Firm Performance in the Hospitality Industry: Do CEO Attributes and Compensation Matter?

Abstract

Past research has shown mixed results regarding the role CEO compensation plays in influencing firm financial performance in the hospitality industry. To explore this relationship further, we concomitantly examine the role of compensation and CEO attributes like education, age, tenure, functional background, and gender on firm financial performance. Our analyses are based on secondary and hand-collected data from a large and comprehensive sample of U.S. publicly traded hospitality firms. The results from panel data analyses show that CEO cash compensation is positively related to return on assets, while equity compensation is unrelated to firm performance. We further find that when CEO compensation and attributes are jointly examined, CEO compensation has a relatively lower impact on firm performance than CEO attributes do. The results imply that the hospitality industry may want to reconsider its compensation practices in order to better align the interests of managers and shareholders and motivate managers to maximize firm value.

Keywords

firm performance CEO compensation CEO attributes agency theory upper echelons theory hospitality firms

Strategic leadership theorists argue that executives, particularly chief executive officers (CEOs), have strong effects on organizations. By isolating the proportion of variance in firm performance that is attributable to CEOs (as opposed to contextual factors related to macroeconomic conditions, industry, and firm), researchers find that the “CEO effect” accounts for 38.5% of variance in return on assets (ROA), 35.5% of variance in return on sales, and 46.4% of variance in market-to-book value of common stock (Hambrick & Quigley, 2014). Although the CEO effect is particularly greater in industries with greater advertising intensity (Lieberson & O’Connor, 1972) like in the hospitality industry, relatively few studies have examined hospitality CEOs. It is important to examine CEOs in the hospitality industry because compared with other industries the hospitality industry has higher competition and risk that requires greater monitoring of the external environment and possibly higher CEO compensation that rewards long-term investment and risk-bearing (Singal, 2015). These industry characteristics may also need different skill sets and background for CEOs to be successful.

Existing research on hospitality CEOs mainly focuses on the relationship between CEO compensation and firm performance. While agency theory suggests that linking CEO pay to firm performance is an effective way of aligning divergent interests of managers and shareholders, findings on the pay-performance link for CEO compensation in the hospitality industry are inconsistent. For instance, within the restaurant sector, Kim and Gu (2005) find no relationship between cash compensation and stock returns, whereas Madanoglu and Karadag (2008) find a positive relationship between change in cash compensation and stock returns. Perhaps, the inconsistent findings are due to the use of different compensation measures, such as cash (Kim & Gu, 2005), equity-based (Guillet, Kucukusta, & Xiao, 2012), and aggregated compensation (Barber, Ghiselli, & Deale, 2006), as well as different performance measures such as ROA (Madanoglu & Karadag, 2008), stock returns (Upneja & Ozdemir, 2014), and Tobin’s Q (Guillet et al., 2012). Nevertheless, inconsistent findings make comparison between studies difficult and retard progress for future scholarship. In addition, existing evidence on the pay-performance relationship is predominantly cross-sectional, and it may simply reflect unobservable variables that affect both compensation practices and firm performance.

An important factor in the CEO effect that may affect findings on the pay-performance relationship is CEO attributes, which are rarely studied in the hospitality literature. Upper echelons theory postulates that CEO demographic and other attributes such as gender, education, and functional background affect firm performance (Hambrick, 2007). Although not directly studying the impact of CEO attributes on firm performance, limited studies on hospitality executives provide some evidence of the association between personal characteristics and firm performance. For example, when studying the effect of CEO compensation on firm performance, Upneja and Ozdemir (2014) find that tenure as a proxy for expertise has a positive impact on firm performance. Guillet, Seo, Kucukusta, and Lee (2013), on the other hand, argue that age and tenure may affect CEO duality, which in turn affects firm performance, and, therefore, should be controlled for when studying the effect of duality on firm performance. Similarly, prior research shows that CEO attributes, such as age and tenure, are also related to CEO compensation (Hill & Phan, 1991; Ryan & Wiggins, 2001) and, therefore, should be studied along with CEO compensation. In other words, the effect of CEO compensation on firm performance may be confounded by the effect of CEO attributes if they are not simultaneously studied in one model. Since CEO attributes, besides age and tenure, have not been hitherto explored in the hospitality context, we extend our analyses to examine if CEO experience, functional background, and educational background along with CEO compensation affect financial performance.

To that end, our study integrates upper echelons theory with agency theory to investigate whether CEO attributes and compensation jointly affect the performance of firms in the hospitality industry. Specifically, the present study aims to examine (1) the effect of CEO compensation on firm performance and (2) the joint effect of CEO attributes and compensation on firm performance.

