corporate culture and ceo turnover

Journal of Corporate Finance xxx (2013) xxx–xxx

CORFIN-00739; No of Pages 17

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Journal of Corporate Finance

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Corporate culture and CEO turnover

Franco Fiordelisi a,b,⁎, Ornella Ricci a

a University of Rome III, Italyb SDA Bocconi, Italy

a r t i c l e i n f o

⁎ Corresponding author at: Via S. D'Amico 77, 001E-mail address: [email protected] (F.

0929-1199/$ – see front matter © 2013 Elsevier B.V. Ahttp://dx.doi.org/10.1016/j.jcorpfin.2013.11.009

Please cite this article as: Fiordelisi, F., Ric10.1016/j.jcorpfin.2013.11.009

a b s t r a c t

Article history:Received 16 September 2013Received in revised form 13 November 2013Accepted 18 November 2013Available online xxxx

We study the effect of corporate culture on the relationship between firm performance andCEO turnover. Utilising a measure of cultural dimension developed in organisation behaviourresearch, we quantify corporate culture by assessing official documents using a text analysisapproach. 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 anegative relationship between firm-specific performance and CEO turnover. Second, wedemonstrate that the probability of a CEO change, on average, is positively influenced by thecompetition- and creation-oriented cultures. The negative relationship between firm-specificperformance and CEO turnover is reinforced by the control-oriented culture and reduced bythe creation-oriented culture. Finally, we study the CEO insider or outsider succession andobserve that the creation-oriented culture has a negative relationship with the probability ofhiring an outsider. Moreover, the creation-oriented culture weakens the negative relationshipexisting between the firm-specific performance under the incumbent CEO and the probabilityof hiring an outsider.

© 2013 Elsevier B.V. All rights reserved.

JEL classification:G14G21G34M14

Keywords:Corporate cultureText analysisCorporate governanceCEO

1. Introduction

The threat of CEO change after poor performance is one of the main corporate governance instruments. It is widely believedthat corporate culture plays an important moderating role in linking CEO turnover and past performance. Surprisingly, we areunaware of any large-sample empirical evidence indicating whether and how corporate culture influences the link between firmperformance and the probability of CEO change. This lack of research is perhaps due to the somewhat nebulous nature of thenotion of culture, which raises several measurement issues in empirical research (Guiso et al., 2006). Nonetheless, recent researchhas begun to explore the empirical link between culture and various economic phenomena using novel approaches to measuringculture (Bernhardt et al., 2006; Fang, 2001; Guiso et al., 2006, 2009; Luttmer and Singhal, 2011). However, this research has notaddressed CEO turnover.

What role does corporate culture play in the decision to fire a CEO after poor performance? Is there a specific firm culture thatincreases (decreases) theprobability of changing CEOs after poor performance? These questions are critical for assessing the credibilityof the CEO change threat as a corporate governance instrument. The purpose of this paper is to empirically address these questions byfocusing on a large sample of US listed companies between 1994 and 2011. Our approach involves obtaining a quantitativemeasurement of corporate culture by assessing corporate financial statements (e.g., 10-K reports). Text analysis has recently been usedin 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.

45 Rome, Italy. Tel.: +39 06 57335672; fax: +39 06 57335797.Fiordelisi).

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ci, O., Corporate culture and CEO turnover, J. Corp. Finance (2013), http://dx.doi.org/

http://dx.doi.org/10.1016/j.jcorpfin.2013.11.009

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2 F. Fiordelisi, O. Ricci / Journal of Corporate Finance xxx (2013) xxx–xxx

Consistently with previous papers (e.g., Coughlan and Schmidt, 1985; Warner et al., 1988), we find a strong negativerelationship between firm-specific performance and the probability of changing CEOs, indicating that the threat of turnover afterpoor performance is credible. Our main result is that corporate culture influences the probability of a CEO change and moderatesthe negative relationship with performance. Specifically, the probability of CEO change, on average, increases in the case of acorporate culture oriented toward competition (i.e., focusing on emphasising organisational effectiveness and fast response) orcreation (i.e., focusing on generating future opportunities through innovation). Furthermore, the negative relationship withfirm-specific performance is reinforced by a culture oriented toward control (i.e., focusing on internal improvements in efficiencythrough the implementation of better processes) and reduced by a culture oriented toward creation. Finally, when we disentangleCEO 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 thefirm-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 ofcorporate culture and formulates our research hypotheses. The investigated sample and the variables used in our empirical designare described in Section 4. Section 5 discusses the empirical results and robustness checks for CEO turnover. Section 6 focuses onthe 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 changemust be credible in the sense that the CEO turnoveris negatively related to firm performance. Early papers (Coughlan and Schmidt, 1985; Warner et al., 1988) find a negativerelationship 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 orempirical 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 alwaysconsistent, and past performance often explains only a very low portion of the turnover phenomenon (Pitcher et al., 2000). Morerecent 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 severalvariables that may play a moderating role (e.g., CEOs' influence on boards through direct ownership, as outlined in Easterwood etal., 2012; CEO's outside employment options, as outlined in Liu, forthcoming).

