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The impact of customer satisfaction on CEO bonuses

Abstract

In this study, we build on prior research in marketing and executive compensation to show that customer satisfaction is a significant determinant of CEO bonuses. Findings demonstrate that the success of CEOs in managing customer satisfaction has a direct, personal, and economic impact in the form of their annual bonus awards. Our study contributes to research on the use of customer satisfaction information, marketing accountability, and marketing’s board level relevance. Our research also extends marketing theory by pointing to a previously unexamined role for marketing performance metrics.

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Notes

  1. In an unpublished study, Srinivasan et al. (2003) find that satisfaction—as measured by the American Customer Satisfaction Index—has no incremental explanatory power for CEO compensation in their study of the airline industry. However, their work focuses on a very small sample drawn from a single industry. In another unpublished paper, Chen et al. (2008b) predict and find statistically significant regression coefficients for terms representing the interaction between satisfaction and various proxies for industry competition, but report no significant “main effect” association between CEO bonus and satisfaction. Indeed Davila and Venkatachalam’s (2004) study, which demonstrates that passenger load factor is a positive and significant determinant of CEO bonus in the airline industry, is the only evidence showing a direct statistical association between any nonfinancial measure and CEO compensation in any sector.

  2. Customer satisfaction impacts each of the financial metrics (Anderson et al. 2004; Gruca and Rego 2005). Therefore, testing the incremental independent impact of U(ACSI) provides a conservative estimate of the relationship between customer satisfaction and compensation. Similarly, studies by Jacobson and colleagues investigating the incremental information content of marketing metrics with respect to firm value (e.g., Aaker and Jacobson 1994; Mizik and Jacobson 2008) provide a conservative estimate of value relevance.

  3. Separately, Dikolli and Sedatole (2007) and Chen (2009) demonstrate that the benchmark against which satisfaction is measured influences its information content.

  4. As discussed, consistent with standard practice for studies that employ an expected/unexpected framework, U(RET) = RET throughout.

  5. We are grateful to the anonymous review team for their suggestions with respect to this test.

  6. The mean for U(ACSI) for the CLEAR SIGNAL observations is .677 (N = 536) while that for the AMBIGUOUS SIGNAL observations is -1.04 (n = 212) and the overall mean is .18 (N = 748). A t-test of the difference between the means for the CLEAR SIGNAL and AMBIGUOUS SIGNAL subsamples is significant at p = .000 with a t-statistic = 6.25. This finding is confirmed by Hotelling and Kruskal-Wallis tests. These findings suggest that U(ACSI) is significantly different for the AMBIGUOUS SIGNAL observations. No other significant differences in the mean values of variables across the CLEAR SIGNAL and AMBIGUOUS SIGNAL subsamples are evident.

  7. For each individual regression estimate outliers defined as those observations with values of Cook’s Distance greater than 4/N are excluded from the analysis (Cook 1977). Including outliers has no material impact on our results for U(ACSI).

  8. Using the values in Table 6, the partial derivative of U(CASH) with respect to U(ACSI) for quadrant II observations (i.e., when QUAD_II = 1) is .018 ([.012 + .006 × 1]) and .010 for quadrant III observations ([.012−.002 (×1)]). For U(TOTALCASH), the equivalent figures are .020 for quadrant II observations and .014 for quadrant III observations.

  9. We use Eq. 6 (i.e., we include both CLEAR SIGNAL and AMBIGUOUS SIGNAL observations) for the estimates reported in Panels A and B of Table 8. To maximise sample size, we include outliers in the sector and period estimates in Panel A. Four observations, which are outside of the SIC codes included in our analysis, are excluded from the sector tests. The estimates in Table 8 are for U(BONUS) as the dependent variable in all cases—the results when U(TOTALCASH) is the dependent variable are equivalent and are available from the authors on request.

  10. One potential noteworthy aspect of these results is that one of our control variables (VAR(RET)) drops out of the analysis as time-invariant variables are dropped in fixed effects estimation. For this reason, we report our main results using Huber-White-Rogers estimation (Rogers 1993).

  11. To investigate the potential impact of our decision to use lagged satisfaction, we examine an alternative measure of satisfaction—defined as the average of the contemporaneous and prior period’s measures of satisfaction relative to peer firms—as an alternative to U(ACSI) in Eq. 5. The coefficient estimates (p values) for satisfaction using this alternative measure for the regressions in columns (1) to (4) respectively of Table 5 are: [.019, (.009);.016 (.013);.009 (.036).009 (.023)]. These results show that the average measure—which combines both contemporaneous and lagged satisfaction relative to peer firms—is also positive and statistically significant.