In doing so, we contribute to the literature by addressing several potential causes for mixed findings, including small sample size, failure to include firm-fixed effects, omitted variable bias, and inconsistent performance measures. Our large and comprehensive sample of hospitality and tourism firms reduces noise in the data, and by employing panel regressions with firm- and year-fixed effects along with clustered standard errors, we are able to provide time-series evidence of the CEO compensation-performance relationship. We facilitate a comparison of findings and demonstrate that the compensation–performance relationship is performance-measure-specific by including three common firm performance measures. By studying CEO attributes in parallel with CEO compensation, we thus contribute to the literature by addressing a research gap about the relative effects of executive characteristics and compensation systems on firm performance (Hambrick, 2007).

CEO Compensation and Firm Performance

Executive compensation includes basic salary, short-term and long-term incentives, bonuses, stock options, and other forms of compensation (Guillet et al., 2012). Two types of executive compensation are often studied in the literature: cash compensation (i.e., salary plus cash bonuses) and equity compensation (i.e., restricted stocks plus stock options; Upneja & Ozdemir, 2014). Cash compensation aims to align a CEO’s interest with the firm’s short-term performance, whereas equity compensation aims to align a CEO’s interest with the firm’s long-term performance. To provide additional evidence on the link between compensation and firm performance for CEOs in the hospitality industry where previous researchers (Kim & Gu, 2005) note that a pay-for-performance guideline is not always implemented, we employ a large and comprehensive sample of hospitality firms (including hotels, restaurants, airlines, casinos, cruises, and theme parks) with data available from both Compustat and Execucomp for the years 1992-2016, consisting of 1,537 firm-years, for 252 distinct CEOs, and 106 unique companies. We adjust data for Consumer Price Index in 2016 dollars and winsorize data at 1% and 99% levels to moderate effects of extreme values. Because firm-fixed effects control for unobservable firm characteristics, such as a firm’s culture, policies, history, and product mix, that may affect firm performance, we compare regression models with and without firm-fixed effects to examine whether and to what extent the unobservable, time-invariant firm characteristics affect the CEO compensation-performance relationship. Following Guillet et al. (2013) and Upneja and Ozdemir (2014), we include firm size, leverage, CEO change, duality, and year as control variables. Firm size is controlled because larger firms may employ better-qualified managers and pay them more, whereas leverage is controlled because highly levered firms are riskier and have lower firm value. CEO change is controlled because such changes may distort the pay-for-performance relationship, whereas duality is controlled because duality is found to positively affect hospitality firm performance (Guillet et al., 2013). Year dummies are included to control for the macroeconomic conditions that affect all firms in a given year. Table 1 provides details of the variables used in this study.

Table 1

Descriptions of Variables

Variables	Descriptions
Firm performance
ROA	Ratio of net income and average total assets
Tobin’s Q	Approximate q = (MVE + PS + DEBT)/TA, where MVE is the product of a firm’s stock price and the number of common shares outstanding; PS is the liquidating value of outstanding preferred shares; DEBT is the value of short-term liabilities, net of short-term assets, plus the book value of long-term assets; and TA is the book value of total assets
Stock return	One-year holding period return
CEO compensation
Cash	Annual salary plus bonus
Equity	Stock options plus restricted stocks
CEO characteristics
Age	CEO age
Gender	= 1 if a CEO is male, 0 otherwise
Tenure	A CEO’s years of employment as CEO at the focal firm
Experience1	= 1 if a CEO has no prior CEO experience, 0 otherwise
Experience2	= 1 if a CEO has prior CEO experience in the same industry as the focal firm, 0 otherwise
Experience3	= 1 if a CEO has prior CEO experience in other service industries, 0 otherwise
Experience4	= 1 if a CEO has prior CEO experience in manufacturing industries, 0 otherwise
Education1	= 1 if a CEO has a nongraduate degree, 0 otherwise
Education2	= 1 if a CEO has an MBA, 0 otherwise
Education3	= 1 if a CEO has a graduate degree in law, 0 otherwise
Education4	= 1 if a CEO has a non-MBA and non–law graduate degree, 0 otherwise
Function1	= 1 if a CEO has an engineering, operations, or R&D background, 0 otherwise
Function2	= 1 if a CEO has a sales and marketing background, 0 otherwise
Function3	= 1 if a CEO has an accounting, finance, law, personnel, or general administration background, 0 otherwise
Control variables
Size	Natural logarithm of total assets
Leverage	Ratio of total debt and total assets
CEO change	= 1 if a new CEO assumes office in current year, 0 otherwise
Duality	= 1 if the CEO is also chair of the board, 0 otherwise

Note: ROA = return on assets; CEO = chief executive officer.

