The influence of materialism on consumption indebtedness in the context of low income consumers from the city of São Paulo

This research is in the domains of materialism, consumer vulnerability and consumption indebtedness, concepts frequently approached in the literature on consumer behavior, macro-marketing and economic psychology. The influence of materialism on consumer indebtedness is investigated within a context that is characterized by poverty and by factors that cause vulnerability, such as high interest rates, limited access to credit and to quality affordable goods. The objectives of this research are: to produce a materialism scale that is well adapted to its environment, characterizing materialism adequately for the population studied; to compare results obtained with results of other studies; and to measure the relationship between materialism, socio-demographic variables, attitude to debt and consumption indebtedness. The primary data used in the analyses were collected from field research carried out in August, 2005 that relied on a probabilistic household sample of 450 low income individuals who live in poor regions of the city of Sao Paulo. The materialism scale, adapted and translated into Portuguese from Richins (2004), proved to be very successful and encourages new work in the area. It was noted that younger adults tend to be more materialistic than older ones; that illiterate adults tend to be less materialistic than those who did literacy courses when they were already adults; and that gender, income and race are not associated with the materialism construct. Among the other results, a logistic regression model was developed in order to distinguish those individuals who have an installment plan payment booklet from those who do not, based on materialism, socio-demographic variables and purchasing and consumer habits. The proposed model confirms materialism as a behavioral variable useful for forecasting the probability of an individual getting into debt in order to consume, in some cases almost doubling the chance of occurrence of this event. Findings confirm the thesis that it is not only adverse economic factors that lead people to get into debt; and that the study of demand for credit for consumption purposes must, of necessity, include variables of a psychological nature. It is suggested that the low income materialistic consumer experiences feelings of powerlessness and exclusion because of the gap that exists between their possessions and their desires. Lines of conduct to combat this marginalization from the consumer society are drawn targeting marketing professionals, public policy makers and vulnerability researchers. Finally, the possibility of new studies involving the materialism construct, which is central to literature on consumer behavior, albeit little used in empirical studies in Brazil, are discussed.

Probabilidade de financiamento por cartões de crédito híbridos

Esta pesquisa tem o objetivo de identificar as variáveis e sua influência na propensão à aquisição de crédito pessoal, propondo um modelo estatístico de propensão ao financiamento por cartões de crédito híbridos para maximização de contratação de crédito e otimização dos esforços de marketing. O estudo descritivo pode gerar insights para a compreensão da expansão do crédito ao consumo, sobretudo num contexto de escassez de opções de financiamento e limitação no canal de distribuição. Foram usados dados de uma base de clientes de uma instituição financeira com variáveis sócio demográficas e transacionai, e o modelo matemático foi seguido da validação de sua capacidade preditiva.

Variáveis discriminantes para inferência da insolvência de empresas brasileiras: um estudo para o período de 2008 a 2016

This study aimed to determine if accounting and governance indicators are relevant to foresee the stages of financial stress of companies by using a logistic regression. With the formation of two samples was possible to verify if the inclusion of insolvency data defined by cash flow shortage events were relevant to increase model capacity for prediction of insolvency. The remaining insolvency stages were judicial reorganization and bankruptcy. The control sample is formed by healthy companies, from the same sector and size. The period of analysis includes events that occurred between January 2008 and March 2016. The main variables that showed significant results to predict insolvency states, a year before the event happens, were Profitability, Efficiency and Payment Capacity indicators. The Governance indicator was only significant to predict insolvency arising from judicial reorganization and bankruptcy. Among the models studied, the most accurate model presented total correctness capacity of 88,7%, classifying correctly 88% of solvent companies and 89,3% of insolvent companies. The results indicate the usefulness of financial indicators of Payment Capacity, Efficiency and Profitability, as well as the Governance variable, to discriminate the insolvency of companies.