Corporate culture and CEO turnover

Journal of Corporate Finance 28 (2014) 66–82

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Corporate culture and CEO turnover Franco Fiordelisi a,b,⁎, Ornella Ricci a a b

University of Rome III, Italy SDA Bocconi, Italy

a r t i c l e

i n f o

Article history: Received 16 September 2013 Received in revised form 13 November 2013 Accepted 18 November 2013 Available online 23 November 2013 JEL classification: G14 G21 G34 M14 Keywords: Corporate culture Text analysis Corporate governance CEO

a b s t r a c t We study the effect of corporate culture on the relationship between firm performance and CEO turnover. Utilising a measure of cultural dimension developed in organisation behaviour research, we quantify corporate culture by assessing official documents using a text analysis approach. We employ this quantification to examine the impact of culture on CEO turnover, especially in the case of poor firm-specific performance. First, we find strong evidence of a negative relationship between firm-specific performance and CEO turnover. Second, we demonstrate that the probability of a CEO change, on average, is positively influenced by the competition- and creation-oriented cultures. The negative relationship between firm-specific performance and CEO turnover is reinforced by the control-oriented culture and reduced by the creation-oriented culture. Finally, we study the CEO insider or outsider succession and observe that the creation-oriented culture has a negative relationship with the probability of hiring an outsider. Moreover, the creation-oriented culture weakens the negative relationship existing between the firm-specific performance under the incumbent CEO and the probability of hiring an outsider. © 2013 Elsevier B.V. All rights reserved.

1. Introduction The threat of CEO change after poor performance is one of the main corporate governance instruments. It is widely believed that corporate culture plays an important moderating role in linking CEO turnover and past performance. Surprisingly, we are unaware of any large-sample empirical evidence indicating whether and how corporate culture influences the link between firm performance and the probability of CEO change. This lack of research is perhaps due to the somewhat nebulous nature of the notion of culture, which raises several measurement issues in empirical research (Guiso et al., 2006). Nonetheless, recent research has begun to explore the empirical link between culture and various economic phenomena using novel approaches to measuring culture (Bernhardt et al., 2006; Fang, 2001; Guiso et al., 2006, 2009; Luttmer and Singhal, 2011). However, this research has not addressed CEO turnover. What role does corporate culture play in the decision to fire a CEO after poor performance? Is there a specific firm culture that increases (decreases) the probability of changing CEOs after poor performance? These questions are critical for assessing the credibility of the CEO change threat as a corporate governance instrument. The purpose of this paper is to empirically address these questions by focusing on a large sample of US listed companies between 1994 and 2011. Our approach involves obtaining a quantitative measurement of corporate culture by assessing corporate financial statements (e.g., 10-K reports). Text analysis has recently been used in various finance papers (e.g., Antweiler and Murray, 2004; Li, 2008; Loughran and McDonald, 2011; Tetlock, 2007; Tetlock et al., 2008). This method allows us to link the probability of a CEO change to the extent of various corporate culture orientations.

⁎ Corresponding author at: Via S. D'Amico 77, 00145 Rome, Italy. Tel.: +39 06 57335672; fax: +39 06 57335797. E-mail address: franco.fi[email protected] (F. Fiordelisi). 0929-1199/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jcorpfin.2013.11.009

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Consistently with previous papers (e.g., Coughlan and Schmidt, 1985; Warner et al., 1988), we find a strong negative relationship between firm-specific performance and the probability of changing CEOs, indicating that the threat of turnover after poor performance is credible. Our main result is that corporate culture influences the probability of a CEO change and moderates the negative relationship with performance. Specifically, the probability of CEO change, on average, increases in the case of a corporate culture oriented toward competition (i.e., focusing on emphasising organisational effectiveness and fast response) or creation (i.e., focusing on generating future opportunities through innovation). Furthermore, the negative relationship with firm-specific performance is reinforced by a culture oriented toward control (i.e., focusing on internal improvements in efficiency through the implementation of better processes) and reduced by a culture oriented toward creation. Finally, when we disentangle CEO turnover into insider and outsider successions, we find that the creation-oriented culture plays an important role. First, it negatively impacts the probability of hiring an outsider. Second, it also weakens the negative relationship between the firm-specific performance under the incumbent CEO and the probability of hiring an outsider. The rest of this paper is organised as follows. Section 2 provides a literature review, and Section 3 presents our definitions of corporate culture and formulates our research hypotheses. The investigated sample and the variables used in our empirical design are described in Section 4. Section 5 discusses the empirical results and robustness checks for CEO turnover. Section 6 focuses on the type of CEO succession (insider vs. outsider), while Section 7 presents our conclusions. 2. Related literature To be considered a valuable corporate governance instrument, CEO change must be credible in the sense that the CEO turnover is negatively related to firm performance. Early papers (Coughlan and Schmidt, 1985; Warner et al., 1988) find a negative relationship between firm performance and CEO change. The relationship between performance and CEO change is not simple and direct. Since the 1990s, various authors (e.g., Zajac, 1990) have noted that neither the strategic management nor the financial economic literature offers a unified theoretical or empirical framework for topics related to CEO succession. Furthermore, these studies have relied exclusively on archival data, with no attempt to collect or analyse primary data provided by the CEOs themselves. Consequently, the results are not always consistent, and past performance often explains only a very low portion of the turnover phenomenon (Pitcher et al., 2000). More recent papers (e.g., Wiersema and Zhang, 2011) recognise that research has advanced our knowledge of the firm performance — CEO turnover linkage, but the relationship continues to appear complex and somewhat ambiguous amid the existence of several variables that may play a moderating role (e.g., CEOs' influence on boards through direct ownership, as outlined in Easterwood et al., 2012; CEO's outside employment options, as outlined in Liu, 2014). Although there appears to be convergent evidence that CEO change is credible, there are no studies assessing the reason for this link, and more research is needed to identify the roots of this relationship (Jenter and Kanaan, forthcoming). The main contribution of our paper is that it is the first to provide empirical evidence (based on a large sample) that the relationship between performance and CEO turnover is strongly influenced by corporate culture. Although this finding is certainly logical and intuitive, there have been no studies documenting whether and how corporate culture influences the relationship between firm performance and the decision to fire the CEO. We build a unique dataset of all US listed companies between 1994 and 2011 and obtain a quantitative measurement (at the company level) of corporate culture by assessing financial statements. Our approach is based on text analysis (recently used in such finance papers as Antweiler and Murray, 2004; Li, 2008; Loughran and McDonald, 2011; Tetlock, 2007; Tetlock et al., 2008), which provides an objective assessment of corporate culture. As suggested by Jenter and Kanaan (forthcoming), we assess the credibility of (the threat of) CEO change by measuring the sensitivity of CEO turnover to firm-specific performance. Jenter and Kanaan's (forthcoming) approach enables us to decompose firm performance into a systematic component (caused by peer group performance) and a firm-specific component that should reflect CEO ability.1 This approach fits our research needs very well because it allows us to obtain a proxy of the (unobservable) CEO's ability and then investigate the role of corporate culture in the evaluation of his/her performance with the relative consequences in terms of turnover. 3. Theory and hypotheses Culture is a broad concept and represents the implicit and explicit contracts that govern behaviour within an organisation (Bénabou and Tirole, 2002, 2011; Tabellini, 2008). Corporate culture is traditionally considered to have an important influence on an organisation's effectiveness (Deal and Kennedy, 1982; Peters and Waterman, 1982; Schein, 1992; Wilkins and Ouchi, 1983), and in a recent review of the literature, Sackmann (2010) suggests that some culture orientations have a positive effect on performance measures. A first necessary step for our analysis is to define culture in a sufficiently narrow way within this framework so that it is possible to identify its influence on the relationship between CEO turnover and company performance change. We adopt the definition proposed by Cameron et al. (2006), who identify the following four types of corporate cultures (termed culture dimensions): control, competition, collaboration, and creation. We choose Cameron et al.'s (2006) framework because it draws on Quinn and Rohrbaugh 1 In the financial and economic literature, it is a common belief that boards filter out exogenous industry and market shocks in assessing CEO performance. However, recent papers (e.g., Eisfeldt and Kuhnen, 2013; Jenter and Kanaan, forthcoming) show that the industry and market performances are also relevant in determining CEO turnover.

