Promoting work Engagement in the Accounting Profession: a Machine Learning Approach

Abstract

In this paper, a non-linear multi-dimensional (machine learning-based) index for accountants that relates work engagement scores (according to accountants’ perceptions) with the seven Job Quality Indices (JQI) (proposed by Eurofound) has been proposed. The goal of the research is two-fold, namely, (i) to quantify the extent to which the JQI variables explain the work engagement scores, and (ii) to determine which JQI variables most afect the work engagement scores. The best performing regression model achieved a competitive root mean square percentage, highlighting that the selected variables primarily determine the work engagement values. Other important fndings include (i) that the work engagement index is mainly infuenced by the social environment index and (ii) that the skills and discretion and prospects indices are also crucial in the promotion of the work engagement of accountants. The instrument implemented could be employed by human resources practitioners to propose efcient human resources strategies that improve both individual wellbeing and company performance in the accounting sector.