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Me, myself, and I: influence of CEO narcissism on firms’ innovation strategy and the likelihood of product-harm crises

  • Original Empirical Research
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Abstract

This research examines the relationship between narcissistic personality characteristics in Chief Executive Officers (CEOs) and firms’ innovation outcomes. The authors argue that firms led by narcissistic CEOs are likely to exhibit a higher rate of new product introductions and a greater proportion of radical innovations in their new product portfolios, but they are also more likely to encounter product-harm crises. The impact of CEO narcissism on these innovation outcomes is partially mediated by firms’ higher competitive aggressiveness. High power of the marketing department in the top management team, however, increases firms’ customer orientation, which in turn weakens the relationship between CEO narcissism and product-harm crises. A longitudinal analysis of a sample of 395 publicly listed U.S. firms in the period 2006–2010 provides considerable support for the authors’ hypotheses. This research underscores the importance of studying CEOs’ personality traits as antecedents of firms’ innovation outcomes, highlights the positive and negative impact of CEO narcissism on firms’ innovation-related behavior, and delineates the process through which this impact takes place.

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Notes

  1. A classification scheme for radical and incremental innovations is provided in Table 2.

  2. We thank the Area Editor for suggesting that we explore the role of customer orientation in the link between CEO narcissism and innovation outcomes.

  3. These industries include SIC 1 (construction), SIC 2 (light manufacturing), SIC 3 (heavy manufacturing), SIC 4 (transportation and communications), SIC 5 (retail), SIC 6 (finance and insurance), SIC 7 (personal, business, and recreation), and SIC 8 (health and education). We considered it important to test our conceptual framework across multiple industries in order to increase the generalizability of our results.

  4. The average CEO tenure in S&P 500 firms was 9.2 years between 2006 and 2014, with CEO turnover being 9.9 years in 2014 (Aguilar et al. 2015). These statistics suggest that restricting our sample to firms whose CEOs were appointed between 2003 and 2005 and remained CEOs for at least 5–7 years (i.e., remained CEOs through 2010), did not result in a highly skewed sample of very stable CEOs. Nevertheless, we repeated our analysis after dropping firms whose CEOs had the longest tenure (CEOs who were appointed in 2003 and remained CEOs through 2010) with our overall conclusions remaining the same (see Appendix 1, Table 8).

  5. Chatterjee and Hambrick (2007) conduct a series of validity tests which show that their index has strong construct validity. These tests include having a panel of experienced securities analysts rate the degree of narcissism of 40 of the CEOs in their sample. The analysts exhibited strong interrater reliability and their ratings of the CEOs were very much in line with Chatterjee and Hambrick’s (2007) unobtrusive index scores (correlation = .82, p < .01). We believe the unidimensional measure of narcissism developed by Chatterjee and Hambrick (2007, 2011) that we employ is also theoretically justified because narcissism, by definition, is a unitary superordinate construct that has multiple elements (Edwards 2001). Furthermore, as explained by Chatterjee and Hambrick (2007, 2011), the four indicators together capture the four facets of narcissism identified by Emmons (1987): superiority/arrogance, exploitativeness/entitlement, self-absorption/self-admiration, and leadership/authority. All of the four indicators we used can reasonably be thought to align with one or more of Emmon’s (1987) facets. Prominence in annual report photographs/ prominence in press releases align with superiority/arrogance, self-absorption/self-admiration, and leadership/authority, while the two compensation items (CEO relative cash/non-cash pay) align with superiority/arrogance, and exploitativeness/entitlement (Chatterjee and Hambrick 2007).

  6. The proportion of radical NPIs was not defined for firm-years with zero NPIs. These firm-years were dropped while analyzing the link between CEO narcissism and proportion of radical NPIs.

  7. We used negative binomial regression rather than a poisson regression because while both types of regression can model count dependent variables, a poisson regression assumes that the mean and variance of the dependent variable are equal (Kennedy 2003), which (as Table 3 shows) was not true for our dependent variable, i.e., NPIs. We used random effects rather than fixed effects in equations (1) and (3) as our focal independent variable (CEO narcissism) was time-invariant, and using a fixed effects would have necessitated that our focal independent variable be dropped. Nevertheless, for Models 2 and 4 in Table 4, we carried out a Hausman test and failed to reject the null hypothesis that random effects are consistent and efficient. The footnote of Table 4 provides details of these tests.

