CEO Reputation and Firm Value: The Impact of Social Media
Violetta Kräuter
s3047652
MSc BA – Management and Organizational Control
Supervised by dr. Y. Karaibrahimoglu
Table of Content
Abstract ... 2
Introduction ... 3
Theoretical Background ... 5
Agency Theory ... 5
Rent Extraction Hypothesis... 5
Efficient Contracting Hypothesis ... 6
Literature Review and Hypothesis Development ... 6
CEO Reputation ... 6
Social CEOs ... 7
Methodology ... 8
Sample ... 8
Model and Variable Definitions ... 9
Results ... 10
Summary Statistics ... 10
CEO Reputation and Firm Value... 12
Social Media, CEO Reputation and Firm Value ... 13
Robustness Test ... 16
Discussion ... 17
Implications and Limitations ... 18
Conclusion ... 19
References ... 20
Abstract
This research aims to contribute to the ongoing discussion around the rent extraction and efficient contracting effect of CEO reputation. It provides empirical evidence for the effect of CEO reputation on the firm value and investigates the moderating role of social media in this relation. Media coverage is used as a proxy for CEO reputation and social media is assessed in terms of a Twitter account and the number of followers. The results of the regression analyses, using a sample from S&P 500 companies for the period 2005-2014, show a highly significant negative relation between CEO reputation and firm value and a highly significant negative moderating effect of social media. The findings suggest that more reputable CEOs are related with a lower firm value and a weakening impact of social media.
Introduction
Since the turn of the century a new phenomenon has emerged where a CEO is not only the strategic head of a company, but also the face of the company and an ambassador for its values (Fetscherin, 2015b) . Some individuals have even gained celebrity status, for example Elon Musk, Jeff Bezos, Mark Zuckerberg and Steve Jobs, just to mention the most popular representatives (Fetscherin, 2015b). The role of the CEO in the company has changed from solely the strategic decision maker to someone whose field of responsibility is enhanced with operational engagement and active interaction with stakeholders (Gaines-Ross, 2013a). The CEO is perceived as the personification of the organization by the stakeholders and represents the values the firm stands for (Bendisch, Larsen, & Trueman, 2013).
Often the name of the organization and the CEO’s name are used interchangeably. CEOs represent the firm as a whole and their image is inseparably linked to the image of the firm they represent (Aaker, 2004; Bendisch et al., 2013). In some cases, actions outside organizational boundaries influence the company, because the boundaries between the public and private persona of the CEO blur (Fetscherin, 2015b). Considering that a CEO’s reputation accounts for more than 50% and in Germany for even 60% of the public image of a firm, which is directly linked to the company (Gaines-Ross, 2000) and that people can be perceived as brands (Bendisch et al., 2013), it becomes clear that the CEO reputation is of great managerial interest. It poses new challenges on the election of a suitable CEO, just as it amplifies and impedes the job of a CEO additionally.
The problem behind a superior CEO that is utterly present in the public for the whole organization, is that the impact and the scope on the firm are still unclear. In recent literature, there are contradicting opinions about the influence of the CEO reputation on the organization. On the one hand, there is the “rent extraction perspective”. This view implies that CEOs see their own interests as preferential and take action that have a negative impact on the company (Holmstrom, 1982). Prior findings show that reputed CEO overestimate their own abilities (Malmendier & Tate, 2008) and influence the quality of financial reporting to their favour (Francis, Huang, Rajgopal, & Zang, 2008). On the other hand, the “efficient contracting perspective” predicts a positive association between the CEO reputation and the firm’s performance. Jian & Lee (2011) show that reputable CEOs evoke a more favourable response by the stock market about capital investment decisions. Accordingly, Ali & Zhang (2015) find new CEOs to favourably influence the market’s perception of the earnings.
interactive and direct type of communication, but opinions about the necessities and economic effects are mixed (Porter, Anderson, & Nhotsavang, 2015). It has evolved to an influencing factor on the firm performance (Oh & Bunkanwanicha, 2016), where some say it poses new challenges to firms, such as losing control because stakeholders can mobilize movements against firms more easily, while others emphasize the emerging chances created through the direct communication (Lee et al., 2013).
