Das Ziel der Masterarbeit ist es zu klären, ob private Haushalte variable Strompreise akzeptieren und die Stärke der charakteristischen Merkmale zu ermitteln. Der dazu benötigte Datensatz wurde mit Hilfe einer Stated Choice Befragung im Internet ermittelt. Dafür wurden drei Gerätekategorien und ein Dreitarifmodell formuliert. Für die Auswertung wurde ein additiv verknüpftes Teilwert-Nutzenmodell und ein binäres Logit-Choice-Modell verwendet. Signifikante Variablen wurden über das Top-down-Verfahren bestimmt. Das Modell und die Schätzer der Preise wurden im Anschluss durch Hypothesentest getestet. Als signifikante Schätzer, mit stark negativen Werten, stellten sich in allen Kategorien die Preise heraus. Die Hypothesentests ergaben, dass es sinnvoll ist, die Schätzer der Preise für die ersten beiden Gerätetypen zusammenzufassen. Es stellte sich eine unterproportionale Preiselastizität der Nachfrage heraus und eine hohe Akzeptanz ein Teil der Geräte in den Nachtstunden zu nutzen. Insgesamt sprachen sich mehr Teilnehmer für ein Smart-Meter-Gateway aus als dagegen.:Kurzfassung I Abstract I Themenbeschreibung für eine Forschungsarbeit II Inhaltsverzeichnis III Abbildungsverzeichnis V Tabellenverzeichnis VI Abkürzungsverzeichnis VII 1. Einleitung - 1 - 2. Gegenwärtiger Strommarkt - 3 - 2.1 Aufbau der Elektrizitätswirtschaft - 3 - 2.2 Strombörse - 5 - 2.3 Preisbildung des Stroms - 8 - 3. Nutzung variabler Strompreise - 13 - 3.1 Probleme und Gestaltung eines zukünftigen Strommarktes - 14 - 3.2 Funktionsweise des Demand Side Management - 19 - 3.3 Ausblick auf zukünftige Tarife - 25 - 3.4 Aufbau einer zukünftigen überregionalen und häuslichen Energieinfrastruktur - 28 - 3.5 Bandbreite möglicher Speichertechnologien des zukünftigen Strommarktes - 32 - 4. Theoretische Grundlagen - 39 - 4.1 Stated Preference vs. Revealed Preference - 39 - 4.2 Conjoint-Analyse - 40 - 4.3 Diskrete Wahlmodelle - 42 - 5. Hintergründe zur Erstellung des Fragebogens - 50 - 6. Modellspezifikation - 53 - 7. Analyse der Umfrage - 57 - 7.1 Auswertung des Modells - 57 - 7.2 Teststatistik - 62 - 8. Interpretation der Ergebnisse - 66 - 9. Fazit - 68 - Literaturverzeichnis IX Anhang XIV Erklärung zur Urheberschaft XXII / The aim of the master thesis is to clarify whether private households accept variable electricity prices and determine the strength of the characteristic attributes. The data set was determined with a Stated Choice survey on the Internet. For this purpose, three device categories and a three-tariff model were formulated. An additive-linked partial-value model and a binary logit choice model were used for the evaluation. Significant variables were determined by using the top-down method. Afterwards the model and the estimators of the prices were tested with statistical hypothesis testings. The price emerged as a significant estimator, with strongly negative values in all categories. The hypothesis tests showed that it is useful to conclude the estimators of the prices for the first two device types. The results showed an inelastic price elasticity of demand and a high acceptance of the subjects to use a part of the devices in the night hours. Overall, more participants decide to use a smart meter gateway than to refuse it.:Kurzfassung I Abstract I Themenbeschreibung für eine Forschungsarbeit II Inhaltsverzeichnis III Abbildungsverzeichnis V Tabellenverzeichnis VI Abkürzungsverzeichnis VII 1. Einleitung - 1 - 2. Gegenwärtiger Strommarkt - 3 - 2.1 Aufbau der Elektrizitätswirtschaft - 3 - 2.2 Strombörse - 5 - 2.3 Preisbildung des Stroms - 8 - 3. Nutzung variabler Strompreise - 13 - 3.1 Probleme und Gestaltung eines zukünftigen Strommarktes - 14 - 3.2 Funktionsweise des Demand Side Management - 19 - 3.3 Ausblick auf zukünftige Tarife - 25 - 3.4 Aufbau einer zukünftigen überregionalen und häuslichen Energieinfrastruktur - 28 - 3.5 Bandbreite möglicher Speichertechnologien des zukünftigen Strommarktes - 32 - 4. Theoretische Grundlagen - 39 - 4.1 Stated Preference vs. Revealed Preference - 39 - 4.2 Conjoint-Analyse - 40 - 4.3 Diskrete Wahlmodelle - 42 - 5. Hintergründe zur Erstellung des Fragebogens - 50 - 6. Modellspezifikation - 53 - 7. Analyse der Umfrage - 57 - 7.1 Auswertung des Modells - 57 - 7.2 Teststatistik - 62 - 8. Interpretation der Ergebnisse - 66 - 9. Fazit - 68 - Literaturverzeichnis IX Anhang XIV Erklärung zur Urheberschaft XXII