  8. Our results remained robust to the use of a GLS random effects regression and to a two-limit Tobit regression bounded between 0 and 1. However, we present the results of a fractional logit regression given that a GLS random effects regression ignores the zero lower bound (Papke and Wooldridge 1996), while a Tobit regression employed in our case resulted in an excessive amount of censoring (values below 0 or above 1).

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Acknowledgements

The authors thank the marketing faculty at the University of Mississippi for their insightful comments on a previous version of the paper. The authors also thank the Editor, the Area editor, and three anonymous reviewers for their very constructive suggestions.

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  1. School of Business Administration, University of Mississippi, Holman 336, University, MS, 38677, USA

    Saim Kashmiri

  2. McAfee School of Business, Union University, BAC 10, Jackson, TN, 38305, USA

    Cameron Duncan Nicol

  3. Asper School of Winnipeg, University of Manitoba, 662 Drake Centre, Winnipeg, MB, R3T 2N2, Canada

    Sandeep Arora

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  1. Saim Kashmiri
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  2. Cameron Duncan Nicol
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  3. Sandeep Arora
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Correspondence to Saim Kashmiri.

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Neil Morgan served as Area Editor for this article.

Appendices

Appendix 1

Table 8 Robustness analysis: results of regression analysis after dropping firms whose CEOs were appointed in 2003
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Appendix 2

Table 9 Illustrative examples of incremental and radical new product introductions in sample
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Appendix 3

Predictive validity: 10-fold cross-validation to assess forecasting performance

We tested the forecasting accuracy of Models 2, 3, and 4, presented earlier in Table 4, by following the 10-fold cross-validation procedure used by Geyskens et al. (2002) and Dekimpe et al. (1997). As per the 10-fold cross-validation procedure, our sample of firm-years was randomly partitioned into 10 subsamples of roughly equal size. Of the 10 subsamples, a single subsample was initially retained as the validation set for testing the model, and the remaining 9 subsamples combined were used as the training set for fitting the sample. The cross-validation process was then repeated 10 times, with each of the 10 subsamples used exactly once as the validation set. The results from the 10 iterations were then averaged to produce a single estimation. The predictive validity statistic we report is ‘Cross-Validation Predicted Residual Sum of Squares’ or CV PRESS, where the mean square error (MSE) of prediction is calculated by the formulae: MSE (of prediction) = CVPRESS/n, with n being the total sample size. The model with the smallest CV PRESS was selected as the model with the best predictive validity. We found that the CV PRESS score of this parsimonious model was 193,955 while predicting NPIs, which translated into an MSE of prediction of 98.20. Similarly, we found that the CV PRESS score of the parsimonious model was 17.33 and 216.87 while predicting proportion of radical innovations and product-harm crisis, respectively, translating into a MSE of prediction of 0.0148 and 0.117, respectively. The MSE of prediction of these parsimonious models was 1.0%, 1.4%, and 1.7% higher than the MSE of estimation of the same models prior to 10-fold cross-validation (i.e., 97.20, 0.0146, and 0.115, respectively). These prediction statistics compare well with the predictive accuracy statistics reported by prior researchers using this approach (Geyskens et al. 2002).

Table 10 Details of predictive validity analysis with new product introductions as dependent variable: 10-fold cross-validation
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Table 11 Details of predictive validity analysis with proportion of radical innovations as dependent variable: 10-fold cross-validation
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Table 12 Details of predictive validity analysis with product-harm crisis as dependent variable: 10-fold cross-validation
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Kashmiri, S., Nicol, C.D. & Arora, S. Me, myself, and I: influence of CEO narcissism on firms’ innovation strategy and the likelihood of product-harm crises. J. of the Acad. Mark. Sci. 45, 633–656 (2017). https://doi.org/10.1007/s11747-017-0535-8

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