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One of the major demand related risks for companies that produce consumer electronics goods is change in consumer preferences over time as reflected in the weights they attach to the attributes of products. This contributes to the difficulty of predicting whether consumers will purchase a new product or not and the accuracy of such forecasts can have significant ramifications for companies’ strategies, profitability and even their chances of survival. Knowledge of attribute-weights and accurate forecasts of new products can give companies better insights during the product development stages, inform go-no-go decisions on whether to launch a developed product and also support decisions on whether a recently launched product should be withdrawn or not due to poor early stage sales. Despite the important implications of change in attribute-weights, no research has investigated the extent to which such changes occur and impact on the accuracy of forecasts of the future market share of these products. Prior to the current research, it was assumed that the weights are constant over time – even when the nature of the attributes was assumed to change. To investigate these concerns choice based conjoint (CBC) was applied to data gathered in a longitudinal survey of consumer choices relating a range of consumer electronic products, where innovation has different rates and the product life cycles are various. This allowed an assessment of the extent to which the weights of attributes of choice-based conjoint models change over a six months period for consumer durable products and the degree to which this variability is dependent on the nature of the product. It demonstrates that the change in weights is greater for products that have high technological complexity and shorter lifecycles and also links the changeability of weights to the characteristics of potential consumers. The results of thesis demonstrate that the assumption of constant weights can potentially lead to inaccurate market share forecast for high-tech, short life-cycle products that are launched several months after the choice-based modelling has been conducted.

Esta dissertação visa avaliar o padrão comportamental dos pedestres nos deslocamentos na cidade de Porto Alegre. É abordado a partir da base de dados provenientes da pesquisa de entrevistas domiciliares realizadas em 2003 em Porto Alegre. Para isto, caracterizaram-se os deslocamentos a pé na cidade e identificaram-se as regiões de maior e menor concentração de viagens a pé. A fim de determinar os fatores que influenciam a decisão de caminhar foram estimados modelos logit binomiais para as viagens menores que 2 km em cada uma das regiões identificadas anteriormente. As variáveis explicativas para os modelos analisados incluem características do domicílio (disponibilidade de automóvel e renda por domicílio), dos residentes (idade), das viagens (distância e motivo da viagem), da forma urbana (densidade de domicílios, densidade populacional, comprimento médio das quadras, padrão do sistema viário, tipo de uso do solo e estacionamento tarifado em área pública) e da disponibilidade de transporte coletivo na origem da viagem. Foram consideradas duas categorias de viagens: viagens por motivo trabalho/estudo e viagens por motivo não trabalho/estudo (motivos recreacionais, compras, saúde, assuntos pessoais e outros). Os resultados do estudo mostram que características sócio-econômicas dos residentes, características das viagens e da forma urbana influenciam a escolha do modo a pé. Analisando os valores de elasticidade obtidos para as duas categorias de viagens originadas em Petrópolis e no Centro pode-se inferir que as variáveis que exercem maior influência estão relacionadas principalmente a características da viagem (distância) e à configuração física da rede viária. A análise de sensibilidade evidenciou a sensibilidade do modelo frente a alterações das variáveis estudadas. Os resultados obtidos servem de apoio para um planejamento mais adequado da mobilidade e acessibilidade dos pedestres. / This thesis aims to evaluate the pedestrians’ behavior in Porto Alegre. The study was based on a Porto Alegre household survey of 2003. During the analysis, the pedestrian trips were characterized and the traffic zones with the larger and the smaller number of pedestrian trips were identified. In order to determine the influencing factors related to the walk choice, binomial logit models were developed for trips with less than 2km in each traffic zone previously identified. The explanatory variable used in the models included the characteristics of the household (auto availability and household income), of the household members (age), of the trip (distance and purpose of the trip), of the built environment (housing units density, population density, mean block size, street patterns, land use and public parking), and transit availability in the origin of the trip. Two types of pedestrian travel were considered: work and non-work trips (shopping, health, personal purposes and others). The study results showed that socio-economic characteristics, trip characteristics and local measures of the built environment influence walk modechoice. Elasticity results for the two types of trips, with origin in “Petrópolis” and Downtown, indicate that the most influence variables are connected with trip characteristics (distance) and street design. The sensibility analysis showed the model sensibility strength under the changes introduced in the variables studied. These analysis results may provide support for a better planning for pedestrians’ mobility and accessibility.

