Emotional Intelligence as a Predictor of Employee Engagement: A Study of U.S. Manufacturing Workers
BMRA
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Keywords

emotional intelligence
employee engagement
self-determination theory
WLEIS
UWES-9

How to Cite

Lang, T., & Saurage-Altenloh, S. (2023). Emotional Intelligence as a Predictor of Employee Engagement: A Study of U.S. Manufacturing Workers. Business Management Research and Applications: A Cross-Disciplinary Journal, 2(1), 77–96. Retrieved from https://bmrajournal.columbiasouthern.edu/index.php/bmra/article/view/5400

Abstract

According to the 2016 Gallup Report, manufacturing workers are the least engaged workers in the U.S. (Gallup, 2017). Studies on emotional intelligence (EI) indicate that EI has a significant, positive relationship with employee engagement (EE). Internationally, recent studies have operationalized the EI and EE constructs as a mix of unidimensional and multidimensional constructs, while domestically studies on EI and EE have been sparse, with more focus on EI and EE operationalized as unidimensional constructs examined along with other constructs. This study addressed these gaps by using the self-determination theory (SDT) to examine the extent to which EI and its dimensions of self-emotion appraisal (SEA), other’s emotion appraisal (OEA), use of emotions (UOE), and regulation of emotion (ROE) predict EE and its facets of vigor (VI), dedication (DE), and absorption (AB) in 167 manufacturing workers in the continental U.S. The research study used a quantitative methodology incorporating nonexperimental reasoning in a predictive, cross-sectional survey using linear and hierarchical multiple regression analyses to analyze the data. The results go beyond the strength of the relationship between the constructs to demonstrate how each dimension of EI explains unique variance in EE and each of its facets. Data was collected using an online survey that included the WLEIS and UWES-9 instruments. The results of the study demonstrated that (a) EI and its dimensions have significant predictive relationships with EE and VI, (b) EI and its dimensions of SEA and UOE have significant predictive relationships with DE, but OEA and ROE do not, and (c) EI has a significant predictive relationship with AB, but SEA, OEA, UOE, and ROE do not. These outcomes provide information about the drivers of the relationship between EI and EE that leaders in manufacturing organizations may find influential when considering hiring practices, EI initiatives, and engagement efforts in the workplace.

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