica

Esta tesis realiza una contribución metodológica al problema de la gestión óptima de embalses hidroeléctricos durante eventos de avenidas, considerando un enfoque estocástico y multiobjetivo. Para ello se propone una metodología de evaluación de estrategias de laminación en un contexto probabilístico y multiobjetivo. Además se desarrolla un entorno dinámico de laminación en tiempo real con pronósticos que combina un modelo de optimización y algoritmos de simulación. Estas herramientas asisten a los gestores de las presas en la toma de decisión respecto de cuál es la operación más adecuada del embalse. Luego de una detallada revisión de la bibliografía, se observó que los trabajos en el ámbito de la gestión óptima de embalses en avenidas utilizan, en general, un número reducido de series de caudales o hidrogramas para caracterizar los posibles escenarios. Limitando el funcionamiento satisfactorio de un modelo determinado a situaciones hidrológicas similares. Por otra parte, la mayoría de estudios disponibles en este ámbito abordan el problema de la laminación en embalses multipropósito durante la temporada de avenidas, con varios meses de duración. Estas características difieren de la realidad de la gestión de embalses en España. Con los avances computacionales en materia de gestión de información en tiempo real, se observó una tendencia a la implementación de herramientas de operación en tiempo real con pronósticos para determinar la operación a corto plazo (involucrando el control de avenidas). La metodología de evaluación de estrategias propuesta en esta tesis se basa en determinar el comportamiento de éstas frente a un espectro de avenidas características de la solicitación hidrológica. Con ese fin, se combina un sistema de evaluación mediante indicadores y un entorno de generación estocástica de avenidas, obteniéndose un sistema implícitamente estocástico. El sistema de evaluación consta de tres etapas: caracterización, síntesis y comparación, a fin de poder manejar la compleja estructura de datos resultante y realizar la evaluación. En la primera etapa se definen variables de caracterización, vinculadas a los aspectos que se quieren evaluar (seguridad de la presa, control de inundaciones, generación de energía, etc.). Estas variables caracterizan el comportamiento del modelo para un aspecto y evento determinado. En la segunda etapa, la información de estas variables se sintetiza en un conjunto de indicadores, lo más reducido posible. Finalmente, la comparación se lleva a cabo a partir de la comparación de esos indicadores, bien sea mediante la agregación de dichos objetivos en un indicador único, o bien mediante la aplicación del criterio de dominancia de Pareto obteniéndose un conjunto de soluciones aptas. Esta metodología se aplicó para calibrar los parámetros de un modelo de optimización de embalse en laminación y su comparación con otra regla de operación, mediante el enfoque por agregación. Luego se amplió la metodología para evaluar y comparar reglas de operación existentes para el control de avenidas en embalses hidroeléctricos, utilizando el criterio de dominancia. La versatilidad de la metodología permite otras aplicaciones, tales como la determinación de niveles o volúmenes de seguridad, o la selección de las dimensiones del aliviadero entre varias alternativas. Por su parte, el entorno dinámico de laminación al presentar un enfoque combinado de optimización-simulación, permite aprovechar las ventajas de ambos tipos de modelos, facilitando la interacción con los operadores de las presas. Se mejoran los resultados respecto de los obtenidos con una regla de operación reactiva, aun cuando los pronósticos se desvían considerablemente del hidrograma real. Esto contribuye a reducir la tan mencionada brecha entre el desarrollo teórico y la aplicación práctica asociada a los modelos de gestión óptima de embalses. This thesis presents a methodological contribution to address the problem about how to operate a hydropower reservoir during floods in order to achieve an optimal management considering a multiobjective and stochastic approach. A methodology is proposed to assess the flood control strategies in a multiobjective and probabilistic framework. Additionally, a dynamic flood control environ was developed for real-time operation, including forecasts. This dynamic platform combines simulation and optimization models. These tools may assist to dam managers in the decision making process, regarding the most appropriate reservoir operation to be implemented. After a detailed review of the bibliography, it was observed that most of the existing studies in the sphere of flood control reservoir operation consider a reduce number of hydrographs to characterize