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Knowing that you know: incentive effects of relative performance disclosure

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Abstract

This paper studies differential employee responses to the public disclosure of individual performance information throughout an organization. We argue that, to the extent that employees care about their colleagues’ perceptions of their productivity, public disclosure will increase motivation. Moreover, the effect should be stronger for employees whose colleagues expect them to have higher performance. We obtained data from a bank that transitioned from private to public disclosure of employee rankings and, consistent with our hypothesis, find heterogeneity in employee responses to public disclosure. Employees with a history of poor performance increase their output more than past good performers when rankings become public. Additionally, more highly educated employees react more strongly to the change. However, contrary to the literature that finds gender differences in competitive environments, we do not find systematic differences in the response to public disclosure on this dimension. Overall, the results suggest that public disclosure is an important dimension to consider when designing a compensation system.

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Notes

  1. For a review of recent trends and research on salary transparency, see Glassdoor’s April 2015 report “Is Salary Transparency More Than a Trend? Economic Research on the Impact of Greater Workplace Transparency.”

  2. As we measure historical performance two years prior to the public disclosure of performance ranking, we believe reversion to the mean is unlikely to explain the observed pattern.

  3. In Tafkov’s (2013) experimental setting, employees work under either a fixed-wage or an individual performance-based contact. In our setting, employees are competing in a tournament, so pay depends on peer performance.

  4. In the context of a worker training program, Ashraf et al. (2014) find that low-ability individuals perform worse on an exam if they are to receive rank information at the end of the performance period. Our results suggest that making rank information public might offset the effect that they document.

  5. Specifically, these authors state, “The improvement that we observe is most likely exhibited because public RPF [relative performance feedback] facilitates the identification and adoption of best practices” (p. 2,644). They describe best practice sharing as “a mechanism other than worker effort through which RFP may influence worker performance” (p. 2,629). In the private-relative-performance-information (i.e., control) group studied by Song et al. (2018), there were efforts to facilitate best-practice sharing, such as a page on the internal website devoted to best practices, but the interview evidence suggests that physicians were not utilizing this information.

  6. Points were awarded as a function of the number of products sold regardless of their balance (provided they met the minimum requirement), and there was no limit on the number of points that could be scored with respect to sales of each type of product. The minimum balance for products such as pension funds, life insurance, and mutual fund accounts was designed to ensure that the client was aware of what she was acquiring without being so high that it would lead to undercounting of legitimate sales.

  7. Thus, if an employee ranking placed her in the 34th percentile, she would be included in the third performance group and her ranking coefficient for bonus purposes would be 60%. In contrast, an employee in the 81st percentile would be included in the fifth performance group and her ranking coefficient for bonus purposes would be 20%.

  8. Even if some employees perceived the performance system as unfair, this cannot account for the effects of public disclosure of performance we observe. If anything, making performance public should exacerbate perceptions of unfairness and lower the motivation of underperforming employees. The fact that we find the opposite result suggests that a feeling of unfairness was not the main force driving the response to the change.

  9. As noted earlier, the points assigned to each product could vary from year to year. However, between 2004 and 2005, there was no change in the set of products used to compute the ranking, nor in the points assigned to each product.

  10. Social comparison theory (Festinger 1954) would also suggest that greater involvement in social comparisons provides information that reduces one’s uncertainty in self-evaluation and enhances employee motivation (Brown et al. 2007; Garcia and Tor 2007). Kolstad (2013) uses these arguments to support his finding that surgeons respond to the information in quality report cards significantly more than they do to economic incentives driven by patient demand. However, in our setting, the main change is in the ability of co-workers to see where each employee stands, rather than one’s ability to engage in social comparisons. Thus, our model and arguments do not highlight any learning effects that publicity offers the employee; instead, we focus on the motivational effects of co-worker perceptions about employee performance.

  11. The parameter a captures any dimension of performance that is persistent and unobservable, such as ability, human capital, or innate inclination to exert effort (intrinsic motivation). The formal modeling of the latter could be operationalized by defining output as π(e) = e + u and the cost of effort as c(e, a) = c(e − a) (assuming θ = 1 for simplicity). Under this formulation, optimal effort would be a linear function of a, so that we can interpret this parameter as the employee’s intrinsic motivation. The predictions of such a model with respect to parameter a would be analogous to the model developed in this section. Although we want to interpret the parameter broadly, for convenience we will refer to a as ability.