Although there appears to be convergent evidence that CEO change is credible, there are no studies assessing the reason forthis 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 therelationship between performance and CEO turnover is strongly influenced by corporate culture. Although this finding is certainlylogical and intuitive, there have been no studies documenting whether and how corporate culture influences the relationshipbetween firm performance and the decision to fire the CEO. We build a unique dataset of all US listed companies between 1994and 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; Loughranand 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 thesensitivity of CEO turnover to firm-specific performance. Jenter and Kanaan's (forthcoming) approach enables us to decomposefirm performance into a systematic component (caused by peer group performance) and a firm-specific component that shouldreflect 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 relativeconsequences 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 anorganisation's effectiveness (Deal and Kennedy, 1982; Peters andWaterman, 1982; Schein, 1992;Wilkins and Ouchi, 1983), and in arecent review of the literature, Sackmann (2010) suggests that some culture orientations have a positive effect on performancemeasures.

A first necessary step for our analysis is to define culture in a sufficiently narrowwaywithin this framework so that it is possible toidentify its influence on the relationship between CEO turnover and company performance change.We adopt the definition proposedby 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 indetermining CEO turnover.

Please cite this article as: Fiordelisi, F., Ricci, O., Corporate culture and CEO turnover, J. Corp. Finance (2013), http://dx.doi.org/10.1016/j.jcorpfin.2013.11.009



3F. Fiordelisi, O. Ricci / Journal of Corporate Finance xxx (2013) xxx–xxx

(1983)'s competing values framework (CVF), which is an organisational taxonomywidely 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 Cameronet al. (2006).

There are two internally oriented culture types. The first is the collaboration-oriented culture (termed “clan culture type” in theCVF), which focuses on its employees and attempts to develop human competencies and strengthen organisational culture bybuilding consensus. The underlying logic is that human affiliation produces positive affective employee attitudes directed towardthe organisation. The goal of this culture is to develop cooperative processes and attain cohesion through consensus and broademployee involvement, e.g., clarifying and reinforcing organisational values, norms, and expectations, developing employees andcross-functional work groups, implementing programmes to enhance employee retention, and fostering teamwork anddecentralised decision making. Companies with this culture usually succeed because they hire, develop, and retain their humanresource base. The other internally oriented culture is the control-oriented culture (also called “hierarchy culture”), which issupported by an organisational structure driven by control mechanisms, and the corporate aim is creating value through internalimprovements 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

ycarcohdAnalCThrust Collaborate Thrust Create

Means Cohesion, participation, communication, empowerment

Ends Morale, people development, commitment

Means Adaptability, creativity, agility

Ends Innovation and cutting-edge output

Internal focus and integration

External focus and differentiation

tekraMyhcrareiHThrust Control

Means Capable processes, consistency, process control,

measurement Ends Efficiency, timeliness, smooth

functioning

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 (stcafetrAseulaVsfeileBsnoitpmussAepyterutluC behaviours) Effectiveness

criteria

Collaborate (Clan)

Human affiliation

People behave appropriately when they have trust in, loyalty

to, and membership in the organisation

Attachment, affiliation,

collaboration, trust, and support

Teamwork, participation, employee involvement, and

open communication

Employee satisfaction and

commitment

Create (Adhocracy)

Change

People behave appropriately when they understand the

importance and impact of the task.

