Abstract Purpose This study aims to examine the effects of peer ethical behavior and individual differences in valuation of fairness vs loyalty on whistleblowing intentions in academic settings. This study also tests the underlying mechanism responsible for the effects of peer behavior on reporting intentions, namely, fear of reprisal. Design/methodology/approach A survey was conducted with 947 undergraduate students. The model was tested using ordinary least squares regression models followed by bootstrapped mediation analyses. Findings Results showed that the effects of peer ethical behavior on whistleblowing intentions are mediated by fear of retaliation. Moreover, the findings indicated that, for low-severity transgressions, there is an interactive effect between fear of retaliation and endorsement of fairness over loyalty on whistleblowing intentions. Research limitations/implications When the misconduct is seen as minor, a potential whistleblower may understand that the expected costs outweigh the possible benefits of blowing the whistle. In such situations, higher fear of retaliation would undermine the effects of individual’s endorsement of fairness over loyalty on reporting intentions. Practical implications As the social environment significantly affects someone’s whistleblowing intentions, there should be visible efforts to improve and to foster an ethical infrastructure in organizations. Social implications As fear of retaliation by peers is one of the most important determinants affecting the decision to report misconduct in general, there must be serious efforts from leaders to mitigate any threat of retaliation to those who come forward. Originality/value This work contributes to the discussion about individual and situational antecedents of whistleblowing. More importantly, it sheds light on one potential boundary condition for the influence of the fairness–loyalty tradeoff on whistleblowing decisions: severity of the transgression. The findings provide initial evidence that, for low-severity transgressions, fear of retaliation weakens the positive effects of one’s moral compass in terms of preference for fairness over loyalty on whistleblowing intentions.

Abstract Purpose Although credit unions are nonprofit organizations, their objectives depend on the efficient management of their resources and credit risk aligned with the principles of the cooperative doctrine. This paper aims to propose the combined use of credit scoring and profit scoring to increase the effectiveness of the loan-granting process in credit unions. Design/methodology/approach This sample is composed by the data of personal loans transactions of a Brazilian credit union. Findings The analysis reveals that the use of statistical methods improves significantly the predictability of default when compared to the use of subjective techniques and the superiority of the random forests model in estimating credit scoring and profit scoring when compared to logit and ordinary least squares method (OLS) regression. The study also illustrates how both analyses can be used jointly for more effective decision-making. Originality/value Replacing subjective analysis with objective credit analysis using deterministic models will benefit Brazilian credit unions. The credit decision will be based on the input variables and on clear criteria, turning the decision-making process impartial. The joint use of credit scoring and profit scoring allows granting credit for the clients with the highest potential to pay debt obligation and, at the same time, to certify that the transaction profitability meets the goals of the organization: to be sustainable and to provide loans and investment opportunities at attractive rates to members.

Resumo Analisa-se a influência do capital humano do empreendedor, o seu capital social e a adoção de práticas gerenciais na sobrevivência de empresas em seus primeiros anos de atividade. De forma inédita, verifica-se como o efeito desses fatores varia de acordo com o gênero, masculino ou feminino, do empreendedor. Usando uma base de 2.000 empresas cadastradas na Junta Comercial do Estado de São Paulo (Jucesp), entre 2003 e 2007, foram ajustados dois modelos econométricos para mensurar o efeito dessas variáveis na sobrevivência de empresas nascentes. Os resultados sugerem que a adoção de práticas gerenciais e alguns aspectos ligados ao capital humano do empreendedor podem favorecer a sobrevivência da empresa. O efeito de competências superiores e capital social sobre a sobrevivência foram maiores para mulheres do que para homens. Os resultados sugerem que empreendedoras enfrentam mais barreiras à constituição de novos negócios, exigindo, portanto, configurações distintas de recursos para atenuar essas barreiras e aumentar a probabilidade de sobrevivência das empresas nascentes.

Abstract In this article, we assess the impact of an entrepreneur’s human capital, social capital, and adoption of management practices on the survival of firms in their first years of life. We innovate by assessing how the effect of those factors varies according to gender: whether the entrepreneur is male or female. Using a database of 2,000 firms registered in the Junta Comercial do Estado de São Paulo (Jucesp), between 2003 and 2007, we employed two distinct econometric models to measure the effect of those variables on the survival of new firms. Our results suggest that the adoption of management practices and some traits related to human capital positively affect firm survival. The effect of competencies and social capital on firm survival was higher for female than for male entrepreneurs. These results suggest that female entrepreneurs face higher barriers to launch new firms, thus require distinct resource configurations to overcome these barriers and increase the probability of survival.