  12. The benefits of this estimation approach are discussed in depth in Gow et al. (2009).

  13. All of the findings discussed here are confirmed for U(TOTALCASH) in unreported tests.

  14. For these tests, U(ROA) is defined as the residual from the following regression: \( {\hbox{RO}}{{\hbox{A}}^{\rm{FIRM}}} = \alpha + {\beta_1}{\hbox{RO}}{{\hbox{A}}^{\rm{IND}}} + {\hbox{u}} \). Similarly, U(RET) is defined as the residual from the following regression: \( {\hbox{RE}}{{\hbox{T}}^{\rm{FIRM}}} = \alpha + {\beta_1}{\hbox{RE}}{{\hbox{T}}^{\rm{IND}}} + {\hbox{u}} \). U(ACSI) in these tests is defined as per Eq. 1.

  15. A detailed discussion of the underlying rationale for the use of levels in such contexts is presented in Wooldridge (2006) and Fahlenbrach (2009).

References

  • Aaker, D. A., & Jacobson, R. (1994). The financial information content of perceived quality. Journal of Marketing Research, 38(4), 485–493.

    Article  Google Scholar 

  • Aggarwal, R. K., & Samwick, A. A. (1999). The other side of the trade-off: the impact of risk on executive compensation. Journal of Political Economy, 107(1), 65–105.

    Article  Google Scholar 

  • Aksoy, L., Cooil, B., Groening, C., Keiningham, T. L., & Yalcin, A. (2008). The long term stock market valuation of customer satisfaction. Journal of Marketing, 72(4), 105–122.

    Article  Google Scholar 

  • Albuquerque, A. (2009). Peer firms in relative performance evaluation. Journal of Accounting and Economics, 48(1), 69–89.

    Article  Google Scholar 

  • Anderson, E. W., & Mittal, V. (2000). Strengthening the satisfaction-profit chain. Journal of Service Research, 3(2), 107–120.

    Article  Google Scholar 

  • Anderson, E. W., Fornell, C., & Rust, R. T. (1997). Customer satisfaction, productivity, and profitability: differences between goods and services. Marketing Science, 16(2), 129–147.

    Article  Google Scholar 

  • Anderson, E. W., Fornell, C., & Mazvancheryl, S. K. (2004). Customer satisfaction and shareholder value. Journal of Marketing, 68(4), 172–185.

    Article  Google Scholar 

  • Antle, R., & Smith, A. J. (1986). An empirical investigation of the relative performance evaluation of corporate-executives. Journal of Accounting Research, 24(1), 1–39.

    Article  Google Scholar 

  • Baber, W. R., Kang, S.-H., & Kumar, R. K. (1998). Accounting earnings and executive compensation: the role of earnings persistence. Journal of Accounting & Economics, 25(2), 169–193.

    Article  Google Scholar 

  • Baber, W. R., Kang, S.-H., & Kumar, R. K. (1999). The explanatory power of earnings levels vs. earnings changes in the context of executive compensation. The Accounting Review, 74(4), 459–472.

    Article  Google Scholar 

  • Boulding, W. (1990). Unobservable fixed effects and business performance: do fixed effects matter? Marketing Science, 9(1), 88–91.

    Article  Google Scholar 

  • Boulding, W., & Staelin, R. (1995). Identifying generalizable effects of strategic actions on firm performance: the case of demand-side returns to R&D spending. Marketing Science, 14(3), 222–235.

    Article  Google Scholar 

  • Bushman, R. M., & Smith, A. J. (2001). Financial accounting information and corporate governance. Journal of Accounting and Economics, 32(1–3), 237–333.

    Article  Google Scholar 

  • Casas-Arce, P., & Martinez-Jerez, A. (2009). Relative performance compensation, contests, and dynamic incentives. Management Science, 55(8), 1306–1320.

    Article  Google Scholar 

  • Chen, C. X. (2009). Who really matters? Revenue implications of stakeholder satisfaction in a health insurance company. The Accounting Review, 84(6), 1781–1804.

    Article  Google Scholar 

  • Chen, C. X., Martin, M., & Merchant, K. A. (2008a). The effects of measurement alternatives on the forward-looking properties of customer satisfaction measures. SSRN eLibrary.

  • Chen, C. X., Matsumura, E. M., & Shin, J. Y. (2008b). The effect of competition on the contracting use of customer satisfaction: Evidence from the American Customer Satisfaction Index. Working Paper. University of Illinois at Urbana-Champaign.

  • Cooil, B., Keiningham, T. L., Aksoy, L., & Hsu, M. (2007). Longitudinal analysis of customer satisfaction and share of wallet: investigating the moderating effect of customer characteristics. Journal of Marketing, 71(1), 67–83.