This thesis investigates the relationship between conflict, economic growth, state capacity and natural resources in Sub-Saharan Africa. It contributes to the limited research in this area and empirically examines these relationships using different econometric models. The first empirical chapter uses a panel dataset that covers the period 1997 - 2013 to analyse the effects of economic growth on conflict in Nigeria using the negative binomial model. The findings support the direct relationship between economic growth and conflict in Nigeria. Controlling for other factors, the results indicate that increase in growth rate - measured by annual growth rate of GDP per capita - decreases the expected number of conflicts. The study finds no evidence of a relationship between levels of wealth in a state and the incidence of conflicts. The analysis controls for factors such as spill-over effects from other states and year and state effects. Finally, to address potential concerns that economic growth could be a cause of conflict or that other unobserved factors could confound the relationship between economic growth and conflict, the chapter employs instrumental variable (IV) estimation using percentage change in rainfall as an instrument. The results with the IV estimation are similar to the results without IV in terms of both sign and significance, indicating that the negative effect of economic growth on conflicts is not due to reverse causality or omitted variables. For robustness checks, a Panel Autoregressive model (PVAR) is also employed. The second empirical chapter analyses the effect of conflict on state capacity in Sub-Saharan Africa. State capacity is measured in terms of fiscal and legal capacity. It also looks at the effects of internal and external conflicts on state capacity. The chapter adopts the Ordinary least squared (OLS) and the system generalised methods of moments (GMM) estimation methods to analyse the panel data consisting of 49 Sub-Saharan countries over the period 2000 - 2015. The results suggest that conflicts have a negative and significant effect on state capacity. However, when military expenditure is used as a proxy for state capacity it is found that conflict strengthens state capacity. The results are consistent with theoretical argument that internal conflicts polarise societies and make it more difficult for governments to reach a consensus in investing in state capacity, while external conflicts mobilise domestic population against a common enemy thereby helping in state capacity building. Finally, the third empirical chapter examines the effect of natural resources on conflict onset and duration using discrete choice models with a dataset covering the period 1980 -2016. The results on the duration analysis show that natural resources prolong duration of conflicts. However, it is found that not all natural resources prolong duration of conflicts. Oil production does not seem to affect duration, whereas oil reserves and gas production lengthens the duration. The findings from the onset analysis show that both production and reserves of natural resources increase the risk of conflict onset.

Travel to outdoor recreational spaces belongs to a general class of research questions for understanding destination and travel mode choices. In travel demand modelling, discrete choice models (DCMs) have been applied to understand and predict a wide range of choices, such as how people choose among alternative destinations for jobs, homes, shopping, personal services etc. Surprisingly, DCMs have rarely been used to understand and model travel to outdoor recreational spaces. In the current literature for modelling travel to outdoor recreational spaces, the established models are Negative Binomial Regression (NBR) models, such as what was used in the UK NEA studies. However, these NBR models were developed to assess the effects of travel to outdoor recreational spaces at a national level, and they are not intended for assessing choices of individual sites. One reason for this is, as identified by previous studies, is that compared with the DCMs, the NBR models have certain limits on estimating people's choice behaviours. There is, therefore, no existing model that can represent and predict how people choose to travel to outdoor recreational spaces. Given the importance of outdoor recreational activities to urban land use planning and public health, this is a clear gap in the field. The aim of this study is to develop a new travel demand model capable of representing and predicting travel to individual outdoor recreational sites. This is achieved by answering four main research questions: First, how to build the new model for outdoor recreational travel? Secondly, is the estimation accurate enough? Thirdly, to what extent can the new model be transferred to destinations outside the case study area? And, finally, how can city planners and designers use this new method? The new model draws upon ideas from random utility theory that underlies the conventional travel demand models to represent trip generation, trip distribution and mode choice. This research follows the standard modelling procedure: data collection and preliminary analysis, model calibration, model validation and model application. The data are collated from a wide range of sources that, importantly for model transferability, cover all areas in England. The new model has been calibrated for a case study area which spanned 14 selected districts in the North-West region. Validation of the new model is based on estimating the numbers of trips to two outdoor recreational sites (Wigg Island and Wigan Flashes) and to nine English National Parks where data on visitor trips exist. In the final stage of the research, the new model is applied to estimate the changes that would arise from planning and design interventions in existing (Wigg Island and Moore Nature Reserve) and proposed (Arpley Country Park) sites. At the end of this process, it is possible to show that the new model can predict the number of trips to individual destinations and that the model can be transferred to other outdoor recreation sites. Furthermore, the new model presented here is capable of predicting the changes in the volume and catchment of visits to an existing green space after land use planning or urban ecological interventions. This is a completely new theoretical model that is focused on understanding and quantifying the travel choices to outdoor recreation sites, which can inform decision makers by forecasting changes in outdoor recreational travel demand, according to different planning scenarios.

