Title Promoting work Engagement in the Accounting Profession: a Machine Learning Approach
Authors del Pozo-Antunez, Jose Joaquin , MOLINA SÁNCHEZ, HORACIO, ARIZA MONTES, JOSÉ ANTONIO, FERNÁNDEZ NAVARRO, FRANCISCO DE ASÍS
External publication No
Means Soc. Indic. Res.
Scope Article
Nature Científica
JCR Quartile 2
SJR Quartile 1
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103151521&doi=10.1007%2fs11205-021-02665-z&partnerID=40&md5=e4d109e1e02998761e611c50f6934916
Publication date
ISI 000630994900001
Scopus Id 2-s2.0-85103151521
DOI 10.1007/s11205-021-02665-z
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 affect 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 findings include (i) that the work engagement index is mainly influenced 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 efficient human resources strategies that improve both individual well-being and company performance in the accounting sector.
Keywords Accountants; Global sensitivity analysis; Multi-dimensional indices; Work engagement; Job quality
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