Motivated by the ambiguous results on the effect of CEO reputation on the firm performance and the increasing importance of social media, it is the goal of this research to contribute to the existing CEO reputation literature and enlarge it with an insight into the effect of the CEO reputation on the firm value under the condition that the CEO is active on social media. The purpose is to provide empirical evidence how social media appearances influence the impact the reputation of a CEO has on the firm value. Practical information for organizations can be derived from the results as well. For instance, the outcome of the research can be consulted as a decision-making support for managerial implications when a new CEO post must be occupied, or the activeness on social media can serve as an election criteria for an eligible CEO. In case the CEO is already in charge, due to the findings it can be decided if it is more favourable to generate much media coverage, or to stay in the background and adjust the behaviour accordingly. The results are also interesting for stakeholders of companies who have introduced a new CEO. It helps to anticipate changes in the firm value, form expectations about the new CEO and take actions prior to the replacement to protect their own interests. Further, it enables professionals to better understand the scope of CEO reputation and raises awareness for the importance of social media. The motivation underlying this thesis is to show how financial numbers are not only influenced by the decisions of a CEO, but also by the CEO’s persona and the actions they undertake on social media.
Based on the previously mentioned contradicting results in recent research and the prominent role of CEOs in today’s business world, my aim is to extent the CEO literature, provide practitioners and stakeholders with guidance about the usage of social media by answering the question of whether and how social media influence the relation between CEO reputation and firm value?
extend the CEO literature and provide practitioners with decision-making support and information about the consequences of their social media presence.
Theoretical Background Agency Theory
The Agency Theory, also known as the principal-agent problem, takes places when one person (the agent) enacts on behalf of another person (principal) (Eisenhardt, 1989). When information is distributed asymmetrically, meaning that the agent has more information than the principal, it is not certain for the principal if the agent acts in the interest. This dilemma arises when the two cooperating parties have conflicting goals and/or the principal cannot relate to what the agent is doing. This conflict of interest intensifies when the agent undertakes activities that are costly for the principal. (Eisenhardt, 1989). Putting it into an economic setting, this dilemma often occurs in the relationship between the management and shareholders. The manager is supposed to act in the best interest of the shareholders, but at the same time the own interests are important, too. Applying this to an even more specific setting, where the CEO is the agent, it is assumed that the own interests are preferential and the organization he acts on behalf of is the principal.
Rent Extraction Hypothesis
The rent extraction hypothesis states that the CEO reputation is negatively associated with the firm performance. This is an example for the previously mentioned agency theory where the CEO as the agent puts his own interest above the companies interest, with negative consequences for the firm he acts on behalf of. Francis et al. (2008) prove this by showing that CEO reputation and the earnings quality of a firm are associated negatively. It is assumed that reputed managers are more likely to use their autonomous position to manipulate earnings, so the labour and stock market are influenced to their favour (Francis et al., 2008). Moreover, reputed CEOs take advantage of their position and manipulate the earnings to be portrayed in a favourable light and to maintain their good reputation (Francis et al., 2008).
In addition, Malmendier & Tate (2009) state that CEOs who win an award perform worse compared to their non-winning peers and to their prior performance. After winning the award, they demand higher compensation for their work and dedicate more time to activities that strengthen their own reputation while neglecting their actual job (Malmendier & Tate, 2009). This influences the short-term success in a positive way but affects the performance in the long-term negatively. Further, CEOs with a high reputation may invest in prestigious projects in order to enhance their reputation, although they are risky and have a negative net present value. This is made at the expenses of shareholders (Jian & Lee, 2011).
is in line with the rent extraction hypothesis and the agency theory. The CEO as an agent puts his own interests and the short-term success above the long-term interests of the firm so they are not labelled as low performers or risk their careers (Ali & Zhang, 2015). All this argumentation is representative for an “agency dilemma” where the CEO as an agent is more motivated to act in his own interest than in the interest of the organization.
