Abstract
This study investigates explicit –implicit motive discrepancies and their effect on well-being. Participants were 382 executive managers (107 females and 275 males). Female managers had higher explicit affiliation scores than males, whereas male managers had marginally significant higher explicit power scores than females. Males and females did not differ in their implicit motives. We expected a directional discrepancy on the power motive (explicit vs. implicit: “Striving for goals without gaining pleasure from doing so”) to predict impaired well-being. Results were consistent with this hypothesis, using polynomial regression analysis with response surface methods, instead of calculating motive difference scores. Discrepancies in the achievement and affiliation motives were not related to well-being. Results are discussed considering the specificity of motive discrepancies for selected groups, such as managers, and the importance of distinguishing between absolute versus directional motive discrepancy scores in motivation research.
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Notes
Edwards (personal communication) does not recommend standardizing the predictors based on the sample data. He affirms that “the scales cannot be made equivalent by standardizing them, because the standardized scores do not indicate the position of the component variables relative to one another.” We believe, however, that standardizing both predictors according to the norms of the population, if they are available, overcomes this problem. Edwards recommends to measure each predictor from the beginning using the same scale (e.g., a scale ranging from 1 to 7) and then to center each predictor using the midpoint of their common scale (i.e., 4). What can one do if the predictors are not measured using the same scale? One could convert the values of one predictor into the metric of the second. Harris et al. (2008), for example, did that by recoding actual salary range in dollars (first predictor) into 1–8, the values of the scale they used to measure upward comparison (second predictor), and then centered by subtracting from each predictor the common midpoint (4.5). This procedure, however, has the disadvantage that results in data reduction.
Readers interested in applying Polynomial Regression Analysis with Response Surface Methods as an alternative to difference scores are referred to the article of Linda Shanock et al. (2010). These authors not only explain the method in an understandable manner but also include a SPSS-Syntax showing how to carry out the polynomial regression analysis. Moreover, the paper is accompanied by an Excel spreadsheet, with which one can obtain the four surface values (a1 to a4) and the corresponding 3-dimensional response surface graphic, based on the results of the polynomial regression analysis. Instructions for downloading the Excel spreadsheet are given in the paper of Shanock et al. (2010).
After this article was accepted for publication we became aware of a paper by Gröpel (2008), confirming that explicit/implicit discrepancies in the power motive but not on achievement or affiliation predicted well-being in a sample of managers. This author calculated partial correlations between motive discrepancies and well-being, controlling for action orientation.
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Acknowledgments
We thank Linda Shanock for her useful methodological advice. Jeff Edwards helped us in clarifying some methodological issues related to polynomial regression. Finally, we are also thankful to Frank Pundsack for his feedback on portions of the manuscript and his valuable help in the preparation of the response surface graphics.
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Kazén, M., Kuhl, J. Directional discrepancy between implicit and explicit power motives is related to well-being among managers. Motiv Emot 35, 317–327 (2011). https://doi.org/10.1007/s11031-011-9219-8
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DOI: https://doi.org/10.1007/s11031-011-9219-8