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(1983)'s competing values framework (CVF), which is an organisational taxonomy widely used in the literature (Hartnell et al., 2011; Ostroff et al., 2003; Schneider et al., 2013). Fig. 1 summarises the attributes of the corporate culture orientations proposed by Cameron et al. (2006). There are two internally oriented culture types. The first is the collaboration-oriented culture (termed “clan culture type” in the CVF), which focuses on its employees and attempts to develop human competencies and strengthen organisational culture by building consensus. The underlying logic is that human affiliation produces positive affective employee attitudes directed toward the organisation. The goal of this culture is to develop cooperative processes and attain cohesion through consensus and broad employee involvement, e.g., clarifying and reinforcing organisational values, norms, and expectations, developing employees and cross-functional work groups, implementing programmes to enhance employee retention, and fostering teamwork and decentralised decision making. Companies with this culture usually succeed because they hire, develop, and retain their human resource base. The other internally oriented culture is the control-oriented culture (also called “hierarchy culture”), which is supported by an organisational structure driven by control mechanisms, and the corporate aim is creating value through internal improvements in efficiency, the implementation of better processes (e.g., by the extensive use of processes, systems, and

A) The Competing Values Framework Flexibility and discretion C lan Thrust Collaborate Means Cohesion, participation, communication, empowerment Ends Morale, people development, commitment

Adhocracy Thrust Create Means Adaptability, creativity, agility Ends Innovation and cutting-edge output

Internal focus and integration

External focus and differentiation Hierarchy Thrust Control Means Capable processes, consistency, process control, measurement Ends Efficiency, timeliness, smooth functioning

Market Thrust Compete Means Customer focus, productivity, enhancing competitiveness Ends Market share, profitability, goal achievement

Stability and control

Source: Hartnell et al. (2011, p.679), figure 1, which is adapted from figure 3.1 in Cameron et al. (2011)

B) The competing value framework’s four culture types Culture type

Assumptions

Collaborate (Clan)

Human affiliation

Create (Adhocracy)

Change

Beliefs

Values

People behave appropriately when they have trust in, loyalty to, and membership in the organisation People behave appropriately when they understand the importance and impact of the task.

Attachment, affiliation, collaboration, trust, and support Growth, stimulation, variety, autonomy, and attention to detail

Competition (Market)

Achievement

People behave appropriately when they have clear objectives and are rewarded based on their achievements

Control (Hierarchy)

Stability

People behave appropriately when they have clear roles and procedures are formally defined by rules and regulation

Artefacts (behaviours)

Effectiveness criteria

Teamwork, participation, employee involvement, and open communication

Employee satisfaction and commitment

Risk-taking, creativity, and adaptability

Innovation

Communication, competition, competence, and achievement

Gathering customer and competitor information, goal-setting, planning, task focus, competitiveness, and aggressiveness

Increased market share, profit, product quality, and productivity

Communication, routinisation, formalisation, and consistency

Conformity and predictability

Efficiency, timeliness and smooth functioning

Source: adapted from Hartnell et al. (2011, p.679), figure 2

C) Bag of words Culture type

Bag of words

Control (CON)

capab*, collectiv*, commit*, competenc*, conflict*, consens*, control*, coordin*, cultur*, decentr*, employ*, empower*, engag*, expectat*, facilitator*, hir*, interpers*, involv*, life*, long-term*, loyal*, mentor*, monit*, mutual*, norm*, parent*, partic*, procedur*, productiv*, retain*, reten*, skill*, social*,tension*, value* achiev*, acqui*, aggress*, agreem*, attack*, budget*, challeng*, charg*, client*, compet*, customer*, deliver*, direct*, driv*, excellen*, expand*, fast*, goal*, growth*, hard*, invest*, market*, mov*, outsourc*, performanc*, position*, pressur*, profit*, rapid*, reputation, result*, revenue*, satisf*, scan*, succes* signal*, speed*, strong, superior, target*, win* boss*, burocr*, cautio*, cohes*, certain*, chief*, collab*, conservat*, cooperat*, detail*, document*, efficien*, error*, fail*, help*, human*, inform*, logic*, method*, outcom*, partner*, people*, predictab*, relation*, qualit*, regular*, solv*, share*, standard*, team*, teamwork*, train*, uniform*, work group* adapt*, begin*, chang*, creat*, discontin*, dream*, elabor*, entrepre*, envis*, experim*, fantas*, freedom*, futur*, idea*, init*, innovat*, intellec*, learn*, new*, origin*, pioneer*, predict*, radic*, risk*, start*, thought*, trend*, unafra*, ventur*, vision*

Compete (COM) Collaborate (COL) Create (CRE)

Fig. 1. The corporate culture dimensions investigated.

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technology) and quality enhancements (such as statistical process control and other quality control processes). Companies that have this culture usually make extensive use of standardised procedures and emphasise rule reinforcement and uniformity. The other two types of culture are externally oriented. The first is the competition-oriented culture (termed “market culture type” in the CVF). This type of culture focuses on the organisation's external effectiveness by pursuing enhanced competitiveness and emphasising organisational effectiveness, fast response, and customer focus. These companies usually attach the highest priority to customers and shareholders and judge success based on such indicators as market share, revenues, meeting budget targets, and profitability growth. The other culture type is the creation-oriented culture (termed “adhocracy” in the CVF), which focuses on creating future opportunities in the marketplace through innovation in the organisation's products and services. The organisation encourages entrepreneurship, vision, and constant change, e.g., allowing for freedom of thought and action among employees such that rule breaking and reaching beyond barriers are common characteristics of the organisation's culture. These companies usually aim to include innovative product-line extensions, radical new process breakthroughs, and innovations in distribution and logistics that redefine entire industries and to develop new technologies. 3.1. Hypotheses In this section, we develop our research hypotheses by linking the four CVF culture types and the company's decision to change its CEO. The analysis of CEO turnover is based on the general hypothesis that different culture types influence a company's decision to change its CEO, especially in the case of poor performance. In the first step, we test a common result in previous papers (e.g., Coughlan and Schmidt, 1985; Warner et al., 1988) that, as firm performance declines, the probability of changing CEOs increases.2 Hypothesis 1 (H1). As firm-specific performance declines, the probability of changing CEOs increases. In the second step, we develop some new testable hypotheses related to corporate culture. We loosely follow Hartnell et al. (2011), who link CVF culture types and three effectiveness categories3: employee attitudes (e.g., employees' commitment and satisfaction), operational effectiveness (e.g., organisations' innovative processes and products), and financial effectiveness (i.e., organisations' ability to achieve profits, growth, and, in general, measures of success). Hartnell et al. (2011) suggest that the competition-oriented culture exhibits a strong positive association with financial effectiveness: these companies are inclined to integrate external environmental information to construct clear and coherent goals to increase organisational members' attention toward profitable activities (Cameron et al., 2006; Chao et al., 1994). Highly competition-oriented cultures tolerate change and instability and even trumpet these values, such that changing everything – including the CEO – would be perceived as a natural step. Furthermore, Hartnell et al. (2011) suggest that creation- and collaboration-oriented cultures also exhibit a positive link with financial effectiveness, e.g., through a team empowerment mechanism (Chen et al., 2007), but this relationship is weaker than that for the competition-oriented culture. Collaboration and creation cultures' distal association with financial effectiveness may thus operate through group efficacy mediating mechanisms (Jung and Sosik, 2002) as well as other mechanisms, such as human resource management practices (Combs et al., 2006) and group cohesion (Gully et al., 1995). Instead, a control-oriented culture implies deference to superiors for various reasons. One could conjecture that in high-control firms, the board would be reluctant to address problems by replacing the leader. Indeed, high-control firms may have CEOs who pick their own boards. Based on Hartnell et al.'s (2011) assumptions, we expect that companies with a culture type strongly linked to financial effectiveness have a greater orientation to change CEOs. First, we predict that companies with a competition-, creation-, and collaboration-oriented culture have a positive link with CEO turnover. Second, we posit that companies with a competition-oriented culture have a stronger orientation to change CEOs than companies with a creation- and collaboration-oriented culture. Hypothesis 2 (H2). Companies with a competition-, creation-, or collaboration-oriented culture have, on average, a stronger orientation to change CEOs than companies with a control-oriented culture. Hypothesis 3 (H3). Companies with a competition-oriented culture have, on average, a stronger orientation to change CEOs than companies with a creation- or collaboration-oriented culture. We need also to consider the “incremental effect” provided by the four culture types on the probability of CEO change in the case of poor performance. Based on Hartnell et al.'s (2011) assumptions and our previous discussion, we expect that companies with a competition-, creation-, or collaboration-oriented culture have an additional positive incentive to change CEOs (i.e., negative 2 We would like to note that our paper does not aim to assess who makes the decision to fire the CEO (turnover) and/or select the new CEO (succession). We are aware that it is debatable whether this decision is made by boards or shareholders. The theory of friendly boards (Adams and Ferreira, 2007) provides an interesting framework to explain the board-CEO game. In this paper, we follow a factual–objective approach: we observe companies changing CEOs (without formally discussing who is making this decision) and measure organisational culture in an objective way, specifically, by a text analysis of 10-K reports. These reports must be signed by the majority of the board of directors and are usually written by top managers. As such, we are confident in assessing the culture of “the majority of board members” and “top managers”, reasonably assuming that they share the same culture type as the other members of the organisation. As such, we do not suggest that our estimates of organisational culture capture the shareholder culture, especially because we analyse widely held, public US firms (in which shareholders are dispersed and do not play a role in the corporation and are thus relatively external to its culture). Similarly, our paper is not assessing to the extent to which the corporate culture is created by a CEO. We would like to thank the referee for providing very constructive suggestions to clarify this point. 3 We would like to thank the referee for providing very constructive suggestions to refine our research hypotheses.

