[We’re pleased to welcome Brad Shuck of University of Louisville. Brad recently published an article in Group & Organization Management entitled “Untangling the Predictive Nomological Validity of Employee Engagement: Decomposing Variance in Employee Engagement Using Job Attitude Measures” with co-authors Kim Nimon of University of Texas at Tyler and Drea Zigarmi of The Ken Blanchard Companies and the University of San Diego.]
Our interest in this work was driven by the need for practical understanding of the employee engagement construct in connection with precise theoretical positioning – we knew from growing citations in the literature that many scholars and practitioners are using employee engagement in their work, but there remained some level of confusion about what employee engagement was, and how it should be applied.
Of great interest to us was whether employee engagement was adding anything to the research literature or, if engagement was redundant as some scholars had suggested. We believed, based on our experience and understanding, that employee engagement did offer something unique from say, job satisfaction or organizational commitment, but beyond the primary use of bivariate relationships, no work had deconstructed the inner empirical makeup of the psychological construct. More, no one had graphed the theoretical structure of the relationships physically, so we took that task on. The purpose of our work was to examine the predictive nomological validity of employee engagement using a set of three job attitudes commonly linked to employee engagement – that, is we opened up the hood to explore its inner make-up.
Roughly speaking, our findings suggested that that across two overall measures of engagement (the UWES and the JES), job satisfaction contributed the most unique variance to employee engagement, followed by job involvement, and organizational commitment. We were not surprised that job satisfaction contributed the most variance to employee engagement, but we were surprised that job involvement lacked almost any degree of emotion – rather, it functioned at a mostly cognitive level and was identify related, versus emotionally driven. The main finding from our work was that no 1st-order, 2nd-order, or 3rd-order commonality coefficients fully explained, stand-alone or in combination, all the variance in the two engagement measures. In fact, there remained a substantial amount of unexplained variance in each measurement (47% of the variance remained unexplained in the JES and 34% of the variance remains unexplained in the UWES-9). In short, this told us that engagement operated as a standalone construct and was not fully redundant with anyone job attitude or combination of job attitudes. We were not surprised by this finding, but we suspect that others might be.
Within this work, we see many possibilities for future research. First, there is no question that researchers will need to continually examine the underlying meaning and quality of measurement used in building the still emerging nomological network of engagement. We also see an opportunity to more fully explore the role of affect in the engagement construct and the job attitudes. For example, in our results, affect demonstrated noteworthy and interesting theoretical patterns. As such, one avenue for future research might focus toward disentangling affect as a common factor between like constructs and engagement. Research might fully examine how measures of affect (both positive and negative) operate in context with JS, JI, OC, and engagement and how indicators of performance might be connected. Finally – and what we think is one of the more novel outcomes of this work – is the naming those spaces of joint common variance we uncovered. For example, in our work Coc.js explained the greatest amount of variance across both engagement scales, but what exactly is Coc.js? At present, research has not adequately explored such combinations and when paired together – such as the case with organizational commitment and job satisfaction – combined constructs might take on a new identity. For example, theoretically, when an employee is both satisfied with their work and committed to the organization, we might call that organizational contentment as the employee is both satiated and committed to the organization, making them more likely to express a state of overall organizational contentment. A construct called organizational contentment is all but absent in the research literature yet our results would indicate that this construct – whether we call it organizational contentment or something else – explains sizeable portions of variance in employee engagement.
As a final note, we hope or work brings about conversation and dialogue. This work has brought about many new questions for our team and, we know that only through dialogue and working together with other scholars can we really begin to understand what it means to be engaged and, how the experience of employee engagement unfolds overtime.
The abstract for the paper:
The purpose of this study was to examine the predictive nomological validity of employee engagement using a set of three job attitudes commonly linked to employee engagement. Prior research concerned with the nomological network of employee engagement has predominantly considered bivariate relationships, thus missing the opportunity to fully understand the intricate and interrelated relationship between employee engagement and job attitudes. Scale- and subscale-level correlations were obtained from a previously published set of survey responses (n = 1,580) to decompose employee engagement variance into orthogonal (i.e., non-overlapping) components associated with every possible combination of the three job attitude predictor set (2k − 1 = 7). Results suggested that across both overall measures, job satisfaction contributed the most unique variance to employee engagement, followed by job involvement and organizational commitment. Findings indicated that when applying employee engagement in both research and practice, care should be taken in scale selection across models—especially those involving such as constructs. This study provides evidence of the importance for considering a construct’s nomological network within the broader management and human resource–related literature. This research not only advances the theoretical and research understanding of employee engagement but also assists practitioners in deploying precise, well-crafted measures of engagement in the field.
You can read “Untangling the Predictive Nomological Validity of Employee Engagement: Decomposing Variance in Employee Engagement Using Job Attitude Measures” from Group & Organization Management free for the next two weeks by clicking here.
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