Growth, stimulation, variety, autonomy,

and attention to detail

Risk-taking, creativity, and adaptability

Innovation

Competition (Market)

Achievement

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

achievements

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

Control (Hierarchy)

Stability

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

by rules and regulation

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*

Compete (COM)

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*

Collaborate (COL)

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*

Create (CRE)

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*

Fig. 1. The corporate culture dimensions investigated.


image of Fig.�1




technology) and quality enhancements (such as statistical process control and other quality control processes). Companies thathave 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 culturetype” in the CVF). This type of culture focuses on the organisation's external effectiveness by pursuing enhanced competitivenessand emphasising organisational effectiveness, fast response, and customer focus. These companies usually attach the highestpriority to customers and shareholders and judge success based on such indicators as market share, revenues, meeting budgettargets, and profitability growth. The other culture type is the creation-oriented culture (termed “adhocracy” in the CVF), whichfocuses on creating future opportunities in the marketplace through innovation in the organisation's products and services. Theorganisation encourages entrepreneurship, vision, and constant change, e.g., allowing for freedom of thought and action amongemployees such that rule breaking and reaching beyond barriers are common characteristics of the organisation's culture. Thesecompanies usually aim to include innovative product-line extensions, radical new process breakthroughs, and innovations indistribution 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 tochange its CEO. The analysis of CEO turnover is based on the general hypothesis that different culture types influence a company'sdecision 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 CEOsincreases.2

Hypothesis 1 (H1). As firm-specific performance declines, the probability of changing CEOs increases.

In the second step,we develop somenew testable hypotheses related to corporate culture.We loosely followHartnell 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 financialeffectiveness: these companies are inclined to integrate external environmental information to construct clear and coherent goalsto increase organisational members' attention toward profitable activities (Cameron et al., 2006; Chao et al., 1994). Highlycompetition-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- andcollaboration-oriented cultures also exhibit a positive link with financial effectiveness, e.g., through a team empowermentmechanism (Chen et al., 2007), but this relationship is weaker than that for the competition-oriented culture. Collaboration andcreation cultures' distal association with financial effectiveness may thus operate through group efficacy mediating mechanisms(Jung and Sosik, 2002) aswell as othermechanisms, such as human resourcemanagement practices (Combs et al., 2006) and groupcohesion (Gully et al., 1995). Instead, a control-oriented culture implies deference to superiors for various reasons. One couldconjecture 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 financialeffectiveness have a greater orientation to change CEOs. First, we predict that companies with a competition-, creation-, andcollaboration-oriented culture have a positive link with CEO turnover. Second, we posit that companies with a competition-orientedculture 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 strongerorientation 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 thancompanies 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 ofpoor performance. Based on Hartnell et al.'s (2011) assumptions and our previous discussion, we expect that companies with acompetition-, 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). Weare aware that it is debatable whether this decision is made by boards or shareholders. The theory of friendly boards (Adams and Ferreira, 2007) provides aninteresting framework to explain the board-CEO game. In this paper, we follow a factual–objective approach: we observe companies changing CEOs (withoutformally discussing who is making this decision) and measure organisational culture in an objective way, specifically, by a text analysis of 10-K reports. Thesereports 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 “themajority 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 (inwhich 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 tothe 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.





performance reinforces the company's “base” orientation to change CEO in the case of poor firm performance). Next, we alsoposit that companies with a competition-oriented culture have a stronger “incremental” incentive to change CEOs thancompanies with a creation- or collaboration-oriented culture.

Hypothesis 4 (H4). As performance declines, companies with a competition-, creation-, or collaboration-oriented culture have astronger “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 ourhypotheses.

4.1. Data

To answer our research questions, we build a unique dataset by collecting information from three different sources to compilea comprehensive and accurate profile of each company.

First, we obtained information on top executive officers (specifically, on CEOs) from the Execucomp database. Data wereavailable 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 theinformation about the identity of the CEO was available only for a specific year but not for the previous one, rendering itimpossible 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'sEdgar database, and for each of these filings, we ran a text analysis to estimate each cultural dimension identified by Cameron etal. (2006) (513,956 texts analysed in all).