  12. Notice that supervisors have the same information regardless of whether employee performance is publicly disclosed or not. If promotion decisions had a significant subjective component, performance disclosure could constrain a supervisor’s discretion, for instance, by making it costlier to deny a promotion to the employee with the highest objective performance. This was not the case in the bank we studied, as promotions were based strictly on objective performance and hence did not change as a result of the public disclosure. As a result, implicit incentives were likely the same before and after the change. Further, it is unlikely that the public disclosure resulted in increased demand for high-performing employees by other units and, therefore, better career prospects. In the bank’s culture, poaching employees from another unit was considered highly inappropriate behavior. Moreover, higher-level managers, with the support of Human Resources, determined the transfer of resources, and both groups knew employees’ performance before and after the ranking disclosure change.

  13. Recall that in our setting the disclosed performance is based purely on objective metrics. The absence of subjectivity means we are better able to conclude that our effects are due to reputational concerns than would be the case if subjectivity were present (with subjectivity, employee responses may be triggered in part by fairness considerations, such as perceptions of favoritism or bias).

  14. Our model is closely related to the career concerns literature (Holmstrom 1999; Autrey et al. 2007). While incentives in these models come from the effects of reputation on future compensation, reputation enters the employee’s utility function directly in our model. In this respect, our model is similar the Benabou and Tirole (2006) model on social incentives and the Moldovanu et al. (2007) model on status. We differ in that we allow for social concerns to be nonlinear and depend on the reference point of prior expectations, with utility having a prospect theoretic form (Kahneman and Tversky 1979).

  15. This result is reversed when γ < γ+. In that case, the employee’s effort would be increasing in a and decreasing in r0.

  16. Saenz (1994), Steele (1997), Brown and Josephs (1999), and Inzlicht and Ben-Zeev (2000) make similar arguments about the effects of stereotypes and how they can inhibit performance.

  17. The eliminated observations pertain to three types of employees: (i) employees who joined the bank or transferred from the staff organization to the branch network after January 1, 2004; (ii) employees who left the bank or the branch network prior to December 31, 2005; and (iii) employees who transferred across branch regions or positions throughout the period (triggering a change in the tournament in which they competed) and/or were absent from one or more monthly tournaments during the period. These scenarios make it difficult to compare employee performance between 2004 and 2005 and thus to gauge the impact of ranking disclosure.

  18. We restrict construction of this measure to employees who were participating in a single tournament for the entire six months, and we require that, for the 2003 tournament, the employee had the same job type—advisor or teller—and worked in the same region—traditional or nontraditional—as during the 2004/2005 tournament.

  19. http://www.ine.es and http://www.anuarieco.lacaixa.comunicacions.com/java/X?cgi=caixa.le_DEM.pattern& accessed on 9/21/2018

  20. Our results reported in Table 5 are robust to winsorizing all variables at 1% and 99%.

  21. Indeed, because we only have two years of observation, OLS on the differenced model is equivalent to using a fixed-effects model on the original model.

  22. The average (winsorized) monthly points for the full sample was 125 points in 2004 and 134 points in 2005.

  23. An alternative interpretation for this result is that employees with higher past performance may reduce effort under public disclosure if they are concerned that their superior performance may be met with social disapproval. However, this alternative interpretation is inconsistent with our conversations with managers and employees of the bank and with the common interpretation of social comparison theory: “Just as our inferior, blameworthy attributes create less shame if they are kept private, our superior praiseworthy attributes create greater pride if they are made public.” (Smith 2000, p. 188).

  24. As a robustness test, we replaced employee age with employee experience (i.e., total years at the bank as of 2005) and reran our regressions appearing in Table 4 and in columns (4), (8), and (12) of Table 5 (our preferred specification). We did not include both variables in a single regression because they are highly correlated (0.79 for our main sample and significant at the 1% level). While we found results in the teller sample for our age variable, we found no such results for experience (recall, however, that we treat the age results cautiously due to the results of our placebo tests). Our results related to prior performance (in the advisor sample) and years of education (in the full sample and in the advisor sample) continue to hold whether we use employee age or employee experience.

  25. All of the results that we report in columns (4), (8), and (12) of Table 5 (our preferred specification) are robust to excluding outlier observations (we define an observation as an outlier if the value for any of the variables appearing in Table 2 is below the 1st percentile or above the 99th percentile within the respective sample). That is, the coefficient on Public*Years of Education for the full sample and for the advisor sample remains positive and statistically significant (both at the 1 % level), and the coefficient on Public*Prior Performance for the advisor sample remains negative and statistically significant (though at the 5 % level).

  26. In a further untabulated robustness test, we confirm that the results in columns (4), (8), and (12) of Table 5 are robust to clustering at the employee level rather than the branch level.

  27. While the total number of tournament observations in 2003/2004 is very similar to the total number of observations in 2004/2005, far fewer of the observations in 2003/2004 pertain to employees with full (i.e., 24) observations in a single tournament. This is likely to be at least partly explained by an efficiency initiative that the research site was undertaking during 2003, whereby many employees working at headquarters were redeployed to various branches.

