Developing a Bayesian Network Model for Measuring the Role of Family in Private Family Businesses

Abstract

The objective was to identify causality between variables that generate the highest level of familiness in private family businesses. Bayesian Network theory was used to measure the effectiveness of resources and capabilities generated by family members within the family business and understand the causal relationship between the variables, through probabilistic reasoning and graphs. The results show that if the salary of family members were higher than the salary of non-family employees, family members exchange information among themselves, and family and employee ties exist, there is 83%, 70%, and 79% of probability of achieving a high level of familiness, respectively. The limitation of the study is that any modification to the network could generate different results. The study increases knowledge of family businesses and offers alternatives for leaders of these companies to increase familiness. If family businesses want to strengthen their competitive advantage, the main variables on which they must bet, among all the resources and capabilities that represent familiness, are salaries of family members, exchange of information and family-employee relationships.