Modelagem comportamental da escolha do modo de viagem sob influência da interação social

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2019.Pauta recorrente na pesquisa internacional, a temática que relaciona comportamento de viagem e rede de interação social de um indivíduo é o escopo deste trabalho. A incorporação da dimenção social na pesquisa em comportamento de viagem permite verificar como o meio social influencia as escolhas de viagens que um indivíduo realiza e adiciona uma nova perspectiva junto a aspectos tradicionalmente considerados, como as características do ambiente urbano e o contexto pessoal do indivíduo. Dessa forma, busca-se definir um modelo comportamental para verificar a existência da influência social na escolha do modo de viagem no contexto brasileiro. Para alcance de tal objetivo, realizou-se uma pesquisa no campus Darcy Ribeiro da Universidade de Brasília, com a aplicação de um método de três etapas: i) delimitação da pesquisa; ii) coleta de dados, a partir da definição das variáveis, da estruturação do questionário e da definição da forma de coleta de dados sociais, feita pela abordagem egocentrada; iii) análise dos dados por meio da sua caracterização e análise exploratória, da definição de hipóteses de modelagem e da modelagem dos dados através de um modelo logit multinomial. Verificou-se, como resultado, a existência da influência social por conformidade na escolha do modo de viagem para a universidade quando se consideram os modos sustentáveis (bicicleta e caminhada) e a carona. A probabilidade de um indivíduo usar um modo sustentável em relação ao carro é 76% maior quando a quantidade de contatos sociais que utilizam modos sustentáveis aumenta em 10%. A probabilidade de uso da carona em relação ao carro aumenta 27% junto ao aumento de 10% no total de contatos sociais adeptos à carona. Foi possível verificar ainda que, além da influência social, o uso do transporte público, da carona e de modos sustentáveis, em detrimento do automóvel, tem probabilidades maiores quando são considerados indivíduos jovens, de domicílios com menores taxas de motorização e localizados em áreas urbanas mais adensadas. A consideração da influência social permite a percepção mais abrangente dos fatores relevantes no processo decisório individual, sendo referência para a formulação de políticas públicas de mobilidade, com destaque para aquelas que buscam promover alternativas sustentáveis e compartilhadas.This dissertation comprehends the travel behavior and social network interaction theme, which has been an international research interest. The incorporation of the social view into travel behavior research allows us to establish a method of identifying and analyzing the social influence on travel choices, thus, adding a new perspective combined with traditional features such as built environment and personal characteristics. This research aims to define a behavioral model to verify whether there is a social influence on the travel mode choices in the Brazilian context. To achieve this goal, the research was carried out on the Darcy Ribeiro campus of the University of Brasília taking into account a three steps method: a) research delimitation; b) data collection, that consists of variables definition, a survey design, and a definition of social data collection, which was made by the egocentric approach; c) data analysis with the characterization and exploratory analysis, the definition of the hypotheses and a data modeling through a multinomial logit model. The results of the research reveal that there is social influence in the travel mode choice among students commuting to the University of Brasília, especially when considering sustainable modes (biking and walking) and carpooling. The odds of an ego using a sustainable mode are 76% higher if there is an increment of 10% in the proportion of alters that also use sustainable modes. The odds of an ego to carpool are 27% higher when their alter carpooling proportion increases 10%. Taking into account social influence, the odds of using public transportation, carpooling, and sustainable mode are higher when an ego is young, belongs to a household with lower motorization rates, and lives in denser neighborhood. The knowledge of social influence allows better perception of relevant factors of the decision-making process. Urban mobility policies must consider this perspective, especially those policies that aim to promote sustainable and shared travel modes as alternatives to great automobile use

Choice Modeling Perspectives on Social Networks, Social Influence, and Social Capital in Activity and Travel Behavior

Understanding the determinants of activities and travel is critical for transportation policymakers, planners, and engineers to design and manage transportation systems. These systems, and their externalities, are interwoven with social systems in communities, cities, regions, and societies. But discrete choice models - the predominant modeling tool for researching travel behavior and planning transportation systems - are grounded in theories of individual decision-making. This dissertation expands knowledge about the incorporation of social interactions into activity-travel choice models in the areas of social capital and social network indicators; social influence motivations and informational conformity; and misspecification errors from social network data collection. Incorporating social capital into activity choice models involves using social capital indicators from surveys. Using a position generator question type, the role of social network occupational diversity in activity participation was explored and the performance of models using name generator and position generator data was compared. Access to the resources embedded in diverse networks (extensity) was found to positively correlate with leisure activity participation. Compared to core network indicators from name generators, position generator indicators were typically better at predicting activity participation in a cross-validation study. Current models of social influence in travel do not account for varying motivations for social influence such as for accuracy, affiliation, and self-concept. To test for an accuracy motivation, a latent class discrete choice model was formulated that places individuals into classes based on information exposure. Contrasting with existing work, this model showed that "more informed" households are more likely to own bicycles due to preference changes causing less sensitivity to smaller home footprints and limited incomes. A Bayesian prediction procedure was used to derive distributions of local-level equilibria and social influence elasticity. The effect of errors in social network data collection using name and position generators is not fully understood for choice models. In a case study, the social network occupational diversity measure was robust to varying position generator lengths. Simulation experiments tested the implications of social network structure, misspecification, and small samples on social influence choice models where sample size, social influence strength, and degree of misspecification had the greatest impact