Abstract Paper aims This paper presents a comparison of the performances of the Bayesian additive regression trees (BART), Random Forest (RF) and the logistic regression model (LRM) for the development of credit scoring models. Originality It is not usual the use of BART methodology for the analysis of credit scoring data. The database was provided by Serasa-Experian with information regarding direct retail consumer credit operations. The use of credit bureau variables is not usual in academic papers. Research method Several models were adjusted and their performances were compared by using regular methods. Main findings The analysis confirms the superiority of the BART model over the LRM for the analyzed data. RF was superior to LRM only for the balanced sample. The best-adjusted BART model was superior to RF. Implications for theory and practice The paper suggests that the use of BART or RF may bring better results for credit scoring modelling.

Resumo Nosso objetivo é entender dois principais fatores ligados à escolha profissional: o perfil dos indivíduos que optam por diferentes ocupações e a consequente diferenciação da remuneração dessas pessoas tanto por suas características pessoais como pelas escolhas ocupacionais. Usando dados da Pesquisa Nacional por Amostra de Domicílios - Pnad - 2013 (INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA - IBGE , 2014), concluímos que existem diferenças significativas tanto nas características dos indivíduos que escolhem ocupações tradicionais como na forma como eles são remunerados. Embora mulheres que trabalham em profissões masculinas tenham um retorno - similar aos homens - por sua escolha, elas somente diminuem a diferença salarial com seus pares se a opção for por uma profissão imperial (direito, engenharia ou medicina).

Abstract Our goal is to understand two main factors related to professional choice: the profile of individuals who choose different occupations and the resulting differentiation of remuneration of these people based on their personal characteristics as well as their occupational choices. Using data from Pesquisa Nacional por Amostra de Domicílios - Pnad - 2013 (INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA - IBGE, 2014), we have concluded that there are significant differences in the personal characteristics of individuals who choose traditional occupations in addition to how they are remunerated. Although women who choose to work in male professions earn a salary, which is comparable to that of men, the salary gap is only reduced in traditional professions (law, engineering or medicine).

Resumen Nuestro objetivo es entender dos principales factores vinculados a la elección profesional: el perfil de los individuos que optan por diferentes ocupaciones y la consecuente diferenciación de la remuneración de estas personas tanto por sus características personales como por las elecciones ocupacionales. Usando datos de Pesquisa Nacional por Amostra de Domicílios -Pnad- 2013 (INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA -IBGE, 2014), concluimos que hay diferencias significativas tanto en las características de los individuos que eligen ocupaciones tradicionales como en la forma en la que son remunerados. Aunque las mujeres que trabajan en profesiones masculinas tengan un retorno similar al de los hombres, solamente reducen la diferencia salarial con sus pares si la opción es por una profesión imperial (derecho, ingeniería o medicina).

RÉSUMÉ L’objectif de ce travail est de comprendre deux des principaux facteurs liés au choix professionnel: le profil des individus qui choisissent différentes occupations ainsi que l’écart salariale qui en découle, due à leurs caractéristiques personnelles et à leurs choix. Sur la base des données de la Pesquisa Nacional por Amostra de Domicílios - Pnad - 2013 (INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA - IBGE, 2014) concernant les caractéristiques des individus qui choisissent des professions traditionnelles et la manière dont ils sont rémunérés. Bien que les femmes qui exercent des professions dites masculines, de par leur choix, aient une rémuneration identique à celle des hommes, les écarts salariaux entre les sexes ne diminuent que dans le cas òu elles optent pour des professions imperiales comme le droit, l’ingénierie ou la médecine.

Abstract The main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We also used logistic regression models to compare the results with those obtained using multi-state Markov models. The models were applied to an actual database of a Brazilian financial institution. In this application, multi-state Markov models performed better than logistic regression models in predicting default risk, and logistic regression models performed better in predicting cancellation risk.

The objective of this article is to estimate insurance claims from an auto dataset using the Tweedie and zeroadjusted inverse Gaussian (ZAIG) methods. We identify factors that influence claim size and probability, and compare the results of these methods which both forecast outcomes accurately. Vehicle characteristics like territory, age, origin and type distinctly influence claim size and probability. This distinct impact is not always present in the Tweedie estimated model. Auto insurers should consider estimating total claim size using both the Tweedie and ZAIG methods. This allows for an estimation of confidence interval based on empirical quantiles using bootstrap simulation. Furthermore, the fitted models may be useful in developing a strategy to obtain premium pricing.