Measuring Employees’ Psychological Capital Using Data Mining Approach

Abstract

In this research, the logistic regression model was employed to develop a classifier that measures psychological capital of workers in organization. Psychological capital (PsyCap) is the positive state of an individual, comprising of self-efficacy, optimism, hope, and resilience. Employees with high psychological capital contribute positively to objectives and business strategy of an organization. An experimental dataset comprising of the psychological capital information of 329 employees in an organization was used to fit a data mining classification model. To ensure model accuracy, 220 observations were used as training set, whereas 109 were set aside to validate the model. Various statistical tests for goodness of fit and predictive accuracy were deployed to test model performance. The model has the ability to classify an individual's psychological capital into either high or low class with a predictive accuracy of 93%. The classification model is expected to serve as a tool in human resource management when measuring psychological capital of employees during recruitment interviews and promotion appraisals.