Efficient Contracting Hypothesis
In contrast, the efficient contracting hypothesis assumes that reputable CEOs have a positive impact on the firm performance and act in the best interest of the company. In other words, it is the countermovement to the rent extraction hypothesis and can be regarded as the solution to the agency dilemma from the agency theory. In this argumentation CEOs are positively associated with a higher earnings quality because they have more to lose with respect to credibility and prospective career chances. Therefore, the CEO as an agent is willing and has the incentives to act accordingly to the market beliefs (Francis et al., 2008). It is assumed that reputable CEOs impact the firm value positively because they attract talented people that improve the organization’s performance (Malmendier & Tate, 2009) and work harder to enhance their good reputation (Olsen, Dworkis, & Young, 2014). Also, CEOs with high reputation are more likely to invest in projects with a positive net present value to underline and enhance their credibility (Jian & Lee, 2011). Moreover, the stock market reacts to announcements of reputed CEOs about investments more favourably and good reputation mitigates negative price reactions. Besides, companies with a more reputable CEO perform better after an investment, than their less reputable counterparts do (Jian & Lee, 2011).
Literature Review and Hypothesis Development CEO Reputation
The CEO reputation is part of the 4P framework that is introduced by Fetscherin (2015a) and constitutes together with the CEO image the CEO brand. The CEO reputation consists of the performance and prestige, whereas the person and personality account for the CEO image. Suggested proxies to measure the performance are the stock price or other profitability measures, whereas the prestige can be transformed into numbers by using the number of awards won or press coverage (Fetscherin, 2015a).
2010; Kaplan, Samuels, & Cohen, 2013). Further, the repuation can even attract new investors or, on the opposite, lead to withdrawal of existing investors (Bailey, 2010; Bendisch et al., 2013).
According to Ranft et al. (2006) the CEO reputation is also a sort of intangible asset. It can be build either by ‘pushing’ it, which means actively creating it by impression management or it is pulled, when it is created by the media, or both. It has an immediate, long lasting and broad impact on the organization on which behalf the CEO acts (Ranft et al., 2006). Moreover, the reputation is linked to the organization beyond a CEO’s tenure, as it is the case with Walt Disney (Ranft et al., 2006). Even after his death his reputation is still associated with the company.
The CEO reputation has an impact on several realms of a firm. It affects the organization internally, as well as the external environment and how the company is perceived by third parties, such as other stakeholders. From the internal perspective, research shows CEO reputation and earnings quality to be related negatively (Francis et al., 2008). This effect of a poorer earnings quality is consistent with the rent extraction hypothesis. Externally, Jian & Lee (2011) yet find evidence that the stock market does not only react more positively to announcements of capital investment from reputable CEO, but the reputation also functions as a mitigation for negative capital investment announcements. In other words, a positive reputation diminishes the effects of negative rating changes and keeps the value of the firm stable and vice versa.
This study takes a closer look at the negative impact of CEOs and investigates the rent extraction hypothesis. I assume the rent extraction hypothesis to dominate the efficient contracting hypothesis in connection with the firm value because of the examples Fetscherin (2015b) lists and the concerns of Ranft et al. (2006). Fetscherin (2015b) lists two examples for reputable CEOs causing negative headlines, which in turn affected their firm negatively and points to the argumentation of Malmendier & Tate (2009) who observe a decreasing performance level of CEOs after being honoured with an award. Ranft et al. (2006) explain that CEO reputation bears opportunities but also comes with significant risks that are believed to predominate. Based on this previous line of reasoning CEO reputation is assumed to have a negative impact on the firm performance and the following hypothesis is developed:
H1: Under the rent extraction hypothesis, firms with a more reputable CEO have a lower firm value.
Social CEOs
The term Social CEOs is used for CEOs that are active on social media such as Twitter, Facebook, LinkedIn etc. and was coined by the communication agency Weber-Shandwick (Gaines-Ross, 2013b).