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Le problème de tarification qui nous intéresse ici consiste à maximiser le revenu généré par les usagers d'un réseau de transport. Pour se rendre à leurs destinations, les usagers font un choix de route et utilisent des arcs sur lesquels nous imposons des tarifs. Chaque route est caractérisée (aux yeux de l'usager) par sa "désutilité", une mesure de longueur généralisée tenant compte à la fois des tarifs et des autres coûts associés à son utilisation. Ce problème a surtout été abordé sous une modélisation déterministe de la demande selon laquelle seules des routes de désutilité minimale se voient attribuer une mesure positive de flot. Le modèle déterministe se prête bien à une résolution globale, mais pèche par manque de réalisme. Nous considérons ici une extension probabiliste de ce modèle, selon laquelle les usagers d'un réseau sont alloués aux routes d'après un modèle de choix discret logit. Bien que le problème de tarification qui en résulte est non linéaire et non convexe, il conserve néanmoins une forte composante combinatoire que nous exploitons à des fins algorithmiques. Notre contribution se répartit en trois articles. Dans le premier, nous abordons le problème d'un point de vue théorique pour le cas avec une paire origine-destination. Nous développons une analyse de premier ordre qui exploite les propriétés analytiques de l'affectation logit et démontrons la validité de règles de simplification de la topologie du réseau qui permettent de réduire la dimension du problème sans en modifier la solution. Nous établissons ensuite l'unimodalité du problème pour une vaste gamme de topologies et nous généralisons certains de nos résultats au problème de la tarification d'une ligne de produits. Dans le deuxième article, nous abordons le problème d'un point de vue numérique pour le cas avec plusieurs paires origine-destination. Nous développons des algorithmes qui exploitent l'information locale et la parenté des formulations probabilistes et déterministes. Un des résultats de notre analyse est l'obtention de bornes sur l'erreur commise par les modèles combinatoires dans l'approximation du revenu logit. Nos essais numériques montrent qu'une approximation combinatoire rudimentaire permet souvent d'identifier des solutions quasi-optimales. Dans le troisième article, nous considérons l'extension du problème à une demande hétérogène. L'affectation de la demande y est donnée par un modèle de choix discret logit mixte où la sensibilité au prix d'un usager est aléatoire. Sous cette modélisation, l'expression du revenu n'est pas analytique et ne peut être évaluée de façon exacte. Cependant, nous démontrons que l'utilisation d'approximations non linéaires et combinatoires permet d'identifier des solutions quasi-optimales. Finalement, nous en profitons pour illustrer la richesse du modèle, par le biais d'une interprétation économique, et examinons plus particulièrement la contribution au revenu des différents groupes d'usagers. / The network pricing problem consists in finding tolls to set on a subset of a network's arcs, so to maximize a revenue expression. A fixed demand of commuters, going from their origins to their destinations, is assumed. Each commuter chooses a path of minimal "disutility", a measure of discomfort associated with the use of a path and which takes into account fixed costs and tolls. A deterministic modelling of commuter behaviour is mostly found in the literature, according to which positive flow is only assigned to \og shortest\fg\: paths. Even though the determinist pricing model is amenable to global optimization by the use of enumeration techniques, it has often been criticized for its lack of realism. In this thesis, we consider a probabilistic extension of this model involving a logit dicrete choice model. This more realistic model is non-linear and non-concave, but still possesses strong combinatorial features. Our analysis spans three separate articles. In the first we tackle the problem from a theoretical perspective for the case of a single origin-destination pair and develop a first order analysis that exploits the logit assignment analytical properties. We show the validity of simplification rules to the network topology which yield a reduction in the problem dimensionality. This enables us to establish the problem's unimodality for a wide class of topologies. We also establish a parallel with the product-line pricing problem, for which we generalize some of our results. In our second article, we address the problem from a numerical point of view for the case where multiple origin-destination pairs are present. We work out algorithms that exploit both local information and the pricing problem specific combinatorial features. We provide theoretical results which put in perspective the deterministic and probabilistic models, as well as numerical evidence according to which a very simple combinatorial approximation can lead