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performance reinforces the company's “base” orientation to change CEO in the case of poor firm performance). Next, we also posit that companies with a competition-oriented culture have a stronger “incremental” incentive to change CEOs than companies with a creation- or collaboration-oriented culture. Hypothesis 4 (H4). As performance declines, companies with a competition-, creation-, or collaboration-oriented culture have a stronger “incremental” incentive to change CEOs than companies with a control-oriented culture. Hypothesis 5 (H5). As performance declines, companies with a competition-oriented culture have a stronger “incremental” incentive to change CEOs than companies with a creation- or collaboration-oriented culture.

4. Empirical approach This section describes the data used in our analysis, the estimation of corporate culture, and all the variables used to test our hypotheses. 4.1. Data To answer our research questions, we build a unique dataset by collecting information from three different sources to compile a comprehensive and accurate profile of each company. First, we obtained information on top executive officers (specifically, on CEOs) from the Execucomp database. Data were available for the period 1992–2011, resulting in 209,840 year-observations. We excluded all cases of inconsistent or missing data (i.e., if the CEO annual flag was in conflict with the dates when the interested manager joined or left the company or if the information about the identity of the CEO was available only for a specific year but not for the previous one, rendering it impossible to determine whether there was a turnover). Second, we obtained financial data by extracting 247,796 simplified balance sheets from Compustat between 1990 and 2011. As in the previous case, we removed all companies with missing data. Third, we obtained 128,489 company filings by downloading the 10-K reports (available from 1994 to 2011) from the SEC's Edgar database, and for each of these filings, we ran a text analysis to estimate each cultural dimension identified by Cameron et al. (2006) (513,956 texts analysed in all). Our final sample includes all US listed companies between 1994 and 2011 for which it was possible to a) collect information on top managers, b) determine accounting-based performance, c) measure the relevant cultural dimensions, and d) identify all the control variables used to account for the firm's and the incumbent CEO's characteristics (for a detailed definition of these variables, see Section 4.4). Information relative to the same company and drawn from different databases was matched using the GVKEY code. As a result, we have a unique dataset of 18,088 year-observations, combining managerial, accounting, and cultural information. A CEO change occurs in 1838 year-observations, at a frequency of approximately 10%. We distinguished financial from non-financial companies based on the SPINDEX code and industry group definitions: observations for financial and non-financial companies represent approximately 13% and 87% of our sample, respectively.4 Companies without an assigned industry group were excluded from the sample. 4.2. Corporate culture estimation We now describe our corporate culture variables. First, we outline our text analysis approach to estimating Cameron et al.'s (2006) corporate culture dimensions, and then we present our variables to measure culture homogeneity and heterogeneity. To quantitatively measure Cameron et al.'s (2006) four dimensions of corporate culture, we use text analysis. Text analysis is a technique used to examine, in a systematic and objective manner, the characteristics specific to a text (Stone et al., 1966). The idea underlying our approach is based on the assumption that the words and expressions used by the members of an organisation (labelled “vocabulary”) represent the outcome of the culture they develop over time (Levinson, 2003). We posit that the distinctive features of any organisation are mirrored in its written documents. Text analysis methodology (Stone et al., 1966) is instrumental in measuring the semantic content of firms' publicly available official documents (namely, 10-K reports). This technique provides us with measures that are less prone to the subjectivity of our opinion as researchers in interpreting the data. Recently, the text analysis approach has been exploited in various finance and management papers (e.g., Antweiler and Murray, 2004; Hoberg and Hanley, 2010; Hoberg and Phillips, 2010; Li, 2008; Loughran and McDonald, 2011; Tetlock, 2007; Tetlock et al., 2008). To estimate Cameron et al.'s (2006) culture dimensions (i.e., collaboration, competition, control, and creation, as defined in Fig. 1), we identify a large set of synonyms for each of these aspects. Following Carretta et al. (2011), synonyms are selected using a two-step procedure that minimises subjectivity in the selection process. First, we selected the synonyms suggested by the authors (Cameron et al., 2006) to identify each culture dimension. Second, all words selected in the first step were looked up in 4 We considered the following industry groups as financial groups: asset management and custody banks; consumer finance; diversified banks; insurance brokers; investment banking and brokerage; life and health insurance; multi-line insurance; multi-sector holdings; other diversified financial services; property and casualty insurance; real estate development; real estate services; real estate investment trusts; regional banks; reinsurance; specialised finance; thrifts and mortgage finance.

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the Harvard IV-4 Psychosocial Dictionary to identify other synonyms. Loughran and McDonald (2011) have noted that the Harvard IV-4 Psychosocial Dictionary5 is a commonly used source of word classification, in part because its composition is beyond the control of the researcher and the possible impact of researcher subjectivity is significantly diminished. For example, words such as “capabilities, collective, cooperation, etc.” are associated with the word “collaborate,” and a relatively high frequency of their use in corporate documents suggests that the company has a collaboration-oriented culture. Words such as “achievement, performance, excellence, etc.” are associated with the word “compete,” and a relatively high frequency of their use in corporate documents suggests that the company has a competition-oriented culture. Words such as “boss, efficiency, caution, etc.” are considered synonyms for “control,” and a relatively high frequency of their use in corporate documents suggests that the company has a control-oriented culture. Words such as “dream, begin, elaborate, etc.” are associated with the word “create,” and a relatively high frequency of their use in corporate documents suggests that the company has a creation-oriented culture. We estimated the four corporate culture dimensions for each listed US firm between 1994 and 2011 by determining the number of times that our synonyms occur in each annual report, using percentages to measure cultural emphasis. For example, if the estimate for a “competition-oriented” dimension is equal to 5, the synonyms used to capture this culture dimension (reported in Fig. 1) represent 5% of the entire document. One possible difficulty in our approach is that listed companies may tend to write official documents to “cater” to investors' expectations, and, consequently, most official documents might exhibit significant similarity. This phenomenon may prevent us from detecting any cultural differences in the cross-section. Nonetheless, we document in Table 1 that there is significant cross-section heterogeneity among companies along the four corporate culture dimensions proposed by Cameron et al. (2006). 4.3. Measuring CEO turnover and firm performance Starting from the information contained in the Execucomp database, we identify CEO turnover using the CEOT variable, a dummy taking the value of 1 if the company has changed its CEO with respect to the previous year and 0 otherwise. When more than one top manager is in charge of the company in the same financial year, we choose the person who has been the CEO for the longest period (e.g., if there is a change in 2008, but the entrant CEO is only in charge from October to December, i.e., for only 3 months, we consider the 2008 CEO to be the predecessor and register a CEO change in 2009). Second, with reference to the measurement of firm performance, we prefer accounting-based performance measures because, as noted by Jenter and Kanaan (forthcoming), they are short-term profit measures that are better predictors of CEO turnover than stock market returns if the market incorporates future benefits after replacing an underperforming CEO. Specifically, we focus on the return on assets (ROA), obtained by the ratio between the earnings before interest, tax, depreciation, and amortisation (EBITDA) on total assets. We focus on EBITDA, rather than net income, as EBITDA is a good means of comparing companies within and across industries. 4.4. Control variables The relationship between corporate culture and CEO turnover is investigated by taking into account the impact of a wide range of control variables, to consider both the main characteristics of the incumbent CEO and the features of the analysed firm. With reference to the incumbent CEO, we include in our empirical models the following variables: gender (i.e., a dummy variable taking the value of 1 if the CEO is male and 0 otherwise), age (i.e., the CEO's age), tenure (i.e., the number of years for which the CEO has been in charge), equity incentive (i.e., the proportion of the CEO's total compensation represented by equity incentives), compensation committee (i.e., a dummy variable taking the value of 1 if the CEO is listed in the compensation committee and 0 otherwise), executive director (i.e., a dummy variable taking the value of 1 if the CEO serves as an executive director and 0 otherwise), duality (i.e., a dummy variable taking the value of 1 if the CEO is also chairman and 0 otherwise), and the 5% equity holding threshold (i.e., a dummy variable taking the value of 1 if the CEO owns more than 5% of total stocks in the company and 0 otherwise). With reference to the firm's characteristics, we include the following control variables: size (i.e., the industry-adjusted natural log of total assets), capital expenditure (i.e., the industry-adjusted ratio between total capital expenditure and total assets), financial leverage (i.e., the industry-adjusted ratio between total assets and total common equity), firm age (i.e., the number of years the company is active, proxied by the difference between the considered fiscal year and the first date of appearance in the CRSP database). A detailed definition of all the variables included in our empirical investigation is given in Table 2. 5. Results The test of the credibility of the CEO change threat essentially aims to verify whether the poor performance of a company is related to a future change in the CEO. We test this assumption using both a univariate and a multivariate approach. 5 Although Loughran and McDonald (2011) show that the Harvard IV-4 Psychosocial Dictionary misclassifies words that are not likely to be correlated with the variables under consideration (e.g., taxes and liabilities), we use this dictionary because the list of synonyms used to capture Cameron et al.'s (2006) four dimensions of corporate culture are directly correlated with the variables and do not suffer from the problems reported by Loughran and McDonald (2011).