Table 2 displays the summary statistics for these variables. The mean ROA of the sample firms is 5%, the mean Tobin’s Q 1.9, and the mean annual stock return 12%. A typical firm in our sample has $5,702.84 million worth of total assets and a leverage ratio of 0.62. An average CEO is around 55 years old and has a tenure of 8 years. On average, CEOs in our sample are paid $1,342,270 in cash and $2,900,510 in equity. The median cash and equity compensation is $961,540 and $840,890, respectively.

Table 2

Descriptive Statistics

Variable	N	M	SD	Median	Minimum	Maximum
ROA	1,528	0.05	0.08	0.05	−0.27	0.24
Tobin’s Q	1,464	1.90	1.07	1.59	0.68	6.40
Stock return	1,476	0.12	0.51	0.07	−0.84	2.28
Age	1,384	54.89	7.54	55.00	30.00	80.00
Tenure (in years)	1,407	8.01	7.69	5.67	0.03	40.92
Cash (in 000)	1,537	1,342.27	1,174.47	961.54	0.00	6,765.38
Equity (in 000)	847	2,900.51	5,398.82	840.89	0.00	34,413.83
Size (in millions)	1,535	5,702.84	9,398.47	1,398.70	86.05	41,376.47
Leverage	1,529	0.62	0.29	0.59	0.12	1.75

Note: ROA = return on assets; M = mean; SD = standard deviation.

Table 3 reports the effects of CEO compensation on firm performance. The dependent variable is ROA in Models 1 and 2, Tobin’s Q in Models 3 and 4, and stock returns in Models 5 and 6. Equity compensation is lagged by 1 year. The first, third, and fifth columns report results from a baseline specification using pooled data for each dependent variable. Increases in cash compensation, ceteris paribus, are associated with an increase in ROA, Tobin’s Q, and stock returns. Increases in equity compensation only lead to an increase in Tobin’s Q. In Models 2, 4, and 6, we control for the unobserved firm heterogeneity as well as serial correlation within each firm by including firm-fixed effects and clustering standard errors by firm. As a result, the estimated coefficients change substantially in some cases. For example, cash compensation becomes insignificant in Models 4 and 6, and equity compensation becomes insignificant in Model 4. In Model 2, although cash compensation is still a significant determinant of ROA, the estimated coefficient is smaller in absolute value and its significance level changes from 0.001 to 0.1 compared with Model 1. These differences suggest that unobserved firm characteristics are correlated with observed CEO pay practices, and estimated coefficients in a pooled regression may simply reflect a purely cross-sectional correlation between CEO pay and firm performance. However, even after removing any cross-sectional correlation between CEO pay and ROA, CEO cash compensation remains positively related to ROA.

Table 3

Effects of CEO Compensation on Firm Performance

Explanatory Variables	ROA		Tobin’s Q		Stock Returns
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
	β (SE)	β (SE)	β (SE)	β (SE)	β (SE)	β (SE)
Ln(1 + cash)	0.016**** (0.002)	0.012* (0.006)	0.107**** (0.028)	0.042 (0.065)	0.047*** (0.016)	0.056 (0.052)
Ln(1 + equity)	0.000 (0.001)	0.001 (0.001)	0.020** (0.008)	0.011 (0.011)	−0.008 (0.005)	−0.011 (0.007)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes
Year-fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
Firm-fixed effects	No	Yes	No	Yes	No	Yes
Clustered standard errors	No	Yes	No	Yes	No	Yes
Adjusted R²	0.273	0.512	0.121	0.578	0.109	0.130
N	808	808	805	805	802	802

Note: ROA = return on assets; CEO = chief executive officer.

p < .10. **p < .05. ***p < .01. ****p < .001.

The lack of relationship between equity compensation and market performance is consistent with findings of previous research using pooled ordinary least squares (Upneja & Ozdemir, 2014). One potential explanation for the intriguing results is that the two components of equity compensation may have offsetting effects on firm performance. While options’ convex payoffs can encourage managers to engage in riskier investments because they share all the gains with shareholders but not all the losses (Jensen & Meckling, 1976), restricted stocks’ linear payoffs can induce risk-averse managers to avoid risky investment projects in order to protect their wealth from potential loss (Bryan, Hwang, & Lilien, 2000). To better understand the nature of the relationship between equity compensation and Tobin’s Q/stock returns, we conduct additional analyses to disentangle the effects of option grants and restricted stocks. We repeat Models 3-6 of Table 3 by replacing the single equity compensation measure with two separate measures of options and restricted stocks, both in log form, and lagged by 1 year. The results indicate that both options and restricted stocks have a negative effect on Tobin’s Q/stock returns. Only the effect of restricted stocks on stock returns is significant at 10%. Therefore, the lack of relationship between equity compensation and market performance is not due to the potential opposite effects of options and restricted stocks on firm performance. We believe that this is an interesting finding that merits future research.

