Modelagem de equações estruturais aplicada à propensão ao endividamento: uma análise de fatores comportamentais

Detalhes bibliográficos
Ano de defesa: 2012
Autor(a) principal: Flores, Silvia Amélia Mendonça
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Santa Maria
BR
Administração
UFSM
Programa de Pós-Graduação em Administração
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufsm.br/handle/1/4621
Resumo: This study sought to develop and validate a model of propensity to indebtedness from behavioral factors. For this, we carried out are search survey with 1046 residents of the town of Santa Maria (RS). As an instrument of data collection adopted a structured questionnaire, consisting with ninety questions, that addressed demographic and cultural variable sand seven behavioral factors (financial education, risk perception, risk behavior, emotions, materialism, debt and money values). The analysis was performed by structural equation modeling, and the influences of cultural and demographic variables were measured by parametric hypothesis tests. The results demonstrated that the initial assumption of ten, eight were confirmed. The final model presents four factors directly related to indebtedness: amounts of money, materialism, perception and risk behavior. Due to problems of adjustment, the construct of financial education was excluded from the final model, not interfering with the propensity to indebtedness. The descriptive statistics of the factors showed low level of debt and materialism of the in habitants of Santa Maria (RS). Furthermore, we found a higher risk perception, and consequently a more conservative risk behavior. Hypothesis tests showed a significant difference in the level of debt as age, gender, marital status, education, religion, religious principles, occupation, family income, credit card, reliance on credit and spending. As for income, it is emphasized that people with higher income groups received most media, or, in other words, more prone to debt.