to the best solutions. Also, our experiments clearly indicate that under any reasonable setting, the logit pricing problem is much smoother, and admits less optima then its deterministic counterpart. The third article is concerned with an extension to an heterogeneous demand resulting from a mixed-logit discrete choice model. Commuter price sensitivity is assumed random and the corresponding revenue expression admits no closed form expression. We devise nonlinear and combinatorial approximation schemes for its evaluation and optimization, which allow us to obtain quasi-optimal solutions. Numerical experiments here indicate that the most realistic model yields the best solution, independently of how well the model can actually be solved. We finally illustrate how the output of the model can be used for economic purposes by evaluating the contributions to the revenue of various commuter groups.

Cette thèse a pour objectif d’incorporer des éléments de théories de psychologie et d’économie comportementale dans des modèles de choix discret afin d’améliorer la compréhension du choix modal réalisé à l’échelle régionale. Les estimations se basent sur une enquête de type choice experiment présentée en première partie. Une deuxième partie s’intéresse à l’incorporation de variables latentes pour expliquer le choix modal. Après une revue de littérature sur les modèles de choix hybrides, c’est-à-dire des modèles combinant modèle d’équations structurelles et modèle de choix discret, un tel modèle est estimé pour montrer comment l’hétérogénéité d’outputs économiques (ici, la valeur du temps) peut être expliquée à l’aide de variables latentes (ici, le confort perçu dans les transports en commun) et de variables observables (ici, la garantie d’une place assise). La simulation de scénarios montre cependant que le gain économique (diminution de la valeur du temps) est plus élevé lorsque les politiques agissent sur des dimensions palpables que sur des dimensions latentes. S’appuyant sur un modèle de médiation, l’estimation d’un modèle d’équations structurelles montre par ailleurs que l’effet de la conscience environnementale sur les habitudes de choix modal est partiellement médié par l’utilité indirecte retirée de l’usage des transports en commun. Une troisième partie s’intéresse à deux formalisations de l’utilité issues de l’économie comportementale : 1) l’utilité dépendante au rang en situation de risque et 2) l’utilité dépendante à la référence. Dans un premier temps, un modèle d’utilité dépendante au rang est inséré dans des modèles de choix discret et, en particulier, un modèle à classes latentes, afin d’analyser l’hétérogénéité intra- et inter-individuelle lorsque le temps de déplacement n’est pas fiable. La probabilité de survenue d’un retard est sur-évaluée pour les déplacements en train et sous-évaluée pour les déplacements en voiture, en particulier pour les automobilistes, les usagers du train prenant d’avantage en compte l’espérance du temps de déplacement. Dans les modèles prenant en compte l’aversion au risque, les fonctions d’utilité sont convexes, ce qui implique une décroissance,de la valeur du temps. Dans un deuxième temps, une nouvelle famille de modèles de choix discret généralisant le modèle logit multinomial, les modèles de référence, est estimée. Sur mes données, ces modèles permettent une meilleure sélection des variables explicatives que le logit multinomial et l’estimation d’outputs économiques plus robustes, notamment en cas de forte hétérogénéité inobservée. La traduction économique des modèles de référence montre que les meilleurs modèles empiriques sont également les plus compatibles avec le modèle de dépendance à la référence de Tversky et Kahneman. / The objective of this thesis is to incorporate aspects of psychology and behavioral economics theories in discrete choice models to promote a better understanding of mode choice at regional level. Part II examines the inclusion of latent variables to explain mode choice. A literature review of integrated choice and latent variable models – that is, models combining a structural equation model and a discrete choice model – is followed by the estimation of an integrated choice and latent variable model to show how the heterogeneity of economic outputs (here, value of time) can be explained with latent variables (here, perceived comfort in public transport) and observable variables (here, the guarantee of a seat). The simulation of scenarios shows, however, that the economic gain (decrease in value of time) is higher when policies address tangible factors than when they address latent factors. On the basis of a mediation model, the estimation of a