Perceived Intrinsic Motivation Mediates the Effect of Motive Incongruence on Job Burnout and Job Satisfaction

Abstract

Job burnout is a profound concern in modern society producing enormous financial and emotional costs for companies, health insurances, and the individual employee. In this study, we aimed at contributing to the literature on determinants of job burnout by investigating the indirect effects of implicit and explicit motive discrepancies (IED) through intrinsic motivation, with the aim of replicating previous findings from the literature. In addition, we extended this research by adding job satisfaction as an outcome variable in the mediation model, as well as volition as a moderator in these relationships. We preregistered our study and collected data from 136 participants (82 females; M_age = 29.33 years, SD_age = 6.30) using indirect measures (for implicit motives) and self-report measures (for explicit motives, job burnout, job satisfaction and volition). IED was shown to have an indirect effect on both job burnout and job satisfaction through intrinsic motivation. Additionally, these indirect effects were mitigated by high levels volition. We discuss implications of our findings for research and practice.

Supplemental data for this article is available online at https://doi.org/10.1080/00223980.2021.1980758.

Keywords:

• Implicit-explicit motive discrepancies
• intrinsic motivation
• job burnout
• job satisfaction
• volition

Data Availability Statement

The data materials that support the findings of this study are openly available at https://osf.io/b6y8u/?view_only=bd8815c25b6e4db6a79c277596ecc354.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent: Informed consent was obtained from all individual participants included in the studies.

Author Notes

Cafer Bakac is a research associate and doctoral student at the TUM School of Management, Technical University of Munich. His current research focuses on implicit and explicit motives as determinants of work-related variables.

Yixian Chen is a master graduate from TUM School of Education, Technical University of Munich. She currently works in HR & management consulting industry and researches on how organizations best cope with impacts brought by corona and remote work.

Jetmir Zyberaj is a research associate and doctoral student at the Department of Psychology, Chair of Work and Organizational Psychology, University of Bamberg, Germany. His research interests generally focus on leadership and performance management.

Hugo M. Kehr is a professor of psychology at the TUM School of Management, Technical University of Munich. His research focuses on implicit motives, leadership and visions.

Markus Quirin is a professor of psychology at PFH Göttingen and research associate at Technical University of Munich. His research focus is on personality, motivation, and emotion.

Notes

1 Please see Methods section for more clarifications of these methods for measuring implicit motives.

2 In a polynomial regression analysis, the outcome variable is predicted by centered predictors, their interactions and their squared values. To put it in a more mathematical notation, the general form of a polynomial regression follows as:

Z = b₀ + b₁X + b₂Y + b₃X² + b₄XY + b₅Y² + e.

Z is the outcome variable (intrinsic motivation in our case), X and Y are centered predictor variables (implicit and explicit motives in our case respectively) and e is the error term. For the coefficients, b₀ is the intercept and b₁ through b₅ are the estimated coefficients. Using these estimated coefficients, four additional surface test parameters are estimated, which are:

a₁ (b₁ + b₂) is the slope of line of congruence between the predictors (implicit and explicit motives). This line of congruence indicates a perfect a perfect agreement, where individuals’ predictor values perfectly match. When this parameter is significant, it indicates the outcome variable increases as the two predictor increase. a₂ (b₃ + b₄ + b₅) demonstrates if there is a curvature along the line of agreement. If significant, it indicates a difference in the congruence effect at different levels of line of congruence. That is, there is a difference between the average values of congruence and high and low levels of congruence. a₃ (b₁ – b₂) represents the slope along the line of incongruence. This parameter has been used as a test for directional hypothesis (e.g., Kazén & Kuhl, 2011). For example in our case, it might test the hypothesis that in the cases that there is a incongruence between implicit and explicit motives, the higher values of implicit motives as compared to explicit motives, the higher the intrinsic motivation. a₄ (b₃ − b₄ + b₅) is the most important parameter for testing the congruence (incongruence) hypothesis. It tests the curvature along the line of incongruence and test the hypothesis if an increase in incongruence (between implicit and explicit motives) has any effects on outcome variable (intrinsic motivation).

However, Edwards and Cable (2009) warns that one should not readily talk of an incongruence when a₄ parameter is significant, but only when at least three criteria are met: 1) if a surface is curved downward along the incongruence line, then the a₄ parameter should be negative. 2) If the ridge of the surface runs along the congruence line, then the first principal axis of the surface should have a slope of 1 and an intercept of 0. 3) If a surface is flat along the congruence line, then the quantities a₁ and a₂ should both equal 0. They further mentions these conditions does not have to hold all the times and one can be at failure if he/she concludes, if these conditions do not hold, the nonexistence of congruence hypothesis. In our analyses we followed these recommendations and we conducted these analyses using RSA package (Schönbrodt, 2016) in R.

Additional information

Funding

This research was partially made possible through a grant from Templeton Religion Trust (TRT 0119) supporting Hugo M. Kehr, and Markus Quirin