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Table 1 Corporate culture dimensions estimates. Overall

Collaborate (COL)

Compete (COM)

Control (CON)

Create (CRE)

Mean St. Deviation Min Max Mean St. Deviation Min Max Mean St. Deviation Min Max Mean St. Deviation Min Max

1.386 0.440 0 8.60 4.844 1.184 0 25.72 1.410 0.509 0 33.33 1.081 0.387 0 20.00

Industry

Time

Financial

Non-financial

1994

1998

2002

2006

2011

1.620 0.509 0 5.36 4.521 1.103 0 18.04 1.342 0.363 0 5.76 1.262 0.381 0 5.16

1.346 0.413 0 8.60 4.901 1.189 0 25.72 1.422 0.530 0 33.33 1.049 0.379 0 20.00

1.315 0.629 0.43 4.580 4.887 1.989 1.22 19.82 1.460 0.629 0.58 6.500 0.877 0.429 0 3.03

1.264 0.427 0 4.290 4.904 1.045 0 9.57 1.328 0.329 0 3.740 0.932 0.343 0.16 3.71

1.332 0.395 0 3.220 4.914 1.133 0 8.85 1.324 0.926 0 28.570 1.082 0.372 0 7.14

1.504 0.495 0 4.320 5.089 1.700 0 15.80 1.589 0.524 0 5.620 1.266 0.416 0 5.48

1.461 0.349 0.83 4.360 5.076 0.885 3.44 9.76 1.451 0.303 0.77 3.100 1.214 0.267 0.69 2.3

This table reports the descriptive statistics for the four culture dimensions proposed by Cameron et al. (2006) investigated in our study. Data were obtained from the 10-K reports in the SEC's Edgar database.

In the univariate approach, we measure CEO turnover frequencies by past performance quintiles, defined in terms of both ROA and industry-adjusted ROA (IAROA) in the previous year (i.e., at the time t − 1). As shown in Table 3, there is a positive relationship between poor past performance and subsequent CEO turnover. The turnover frequency in the lowest quintile (worst performers) is always greater than in the highest quintile (best performers). However, the Q1–Q5 difference is only statistically significant (5% confidence level) when we consider the industry-adjusted performance (IAROA). This may be a signal that the specific performance linked to the CEO's ability affects turnover more strongly than the peer performance component. When we disentangle successions by the origin of the new CEO, we find a very strong relationship between past poor performance and the choice for an outsider successor (adopting two different definitions: a) someone who has not been among the top managers for at least two years before the nomination or b) someone who did not join the company at least 2 years before the nomination). In this case, the Q1–Q5 difference is highly statistically significant (at the 1% confidence level) for both ROA and IAROA. The results are the same regardless of the chosen definition of outsider successors and are consistent with the idea that when a company uses CEO turnover to remove a bad performer, it will most likely choose someone who is not linked to the previous CEO. In the multivariate approach, we borrow the empirical strategy used by Jenter and Kanaan (forthcoming) to test our hypotheses considering both the firm-specific and peer group components of performance as explanatory variables (see also Bertrand and Mullainathan, 2001; Garvey and Milbourn, 2006; Wolfers, 2002). First, we decompose overall firm performance into a systematic component, caused by peer group performance, and a firm-specific component. The firm-specific component reflects the CEO's skills and other shocks not related to peer performance. As noted by Jenter and Kanaan (forthcoming), because the specific component is partly driven by CEO skills, we interpret this as a proxy for the CEO's ability, which is obviously unobservable in a direct way. To measure performance, we use an accountingbased measure (specifically, the ROA) because short-term profit measures are better predictors for CEO turnover than stock market returns if the market incorporates future benefits for replacing an underperforming CEO. Second, we predict the probability of a CEO turnover using a logit model including the following as regressors: the peer group and firm-specific performance components previously obtained, our estimates of cultural dimensions, their interactions with firm specific-performance, and some control variables to consider the characteristics of the incumbent CEO and the firm. Our approach is specified as follows: P i;t−1 ¼ β0 þ β1 P peergroup;t−1 þ vi;t−1

ð1Þ


 ^i;t−1 þ γ5 COMi;t−1 ^i;t−1 þ γ 3 COLi;t−1 þ γ 4 COLi;t−1  v Pr CEO changei;t ¼ γ 0 þ γ 1 P^ i;t−1 þ γ2 v ^i;t−1 þ γ9 CREi;t−1 þγ 6 COMi;t−1  ^vi;t−1 þ γ7 CONi;t−1 þ γ8 CONi;t−1  v Xn Xm ^i;t−1 þ þγ10 CREi;t−1  v δx þ λ z þ ς i;t j¼1 j j;i;t−1 k¼1 k k;i;t−1

ð2Þ

^ þβ ^ P where P^ i;t−1 ¼ β 0 1 peergroup;t−1 is the estimated exogenous component of firm performance common to the peer group and not attributable to the CEO's actions and ^vi;t−1 is the estimated firm-specific performance component. Following previous studies (e.g., Jenter and Kanaan, forthcoming), we estimate a common peer performance beta for all firms in the regression represented by Eq. (1).

F. Fiordelisi, O. Ricci / Journal of Corporate Finance 28 (2014) 66–82

73

Table 2 Variable descriptions. Variable

Symbol

CEO turnover

CEOT

Definition and calculation method

CEOT is a dummy variable taking the value of 1 if the company has changed its CEO with respect to the previous year and 0 otherwise Outsider_a OUT_A OUT_A is a dummy variable taking the value of 1 if the company has changed its CEO with respect to the previous year with an external successor (i.e., someone who has not been among the top managers for at least two years before the nomination) and 0 otherwise Outsider_b OUT_B OUT_B is a dummy variable taking the value of 1 if the company has changed its CEO with respect to the previous year with an external successor (i.e., someone who did not join the company at least 2 years before the nomination) and 0 otherwise Control-oriented culture CONi, t CONi, t is the control-oriented corporate culture estimate of company i at time t obtained using text analysis Competition-oriented COMi, t COMi, t is the competition-oriented corporate culture estimate of company i at time t obtained using culture text analysis Collaboration-oriented COLi, t COLi, t is the collaboration-oriented corporate culture estimate of company i at time t obtained using culture text analysis Creation-oriented culture CREi, t CREi, t is the creation-oriented corporate culture estimate of company i at time t obtained using text analysis Return on assets ROA ROA is obtained by the ratio between Earnings Before Interest, Tax, Depreciation, and Amortisation (EBITDA) and Total Assets Industry-adjusted ROA IAROA IAROA is the difference between ROA and the average ROA for companies in the same industry group for every financial year (the industry group is identified on the basis of the SPINDEX code) ^i;t−1 ^i;t−1 is the estimated firm-specific performance component. We follow Jenter and Kanaan (forthcoming) ROA firm-specific v v performance component to disentangle the peer group component and the estimated residual component of ROA ROA exogenous component P^ i;t−1 P^ i;t−1 is the estimated exogenous component of firm performance common to the peer group and not attributable to CEO actions. We follow Jenter and Kanaan (forthcoming) to disentangle the peer group component and the estimated residual component of ROA Size SIZE SIZE is the industry-adjusted natural log of Total Assets Capital expenditure CAP_EXP CAP_EXP is the industry-adjusted ratio between Total Capital Expenditure and Total Assets Leverage LEV LEV is the industry-adjusted ratio between Total Assets and Total Common Equity Firm age FIRM_AGE FIRM_AGE is the age of the firm (i.e., the number of years since its first appearance in CRSP) Gender GENDER GENDER is a dummy variable taking the value of 1 if the CEO is male and 0 otherwise Age AGE AGE is the age of the CEO Tenure TENURE TENURE is duration of the CEO's charge Equity incentives EQ_INC EQ_INC is the proportion of the CEO's total compensation represented by equity incentives CEO in the compensation CEO_COMP_CTTE CEO_COMP_COM is a dummy variable taking the value of 1 if the CEO is listed in the compensation committee committee and 0 otherwise Executive director EXECDIR EXECDIR is a dummy variable taking the value of 1 if the CEO serves as an executive director and 0 otherwise Duality DUALITY DUALITY is a dummy variable taking the value of 1 if the CEO is also chairman and 0 otherwise Ownership N 5% SHARE_5% SHARE_5% is a dummy variable taking the value of 1 if the CEO owns more than 5% of total stocks in the company and 0 otherwise Crisis effect CRISIS CRISIS is a dummy variable taking the value of 1 if the ROA of the firm is lower than in the previous year in both t − 1 and t − 2, and 0 otherwise This table defines the variables used in the paper. Data have been obtained by Compustat.