structural equation model furthermore implies that the influence of environmental concern on mode choice habits is partially mediated by the indirect utility derived frompublic transport use. Part III examines two utility formulations taken from behavioral economics: 1) rankdependent utility to model risky choices, and 2) reference-dependent utility. Firstly, a rank-dependent utility model is included in discrete choice models and, in particular, a latent-class model, in order to analyze intra- and inter-individual heterogeneity when the travel time is subject to variability. The results show that the probability of a delay is over-estimated for train travel and under-estimated for car travel, especially for car users, as train users are more likely to take into account the expected travel time. In the models that account for risk aversion, the utility functions are convex, which implies a decrease in value of time. Secondly, a new family of discrete choice models generalizing the multinomial logit model, the reference models, is estimated. On my data, these models allow for a better selection of explanatory variables than the multinomial logit model and a more robust estimation of economic outputs, particularly in cases of high unobserved heterogeneity. The economic formulation of reference models shows thatthe best empirical models are also more compatible with Tversky et Kahneman’s reference-dependent model.

Escolhas são meios para que indivíduos e consumidores atinjam seus objetivos. São objeto de estudo em diversas disciplinas e eu me apoiei em três delas para desenvolver estas tese. Modelos normativos da economia que definem o homo economicus, modelos descritivos das teorias de decisão comportamental que forjam o homo aptabilis, capaz de fazer escolhas que permitam o atingimento de seus objetivos. E modelos econométricos de escolha discreta, que permitem o uso e teste de teorias comportamentais usando métodos flexíveis e realistas. O argumento central desta tese é que modelos econométricos devem considerar a heterogeneidade do comportamento individual em todo o processo de escolha, incluindo objetivos do consumidor, estratégias de decisão, formação de conjuntos de escolha subjetivos, além de preferência. O não reconhecimento desta complexidade nos processos de escolha produz modelos falsos, capturando a heterogeneidade no nível das preferências e induzindo organizações a tomarem decisões equivocadas. Para desenvolver este argumento, esta tese se organiza em três seções. Na primeira eu faço uma revisão da literatura com foco nos diversos níveis do processo de escolha onde a heterogeneidade se manifesta e relaciono os modelos de escolha com as teorias comportamentais de decisão. Na segunda seção é desenvolvido um estudo sobre os vieses provocados quando a heterogeneidade na formação de conjuntos subjetivos de escolha não é levada em consideração. Através de experimentos de Monte Carlo fica comprovado que os parâmetros de modelos econométricos de escolha são generalizadamente viesados, levando à estimadas equivocadas de probabilidades de escolhas das marcas e das elasticidades das probabilidades de escolha. Esses resultados são usados para motivar uma abordagem de teoria dos jogos que resulta em equilíbrio distante do ideal, do ponto de vista de resultados das empresas. Finalmente na terceira seção, é desenvolvido um modelo de escolha discreta baseado em múltiplos meta-objetivos e em diferentes processos de escolha individual. Mais um experimento de Monte Carlo comprova que o modelo é capaz de recuperar o parâmetros do processo gerador de dados. O modelo além de reconhecer a existência de diversos meta-objetivos que ativam diferentes regras comportamentais, também permite estudar a adaptação do processo de escolha individual em função de variáveis de contexto, de situação e individuais. O modelo articula modelos econométricos com teorias comportamentais de decisão e oferece suporte para a compreensão do homo aptabilis / Choices are the means for individuals and consumers to attain their goals. They are the objects of study for several disciplines and I relied on three of them to develop this thesis. Normative models from economicsdefining the homo economicus, descriptive models from behavioral decision theories that forge the homo aptabilis, able to adaptively pursue multiple goals through choices. And discrete-choice econometric models that allow the use and testing of behavioral theories using flexible and realistic methods. The central argument of this thesis is that econometric models should consider the heterogeneity of individual behavior throughout the choice process, including consumer