  28. As a robustness test, we rerun our placebo tests in columns (2), (4), and (6), this time with the restriction that an employee remains at the same branch throughout the period—we no longer include branch fixed effects (since they are redundant when excluding employees who move between branches), and we cluster our standard errors at the branch level. With this restriction, we continue to find no significant interactions for either the full sample or the advisor sample. While for the teller sample we find negative and significant interactions between Placebo and all of our individual level variables—Male, Age, and Years of Education—we are hesitant to rely heavily on this placebo test since this reduced sample represents a mere 15 tellers.

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Acknowledgments

We thank Russell Lundholm (editor), an anonymous referee, Brad Badertscher, Alexander Brüggen, Barbara Fick, Mirko Heinle, Glen Kobussen, Peter Kroos, Michal Matejka, Sebastián Ruiz, and workshop participants at Harvard Business School, the University of Notre Dame, the AAA Management Accounting Section Midyear Meeting, the AAA Annual Meeting, the EAA Annual Meeting, the EIASM Workshop on Accounting and Economics, and GMARS for helpful comments and suggestions.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector.

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Correspondence to Carolyn Deller.

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Conflicts of interest/competing interests

During the time period covered by the data utilized for this study, one of the authors worked for the bank that provided us with the data. However, the author was not responsible for nor involved in the change in the tournament system analyzed in the paper.

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The data used in this project are subject to a confidentiality agreement and cannot be shared.

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At the time of the study, José Manuel Narciso worked for the bank that provided us with the data.

Appendix

Appendix

Proof of Propositions 1 and 2. The employee chooses the effort level to maximize her expected utility (notice that r depends on the realization of π, and hence is a random variable). If we denote the pdf of the posterior r by ϕr, then we can write:

$$ EU=\beta E\pi +{\gamma}_{-}{\int}_{-\infty}^{r_0}\left(r-{r}_0\right){\phi}_r(r) dr+{\gamma}_{+}{\int}_{r_0}^{+\infty}\left(r-{r}_0\right){\phi}_r(r) dr. $$

Because co-workers’ priors about the employee’s ability are normal and the signal they receive (output) is also normal, their posterior will be normally distributed and satisfies r − r0 = μ(π − πe), where π = θe + a + u, \( {\pi}^e=\theta \hat{e}+{r}_0 \), and \( \hat{e} \) is the co-workers’ conjecture about the employee effort. Hence, r > r0 if and only if \( u>{r}_0-a+\theta \left(\hat{e}-e\right) \). From the employee’s perspective, as a is known, the uncertainty about her reputation is driven by u. If we let \( \varGamma (e)={r}_0-a+\theta \left(\hat{e}-e\right) \) and ϕu be the pdf of a \( N\left(0,{\sigma}_u^2\right) \), we have:

$$ EU=\beta \left(\theta e+a\right)+{\gamma}_{-}{\int}_{-\infty}^{\varGamma (e)}\mu \left(\theta e+a+x-\theta \hat{e}-{r}_0\right){\phi}_u(x) dx+{\gamma}_{+}{\int}_{\varGamma (e)}^{+\infty}\mu \left(\theta e+a+x-\theta \hat{e}-{r}_0\right){\phi}_u(x) dx. $$

By differentiating the expected utility using Leibniz’ rule, we get that the optimal choice satisfies:

$$ \beta \theta +\mu \theta \left[{\gamma}_{-}\Pr \left(r<{r}_0\right)+{\gamma}_{+}\Pr \left(r\ge {r}_0\right)\ \right]={c}^{\prime }(e)=e. $$
(1)

Proposition 1.a) follows immediately, as e is increasing in μ, γ, and γ+. Notice also that, because Pr(r ≥ r0) = 1 − Pr(r < r0), we have ∂e/∂a = μθ(γ − γ+) Pr(r < r0)/∂a, and similarly for ∂e/∂r0. Proposition 1.b) then follows from the fact that Pr(r < r0) is decreasing in a and increasing in r0. Finally, Proposition 2 follows from the fact that 2e/∂θ∂a = μ(γ − γ+) Pr(r < r0)/∂a and \( {\partial}^2{e}^{\ast }/\partial {\sigma}_a^2\partial a=\theta \left({\gamma}_{-}-{\gamma}_{+}\right)\left[\partial \Pr \left(r<{r}_0\right)/\partial a\right]\partial \mu /\partial {\sigma}_a^2 \), with \( \partial \mu /\partial {\sigma}_a^2>0 \). ∎

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Casas-Arce, P., Deller, C., Martínez-Jerez, F.A. et al. Knowing that you know: incentive effects of relative performance disclosure. Rev Account Stud 28, 91–125 (2023). https://doi.org/10.1007/s11142-021-09636-2

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