Compared to previous studies (e.g., Jenter and Kanaan, forthcoming), we add our four measures of corporate culture (COL, COM, CON, and CRE) and their interaction with the estimated firm-specific performance component, as we posit that the corporate culture plays a moderating role in the relationship between firm-specific performance and CEO turnover. Regarding the prediction of estimated coefficients, we expect the following. 1) γ1 = 0. We assume that the exogenous performance component will not affect CEO turnover, consistent with the prediction of the strong-form relative performance evaluation hypothesis (see Jenter and Kanaan, forthcoming). 2) γ2 b 0. To be a credible corporate governance instrument, the probability of CEO turnover must be inversely related to firm-specific performance, so we expect to find a negative coefficient. 3) γ3,5,7,9 ≠ 0. Consistent with our research hypotheses, we expect that, on average, companies with a competition-, creation-, or collaboration-oriented culture have a stronger orientation to change CEOs than companies with a control-oriented culture. At the same time, we assume that companies with a competition-oriented culture have a stronger orientation to change CEOs than companies with a creation- or collaboration-oriented culture. As a consequence, the coefficient γ5 should be positive and greater than both γ3 and γ9. At the same time, γ3,5,9 should be greater than γ7. We also expect corporate culture to be a mediator of the relationship between CEO turnover and firm-specific performance: specifically, we posit that companies with different cultures react differently to poor firm-specific performance and thus that the probability of observing a CEO turnover also depends on the interaction of firm-specific performance and corporate culture. Following our research hypotheses, we predict that, as performance declines, companies with competition-, creation-, and collaboration-oriented cultures have a stronger “incremental” incentive to change CEOs than companies with a control-oriented culture. At the same time, companies with a competition-oriented culture have a stronger “incremental” incentive to change CEOs than companies with a creation- or collaboration-oriented culture. We cannot directly consider the coefficients γ4,6,8,10, but we can analyse the value of the correct mean interaction effects. As outlined by Powers (2005), the interpretation of the interaction term coefficients in logit and probit models (in our case, γ4,6,8,10) requires great care. Specifically, in logit and probit models of the type turnover = f(performance, firm type, firm type ∗ performance, controls), Powers (2005) shows that the significance of the

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F. Fiordelisi, O. Ricci / Journal of Corporate Finance 28 (2014) 66–82

Table 3 Univariate analysis. Q1

Q2

Q3

Q4

Q5

Q1 vs. Q5

11.0% 40.8% 39.7%

10.0% 36.2% 36.5%

10.2% 31.6% 31.9%

10.1% 29.4% 31.2%

*** ***

Performance quintiles based on delta industry-adjusted ROA in t + 1 P (CEO turnover in t) 12.4% 11.0% P (CEO turnover in t & Outsider_a) 47.8% 33.8% P (CEO turnover in t & Outsider_b) 48.6% 34.1%

9.4% 33.4% 33.1%

10.6% 35.3% 35.6%

9.9% 30.6% 32.8%

** *** ***

Performance quintiles based on delta ROA in t + 1 P (CEO turnover in t) 11.6% P (CEO turnover in t & Outsider_a) 42.8% P (CEO turnover in t & Outsider_b) 44.8%

This table presents CEO turnover and outsider succession frequencies by performance quintiles in US companies over the period 1994–2011. Performance is measured in terms of ROA and industry-adjusted ROA (i.e., for every financial year, the difference between the single-company ROA and the average ROA for companies in the same industry group, considering the SPINDEX code in the Execucomp database). Companies without an assigned industry group are not considered. The outsider succession is classified based on two different definitions: a) someone who has not been among the top managers for at least two years before the nomination or b) someone who did not join the company at least 2 years before the nomination. ***, **, * indicate statistical significance at the 1%, 5%, and 10% levels, respectively, for the t-test of differences in turnover/outsider succession likelihood between the top and bottom performance quintiles. Data were obtained from Compustat and Execucomp.

interaction term coefficient may be misleading. One possibility is that the true difference in the relationship could be stronger than is indicated by the estimated coefficient, potentially generating Type 1 errors. Alternatively, the true difference in the relationship could be weaker than is indicated by the estimated coefficient, potentially generating Type 2 errors. To overcome this problem, we use the methodology developed by Norton et al. (2004) to compute the correct marginal effects and their standard errors (as in Bushman et al., 2010; Lel and Miller, 2008; Loureiro, 2010). The Norton approach allows us to obtain an unbiased estimation of the mean interaction effect and its level of statistical significance. Consistent with our research hypotheses, we expect that the mean effect for the interaction between competition and firm-specific performance is negative (i.e., with the same sign of the relationship between CEO turnover likelihood and firm-specific performance, so that its effect is reinforced) and greater in absolute value than both the mean effect for the interactions with the creation and the collaboration cultures. At the same time, all these three effects should be greater in absolute value than that relative to the control-oriented culture. In addition, we include a set of firm (xj) and incumbent CEO (zk) control variables. Finally, as suggested by Eisfeldt and Kuhnen (2013), we include both year- and industry-fixed effects. All variables (except those that are dichotomous) are included in the model in standardised values to allow the comparison of the magnitude of the relative coefficients. Finally, we run some robustness checks for the following reasons. a) To overcome potential correlations between several cultural dimensions, we also run models in which cultural variables (and their interaction with the specific performance component) are included one by one. b) To account for a potential crisis effect, we also consider the performance registered by the firm at the time t − 2. The underlying idea is that the CEO should experience more severe consequences if the poor performance is continuative. To explore this issue, we include in the model an additional dummy variable, named CRISIS, taking the value of 1 if the ROA of the firm was lower than in the previous year in both t − 1 and t − 2.6 We report the main results in Tables 4 and 5. Following Bushman et al. (2010), we report both estimated coefficients and marginal effects at the mean values (i.e., the partial derivative of the logit function with respect to the variable of interest, evaluated at the mean values of all other explanatory variables) because nonlinearity makes the estimated coefficients difficult to interpret directly in logit and probit models. As outlined in Bushman et al. (2010), the economic significance should be computed as the product of three different terms: the estimated coefficient times mean turnover density (i.e., the marginal effect) times one standard deviation of the variable. Since our independent variables have been standardised, the economic significance is directly observable from the marginal effects shown in Tables 4 and 5. For interaction terms, the marginal effect is the cross-partial derivative with respect to the two interacted variables, as calculated using the delta method (Powers, 2005). In Tables 4 and 5, the information about interaction effects is summarised reporting the mean interaction effect and its level of statistical significance. For the main model (including all types of cultures), we follow Lel and Miller (2008) and decide to show the corrected marginal effects calculated following Norton et al. (2004) and their significance at every predicted probability (see Fig. 2). For brevity, we focus on culture and performance measures when discussing our results. Regarding the peer-group ROA component, the estimated coefficient is negative, consistent with Jenter and Kanaan (forthcoming) and with Eisfeldt and Kuhnen (2013), suggesting that not only are CEOs appropriately punished for poor performance, but also the peer group effect matters. However, the relative coefficient is never statistically significant at the 10% confidence level or below. Consistent with prior papers, we find a strong negative relationship (statistically significant at the 1% confidence level) between the firm-specific ROA and the probability of CEO turnover in all models, regardless of the introduction of cultural variables as a group (model 1, Table 4) or one by one (models 1a–1d, Table 5). Furthermore, it is worth noting that when we introduce the variable CRISIS (model 2), it assumes a positive coefficient, statistically significant at the 10% confidence level, showing that the continuity of poor performance increases the probability of CEO turnover. Overall, we find strong 6

We would like to thank the referee for suggesting the construction of a firm-crisis variable.