goals, decision strategies, choice set formation, and preferences. Failure to recognize this complexity in the choice process produces false models, capturing process heterogeneity at the level of preferences, and inducing organizations to make the wrong decisions. To develop this argument, this thesis is organized into three sections. In the first one, I review the literature focusing on the different levels of the choice process where the heterogeneity manifests itself and I relate the choice models to the behavioral decision theories. In the second section, a study is developed on the biases caused when heterogeneity in the choice set formation is not accounted for. Through Monte Carlo experiments it has been proven that the parameters of econometric choice models are generally biased, leading to misleading estimates of brands choice probabilities and of attribute\'schoice elasticities. These results are used to motivate a game theoretical approach that results in far-fetched equilibrium from the point of view of business results. Finally, in the third section, a discrete choice model based on multiple meta-goals and on different individual choice processes is developed. One more Monte Carlo experiment proves that the model is capable of retrieving the parameters of the data-generating process. The model, besides recognizing the existence of several meta-objectives that activate different behavioral rules, also allows studying the adaptation of the consumer choice process as a response to context, situation, and individual variables. The model articulates econometric models with behavioral decision theories and supports the understanding of the homo aptabilis.

Este trabalho teve como objetivo analisar a demanda potencial para um sistema de compartilhamento de bicicletas pedelecs no campus da USP de São Carlos, com foco nos deslocamentos de estudantes entre as duas áreas do campus. Para tanto, foi elaborado um conjunto de procedimentos, que constituem duas etapas: caracterização do público-alvo e análise da demanda potencial pelas bicicletas pedelecs compartilhadas. Na primeira etapa foi aplicado um questionário, elaborado com a técnica de preferência declarada, para verificar as preferências dos usuários em relação às pedelecs compartilhadas e ao ônibus operado pela USP. Os resultados desta consulta, que envolveu variáveis de condições meteorológicas, situação de ciclovias/ciclofaixas entre as áreas do campus e lotação do ponto de ônibus USP, foram posteriormente utilizados para calibrar um modelo logit e treinar uma Rede Neural Artificial (RNA). Na segunda etapa foi elaborada uma planilha eletrônica com os dados obtidos na coleta, a fim de analisar as probabilidades de escolha da pedelec (ao invés do ônibus USP). Nesta planilha também foram utilizados dados do histórico meteorológico de São Carlos no período entre 2011 e 2015. Alguns dos resultados obtidos são destacados na sequência. A probabilidade de escolha das pedelecs é, em média, três vezes maior quando existem ciclovias/ciclofaixas (em relação à ausência da referida infraestrutura cicloviária). A ocupação do ponto de ônibus USP também é impactante, pois as probabilidades de uso da bicicleta pedelec praticamente dobram quando o ponto está cheio. No caso da meteorologia, foi constatado que as maiores probabilidades ocorrem no Outono e no Inverno, ou seja, nas épocas em que se concentram os dias mais secos e com menores temperaturas. Para o período letivo de 2011 a 2015, considerando a situação atual (isto é, sem ciclovias/ciclofaixas entre as áreas), os valores de probabilidade de uso da pedelec correspondem a 9% com o ponto vazio e 19% com o ponto cheio. Se houvesse ciclovias/ciclofaixas, a probabilidade seria de até 54%. Desse modo, a estratégia de análise desenvolvida conceitualmente, bem como implantada em planilha eletrônica, se constitui em importante ferramenta de auxílio para a condução da política de transportes que a Prefeitura do campus irá adotar para os anos futuros. Além disso, evidencia uma possível demanda potencial para um sistema com pedelecs compartilhadas. / The objective of this study was to analyze the potential demand for a pedelec sharing system at the São Carlos campus of the University of São Paulo (USP), aiming at the displacements of students between the two campus Areas. The set of procedures developed to reach the objective has involved two steps: characterization of the target audience and analysis of the potential demand for shared pedelecs. The first step was accomplished with a questionnaire designed with a stated preference approach for identifying users\' preferences regarding shared pedelecs and the bus system