Bundling is pervasive in the market, examples include desktop computer bundles, digital single-lens reflex camera kits and cookware sets, to name a few. The advancement in information technology allows more and more companies to provide customized bundles to customers. Wind and Mahajan (1997) recognize the importance of researching mass customization and suggest companies to use consumers’ input “as a response (to a conjoint analysis-type task) that provides operational guidelines for the design of products to inventory for the segment that is not willing to pay the premium required for customized products”. In addition to conjoint analysis, researchers and practitioners are using “build-your-own-bundle” or configuration approach. In a configuration study, participants are presented with a menu from which they can choose individual items to build up their desired product bundle. The process mimics the real decision process, is easy to implement, and is straight forward for participants to understand. However, as the size of the menu grows, the number of possible bundles grows geometrically. This results in computation difficulties. This dissertation investigates the application of configuration approach, and examines if it extends and complements the choice-based conjoint (CBC) approach. We first develop an aggregate model for analyzing configuration data. We show analytically that the aggregate choice model consistent with configuration data has a closed form representation which takes the form of a Multivariate Logistic (MVL) model. WE discuss the strengths and weaknesses of the configuration approach. Because configuration and conjoint data tasks have different strengths and weaknesses, taking advantages of these two choice tasks may improve the understanding of consumer preferences for bundles. A fundamental assumption in the data fusion literature is that the same decision making process is applied under different choice tasks. We examine if consumer decision making process is the same under CBC and configuration studies by comparing the estimation results from CBC and conjoint studies. We show that these two procedures may not be fully comparable. To combine the two data sources we need a data fusion model that takes into account the differences to obtain a reasonable result.

The overall goal of the dissertation is to contribute to the growing literature on multiple discrete-continuous (MDC) choice models. In MDC choice situations, consumers often encounter two inter-related decisions at a choice instance – which alternative(s) to choose for consumption from a set of available alternatives, and the amount to consume of the chosen alternatives. In the recent literature, there is increasing attention on modeling MDC situations based on a rigorous underlying micro-economic utility maximization framework. Among these models, the multiple-discrete continuous extreme value MDCEV model (Bhat, 2005, 2008) provides a number of advantages over other models. The primary objective of this dissertation is to extend the MDCEV framework to accommodate more realistic decision-making processes from a behavioral standpoint. The dissertation has two secondary objectives. The first is to advance the current operationalization and the econometric modeling of MDC choice situations. The second is to contribute to the transportation literature by estimating MDC models that provide new insights on individuals’ travel decision processes. The proposed extensions of the MDCEV model include: (1) To formulate and estimate a latent choice set generation model within the MDCEV framework, (2) To develop a random utility-based model formulation that extends the MDCEV model to include multiple linear constraints, and (3) To extend the MDCEV model to relax the assumption of an additively separable utility function. The methodologies developed in this dissertation allow the specification and estimation of complex MDC choice models, and may be viewed as a major advance with the potential to lead to significant breakthroughs in the way MDC choices are structured and implemented. These methodologies provide a more realistic representation of the choice process. The proposed extensions are applied to different empirical contexts within the transportation field, including participation in and travel mileage allocated to non-work activities during various time periods of the day for workers, participation in recreational activities and time allocation for workers, and household expenditures in disaggregate transportation categories. The results from these exercises clearly underline the importance of relaxing some of the assumptions made, not only in the MDCEV model, but in MDC models in general. / text