F. Fiordelisi, O. Ricci / Journal of Corporate Finance 28 (2014) 66–82

75

Table 4 Multivariate analysis. CEOT = 1

(1) Coefficient

(1) Marginal effect

(2) Coefficient

(2) Marginal effect

P^ i;t−1

−0.03557 (0.04869) −0.15448*** (0.03563) −0.01690 (0.03200) 0.07181** (0.03605) −0.00470 (0.03635) 0.06316* (0.03230) −0.03970 (0.03477) −0.00257 (0.03277) −0.08700** (0.04077) 0.06842** (0.03478) −0.07853 (0.22485) 0.61140*** (0.05033) −0.06727** (0.03069) −0.32132*** (0.03249) −0.17845 (0.14897) −1.71783*** (0.13464) 0.20614*** (0.06583) −0.93436*** (0.11703) 0.06848* (0.03665) 0.10604*** (0.03797) −0.03047 (0.03406) −0.04364 (0.03340) Yes Yes −0.80484* (0.41423) 14,347 0.0821

−0.00283 (0.00388) −0.01229*** (0.00282) −0.00134 (0.00255) 0.00571** (0.00287) −0.00037 (0.00289) 0.00503* (0.00257) −0.00340 (0.00294) −0.00092 (0.0029) −0.00771** (0.00315) 0.00548* (0.00306) −0.00625 (0.01789) 0.04866*** (0.00362) −0.00535** (0.00242) −0.02557*** (0.00255) −0.0142 (0.01185) −0.13671*** (0.01084) 0.01641*** (0.00525) −0.07436*** (0.00903) 0.00545* (0.00291) 0.00844*** (0.00301) −0.00243 (0.00271) −0.00347 (0.00266)

−0.02855 (0.04897) −0.14353*** (0.03593) −0.01602 (0.03201) 0.07158** (0.03604) −0.00849 (0.03644) 0.06318* (0.03229) −0.03970 (0.03469) −0.00383 (0.03261) −0.08727** (0.04066) 0.06795** (0.03464) −0.08085 (0.22526) 0.61143*** (0.05038) −0.06870** (0.03068) −0.32259*** (0.03252) −0.18374 (0.14932) −1.71779*** (0.13481) 0.20630*** (0.06582) −0.93725*** (0.11691) 0.07075* (0.03667) 0.10215*** (0.03796) −0.02982 (0.03367) −0.04298 (0.03345) 0.11378* (0.06545) Yes Yes −0.82134** (0.41445) 14,347 0.0824

−0.00227 (0.00389) −0.01142*** (0.00285) −0.00127 (0.00255) 0.00569** (0.00287) −0.00068 (0.0029) 0.00503* (0.00257) −0.00342 (0.00294) −0.00099 (0.00288) −0.00770** (0.00316) 0.00548* (0.00306) −0.00643 (0.01791) 0.04863*** (0.00363) −0.00546** (0.00242) −0.02566*** (0.00255) −0.01461 (0.01187) −0.13663*** (0.01084) 0.01641*** (0.00524) −0.07454*** (0.00902) 0.00563* (0.00291) 0.00812*** (0.00301) −0.00237 (0.00268) −0.00342 (0.00266) 0.00905* (0.0052)

^i;t−1 v COLt − 1 COMt − 1 CONt − 1 CREt − 1 ^i;t−1 ∗COLt−1 v ^i;t−1 ∗COMt−1 v ^i;t−1 ∗CONt−1 v ^i;t−1 ∗CREt−1 v GENDERt − 1 AGEt − 1 TENUREt − 1 EQ_INCt − 1 CEO_COMP_CTTEt − 1 EXECDIRt − 1 DUALITYt − 1 SHARE_5%t − 1 SIZEt − 1 CAP_EXPt − 1 LEVt − 1 FIRM_AGEt − 1 CRISIS Year effects Industry effects Constant Observations R-squared

This table reports the results for the logit regression of CEO turnover on firm performance reported in Eq. (2). First, we run an OLS regression of individual ROA on contemporaneous industry ROA. The predicted values and errors from this regression are used to disentangle firm performance into specific and systematic components. Second, we run a logit model to predict CEO turnover. All regressors are defined in Table 2. Marginal effects are calculated as the change in the probability of a CEO turnover for a unit change in the explanatory variable, holding other variables at the mean values. For interaction terms, margins are calculated as shown in Ai and Norton (2003) and Norton et al. (2004). Robust standard errors are in parentheses. ***, **, * indicate statistical significance at the 1, 5, and 10% levels, respectively. Source: Authors' elaboration of Execucomp data.

empirical evidence supporting our first hypothesis (H1: As firm-specific performance declines, the probability of changing CEOs increases). The most interesting result we show is that different corporate cultures have a different impact on the probability of changing a CEO. First, we find that both H2 (companies with a competition-, creation-, or collaboration-oriented culture have a stronger orientation to change CEOs than companies with a control-oriented culture) and H3 (companies with a competition-oriented culture have a stronger orientation to change CEOs than companies with a creation- or collaboration-oriented culture) are substantially confirmed. The coefficients for the competition- and creation-oriented cultures are positive, statistically significant (at the 5% and

76

CEOT = 1

(1a) Coefficient

(1a) Marginal effect

(1b) Coefficient

(1b) Marginal effect

(1c) Coefficient

(1c) Marginal effect

(1d) Coefficient

(1d) Marginal effect

P^ i;t−1

−0.03616 (0.04797) −0.15517*** (0.03429) 0.02219 (0.02862)

−0.00289 (0.00384) −0.01241*** (0.00273) 0.00177 (0.00229)

−0.03402 (0.04840) −0.15342*** (0.03509)

−0.00272 (0.00387) −0.01226*** (0.00279)

−0.04028 (0.04811) −0.15187*** (0.03453)

−0.00322 (0.00384) −0.01214*** (0.00275)

−0.03208 (0.04784) −0.15233*** (0.03404)

−0.00256 (0.00382) −0.01216*** (0.00271)

^ vi;t−1 COLt − 1 COMt − 1

0.08010*** (0.02978)

0.0064*** (0.00238)

CONt − 1

0.02341 (0.03437)

0.00187 (0.00275)

CREt − 1 ^ vi;t−1 ∗COLt−1

−0.03369 (0.03063)

−0.01460 (0.02825)

−0.09043** (0.04057)

0.00312 (0.00265) −0.00633 (0.01784) 0.04847*** (0.00363)

−0.0083** (0.003401)

^ vi;t−1 ∗CREt−1

AGEt − 1

0.04417* (0.02486) −0.07929 (0.22352) 0.60717*** (0.05024)

−0.00208 (0.00274)

^ vi;t−1 ∗CONt−1

−0.08359 (0.22424) 0.60564*** (0.05005)

0.00683*** (0.00227)

−0.00324 (0.00264)

^ vi;t−1 ∗COMt−1

GENDERt − 1

0.08561*** (0.02846)

−0.00669 (0.01793) 0.04844*** (0.00363)

−0.08498 (0.22422) 0.61044*** (0.05025)

−0.00679 (0.01791) 0.04878*** (0.00364)

−0.09146 (0.22425) 0.60271*** (0.05019)

−0.00731 (0.01791) 0.04816*** (0.00364)

F. Fiordelisi, O. Ricci / Journal of Corporate Finance 28 (2014) 66–82

Table 5 Multivariate analysis: Robustness check.

TENUREt − 1 EQ_INCt − 1 CEO_COMP_CTTEt − 1 EXECDIRt − 1 DUALITYt − 1 SHARE_5%t − 1 SIZEt − 1 CAP_EXPt − 1

FIRM_AGEt − 1 Year effects Industry effects Constant Observations R-squared

−0.00519** (0.00242) −0.02544*** (0.00256) −0.01433 (0.01195) −0.13734*** (0.01088) 0.01645*** (0.00528) −0.07475*** (0.00905) 0.00493* (0.00291) 0.00856*** (0.00302) −0.00269 (0.00297) −0.0034 (0.00264)

−0.06762** (0.03055) −0.31884*** (0.03246) −0.18205 (0.14935) −1.71552*** (0.13499) 0.20533*** (0.06587) −0.93423*** (0.11671) 0.07099* (0.03654) 0.10681*** (0.03779) −0.03021 (0.03335) −0.03873 (0.03307) Yes Yes −0.78839* (0.41277) 14,347 0.0806

−0.0054** (0.00242) −0.02548*** (0.00256) −0.01455 (0.01193) −0.1371*** (0.01092) 0.01641*** (0.00527) −0.07466*** (0.00904) 0.00567* (0.00292) 0.00854*** (0.00301) −0.00241 (0.00267) −0.0031 (0.00264)