Simultaneously, it differs from the usual hierarchical communication with stakeholders and transforms it into a more ethical mode of communication (Lee et al., 2013). The uncontrollable aspect means that communication on social media is hard to predict and difficult to manage because the flow of communication takes place towards multiple, interconnected directions that include several actors (Lee et al., 2013). The third attribute, uncoordinated actions are converted into coordinated effects, describes the fact that people can gather without the traditional efforts of coordination (Lee et al., 2013). It enables stakeholders to directly approach the company but also demands from the organizations to use social media as a listening tool (Gaines-Ross, 2013a).
Twitter is an example of social media and one of the most popular platforms where users can share 140-character messages with their subscribers and interact with other users, either in a one-directional manner or a more dialogical form (Austmann, 2015; Lee et al., 2013). The subscription is called following, which can be unidirectional and is done by a simple click. The retweet of messages is the forwarding of others’ messages to the own followers. The potential influence a person has is represented by the number of followers one has (Lee et al., 2013).
The opinion among CEOs about Twitter is ambiguous and represents the presence of CEOs on this platform (Porter et al., 2015). Some embrace the functions of Twitter and focus on the potential benefits, e.g. direct communications with stakeholders, however, others have a more suspicious attitude towards it and underline the potential risks, such as uncontrollability (Lee et al., 2013). In general it can be said that younger and higher-paid CEOs are more likely to have an account (Oh & Bunkanwanicha, 2016).
Researchers (Yu & Cao, 2013) find social media to have a stronger effect on the firm performance on the stock market than conventional media and Twitter to have a positive effect on risk. Simultaneously, Oh & Bunkanwanicha (2016) show that CEOs with a Twitter account and the number of followers have a positive effect on the market return of a company’s share. In addition, evidence is found that social media can be used as a predictive indicator for firm equity value (Luo, Zhang, & Duan, 2013). Thus, being popular on social media might be advantageous for a company as well as for stakeholders, but further examination is necessary because of the limited amount of research in this field. In this study, social media is assumed to have a strengthening impact, in line with the existing literature, and the second hypothesis is developed to examine the moderating effect of social media:
H2: Social media strengthens the impact of the CEO reputation on the firm value.
Methodology Sample
CEO-years observations are excluded from firms with ambiguity regarding CEO information. Financial data is obtained from Compustat. Additionally, in the period from the 21st September 2016 until 31st October 2016 data for the CEO reputation and the followers on Twitter was hand collected. 279 observations are eliminated due to missing firm-specific variables. The final sample consists of 3,537 firm-year observations from 689 CEOs and 384 firms over the 2005-2014 period.
Model and Variable Definitions
To assess the relationship between CEO reputation and firm value and to test the first hypothesis the following equation is developed:
Tobin_Q = α + β1 CEO reputation + ∑βi Firm controls + ∑βi CEO controls + ∑βi Industry dummies + ∑βi
Year dummies + ε
Where the dependent variable is the firm value, measured by Tobin’s Q following Basu, Paeglis, & Rahnamaei (2016), Choy, Lai, & Ng (2017) and Cline & Yore (2016). Tobin’s Q is calculated by using the total market value plus the total liabilities of the firm and divided by the book value of the shares plus the liabilities (Tobin, 1969). The premise of this financial figure is that the firm value should be equal to 1, then the market value represents the book value of the firm precisely. When the quotient is higher than 1, the firm is overvalued on the stock market. Correspondingly, a Tobin’s Q value lower than 1 indicates that the firm is undervalued and the assets are more worth than the firm itself.
The independent variable “CEO reputation” is assessed by the media coverage in terms of number of hits on LexisNexis and is similar to the approach Francis et al. (2008), Jian & Lee (2011) and Milbourn (2003) use. Since reputation is perceived individually, it must be put into quantitative measures. For this research I intentionally decided to handle “CEO reputation” as a one-dimensional variable, aiming to investigate a characteristic that can be actively influenced by the CEO (Eccles, Newquist, & Schatz, 2007; Hamilton & Zeckhauser, 2004). This is in contrast to the method of Francis et al. (2008), Jian & Lee (2011) and Milbourn (2003), who use a proxy consisting of combined figures to measure reputation. Media coverage is evaluated by counting the number of hits a CEO evokes in all newspapers that are available to LexisNexis for the ten years from 2005 until 2014. LexisNexis is a service provider for business research and offers access to legal and journalistic documents (Poynder, 1997). For each year data was collected on how many articles mention the full name of a CEO. The number of articles was assessed, irrespective of how many times the name appears in the article.
assets. All numbers are gathered from the ExecuComp database.