operated by the university. The survey results, which involved variables of weather conditions, existence of bike paths/bike lanes between the campus Areas, and occupancy rates at the USP bus stop, were subsequently used to calibrate a logit model and to develop an Artificial Neural Network (ANN). The survey data were also used in the second step of the process, in which an electronic spreadsheet was created to analyze the probabilities of choosing the pedelec alternative (instead of the bus route operated by university). The spreadsheet was also fed with meteorological data of São Carlos in the period between 2011 and 2015. Some of the obtained outcomes are highlighted in the sequence. The probability of a pedelec being chosen is almost three times higher if bike paths/bike lanes do exist than if they do not exist. The occupancy rates of the bus stop are also particularly relevant. The probability of someone choosing a pedelec nearly doubles when the bus stop is crowded. Regarding the weather conditions, the highest probabilities are observed in the Fall and Winter seasons, i. e. in the driest and coldest days. For the entire academic period comprised between 2011 and 2015, the probabilities range from 9% (empty bus stop) to 19% (full bus stop), considering the current situation (i. e. no cycleways connect the two campus Areas). In the presence of this cycling infrastructure, however, the probability goes up to 54%. Thus, the strategy of analysis conceptually developed, and made available through an electronic spreadsheet, may be an important support tool for the implementation of transport policies by the campus administration. In addition, it highlights a likely potential demand for a system of shared pedelecs.

A meta deste trabalho é propor um procedimento para identificar os fatores que influem no uso de bicicletas e apresentar a forma como estes fatores podem ser usados para avaliar e planejar a implantação de ciclovias e/ou ciclofaixas em uma área urbana. Para tanto, foi elaborado um método que consistiu, inicialmente, de obtenção de dados socioeconômicos e de viagens urbanas de locais dotados de ciclovias e/ou ciclofaixas disponíveis para a população e de contagens volumétricas de ciclistas antes e depois da implantação da infraestrutura cicloviária. Em seguida, foi realizado um experimento que consistiu de caracterização dos dados socioeconômicos, de viagens urbanas e de infraestrutura cicloviária, a partir das quais foi estimado um modelo de escolha discreta que possibilitou a identificação de fatores que influem no uso da bicicleta na RMBS e que serviu para quantificar a demanda cicloviária em pontos preestabelecidos. Através da construção de cenários antes e depois da implantação da infraestrutura cicloviária e da comparação entre contagens volumétricas de ciclistas da RMBS, realizadas em vários pontos da rede viária, e a estimação da demanda cicloviária nestes pontos usando o modelo de escolha discreta, concluiu-se que o modelo permite identificar e quantificar os fatores e a forma como eles interferem na demanda cicloviária e que, portanto, os resultados podem ser usados para avaliar e direcionar as intervenções no sistema de transportes com o intuito de facilitar o uso do modo bicicleta. / The main aim of this work is to propose a procedure to identify and quantify the factors that influence the use of bicycles and to present how these factors can be used to evaluate and plan the deployment of segregated bike lanes and/or cyclelanes in an urban area. For attaining the aims, a method was developed and consisted firstly in to obtain socioeconomic data and urban travel data in places equipped with segregated bike lanes and/or cyclelanes available to the population and with counts of cyclists before and after the implementation of cycling infrastructure. Then, an experiment was conducted which consisted of characterization of the socioeconomic data and urban trips and cycling infrastructure from which a discrete choice model was estimated that allowed the identification of factors that influence the use of bicycles in a RMBS and was used to quantify the cycling demand on predetermined points. By the construction of scenarios before and after the implementation of cycling infrastructure and the comparison between counts of cyclists in a RMBS and the estimation of cycling demand in these points using discrete choice model, the main conclusion of this work is that the model allow us to identify and quantify the factors and how they interfere in a cycling demand. Therefore the results can be used to evaluate and direct interventions in the transport system in order to facilitate use of bicycle mode.