−0.06366** (0.03053) −0.31841*** (0.03243) −0.18070 (0.14931) −1.71348*** (0.13470) 0.20707*** (0.06586) −0.93613*** (0.11670) 0.06899* (0.03650) 0.10319*** (0.03784) −0.03287 (0.03688) −0.04791 (0.03314) Yes Yes −0.79420* (0.41264) 14,347 0.0805

−0.00509** (0.00242) −0.02544*** (0.00256) −0.01444 (0.01192) −0.13693*** (0.01089) 0.01655*** (0.00527) −0.07481*** (0.00904) 0.00551* (0.00291) 0.00825*** (0.00301) −0.00263 (0.00295) −0.00383 (0.00265)

−0.06258** (0.03053) −0.31978*** (0.03242) −0.17168 (0.14907) −1.71354*** (0.13377) 0.20334*** (0.06577) −0.94681*** (0.11715) 0.06011* (0.03629) 0.10196*** (0.03749) −0.03089 (0.03483) −0.04131 (0.03298) Yes Yes −0.86211** (0.41296) 14,347 0.0809

−0.005** (0.00242) −0.02553*** (0.00255) −0.01371 (0.01189) −0.13679*** (0.01079) 0.01623*** (0.00526) −0.07558*** (0.00906) 0.0048* (0.00289) 0.00814*** (0.00298) −0.00247 (0.00278) −0.0033 (0.00263)

This table reports the results for the logit regression of CEO turnover on firm performance reported in Eq. (2). First, we run an OLS regression of individual ROA on contemporaneous industry ROA. The predicted values and errors from this regression are used to disentangle firm performance into specific and systematic components. Second, we run a logit model to predict CEO turnover. All regressors are defined in Table 2. Robust standard errors are in parentheses. ***, **, * indicate statistical significance at the 1, 5, and 10% levels, respectively. Source: Authors' elaboration of Execucomp data.

F. Fiordelisi, O. Ricci / Journal of Corporate Finance 28 (2014) 66–82

LEVt − 1

−0.06489** (0.03043) −0.31809*** (0.03244) −0.17911 (0.14956) −1.71707*** (0.13445) 0.20565*** (0.06587) −0.93455*** (0.11675) 0.06167* (0.03642) 0.10706*** (0.03787) −0.03368 (0.03714) −0.04250 (0.03303) Yes Yes −0.81462** (0.41250) 14,347 0.0801

77

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10% confidence levels, respectively), and greater than that for the collaboration-oriented culture (not significantly different from zero), as predicted by H2. However, the effect of the collaboration-oriented culture is negative and not statistically significant at the 10% confidence level or below. In addition, the effect for the competition-oriented variable is the largest in size, as predicted by H3. Regarding the interactions measuring the moderating role of corporate culture, we do not find evidence supporting the hypotheses H4 (as performance declines, companies with a competition-, creation-, or collaboration-oriented culture have a stronger “incremental” incentive to change CEOs than companies with a control-oriented culture) or H5 (as performance declines, companies with a competition-oriented culture have a stronger “incremental” incentive to change CEOs than companies with a creation- or collaboration-oriented culture). The coefficient and the mean interaction effect for the control-oriented culture are both negative, statistically significant at the 5% confidence level, and greater in absolute values than the effect for the collaboration- and competition-oriented cultures. As shown in Fig. 2, the corrected interaction effects for the control-oriented culture are overwhelmingly negative across predicted probabilities and also significant for most probabilities. Being negative, the interaction reinforces the inverse relationship between firm-specific performance and CEO turnover. In addition, the coefficient and the mean interaction effect for the creation-oriented culture are positive and statistically significant at the 10% confidence level. As shown in Fig. 2, the corrected interaction effects for the creation-oriented culture are overwhelmingly positive across predicted probabilities and also significant for most probabilities. Because the interaction effect is generally positive, and then of opposite sign from the relationship between firm-specific performance and CEO turnover, it weakens this relationship. Regarding to the control variables, the effects for AGE and DUALITY are positive and statistically significant at the 1% confidence level: CEO turnover is more likely as he/she becomes older (and therefore closer to retirement age) and when CEO is also a chairman (possibly because duality has been discouraged by most corporate governance rules and best practices, especially over the last ten years). In contrast, the impacts of TENURE, EXECDIR, EQ_INC, and SHARE_5% are all negative and statistically significant at the 5% confidence level or below: turnover is less likely for a CEO that has cumulated a strong experience inside the company, that has an executive role in the firm, and that has his/her interest aligned with the company's through stock ownership and equity incentives. Shifting now to the firm's characteristics, CEO turnover is more likely in larger firms and with higher growth opportunities (the relationship with both SIZE and CAP_EXP is positive and statistically significant at the 10% confidence level or below). Our results appear stable under the robustness checks: the introduction of cultural dimensions one by one (see Table 5) and the incorporation of the CRISIS dummy (Table 4, model 2) do not modify our conclusions.

6. CEO succession In this section, we focus on the CEO succession7 to complement our analysis of CEO turnover, which is the main focus of the paper. A substantial number of papers have compared internal CEO succession (i.e., the new CEO is selected from within the organisation) and external succession (i.e., the new CEO is an outsider), which have traditionally been assessed by focusing on the performance consequences of top executive successions and, more recently, under which circumstances succession benefits or disrupts firm performance (see Ansari et al., 2014 for a recent paper and Karaevli, 2007 for a review). Our perspective is different from that of previous studies because we are interested in assessing how different corporate culture types influence the CEO succession. Previous papers (Boeker, 1997; Boeker and Goodstein, 1993; Brady and Helmich, 1984; Zajac, 1990) have traditionally predicted that external CEO succession would be chosen when organisations perform poorly and need a strategic change, while internal CEO succession is preferred when organisations desire continuity (for a review, see Karaevli, 2007). As such, our hypothesis is that, as firm-specific performance declines, the probability of external CEO succession increases. This hypothesis is somehow mediated by the organisational culture. The collaboration-oriented culture is based on cohesion and support and, as such, the board would be reluctant to replace the leader with an outsider, even in the case of poor performance. Similarly, in high-control firms, the board would be reluctant to address problems by replacing the leader of a very hierarchical system. Turning to external-oriented cultures, competition-oriented companies should tolerate change and instability and even trumpet these values, especially in case of poor performance, e.g., by selecting an external candidate. For the creation-oriented corporate culture, the probable trend is difficult to predict. On the one hand, the CVF suggests that these companies have an external focus and are inclined to change and innovate. On the other hand, the business of these companies is founded on creativity, knowledge, and agility that are often firm-specific and cannot be easily found in other companies, so that the board may not be inclined to replace the leader with an outsider, who may have a different view,8 even in the case of poor performance.9 To test these hypotheses, we conduct a further empirical investigation. With reference to the subsample of year-observations in which a CEO turnover has occurred, we construct two different dummy variables (Outsider_a and Outsider_b), which take the value of 1 if the company chooses an outsider successor (and 0 otherwise) based on two different definitions: a) someone who 7

We would like to thank the JCF Special Issue editors for suggesting investigating both the CEO and succession cases. Various real-life examples support this point: in many creation-oriented companies, the current CEO took charge after a several-year internal career (e.g., Tim Cook for Apple, Steve Ballmer for Microsoft, Ginni Rometty for IBM, and Robert Iger for Disney). 9 Mobbs and Raheja (2012) provide some empirical evidence in this direction, even though they deal with quite a different issue. Their analysis aims to compare firms that promote a single executive (successor-incentive) and companies that conduct tournaments (tournament-incentive) among inside managers to succeed the CEO. They outline that when the firm-specific human capital is important, it is more likely for the firm to select an heir rather than to conduct a tournament succession. In addition, in comparison with firms with tournament succession, firms with a successor-incentive promotion are more likely to experience a turnover, but the turnover is less sensitive to performance, consistently with the greater difficulty in replacing the CEO. 8

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A) Specific performance * collaboration

B) Specific performance * competition

C) Specific performance * control

D) Specific performance * creation

Fig. 2. The economic significance of the impact of different cultures on the relationship between CEO turnover and firm-specific performance.