The CEO control variables “Age”, “Duality”, “Gender”, and “Tenure” are included to control for effects associated with the CEO other than reputation to impact Tobin’s Q: The control variable “Age” is introduced because old CEOs, who will soon retire, may care less about the firm value and long term perspectives of the organization (Jian & Lee, 2011). Next, “Duality” is included because Peni (2014) shows that duality has a positive impact on the firm performance. As research states, the gender of a CEO has an impact on investment decision and risk-taking choices (Faccio, Marchica, & Mura, 2016), therefore the binary variable “Gender” is introduced. Ali & Zhang (2015) note that CEOs in their early years of tenure tend to overstate earnings which effects the RoA, to address this concern the control variable “Tenure” is included. Finally, industry dummies, based on the SIC code and year dummies are included to prevent covariations with time and industry affiliation.
To test the second hypothesis the moderator variable “Social Media” is added to the model:
Tobin_Q = α + β1 CEO reputation + β2 Social media + β3 CEO reputation * Social Media + ∑βi Firm
controls + ∑βi CEO controls + ∑βi Industry dummies + ∑βi Year dummies + ε
Social media is determined by the presence on Twitter and information was hand collected. For each CEO a search was conducted if a Twitter account is available. For CEOs who hold an account, further information about the number of followers was gathered. The variable β3 addresses the moderating effect of social media on the relation between CEO reputation and firm value by multiplying the CEO reputation with the social media variable.
First, an overview of all variables is given to provide a better understanding for the sample. Second, a regression analysis is conducted to examine the effect of CEO reputation on the firm value. Next, the moderator variable is introduced to the model and regression analysis is run to investigate the effect of social media. This process is conducted with a binary moderator variable, indicating the presence on social media and repeated with a numeric variable that stands for the number of followers. Afterwards, several robustness tests are performed to control for selection bias and alternative dependent variables are tested.
Results Summary Statistics
In table 2 the Pearson correlations for all variables are presented. At large, the pairwise correlations are small, except for the correlation between RoA and Tobin’s Q.
Table 2 - Pearson correlation
C EO re put at ion T obi n’ s Q Soc ial M edi a Fir m Si ze L ev er age
RoA Age Dual
ity G end er T en ure CEO reputation 1.0000 Tobin’s Q 0.092 1.0000 Social Media 0.187 0.063 1.0000 Firm Size 0.151 -0.304 0.092 1.0000 Leverage -0.063 -0.486 -0.023 0.212 1.0000 RoA 0.044 0.298 0.005 -0.149 -0.274 1.0000 Age 0.072 -0.138 -0.107 0.140 0.090 -0.012 1.0000 Duality 0.013 -0.077 -0.082 0.151 0.113 0.012 0.278 1.0000 Gender -0.007 -0.041 -0.052 -0.111 -0.098 -0.006 0.044 0.014 1.0000 Tenure 0.128 0.097 0.038 -0.173 -0.110 0.035 0.280 0.184 0.112 1.0000
RoA return on assets
CEO Reputation and Firm Value
After conducting Hausman test, the p-value of chi2 is significant with a value of 0.00, I continue with panel regression with fixed effects model. The fixed effects model approach is favoured over the Ordinary Least Square (OLS) regression to respond better to the panel structure of the data and avoid mistakes based on inconsistency end exogenous factors (Wooldridge, 2013).
Table 3 shows the results of the panel regression analysis with CEO reputation and control variables as predictors of the firm value. The model for the first hypothesis shows a negative highly significant relation between CEO reputation and the dependent variable Tobin’s Q with a two-tail p-value of 0.007 and a coefficient of -0.002. The F-value of 31.76 and the small associated p-value assure that the model predicts the dependent variable reliably and explains 24.8% of the variation.
into account, it can be concluded that the results prove the assumption from the first hypothesis and show that CEO reputation has a highly significant negative impact on the firm value. Consequently, the findings are consistent with the rent extraction hypothesis and support the first hypothesis.