the reservoir inflows. Consequently, the adequate functioning of a certain strategy may be limited to similar hydrologic scenarios. In the other hand, most of the works in this context tackle the problem of multipurpose flood control operation considering the entire flood season, lasting some months. These considerations differ from the real necessity in the Spanish context. The implementation of real-time reservoir operation is gaining popularity due to computational advances and improvements in real-time data management. The methodology proposed in this thesis for assessing the strategies is based on determining their behavior for a wide range of floods, which are representative of the hydrological forcing of the dam. An evaluation algorithm is combined with a stochastic flood generation system to obtain an implicit stochastic analysis framework. The evaluation system consists in three stages: characterizing, synthesizing and comparing, in order to handle the complex structure of results and, finally, conduct the evaluation process. In the first stage some characterization variables are defined. These variables should be related to the different aspects to be evaluated (such as dam safety, flood protection, hydropower, etc.). Each of these variables characterizes the behavior of a certain operating strategy for a given aspect and event. In the second stage this information is synthesized obtaining a reduced group of indicators or objective functions. Finally, the indicators are compared by means of an aggregated approach or by a dominance criterion approach. In the first case, a single optimum solution may be achieved. However in the second case, a set of good solutions is obtained. This methodology was applied for calibrating the parameters of a flood control model and to compare it with other operating policy, using an aggregated method. After that, the methodology was extent to assess and compared some existing hydropower reservoir flood control operation, considering the Pareto approach. The versatility of the method allows many other applications, such as determining the safety levels, defining the spillways characteristics, among others. The dynamic framework for flood control combines optimization and simulation models, exploiting the advantages of both techniques. This facilitates the interaction between dam operators and the model. Improvements are obtained applying this system when compared with a reactive operating policy, even if the forecasts deviate significantly from the observed hydrograph. This approach contributes to reduce the gap between the theoretical development in the field of reservoir management and its practical applications.

Assessing urban mobility through participatory scenario building and combined utility-regret assessment

La planificación de la movilidad sostenible urbana es una tarea compleja que implica un alto grado de incertidumbre debido al horizonte de planificación a largo plazo, la amplia gama de paquetes de políticas posibles, la necesidad de una aplicación efectiva y eficiente, la gran escala geográfica, la necesidad de considerar objetivos económicos, sociales y ambientales, y la respuesta del viajero a los diferentes cursos de acción y su aceptabilidad política (Shiftan et al., 2003). Además, con las tendencias inevitables en motorización y urbanización, la demanda de terrenos y recursos de movilidad en las ciudades está aumentando dramáticamente. Como consecuencia de ello, los problemas de congestión de tráfico, deterioro ambiental, contaminación del aire, consumo de energía, desigualdades en la comunidad, etc. se hacen más y más críticos para la sociedad. Esta situación no es estable a largo plazo. Para enfrentarse a estos desafíos y conseguir un desarrollo sostenible, es necesario considerar una estrategia de planificación urbana a largo plazo, que aborde las necesarias implicaciones potencialmente importantes. Esta tesis contribuye a las herramientas de evaluación a largo plazo de la movilidad urbana estableciendo una metodología innovadora para el análisis y optimización de dos tipos de medidas de gestión de la demanda del transporte (TDM). La metodología nueva realizado se basa en la flexibilización de la toma de decisiones basadas en utilidad, integrando diversos mecanismos de decisión contrariedad‐anticipada y combinados utilidad‐contrariedad en un marco integral de planificación del transporte. La metodología propuesta incluye dos aspectos principales: 1) La construcción de escenarios con una o varias medidas TDM usando el método de encuesta que incorpora la teoría “regret”. La construcción de escenarios para este trabajo se hace para considerar específicamente la implementación de cada medida TDM