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has not been among the top managers for at least two years before the nomination or b) someone who did not join the company at least 2 years before the nomination. We use a similar approach to that applied for CEO turnover.10 However, given that succession is observable only if there has been a turnover, there might be a sample selection problem. To overcome this issue, after the OLS regression decomposes firm performance into specific and systematic components, we adopt an Heckman procedure in which both the selection and the principal regressions are run using a probit specification that better fits the dichotomous nature of our dependent variables (that is, CEOT in the selection model and then OUT_A or OUT_B in the principal one). Our regressors are the same as those used in the main empirical investigation dealing with turnover, except for control variables: when we investigate the type of succession, i.e., the choice of an outsider rather than an insider, we only consider the firm's characteristics and do not include controls for the incumbent CEO in the model. The results from the Heckman procedure are shown in Table 6. We find a negative relationship between the past performance of the incumbent CEO and the choice of an outsider, confirming our hypothesis that, as firm-specific performance declines, the probability of external CEO succession increases. With reference to cultural dimensions, we show that, on average, companies oriented toward creation are more likely to select an insider. Linking this result with findings from the turnover analysis, this suggests that innovative companies encourage changes in top management but prefer that the successor is someone grown inside the company, with the same culture and know-how. This is reasonable if we consider that the way of doing business and the necessary knowledge can be very specific in such companies. At the same time, we find statistically significant evidence that the creation-oriented culture weakens the relationship between the poor performance of the incumbent CEO and the choice of an outsider successor. This may be a further signal that innovative companies like change but with persons having the same background. Finally, with reference to control variables, we find that large companies are less likely to choose an outsider, while the opposite holds for firms with high leverage.

7. Conclusions and discussion In this paper, we show that corporate culture plays a moderating role in the relationships between CEO turnover and performance pre-turnover. Our paper is the first to provide empirical evidence using a large dataset (US listed companies from 1994 to 2011) that corporate culture influences the decision to fire the CEO. Consistently with previous studies, we find a strong negative relationship between the firm-specific ROA (i.e., the ROA component not caused by peer group performance) and the probability of a CEO turnover. The most interesting result of this work is that different corporate cultures have different impacts on the probability of changing CEOs. First, the probability of CEO turnover, on average, increases in the case of a corporate culture oriented toward competition (i.e., focusing on emphasising organisational effectiveness and fast response) or creation (i.e., focusing on generating future opportunities through innovation). Second, we show that companies with a competition-oriented culture have the strongest orientation to change CEOs. When we assess what happens in the case of poor past performance, we find that the negative relationship between firm-specific performance and CEO turnover is reinforced by a culture oriented toward control (i.e., focusing on internal improvements in efficiency through the implementation of better processes) and reduced by a culture oriented toward creation. We also find that CEO turnover is more likely as the CEO becomes older (and thus closer to retirement age) and when the CEO is also a chairman (e.g., duality has been discouraged by most corporate governance rules and best practices, especially over the last ten years). Furthermore, our results show that the turnover of a CEO that has cumulated a strong experience inside the company, that has many appointments in the firm, and that has his/her interest aligned to the company's through stock ownership and equity incentives is less probable. We complement our analysis of CEO turnover by adding a further investigation on succession type (internal vs. external). We show a negative relationship between the past performance of the incumbent CEO and the choice for an outsider, confirming our hypothesis that, as firm-specific performance declines, the probability of external CEO succession increases. We also show that companies oriented toward creation are more likely to select an insider. At the same time, the creation-oriented culture type weakens the relationship between the poor performance of the incumbent CEO and the choice for an outsider successor. We acknowledge some limitations of our analysis that suggest some interesting directions for future research. First, we have very limited information on both the predecessor and the new CEO, e.g., their origin, education, and previous experience. This type of data might help to better explain the moderating role of corporate culture. In addition to this limitation, we believe that cultural variables are likely crucial in not only determining the probability of dismissal for poor results but also influencing the opinions on the current CEO, regardless performance, and directing the choice for a successor that best fits the corporate orientation. Further investigations should be devoted to enriching the database and exploring these issues. Second, it would be interesting to study the moderating role of culture on not only the relationship between CEO turnover and past firm performance (as in our paper) but also the performance effects of succession to assess both CEO credibility and CEO effectiveness. Third, it is probable that a cultural approach is able to offer interesting results if applied to top managers other than the CEO, as the upperechelons perspective suggests. In conclusion, this study represents a first step toward opening a new perspective in the literature, contributing to studies examining both the antecedents and consequences of top management change. 10

We would like to thank referee for providing us constructive suggestions to assess role of corporate culture in the CEO succession.

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Table 6 Investigating succession type: Insider vs. outsider.

P^ i;t−1 ^i;t−1 v COLt − 1 COMt − 1 CONt − 1 CREt − 1 ^i;t−1 ∗COLt−1 v ^i;t−1 ∗COMt−1 v ^i;t−1 ∗CONt−1 v ^i;t−1 ∗CREt−1 v

Y = OUT_A

Y = CEOT

Y = OUT_B

Y = CEOT

−0.05491 (0.05678) −0.19219*** (0.03676) 0.00370 (0.04189) 0.03635 (0.04345) 0.00374 (0.04690) −0.08667** (0.04159) −0.03784 (0.03635) 0.05291 (0.03606) 0.00096 (0.04596) 0.06417* (0.03904)

−0.01579 (0.02438) −0.07280*** (0.01673) −0.00792 (0.01763) 0.03933** (0.01913) 0.00031 (0.01968) 0.03210* (0.01816) −0.01851 (0.01690) −0.00365 (0.01592) −0.04766** (0.02002) 0.03254* (0.01756) 0.28051*** (0.01759) −0.01792 (0.11245) −0.01833 (0.01634) −0.16497*** (0.01609) −0.07987 (0.07549) −0.93556*** (0.08091) 0.12026*** (0.03349) −0.45049*** (0.05445) 0.03538* (0.01857) 0.04781** (0.01873) −0.02029 (0.04216) −0.02486 (0.01782) 0.05865* (0.03483) Yes Yes −0.51926** (0.21096)

−0.04309 (0.05636) −0.18527*** (0.03669) 0.00731 (0.04185) 0.04719 (0.04344) 0.00096 (0.04682) −0.08841** (0.04173) −0.03864 (0.03628) 0.04982 (0.03600) 0.00061 (0.04578) 0.06419* (0.03905)

−0.01578 (0.02438) −0.07282*** (0.01673) −0.00790 (0.01763) 0.03931** (0.01913) 0.00034 (0.01968) 0.03214* (0.01816) −0.01855 (0.01690) −0.00361 (0.01592) −0.04765** (0.02002) 0.03253* (0.01756) 0.28074*** (0.01758) −0.01726 (0.11246) −0.01803 (0.01634) −0.16448*** (0.01611) −0.07906 (0.07545) −0.93512*** (0.08081) 0.12054*** (0.03348) −0.45040*** (0.05443) 0.03527* (0.01857) 0.04775** (0.01873) −0.02025 (0.04211) −0.02491 (0.01782) 0.05863* (0.03483) Yes Yes −0.52041** (0.21093)

AGEt − 1 GENDERt − 1 TENUREt − 1 EQUITY_INCt − 1 CEO_COMP_CTTE

t−1

EXECDIRt − 1 DUALITYt − 1 SHARE_5%t − 1 SIZEt − 1 CAPITAL_EXPt − 1 LEVERAGEt − 1 FIRM_AGEt − 1 CRISIS Year effects Industry effects Constant Observations Uncensored observation

−0.14721*** (0.04181) 0.05461 (0.04370) 0.57340** (0.25238) −0.05505 (0.04041) 0.00076 (0.07923) Yes Yes −0.01657 (0.43660) 14,347 1540

−0.14013*** (0.04182) 0.04768 (0.04376) 0.55609** (0.25229) −0.03032 (0.04042) 0.00779 (0.07913) Yes Yes −0.03907 (0.43620) 14,347 1540

This table reports the results for the model of CEO succession. First, we run an OLS regression of individual ROA on contemporaneous industry ROA. The predicted values and errors from this regression are used to disentangle firm performance into specific and systematic components. Second, we run a selection probit model predicting CEO turnover. Finally, we run a probit model predicting succession by an outsider based on two different definitions: a) someone who has not been among the top managers for at least two years before the nomination or b) someone who did not join the company at least 2 years before the nomination. All regressors are defined in Table 2. ***, **, * indicate statistical significance at the 1, 5, and 10% levels, respectively. Source: Authors' elaboration of Execucomp data.

Acknowledgements We would like to thank Stuart Gillan, Marc Goergen, Luc Renneboog, and the anonymous referee for providing us with very constructive suggestions. We also thank Arnoud Boot, Alessandro Carretta, Olivier DeJonghe, Carlo Favero, Alessandra Ferrari, Giorgio Gobbi, Emmanuel Mamatzakis, Roman Matousek, Phil Molyneux, Nikolas Papanikolaou, Enrico Sette, Amine Tarazi, and Tom Weyman Jones, for their helpful comments. We are also grateful to the Financial Intermediation Network of European Studies (FINEST) seminar participants at the University of Rome III and the Free University of Bozen. We would like to give special thanks to Anjan Thakor for his continuous support and great suggestions. Franco Fiordelisi also wishes to acknowledge the

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