American households spend over $30 billion on tourism and take over 177 million long-distance leisure trips each year. These trips, and the subsequent vehicle miles traveled, have a significant impact on the transportation systems at major destinations across the country, especially those destinations that are still improving their transportation systems. Surprisingly, not much is known related to this type of travel. This dissertation expands the current knowledge of tourism travel behavior, in terms of how people make decisions regarding long-distance leisure activities and time use. Specifically, this dissertation develops and comprehensively examines a behavioral framework for household tourism time use and activity patterns. This framework combines (and builds upon) theory and methods from both transportation and tourism research fields such that it can be used to improve tourism demand modeling. This framework takes an interdisciplinary approach to describe how long distance leisure travelers allocate and maximize their time use across various types of activities. It also considers the many levels of tourism time use and activity patterns, including the structuring the broad annual leisure activity and time budget, forming individual tourism trips within the defined budget, and selecting specific activities and timing during each distinct tourism trip. Subsequently, this dissertation will additionally apply the time use and activity participation behavioral framework to four critical tourism research topics to demonstrate how the tourism behavioral framework can effectively be used to provide behavioral insights into some of the most commonly studied critical tourism issues. These application topics include household participation in broad tourism travel activities, travel parties’ tourism destination and travel mode selection, individuals’ loyalty towards daily and tourism activities, and travel parties’ participation in combinations of specific tourism trip activities. These application studies incorporate a variety of data sources, decision makers, study scales, situation-appropriate modeling techniques, and economic/individual/environmental factors to capture all aspects of the decision and travel activity-making process. / text

Esta dissertação visa avaliar o padrão comportamental dos pedestres nos deslocamentos na cidade de Porto Alegre. É abordado a partir da base de dados provenientes da pesquisa de entrevistas domiciliares realizadas em 2003 em Porto Alegre. Para isto, caracterizaram-se os deslocamentos a pé na cidade e identificaram-se as regiões de maior e menor concentração de viagens a pé. A fim de determinar os fatores que influenciam a decisão de caminhar foram estimados modelos logit binomiais para as viagens menores que 2 km em cada uma das regiões identificadas anteriormente. As variáveis explicativas para os modelos analisados incluem características do domicílio (disponibilidade de automóvel e renda por domicílio), dos residentes (idade), das viagens (distância e motivo da viagem), da forma urbana (densidade de domicílios, densidade populacional, comprimento médio das quadras, padrão do sistema viário, tipo de uso do solo e estacionamento tarifado em área pública) e da disponibilidade de transporte coletivo na origem da viagem. Foram consideradas duas categorias de viagens: viagens por motivo trabalho/estudo e viagens por motivo não trabalho/estudo (motivos recreacionais, compras, saúde, assuntos pessoais e outros). Os resultados do estudo mostram que características sócio-econômicas dos residentes, características das viagens e da forma urbana influenciam a escolha do modo a pé. Analisando os valores de elasticidade obtidos para as duas categorias de viagens originadas em Petrópolis e no Centro pode-se inferir que as variáveis que exercem maior influência estão relacionadas principalmente a características da viagem (distância) e à configuração física da rede viária. A análise de sensibilidade evidenciou a sensibilidade do modelo frente a alterações das variáveis estudadas. Os resultados obtidos servem de apoio para um planejamento mais adequado da mobilidade e acessibilidade dos pedestres. / This thesis aims to evaluate the pedestrians’ behavior in Porto Alegre. The study was based on a Porto Alegre household survey of 2003. During the analysis, the pedestrian trips were characterized and the traffic zones with the larger and the smaller number of pedestrian trips were identified. In order to determine the influencing factors related to the walk choice, binomial logit models were developed for trips with less than 2km in each traffic zone previously identified. The explanatory variable used in the models included the characteristics of the household (auto availability and household income), of the household members (age), of the trip (distance and purpose of the trip), of the built environment (housing units density, population density, mean block size, street patterns, land use and public parking), and transit availability in the origin of the trip. Two types of pedestrian travel were considered: work and non-work trips (shopping, health, personal purposes and others). The study results showed that socio-economic characteristics, trip characteristics and local measures of the built environment influence walk modechoice. Elasticity results for the two types of trips, with origin in “Petrópolis” and Downtown, indicate that the most influence variables are connected with trip characteristics (distance) and street design. The sensibility analysis showed the model sensibility strength under the changes introduced in the variables studied. These analysis results may provide support for a better planning for pedestrians’ mobility and accessibility.