A meta deste trabalho é propor um procedimento para identificar os fatores que influem no uso de bicicletas e apresentar a forma como estes fatores podem ser usados para avaliar e planejar a implantação de ciclovias e/ou ciclofaixas em uma área urbana. Para tanto, foi elaborado um método que consistiu, inicialmente, de obtenção de dados socioeconômicos e de viagens urbanas de locais dotados de ciclovias e/ou ciclofaixas disponíveis para a população e de contagens volumétricas de ciclistas antes e depois da implantação da infraestrutura cicloviária. Em seguida, foi realizado um experimento que consistiu de caracterização dos dados socioeconômicos, de viagens urbanas e de infraestrutura cicloviária, a partir das quais foi estimado um modelo de escolha discreta que possibilitou a identificação de fatores que influem no uso da bicicleta na RMBS e que serviu para quantificar a demanda cicloviária em pontos preestabelecidos. Através da construção de cenários antes e depois da implantação da infraestrutura cicloviária e da comparação entre contagens volumétricas de ciclistas da RMBS, realizadas em vários pontos da rede viária, e a estimação da demanda cicloviária nestes pontos usando o modelo de escolha discreta, concluiu-se que o modelo permite identificar e quantificar os fatores e a forma como eles interferem na demanda cicloviária e que, portanto, os resultados podem ser usados para avaliar e direcionar as intervenções no sistema de transportes com o intuito de facilitar o uso do modo bicicleta. / The main aim of this work is to propose a procedure to identify and quantify the factors that influence the use of bicycles and to present how these factors can be used to evaluate and plan the deployment of segregated bike lanes and/or cyclelanes in an urban area. For attaining the aims, a method was developed and consisted firstly in to obtain socioeconomic data and urban travel data in places equipped with segregated bike lanes and/or cyclelanes available to the population and with counts of cyclists before and after the implementation of cycling infrastructure. Then, an experiment was conducted which consisted of characterization of the socioeconomic data and urban trips and cycling infrastructure from which a discrete choice model was estimated that allowed the identification of factors that influence the use of bicycles in a RMBS and was used to quantify the cycling demand on predetermined points. By the construction of scenarios before and after the implementation of cycling infrastructure and the comparison between counts of cyclists in a RMBS and the estimation of cycling demand in these points using discrete choice model, the main conclusion of this work is that the model allow us to identify and quantify the factors and how they interfere in a cycling demand. Therefore the results can be used to evaluate and direct interventions in the transport system in order to facilitate use of bicycle mode.

La reconversion des friches urbaines est unepriorité pour préserver les sols. Ce sont souvent des sitespollués ; ce qui engendre de nombreux obstacles pour lesreconvertir. Les bénéfices découlant de la reconversionsont sous-estimés tandis que les coûts sont surestimés parles opérateurs techniques et fonciers. L’impact de lastigmatisation du site amène les riverains à ne pass’approprier les nouveaux usages. Le choix de ces usagespeut être à l'origine de conflits entre les parties prenantes.Cette thèse s'intéresse à la reconversion des frichespolluées en tenant compte à la fois de lamultidimensionnalité des parties prenantes, de leurspréférences, et de leurs perceptions. Nous étudions lesobstacles et les leviers pouvant être mobilisés pourpromouvoir leur reconversion à partir d’une enquête auprès de 76 opérateurs techniques et fonciers dans unepremière partie.Dans la seconde, nous analysonsl’importance des stigmates associés aux friches polluéesauprès des riverains et futurs usagers. Une premièreenquête, menée au niveau national (803 observations)analyse leurs perceptions, représentations et préférencesvis-à-vis de ces sites. Ces dernières sont précisées à l’aided’une expérience à choix discrets (338 observations)administrée sur cinq communes impactées par ce type desite. Dans une troisième partie, nous appliquons unedémarche d’aide multicritère à la décision participativedans le cas d’une friche urbaine polluée. Elle identifie lesprojets les plus consensuels en regroupant l’ensemble desparties prenantes. Ils corresponde / Brownfield redevelopment is a key priority topreserve soils. Brownfields are often contaminated yet.Therefore, it creates numerous obstacles to reuse them.Firstly, brownfields redevelopment’s benefits areunderestimated whereas costs are overestimated bydevelopers. Secondly, brownfields are plagued with thestigma effect. This effect persists even after remediationprocess (e.g., individuals may not use facilities on aformer contaminated brownfield). Thirdly, new uses cancause conflicts between the stakeholders. As such, thisthesis deals with contaminated brownfieldredevelopment taking into account both themultidimensionality of stakeholders, their preferencesand their perceptions. developers. In a first part, we study barriers to brownfieldredevelopment and how to tackle them using a surveyamong 76 French developers.In a second part, weanalyse the importance of the stigma associated withcontaminated brownfields. A first survey (803observations), conducted at national level, investigatesindividuals’ perceptions, representations and preferencesregarding brownfield redevelopment. A second survey(338 observations), conducted among five municipalitiesimpacted by such sites, specifies their preferences usinga discrete choice experiment. In the third part, we applya participatory multicriteria decision aid. It determinesthe most consensual projects in the case of acontaminated site. They correspond to individuals’preferences that were previously analysed.