CEO Attributes and Firm Performance

According to upper echelons theory, executive attributes affect strategic actions and decision making, which in turn affect firm performance (Hambrick, 2007). Past research has shown that age is an important variable because executives accrue maturity and human capital (Guillet et al., 2012); when the CEO is female, the firm has lower risk levels than when the CEO is male (Khan, Walayet, & João Paulo, 2013); and as CEOs grow in their tenure, their firm-specific knowledge and their ability to monitor and provide important resources increase, which may have a positive impact on the firm’s financial performance (Baysinger & Hoskisson, 1990). Interestingly, prior CEO experience seems to have a negative effect on firm performance (Hamori & Koyuncu, 2015), and although CEO formal education is said to reflect CEO’s cognitive ability to acquire and process complex information and to facilitate decision making (Wally & Baum, 1994), its impact on firm performance is mixed (Jalbert, Furumo, & Jalbert, 2011). Finally, Elsaid (2014) finds that changes in CEO functional background negatively affect firm performance when a female CEO is succeeded by a male.

We retrieve CEO age, gender, and tenure data from Execucomp and hand collect CEO experience, educational background, and functional background data from Marquis’ Who’s Who and Bloomberg Executive Profiles for the period of 1992-2016. Table 1 presents the variable descriptions.

Table 4 reports the joint effects of CEO attributes and compensation on firm performance by adding CEO attributes to the models in Table 3. Models 7, 9, and 11 are baseline specifications without firm-fixed effects and clustered standard errors. Cash compensation is positively related to firm performance in Models 7, 9, and 11 and unrelated to firm performance in Models 8, 10, and 12 when firm-fixed effects and clustered standard errors are employed. Equity compensation is unrelated to firm performance in any specification in Table 4. The results indicate that accounting for CEO attributes, CEO compensation is unrelated to firm performance, thus supporting prior research findings of a not-so-strong compensation-performance link in the hospitality industry.

Table 4

Joint Effects of CEO Compensation and Attributes on Firm Performance

Explanatory variables	ROA		Tobin’s Q		Stock Return
	Model 7	Model 8	Model 9	Model 10	Model 11	Model 12
	β (SE)	β (SE)	β (SE)	β (SE)	β (SE)	β (SE)
Ln(1 + Cash)	0.014**** (0.003)	0.009 (0.006)	0.139**** (0.034)	0.017 (0.077)	0.035* (0.020)	0.039 (0.052)
Ln(1 + Equity)	0.000 (0.001)	0.001 (0.001)	0.016 (0.011)	0.014 (0.010)	−0.006 (0.006)	−0.007 (0.011)
Age	0.001*** (0.000)	0.001 (0.001)	0.008 (0.006)	0.003 (0.008)	0.005* (0.003)	−0.004 (0.006)
Gender	0.003 (0.026)	0.017 (0.030)	0.437 (0.319)	−0.145 (0.211)	−0.037 (0.183)	0.374 (0.243)
Tenure	−0.000 (0.000)	−0.001 (0.002)	−0.011** (0.006)	0.007 (0.014)	−0.002 (0.003)	0.001 (0.007)
Experience2	−0.020** (0.009)	−0.045** (0.017)	−0.064 (0.105)	−0.125 (0.110)	−0.063 (0.060)	−0.226** (0.104)
Experience3	−0.013 (0.014)	0.036** (0.017)	0.021 (0.172)	0.669* (0.347)	−0.083 (0.098)	−0.501*** (0.157)
Experience4	−0.053** (0.023)	−0.038 (0.033)	−0.490* (0.276)	0.002 (0.210)	0.21 (0.158)	0.07 (0.141)
Education2	−0.008 (0.008)	−0.021* (0.012)	−0.165* (0.092)	−0.115 (0.117)	0.014 (0.053)	−0.002 (0.055)
Education3	−0.012 (0.010)	0.016 (0.018)	0.059 (0.118)	0.336 (0.203)	−0.01 (0.068)	−0.178 (0.150)
Education4	0.012 (0.015)	−0.006 (0.019)	0.013 (0.181)	0.183 (0.209)	0.015 (0.104)	−0.122 (0.122)
Function2	0.024** (0.011)	0.037 (0.036)	0.097 (0.133)	0.110 (0.177)	0.036 (0.076)	0.383* (0.203)
Function3	0.008 (0.007)	0.009 (0.012)	−0.176** (0.087)	0.032 (0.104)	0.043 (0.050)	0.104 (0.089)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes
Year-fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
Firm-fixed effects	No	Yes	No	Yes	No	Yes
Clustered standard errors	No	Yes	No	Yes	No	Yes
Adjusted R²	0.243	0.551	0.122	0.667	0.098	0.109
N	539	539	539	539	536	536

Note: ROA = return on assets; CEO = chief executive officer.

p < .10. **p < .05. ***p < .01. ****p < .001.

