The concept of emotional intelligence and the potential impact on an organization has sparked a concerted effort amongst researchers to examine and more clearly define the role of emotional intelligence in the workplace (Bar-On, 2006; Goleman, 1995; Mayer & Salovey, 1997). Goleman, Boyatzis, and McKee (2002) advised that emotional intelligence was a key element regarding leadership effectiveness, especially in a team environment. Emotional intelligence (EI) and leadership serve a dual purpose which is to encourage teamwork to reach an end goal and to motivate individual members (Prati, Douglas, Ferris, Ammeter & Buckley, 2003). Emotional intelligence, job satisfaction and employee engagement are well researched as individualized topical areas of interest; however, the relationship between supervisor emotional intelligence and manufacturing employee’s job satisfaction and engagement has not been widely researched.
The purpose of this quantitative study was to examine relationships between supervisor and employee emotional intelligence, engagement, and job satisfaction within manufacturing industries industry in Southeast Alabama. The research questions aimed to address the gaps in empirical research surrounding the key variables: emotional intelligence, job satisfaction and engagement. The Schutte Emotion Intelligence Scale (SSEIT) (Schutte, Malouff, & Bhullar, 2009), also referred to as the Assessing Emotions Scale, the Minnesota Satisfaction Questionnaire (MSQ) (Weiss, 1977) and The Utrecht Work Engagement Scale (UWES-9) (Schaufeli & Bakker, 2003), also referred to as the Work & Well-being Survey, were used in this
study to address the five research questions. The sample population were employees and supervisors currently working in manufacturing industries in Alabama manufacturing industries (N =189, M age = 38.40 years). Analyses of the data were conducted using standard multiple linear regression and an independent t-test. Results found that gender and age did not predict emotional intelligence among any level of employee and there was no mean difference in EI among supervisors and employees. Multiple linear regression models were used to examine the relationship between the criterion variables (i.e., emotional intelligence, job satisfaction, and engagement) and results indicated a significant linear relationship in predicting the dependent variables for the fitted model. Specifically, EI was significant in predicating supervisor job satisfaction an overall employee engagement. Future research in this area should seek to improve data collection methods (e.g., multiple reporters) and to better develop measures which account for the unique working environmental conditions of manufacturing industries.
Finally, the findings in this study seem to indicate a more nuanced approach may be necessary to examine the role of the front line supervisor in manufacturing industry settings. In conclusion, future research examining the relationship between front line supervisors and employees and the role of emotional intelligence in the prediction of job satisfaction and engagement warrant improved methods in data collection and better scale development more applicable to the manufacturing industry working environment.||en_US