Utilizing decision trees on employee decision-making processes: a model proposal

Introduction/background: This paper offers an idiosyncratic relational framework built on the organizational silence theory and the organizational support theory. It exploits the distinct advantages that using decision trees in classification and prediction applications offer to form a unique predictive model. Aim of the paper: This paper argues that a relational framework built on the organizational silence theory and the organizational support theory can give important clues about how employees make certain decisions in the workplace as well as about factors that have an impact on their decision-making processes. Materials and methods: The research applies decision trees learning – a data mining technique – to unfold the hidden patterns and unprecedented relationships between the two constructs that until now had not been revealed. Results and conclusions: The suggested model, which consists of rules, exhibits the effects of perceived organizational support and employee silence behavior on employee decisions with an approximately 79% correct classification rate, showing the success of the model as well as its appropriate relational framework. The presented findings indicate that a relational framework built on the organizational silence theory and the organizational support theory has a lot to offer in terms of building effective HR strategies and policies. The study also extends the understanding of the antecedents of silence behavior in different social contexts.