    Article  Google Scholar 

  • Cook, R. D. (1977). Detection of influential observations in linear regression. Technometrics, 19, 15–18.

    Article  Google Scholar 

  • Core, J. E., Guay, W. R., & Verrecchia, R. E. (2003). Price versus non-price performance measures in optimal CEO compensation contracts. The Accounting Review, 78(4), 957–981.

    Article  Google Scholar 

  • Davila, A., & Venkatachalam, M. (2004). The relevance of non-financial measures for CEO compensation: evidence from the airline industry. Review of Accounting Studies, 9(4), 443–464.

    Article  Google Scholar 

  • Dechow, P., Huson, M., & Sloan, R. (1994). The effect of restructuring charges on executives’ cash compensation. The Accounting Review, 69(1), 138–156.

    Google Scholar 

  • Dikolli, S. S., & Sedatole, K. L. (2007). Improvements in the information content of nonfinancial forward-looking performance measures: a taxonomy and empirical application. Journal of Management Accounting Research, 19, 71–104.

    Article  Google Scholar 

  • Dikolli, S. S., & Vaysman, I. (2006). Contracting on the stock price and forward-looking performance measures. European Accounting Review, 15(4), 445–464.

    Article  Google Scholar 

  • Driscoll, J. C., & Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. The Review of Economics and Statistics, 80, 549–560.

    Article  Google Scholar 

  • Epstein, M. J., & Roy, M.-J. (2005). Evaluating and monitoring CEO performance: evidence from US compensation committee reports. Corporate Governance, 5(4), 75–87.

    Article  Google Scholar 

  • Ezzamel, M., & Watson, R. (1998). Market comparison earnings and the bidding-up of executive cash compensation: evidence from the UK. Academy of Management Journal, 41(2), 221–231.

    Article  Google Scholar 

  • Fahlenbrach, R. (2009). Shareholder rights, boards, and CEO compensation. Review of Finance, 13(2), 81–113.

    Google Scholar 

  • Feltham, G., & Xie, J. (1994). Performance measurement congruity and diversity in multitask principal/agent relations. The Accounting Review, 69(3), 429–453.

    Google Scholar 

  • Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., & Everitt Bryant, B. (1996). The American customer satisfaction index: nature, purpose, and findings. Journal of Marketing, 60(4), 7–19.

    Article  Google Scholar 

  • Fornell, C., Mithas, S., Morgeson, F. V., III, & Krishnan, M. S. (2006). Customer satisfaction and stock prices: high returns, low risk. Journal of Marketing, 70(1), 3–14.

    Article  Google Scholar 

  • Gaver, J., & Gaver, K. (1998). The relation between nonrecurring accounting transactions and CEO cash compensation. The Accounting Review, 73(2), 235–253.

    Google Scholar 

  • Gow, I., Ormazabal, G., & Taylor, D. (2009). Correcting for cross-sectional and time-series dependence in accounting research. The Accounting Review, forthcoming. Available at SSRN: http://ssrn.com/abstract=1175614.

  • Granger, C. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424–438.

    Article  Google Scholar 

  • Greene, W. (2003). Econometric analysis (5th ed.). Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Gruca, T. S., & Rego, L. L. (2005). Customer satisfaction, cash flow, and shareholder value. Journal of Marketing, 69(3), 115–130.

    Article  Google Scholar 

  • Gupta, S., & Zeithaml, V. A. (2006). Customer metrics and their impact on financial performance. Marketing Science, 25(6), 718–739.

    Article  Google Scholar 

  • Gupta, S., Lehmann, D. R., & Stuart, J. A. (2004). Valuing customers. Journal of Marketing Research, 41(1), 7–18.

    Article  Google Scholar 

  • Hauser, J. R., Simester, D. I., & Wernerfelt, B. (1994). Customer satisfaction incentives. Marketing Science, 13(4), 327–351.

    Article  Google Scholar 

  • Hayes, R. M., & Schaefer, S. (2000). Implicit contracts and the explanatory power of top executive compensation for future performance. The Rand Journal of Economics, 31(2), 273–293.

    Article  Google Scholar 

  • Healy, P. (1985). The effect of bonus schemes on accounting decisions. Journal of Accounting and Economics, 7(1–3), 85–107.

    Article  Google Scholar 

  • Healy, P., & Wahlen, J. M. (1999). A review of the earnings management literature and its implications for standard setting. Accounting Horizons, 13(4), 365–383.

    Article  Google Scholar 

  • Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. The Stata Journal, 7, 281–312.

    Google Scholar 

  • Holmstrom, B. (1979). Moral hazard and observability. Bell Journal of Economics, 10(1), 74–91.