CEO attributes of age, tenure, experience, education, and functional background are related to firm performance in Models 7, 9, and 11. Controlling for unobserved firm characteristics and serial correlation, experience, education, and functional background remain significant in Models 8, 10, or 12. When the effects of CEO attributes and compensation are compared, interestingly, the results seem to indicate that CEO attributes have a higher explanatory power for hospitality firm performance than CEO compensation does.

Discussion and Conclusion

Taken together, the results in Tables 3 and 4 indicate that unobservable firm-specific characteristics affect the compensation-performance relationship in the hospitality industry. Therefore, coefficients estimated using panel data are more reliable than those estimated using cross-sectional or pooled data. When CEO compensation is examined alone, cash compensation is positively related to ROA and equity compensation is unrelated to firm performance, and this latter effect is not due to the potential offsetting effects of options and restricted stocks. When CEO compensation and CEO attributes are jointly examined, CEO compensation has a relatively lower impact on firm performance than CEO attributes do.

In our sample, equity compensation is insignificantly and inversely related to stock returns, which seems counterintuitive when the value of equity compensation should be tied to stock price appreciation, as predicted by agency theory. One possible explanation is that CEOs in our sample receive twice as much equity compensation as cash compensation. When equity compensation constitutes a large percentage of CEO compensation, CEO personal portfolios become less diversified, and CEOs become more risk averse and are more likely to avoid risky and value-enhancing investments. An alternative explanation could be that several large mergers and acquisitions (M&As) occurred in the hospitality industry during the sample period. For example, Starwood Lodging Trust acquired ITT-Sheraton in 1997, American Airlines merged with US Airways in 2013, and Wendy’s International purchased Baja Fresh in 2002. Research shows that, in general, M&As reduce bidders’ firm value but increase acquiring CEOs’ compensation postacquisition, resulting in an inverse relationship between equity compensation and stock returns. Without controlling for M&A events, our results could reflect such a relationship. A third conjecture is that equity pay can align some portion of CEO personal wealth with shareholder returns but does not necessarily motivate managers to increase stock price (Hodak, 2005). CEOs may simply pay more attention to accounting-based performance metrics because they have more control over revenue or sales growth than stock returns, which are subject to exogenous factors beyond their control.

The current study provides great insights to the board compensation committees as well as CEO search committees of hospitality firms. The search committee can refer to the results when creating search criteria for CEO positions that match the skills, knowledge, and experience of the CEO to the need of the firm, whether it is to increase ROA, stock returns, or Tobin’s Q. The findings also suggest that the current pay structure of CEO compensation in hospitality firms is ineffective in ensuring accounting profitability, stock returns, and future growth outlook. The board compensation committees may want to reconsider its compensation practices in order to better align the interests of managers and shareholders and motivate managers to maximize firm value.

Finally, there are other factors, such as CEO initial salary, CEO performance in prior companies, and firm compensation policies, that may affect the compensation-performance relationship. We urge future research on this important topic to explore the effects of other variables, especially potential mediators and moderators, on the compensation-performance link in the hospitality industry. The current study only examines major components of CEO compensation and their relationship to firm performance, although other components of CEO compensation such as life insurance and supplement executive retirement plans might have different impact on firm performance. Future studies may explore the effect of other compensation components on firm performance. It would also be useful for future research to conduct subsector analyses for each hospitality subsector (i.e., hotels, restaurants, casinos, etc.) in order to gauge if there are nuanced differences between the sectors. Nevertheless, our results show that CEO attributes matter and that the compensation-performance link in the hospitality industry needs to be strengthened.

Footnotes

Yuan Li (e-mail: yuanli@vt.edu), is a graduate student at the Department of Hospitality & Tourism Management, Pamplin College of Business, Virginia Tech, Blacksburg, VA. Manisha Singal, PhD (e-mail: msingal@vt.edu), is an associate professor at the Department of Hospitality & Tourism Management, Pamplin College of Business, Virginia Tech, Blacksburg, VA.

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