O estímulo aos modos ativos de viagem através de modificações na forma urbana - infraestrutura, edificações e atividades - é objeto do planejamento das cidades contemporâneas desde que os problemas do transporte motorizado se revelaram críticos e contrários à ideia de sustentabilidade urbana. Congestionamentos, poluição, custos monetários e sociais elevados estão associados ao modelo de urbanização e mobilidade da maioria das cidades, especialmente nos países em desenvolvimento, onde a explosão da frota motorizada é concomitante à aceleração dos processos de urbanização e espalhamento urbano. Mais recentemente, a revelação de relações de causalidade entre o excesso de utilização dos veículos particulares e problemas de saúde crônica das populações urbanas levou a um crescimento das pesquisas e iniciativas de estímulo às caminhadas como modo de transporte. Também o interesse pela qualidade da experiência da vida na cidade veio somar-se a este corpo de conhecimento, trazendo as ideias de vitalidade urbana e urbanidade para junto dos estudos de caminhabilidade. O interesse extrapolou a análise de demanda agregada que visa o incremento do modo a pé e passou a dar atenção aos caminhos pelos quais as pessoas se movimentam, conectando origens e destinos nos interior das cidades. Este trabalho procura avançar neste aspecto ao propor um método de avaliação dos atributos da forma urbana baseado no monitoramento de caminhantes com dispositivos de posicionamento global (GPS) e modelos de escolha discreta. Um estudo na cidade de Porto Alegre acompanhou indivíduos durante os anos de 2011 a 2014 e, através da representação de diversos atributos urbanos em ambiente SIG, associou as trajetórias realizadas com as características da forma da cidade, concluindo que elas influenciam a utilidade percebida das alternativas de caminho e, portanto, atuam sobre o processo decisório dos pedestres. Para além da simples distância ou declividade, outras características como o tamanho dos trechos, a hierarquia das vias, a presença de prédios marcantes e espaços abertos e a densidade de edificações ao longo dos eixos revelaram-se influentes neste processo. Poucas intersecções e cruzamentos, predomínio de vias amigáveis ao pedestre e edificações arranjadas de forma menos densa são alguns dos atributos que apresentaram maior relevância para a decisão de “por onde ir” no âmbito deste estudo. A amostra relativamente pequena e a concentração das viagens no entorno do Parque Farroupilha e do campus da UFRGS não permitem generalizar os resultados. Porém, o estudo pode ser considerado válido enquanto exploração, pois constrói uma metodologia que pode ser ampliada e aplicada em outros contextos. Além disso, os resultados revelam particularidades da realidade local que parecem indicar a existência de diferenças comportamentais significativas em relação às cidades do primeiro mundo, tornando-o promissor como instrumento de suporte a políticas e projetos de mobilidade urbana sustentável no Brasil. / Since motorized transport problems have proved to be critical and contrary to the concept of urban sustainability, the idea of increasing the active travel modes through changes in urban form is a key subject of today´s mobility agenda. Traffic congestion, air pollution and severe monetary and social costs are associated with the current patterns of urbanization and mobility, especially in developing countries, where an explosive motorized fleet growth occurs simultaneously to an acceleration of urbanization and sprawl processes. Most recently evidences of a causal relationship between massive use of private vehicles and chronic health disorders have led to an increase in research about walking as an effective and clean mode of transportation. Also, the interest about the quality of life experience in the city came to add up to this body of knowledge, bringing in ideas of livability to walkability studies. Beyond the aggregate demand studies that aim to increase the walking mode share, there is now a growing interest on more localized aspects of the walking phenomenon - the routes - trying to understand the ways in which people travel on foot when connecting origins and destinations. This work proposes a method based on assessing data from actually taken walking trips using GPS devices and on modeling pedestrian´s choice behavior using discrete choice models. A study in the city of Porto Alegre, south of Brazil, followed 82 individuals for three consecutive days and, through the representation of several layers of urban data in a GIS environment, associated their trajectories with the main urban form attributes to allow the modeling experiment. The results show that the built environment features play an important role as a decision attribute, producing perceived utility/disutility on the decision-makers´ minds. They indicated that, in addition to the basic travel effort attributes such as trip distance or street slope, other factors such as the straightness of the trip, the road hierarchy, the presence of busy intersections, landmark buildings, noticeable public spaces and the density of buildings along the walking stretches indeed influence the route choice. The relatively small sample size and the spatial clustering of trips around the city´s central area doesn´t allow to the generalization of results. However, the study can be taken as a valid exploratory analysis, since it builds up a methodology that can be expanded and applied in other urban contexts. Furthermore, the results reveal some particular local features that indicate the existence of significant behavioral differences from the developed cities where previous similar studies were performed. These qualities make the proposed framework a promising decision support tool for sustainable urban mobility projects in Brazil.