    Article  Google Scholar 

  • Holmstrom, B., & Milgrom, P. (1987). Aggregation and linearity in the provision of intertemporal incentives. Econometrica, 55(2), 303–328.

    Article  Google Scholar 

  • Hsiao, C. (2003). Analysis of panel data (2nd ed.). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Ittner, C. D., & Larcker, D. F. (1998). Are nonfinancial measures leading indicators of financial performance? An analysis of customer satisfaction. Journal of Accounting Research, 36(Supplement), 1–35.

    Article  Google Scholar 

  • Ittner, C. D., & Larcker, D. F. (2003). Coming up short on nonfinancial performance measurement. Harvard Business Review, 81(11), 88–95.

    Google Scholar 

  • Ittner, C. D., Larcker, D. F., & Rajan, M. V. (1997). The choice of performance measures in annual bonus contracts. The Accounting Review, 72(2), 231–255.

    Google Scholar 

  • Ittner, C. D., Larker, D. F., & Taylor, D. (2009). Commentary—the stock market’s pricing of customer satisfaction. Marketing Science, 28(5), 826–835.

    Article  Google Scholar 

  • Jacobson, R., & Aaker, D. A. (1993). Myopic management behavior with efficient, but imperfect financial markets. Journal of Accounting & Economics, 16(4), 383–405.

    Article  Google Scholar 

  • Jacobson, R., & Mizik, N. (2009). The financial markets and customer satisfaction: reexamining possible financial market mispricing of customer satisfaction. Marketing Science, 28(5), 809–818.

    Article  Google Scholar 

  • Janakiraman, S., Lambert, R. A., & Larcker, D. F. (1992). An empirical investigation of the relative performance evaluation hypothesis. Journal of Accounting Research, 30(1), 53–69.

    Article  Google Scholar 

  • Jaworski, B. J. (1988). Toward a theory of marketing control: environmental context, control types, and consequences. Journal of Marketing, 52(3), 23–39.

    Article  Google Scholar 

  • Jensen, M. C., & Murphy, K. J. (1990). Performance pay and top-management incentives. Journal of Political Economy, 98(2), 225–264.

    Article  Google Scholar 

  • Karuna, C. (2007). Industry product market competition and managerial incentives. Journal of Accounting and Economics, 43, 275–297.

    Article  Google Scholar 

  • Krasnikov, A., Mishra, S., & Orozco, D. (2009). Evaluating the financial impact of branding using trademarks: a framework and empirical evidence. Journal of Marketing, 73(6), 154–166.

    Article  Google Scholar 

  • Kroll, M., Wright, P., & Heiens, R. A. (1999). The contribution of product quality to competitive advantage: impacts on systematic variance and unexplained variance in returns. Strategic Management Journal, 20(4), 375–384.

    Article  Google Scholar 

  • Lambert, R. A., & Larcker, D. F. (1987). An analysis of the use of accounting and market measures of performance in executive compensation contracts. Journal of Accounting Research, 25, 85–129.

    Article  Google Scholar 

  • Lehmann, D. (2004). Metrics for making marketing matter. Journal of Marketing, 68(4), 73–75.

    Article  Google Scholar 

  • Leone, A. J., Wu, J. S., & Jerold, L. Z. (2006). Asymmetric sensitivity of CEO cash compensation to stock returns. Journal of Accounting and Economics, 42(1–2), 167–192.

    Article  Google Scholar 

  • Luo, X., & Donthu, N. (2006). Marketing’s credibility: a longitudinal investigation of marketing communication productivity and shareholder value. Journal of Marketing, 70(4), 70–91.

    Article  Google Scholar 

  • Luo, X., & Homburg, C. (2007). Neglected outcomes of customer satisfaction. Journal of Marketing, 71(2), 133–149.

    Article  Google Scholar 

  • McAlister, L., Srinivasan, R., & Kim, M. (2007). Advertising, research and development and systematic risk of the firm. Journal of Marketing, 71(1), 35–48.

    Article  Google Scholar 

  • Mittal, V., Anderson, E. W., Sayrak, A., & Tadikamalla, P. (2005). Dual emphasis and the long-term financial impact of customer satisfaction. Marketing Science, 24(4), 544–555.

    Article  Google Scholar 

  • Mizik, N. (2010). The theory and practice of myopic management. Journal of Marketing Research, 47(4), 594–611.

    Google Scholar 

  • Mizik, N., & Jacobson, R. (2007). Myopic marketing management: evidence of the phenomenon and its long-term performance consequences in the SEO context. Marketing Science, 26(3), 361–379.