en el marco temporal y marco espacial. Al final, se construyen 13 escenarios TDM en términos del más deseable, el más posible y el de menor grado de “regret” como resultado de una encuesta en dos rondas a expertos en el tema. 2) A continuación se procede al desarrollo de un marco de evaluación estratégica, basado en un Análisis Multicriterio de Toma de Decisiones (Multicriteria Decision Analysis, MCDA) y en un modelo “regret”. Este marco de evaluación se utiliza para comparar la contribución de los distintos escenarios TDM a la movilidad sostenible y para determinar el mejor escenario utilizando no sólo el valor objetivo de utilidad objetivo obtenido en el análisis orientado a utilidad MCDA, sino también el valor de “regret” que se calcula por medio del modelo “regret” MCDA. La función objetivo del MCDA se integra en un modelo de interacción de uso del suelo y transporte que se usa para optimizar y evaluar los impactos a largo plazo de los escenarios TDM previamente construidos. Un modelo de “regret”, llamado “referencedependent regret model (RDRM)” (modelo de contrariedad dependiente de referencias), se ha adaptado para analizar la contribución de cada escenario TDM desde un punto de vista subjetivo. La validación de la metodología se realiza mediante su aplicación a un caso de estudio en la provincia de Madrid. La metodología propuesta define pues un procedimiento técnico detallado para la evaluación de los impactos estratégicos de la aplicación de medidas de gestión de la demanda en el transporte, que se considera que constituye una herramienta de planificación útil, transparente y flexible, tanto para los planificadores como para los responsables de la gestión del transporte. Planning sustainable urban mobility is a complex task involving a high degree of uncertainty due to the long‐term planning horizon, the wide spectrum of potential policy packages, the need for effective and efficient implementation, the large geographical scale, the necessity to consider economic, social, and environmental goals, and the traveller’s response to the various action courses and their political acceptability (Shiftan et al., 2003). Moreover, with the inevitable trends on motorisation and urbanisation, the demand for land and mobility in cities is growing dramatically. Consequently, the problems of traffic congestion, environmental deterioration, air pollution, energy consumption, and community inequity etc., are becoming more and more critical for the society (EU, 2011). Certainly, this course is not sustainable in the long term. To address this challenge and achieve sustainable development, a long‐term perspective strategic urban plan, with its potentially important implications, should be established. This thesis contributes on assessing long‐term urban mobility by establishing an innovative methodology for optimizing and evaluating two types of transport demand management measures (TDM). The new methodology aims at relaxing the utility‐based decision‐making assumption by embedding anticipated‐regret and combined utilityregret decision mechanisms in an integrated transport planning framework. The proposed methodology includes two major aspects: 1) Construction of policy scenarios within a single measure or combined TDM policy‐packages using the survey method incorporating the regret theory. The purpose of building the TDM scenarios in this work is to address the specific implementation in terms of time frame and geographic scale for each TDM measure. Finally, 13 TDM scenarios are built in terms of the most desirable, the most expected and the least regret choice by means of the two‐round Delphi based survey. 2) Development of the combined utility‐regret analysis framework based on multicriteria decision analysis (MCDA). This assessment framework is used to compare the contribution of the TDM scenario towards sustainable mobility and to determine the best scenario considering not only the objective utility value obtained from the utilitybased MCDA, but also a regret value that is calculated via a regret‐based MCDA. The objective function of the utility‐based MCDA is integrated in a land use and transport interaction model and is used for optimizing and assessing the long term impacts of the constructed TDM scenarios. A regret based model, called referente dependent regret model (RDRM) is adapted to analyse the contribution of each TDM scenario in terms of a subjective point of view. The suggested methodology is implemented and validated in the case of Madrid. It defines a comprehensive technical procedure for assessing strategic effects of transport demand management measures, which can be useful, transparent and flexible planning tool both for planners and decision‐makers.