Table 3 - regression results on firm value of CEO reputation and control variables
M ode l 1 p-val ue CEO reputation -0.002 0.007 Firm Size -2.226 0.000 Leverage -11.990 0.000 RoA 2.354 0.018 Age 0.041 0.029 Duality 0.255 0.217 Gender -1.112 0.062 Tenure -0.029 0.225
Year dummies Yes
Industry dummies Yes
R2 0.248
F 31.76
Prob>F 0.000
n 3,537
RoA return on assets; n number of observations
Social Media, CEO Reputation and Firm Value
significant. For the CEO reputation, the categorization into social CEOs shows similar tendencies. CEOs who hold a Twitter account receive more mentions by the media, on average 251.93 in comparison to 58.20 mentions for CEOs without an account. This difference is also highly significant as the p-value of 0.00 indicates.
Table 4 - T-test for the moderating effect
Social Media No Social Media
M ean S.D . M ean S.D . p-val ue Tobin’s Q 5.762 10.577 4.562 5.316 0.0002 CEO reputation 251.925 674.539 58.203 250.388 0.000 Firm Size 9.661 1.347 9.323 1.175 0.000 Leverage 0.570 0.196 0.584 0.214 0.180 RoA 0.070 0.065 0.069 0.084 0.779 Age 54.162 7.742 56.208 5.936 0.000 Duality 0.515 0.501 0.637 0.481 0.000 Gender 0.946 0.227 0.973 0.161 0.002 Tenure 10.057 7.939 9.286 6.323 0.023 n 425 3,112
S.D. standard deviation; RoA return on assets; n number of observations
Table 5 - regression results on firm value with moderating effect of social media
When regressing the binary moderator variable on Tobin’s Q the results show a negative highly significant impact of the moderating variable on the dependent variable. This implies a weakening effect of the moderator and stands in contrast to the second hypothesis which assumes a strengthening effect.
As already mentioned, the process is repeated except that the moderating variable is assessed by the number of followers on Twitter. The results with the numeric moderator resemble the results with the binary moderator in means of direction and significance. The effect of the moderator in terms of followers on the dependent variable is highly significant and negative, indicating a weakening effect. In other terms, in a
Soc ial M edi a = T w itt er p-val ue Soc ial M edi a = Foll ow ers p-val ue CEOrep*SocMedia -0.005 0.000 -4.06e-08 0.000 CEO reputation -0.0003 0.713 0.007 0.017
Social Media 0.315 0.429 9.00e-05 0.000
Firm Size -2.124 0.000 -5.764 0.000 Leverage -11.931 0.000 -15.552 0.000 RoA 2.357 0.017 -1.542 0.824 Age 0.040 0.034 -2.061 0.001 Duality 0.242 0.241 1.547 0.283 Gender -1.485 0.014 6.861 0.182 Tenure -0.026 0.282 1.221 0.043
Year dummies Yes Yes
Industry dummies Yes Yes
R2
0.213 0.118
F 29.76 7.57
Prob>F 0.000 0.000
n 3,537 425
selected sample only consisting of CEOs who are represent on Twitter, the number of followers is weakening the relation between CEO reputation and firm value and is contrary to the second hypothesis. According to these findings, the interaction of CEO reputation and social media is highly significant and negative in both cases, implying a weakening impact of social media on the relation between social media and firm value. This contrasts with the second hypothesis, stating that social media strengthens the impact and leads to the rejection of the second hypothesis.
The two moderating effects of social media are presented in figure 1 as graphs for a better visualization. In the first diagram, the orange line stands for the presence on Twitter and the blue line for the absence on Twitter. The orange line has a higher initial point and is steeper than the blue line, implying that with increasing reputation the effect of social media is decreasing and the variance of Tobin’s Q is bigger when the CEO is on social media. The second diagram shows the moderating effect of the number of followers where the two graphs are nearly identical. In this smaller sample, more reputable CEOs are associated with a higher firm value and the number of followers, either high or low, only slightly changes the effect. In summary, the presence on social media is clearly making a difference, whereas the effect of the number of followers seems to be small.