    Article  Google Scholar 

  • Mizik, N., & Jacobson, R. (2008). The financial value impact of perceptual brand attributes. Journal of Marketing Research, 45(1), 15–32.

    Article  Google Scholar 

  • Morgan, N. A., & Rego, L. L. (2009). Brand portfolio strategy and firm performance. Journal of Marketing, 73(1), 59–74.

    Article  Google Scholar 

  • Morgan, N. A., Anderson, E. W., & Mittal, V. (2005). Understanding firms’ customer satisfaction information usage. Journal of Marketing, 69(3), 131–151.

    Article  Google Scholar 

  • Murphy, K. (2000). Performance standards in incentive contracts. Journal of Accounting and Economics, 30(3), 245–278.

    Article  Google Scholar 

  • Oliva, T. A., Oliver, R. L., & MacMillan, I. C. (1992). A catastrophe model for developing service satisfaction strategies. Journal of Marketing, 56(3), 83–96.

    Article  Google Scholar 

  • Oyer, P. (2004). Why do firms use incentives that have no incentive effects? Journal of Finance, 59(4), 1619–1649.

    Article  Google Scholar 

  • Pauwels, K. H., Silva-Risso, J. M., Srinivasan, S., & Hanssens, D. M. (2004). New products, sales promotions, and firm value: the case of the automobile industry. Journal of Marketing, 68(4), 142–156.

    Article  Google Scholar 

  • Petersen, M. (2009). Estimating standard errors in finance data sets; comparing approaches. Review of Financial Studies, 22, 435–480.

    Article  Google Scholar 

  • Rajgopal, S., Shevlin, T., & Zamora, V. (2006). CEOs’ Outside employment opportunities and the lack of relative performance evaluation in compensation contracts. Journal of Finance, 61(4), 1813–1844.

    Article  Google Scholar 

  • Ramsey, J. (1969). Tests for specification error in classical linear least squares analysis. Journal of the Royal Statistical Society, Series B, 31, 350–371.

    Google Scholar 

  • Rogers, W. (1993). Regression standard errors in clustered samples. Stata Technical Bulletin Reprints, 3, 83–94.

    Google Scholar 

  • Sorescu, A. B., & Spanjol, J. (2008). Innovation’s effect on firm value and risk: insights from consumer packaged goods. Journal of Marketing, 72(2), 114–132.

    Article  Google Scholar 

  • Sorescu, A. B., Chandy, R. K., & Prabhu, J. C. (2007). Why some acquisitions do better than others: product capital as a driver of long-term stock returns. Journal of Marketing Research, 44(1), 57–72.

    Article  Google Scholar 

  • Srinivasan, S., & Hanssens, D. M. (2009). Marketing and firm value: metrics, methods, findings and future directions. Journal of Marketing Research, 46(3), 293–312.

    Article  Google Scholar 

  • Srivastava, R. K., Shervani, T. A., & Fahey, L. (1998). Market-based assets and shareholder value: a framework for analysis. Journal of Marketing, 62(1), 2–18.

    Article  Google Scholar 

  • Srinivasan, D., Sayrak, A., & Nagarajan, N. (2003). Executive compensation and nonfinancial performance measures: A study of major U.S. Airlines. Working Paper. University of Pittsburgh.

  • Tufte, D., & Wohar, M. E. (1999). Models with unexpected components: the case for efficient estimation. Review of Quantitative Finance and Accounting, 13(2), 295–313.

    Article  Google Scholar 

  • Verbeke, G., & Molenberghs, G. (2000). Linear mixed models for longitudinal data. New York: Wiley.

    Google Scholar 

  • Vorhies, D. W., & Morgan, N. A. (2005). Benchmarking marketing capabilities for sustainable competitive advantage. Journal of Marketing, 69(1), 80–94.

    Article  Google Scholar 

  • Webster, F. E. (1988). Rediscovering the marketing concept. Business Horizons, 31(3), 29–39.

    Article  Google Scholar 

  • Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge: MIT.

    Google Scholar 

  • Wooldridge, J. M. (2006). Introductory econometrics: A modern approach (3rd ed.). Mason: Thomson/South-Western.

    Google Scholar 

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Correspondence to Don O’Sullivan.

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We thank the Intellectual Property Research Institute of Australia who provided financial support for our research.

Names appear in alphabetical order; both contributed equally to this article.

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O’Connell, V., O’Sullivan, D. The impact of customer satisfaction on CEO bonuses. J. of the Acad. Mark. Sci. 39, 828–845 (2011). https://doi.org/10.1007/s11747-010-0218-1

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Keywords

  • CEO bonuses
  • Customer satisfaction
  • Marketing metrics