Um Strommärkte so zu konzipieren damit sie sowohl zur Verringerung der Nutzung fossiler Brennstoffe als auch zur Deckung des steigenden Energiebedarfes beitragen, ist Wissen über die Präferenzen der Konsumenten notwendig. Die vorliegende kumulative Dissertation untersucht Präferenzen für Elektrizitätsattribute von privaten Haushalten und trägt zu einem tieferen Verständnis dieser in unterschiedlichen Kontextsituationen bei. Der erste Artikel betrachtet statistische Methoden um die zwei am häufigsten angewandten Modelle – das Random Parameter Logit und das Latent Class Logit Modell – zu vergleichen. Der Artikel trägt dazu bei, den Prozess der Modellwahl zu verbessern und für die angewandte Forschung im Energiebereich anzupassen. Basierend auf den empirischen Ergebnissen des ersten Artikels untersucht der zweite Artikel die Präferenzen von privaten Haushalten in Hyderabad, Indien mit besonderem Fokus auf die physische Qualität der Energieversorgung. Die Ergebnisse deuten auf eine geringe Zahlungsbereitschaft der Konsumenten hin. Jedoch unterscheiden sich die Präferenzen der Haushalte. Die Artikel 3 und 4 basieren auf Datenerhebungen in Deutschland. Im dritten Artikel werden die Präferenzen privater Haushalte hinsichtlich der Organisationsform von Stromanbietern untersucht. Die Ergebnisse zeigen, dass die Kunden bereit sind mehr zu zahlen, wenn die Stromversorgung von Genossenschaften oder Stadtwerken übernommen wird. Der vierte Artikel betrachtet die Erfolgsfaktoren von Energiegenossenschaften in Deutschland. Die Ergebnisse zeigen, dass die Governance des Stromanbieters die Zahlungsbereitschaft für Strom beeinflussen. Insbesondere Genossenschaften werden den großen Privatunternehmen und Aktiengesellschaften vorgezogen. / In order to design electricity markets to simultaneously reduce the share of fossil fuels in energy production and meet the increasing demand for electricity, knowledge on consumer preferences is necessary. The goal of this cumulative dissertation is to contribute to the understanding of preferences of private households for electricity supply attributes in different contexts. In Paper 1 I review statistical methods to compare two frequently applied models, the random parameters logit and the latent class logit. The methods presented here can be readily used by other researchers and practitioners to better understand model performance which ultimately contributes to improving model choice in applied energy research. Based on the empirical findings of Paper 1, Paper 2 identifies preferences of private households in Hyderabad in India for electricity supply quality. The results indicate that willingness to pay for improvements are, on average, rather low. However, the preferences strongly vary between subjects. Papers 3 and 4 investigate preferences of German private households. In \textbf{Paper 3}, the respondents stated their preferences for the organization of the electricity distribution company under different renewable energy scenarios. It turned out that most people are willing to pay more for electricity supplied by municipally-owned companies and cooperatives. This additional willingness to pay increases disproportionally when the share of renewable energy is high. The paper identifies non-profit orientated distribution companies as potential drivers of the energy transition. Paper 4 investigates the determinants for the success of energy cooperatives in Germany. The results indicate that the governance of distribution companies impacts the choices of private households for electricity supply contracts. Especially, people preferred cooperative-like governance attributes.