Figure 1 - the moderating role of social media
Robustness Test
In order to ensure the robustness of the results and address potential concerns, further regression analyses and sensitivity analyses are conducted, where alternative measures for the dependent variable are used. An overview of the results is presented in table 6 and 7, attached in the appendix.
First, an additional fixed effect regression analysis is run with a time lag of one year is. Although social media most probably has an immediate effect (Asur & Huberman, 2010), there has not been set a clear timeframe by academic literature, for this reason a regression with a time lag is run. The introduction of a time lag does not change the negative relation between CEO reputation and firm value, however, the result becomes insignificant (table 6), meaning that there is no significant relation between the CEO reputation
0 0.5 1 1.5 2 2.53 3.54 4.55 Low CEO reputation High CEO reputation T ob in 's Q
The effect of "Twitter"
No Social Media Social Media 0.492 0.494 0.496 0.498 0.5 0.502 0.504 0.506 0.508 Low CEO
reputation High CEOreputation
T
ob
in
's
Q
The effect of "Followers"
and the firm value of the next year.
Second, Heckman’s selection model is run to correct for sample selection bias. The Inverse Mills ratio is generated with Probit regression, then inserted in the original model and treated like a control variable within the regression analysis. A summary of the output can be seen in table 6. The Inverse Mills ratio is significant with a two-sided p-value of 0.012 and stands for a selection bias, showing that companies with a high firm value select more reputable CEOs. However, the CEO reputation stays significant and is not affected by the inclusion of the Inverse Mills ratio.
Finally, alternative measures such as earnings per share (EPS) and the market-to-book ratio as dependent variables are tested. When Tobin’s Q is replaced by the earnings per share the results from table 3 are emphasized: CEO reputation has a highly significant and negative impact on EPS, indicating that more reputable CEOs are associated with less EPS. For a closer investigation, the moderating impact of social media is also tested on the relation between CEO reputation and EPS. Nonetheless, the results of the moderator regression differ to the ones from the main study: the binary version of the moderator has a positive and highly significant impact and the moderator “Followers” shows insignificant results in this scenario. This is opposing to the results of table 3, where the moderator has a negative impact. When the market-to-book ratio is introduced as a dependent variable, no significant results for the relation between CEO reputation and the market-to-book value can be observed.
Discussion
In this study the impact of CEO reputation on the firm value and the moderating role of social media is examined. The results provide empirical evidence for a negative relation between CEO reputation and Tobin’s Q, which is in line with the rent extraction hypothesis and therefore support the first hypothesis. The results are obtained with the help of panel regression analyses with fixed effects.
Also, empirical evidence can be found for a significant effect of social media on the relation between CEO reputation and firm value. The impact of the moderator is tested with two different proxies: initially, a variable that is indicative for the presence on social media of a CEO is used, thereafter the variable social media takes the value of the number of followers a CEO has on Twitter. Contrary to the strengthening expectation of this study, the impact of the moderator is weakening the effect of CEO reputation and firm value. Hence, the second hypothesis is rejected. These findings are opposing to the positive effect of Twitter found by Oh & Bunkanwanicha (2016), but it has to be emphasized that their study is concerned with the market return, whereas this thesis engages the firm value.
of the efficient contracting hypothesis (Jian & Lee, 2011) the findings of this study support the rent extraction hypothesis, stating that CEO reputation is negatively associated with the firm performance and join the path of Ali & Zhang (2015), Francis et al., (2008) and Malmendier & Tate (2009). The results consent to the interpretation of the agency theory, stating that the CEOs as agents are more concerned with their own reputation so that work related duties are neglected and shift to the background.
Implications and Limitations
From the results practical implications can be derived for CEOs, firms and stakeholders. The negative effect of CEO reputation on the firm value can serve as an impulse for CEOs to overthink the communication with the press, and take care of actions that affect the reputation and media coverage. Also, the results are a motivation for CEOs to create a Twitter account and to use it actively, but accurately. Recalling that CEO reputation is measured in terms of press coverage and social media is weakening the impact of CEO reputation on the firm value, it might represent an incentive for some CEOs to become active on social media and use this platform to communicate with stakeholders directly. The strategy to use it as an explanatory tool can be especially useful in times when companies suffer from negative media coverage. It can assist to mitigate unfavourable press coverage by explaining misleading information and starting a dialog with stakeholders via this medium. The results should also be of interest to stakeholders, because a new side of social media is shown. It is not only a medium to communicate, but a powerful tool to anticipate possible changes in the firm value. For example, stakeholders can take actions prior to the appointment of a new CEO to save their interest that are affected by changes in the firm value. All these insights contribute to a better understanding of the scope of social media and point out the many ways in which social media can be used and benefited from.
The theoretical aim of this research is to provide greater clarity regarding the discussion around the rent extraction and efficient contracting hypotheses with the help of empirical evidence. The significant results support the efficient contracting hypothesis and deliver additional arguments to the ambiguous discussion around the two contradicting points of view. Moreover, theoretical implications can be derived from the enlarged insight on the effect of social media, but further research is suggested and other researches are urged to investigate some issues that have come across while conducting this research.
Second, it is recommended to assess the time frame of the effect of social media more closely. Academic literature in this field is scarce and especially results that are generalizable throughout industries are required. The results of this research are based on the assumption of an immediate effect, but it is necessary to set the effect of social media in a timeframe.
Also, the generalizability of the results on other cultures and countries is limited. As the sample only consists of firms from the United States, and the motivation for the usage of social media differs among cultures (Kim, Sohn, & Choi, 2011), it is not safe to say that the results hold for other cultures and countries. Thus, cross-cultural investigation is needed.
Another limitation of this study, is the approach used to measure for reputation. Although the choice of a one-dimensional proxy for CEO reputation is intentional, it should be noted that other researchers use multiple items to estimate reputation, as it is a complex proxy and depends on individual perception. Moreover, the reliability of the results might be questioned, as not all alternative performance measures in the robustness test are significant, in addition the Inverse Mills ratio points out a selection bias. To address the selection bias, it is proposed to investigate the two-way relationship between CEO reputation and firm value. However, it must be mentioned that the independent variable CEO reputation stays significant, despite the inclusion of the Inverse Mills ratio. Concerning the significance of the alternative dependent variables, I emphasize the similar direction of the results throughout all alternative measurements.
Conclusion
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Appendix
Table 6 presents an overview of the additional analyses for the robustness test. The results for the analysis with time lag, with the Inverse Mills ratio as an additional independent variable, with earnings per share as dependent variable and with the market-to-book ratio as dependent variable are illustrated.
Table 7 shows the results of the regression analyses on EPS with social media as a moderator. First, the presence on Twitter is used as a moderator, then the number of followers is employed.
Table 6 - additional regression analyses
T im e L ag p-va lu e Inv ers e M ill s Rat io p-val ue EPS p-val ue M 2B p-val ue CEO reputation -0.0003 0.628 -0.002 0.009 -0.002 0.004 -0.004 0.342 Invmills 6.863 0.012
Control variables Yes Yes Yes Yes
Year dummies Yes Yes Yes Yes
Industry dummies Yes Yes Yes Yes
R2 0.203 0.254 0.300 0.008
F 10.77 30.70 109.55 2.39
Prob>F 0.000 0.000 0.000 0.0003
n 3,536 3,537 3,537 3,537
Table 7 - regression results on EPS with moderating effect of social media Soc ial M edi a = T w itt er p-val ue Soc ial M edi a = Foll ow ers p-val ue CEOrep*SocMedia 0.004 0.022 3.07e-09 0.089 CEO reputation -0.003 0.001 -0.00006 0.959
Social Media 0.458 0.373 5.87e-06 0.281
Control variables Yes Yes
Year dummies Yes Yes
Industry dummies Yes Yes
R2
0.290 0.119
F 100.900 8.630
Prob>F 0.000 0.000
n 3,537 425