Our final sample includes all US listed companies between1994 and 2011 forwhich itwas possible to a) collect information on topmanagers, b) determine accounting-based performance, c) measure the relevant cultural dimensions, and d) identify all the controlvariables used to account for the firm's and the incumbent CEO's characteristics (for a detailed definition of these variables, seeSection 4.4). Information relative to the same company and drawn from different databases wasmatched using the GVKEY code. As aresult, we have a unique dataset of 18,088 year-observations, combining managerial, accounting, and cultural information. A CEOchange occurs in 1838 year-observations, at a frequency of approximately 10%. We distinguished financial from non-financialcompanies based on the SPINDEX code and industry group definitions: observations for financial and non-financial companiesrepresent approximately 13% and 87% of our sample, respectively.4 Companies without an assigned industry group were excludedfrom 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 atechnique used to examine, in a systematic and objective manner, the characteristics specific to a text (Stone et al., 1966). Theidea 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 aremirrored in itswritten documents. Text analysismethodology (Stoneet al., 1966) is instrumental in measuring the semantic content of firms' publicly available official documents (namely, 10-K reports).This technique provides uswithmeasures 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 andmanagement papers (e.g., Antweiler andMurray, 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 inFig. 1), we identify a large set of synonyms for each of these aspects. Following Carretta et al. (2011), synonyms are selected usinga two-step procedure that minimises subjectivity in the selection process. First, we selected the synonyms suggested by theauthors (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; insurancebrokers; investment banking and brokerage; life and health insurance; multi-line insurance; multi-sector holdings; other diversified financial services; propertyand casualty insurance; real estate development; real estate services; real estate investment trusts; regional banks; reinsurance; specialised finance; thrifts andmortgage finance.





the Harvard IV-4 Psychosocial Dictionary to identify other synonyms. Loughran and McDonald (2011) have noted that theHarvard IV-4 Psychosocial Dictionary5 is a commonly used source of word classification, in part because its composition is beyondthe control of the researcher and the possible impact of researcher subjectivity is significantly diminished. For example, wordssuch as “capabilities, collective, cooperation, etc.” are associated with the word “collaborate,” and a relatively high frequency oftheir 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 corporatedocuments suggests that the company has a competition-oriented culture. Words such as “boss, efficiency, caution, etc.” areconsidered synonyms for “control,” and a relatively high frequency of their use in corporate documents suggests that thecompany has a control-oriented culture. Words such as “dream, begin, elaborate, etc.” are associated with the word “create,” and arelatively 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 thenumber of times that our synonyms occur in each annual report, using percentages to measure cultural emphasis. For example, ifthe estimate for a “competition-oriented” dimension is equal to 5, the synonyms used to capture this culture dimension (reportedin 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 usfrom detecting any cultural differences in the cross-section. Nonetheless, we document in Table 1 that there is significantcross-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, adummy taking the value of 1 if the company has changed its CEO with respect to the previous year and 0 otherwise. When morethan one top manager is in charge of the company in the same financial year, we choose the person who has been the CEO for thelongest 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 only3 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 thanstock market returns if the market incorporates future benefits after replacing an underperforming CEO. Specifically, we focus onthe 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 withinand 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 rangeof 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 dummyvariable 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 forwhich the CEO has been in charge), equity incentive (i.e., the proportion of the CEO's total compensation represented by equityincentives), compensation committee (i.e., a dummy variable taking the value of 1 if the CEO is listed in the compensationcommittee and 0 otherwise), executive director (i.e., a dummy variable taking the value of 1 if the CEO serves as an executivedirector and 0 otherwise), duality (i.e., a dummy variable taking the value of 1 if the CEO is also chairman and 0 otherwise), andthe 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 thecompany and 0 otherwise).

With reference to the firm's characteristics, we include the following control variables: size (i.e., the industry-adjusted naturallog 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 ofyears the company is active, proxied by the difference between the considered fiscal year and the first date of appearance in theCRSP 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 isrelated 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 thevariables under consideration (e.g., taxes and liabilities), we use this dictionary because the list of synonyms used to capture Cameron et al.'s (2006) fourdimensions of corporate culture are directly correlated with the variables and do not suffer from the problems reported by Loughran and McDonald (2011).




Table 1Corporate culture dimensions estimates.

Overall Industry Time

Financial Non-financial 1994 1998 2002 2006 2011

Collaborate (COL) Mean 1.386 1.620 1.346 1.315 1.264 1.332 1.504 1.461St. Deviation 0.440 0.509 0.413 0.629 0.427 0.395 0.495 0.349Min 0 0 0 0.43 0 0 0 0.83Max 8.60 5.36 8.60 4.580 4.290 3.220 4.320 4.360

Compete (COM) Mean 4.844 4.521 4.901 4.887 4.904 4.914 5.089 5.076St. Deviation 1.184 1.103 1.189 1.989 1.045 1.133 1.700 0.885Min 0 0 0 1.22 0 0 0 3.44Max 25.72 18.04 25.72 19.82 9.57 8.85 15.80 9.76

Control (CON) Mean 1.410 1.342 1.422 1.460 1.328 1.324 1.589 1.451St. Deviation 0.509 0.363 0.530 0.629 0.329 0.926 0.524 0.303Min 0 0 0 0.58 0 0 0 0.77Max 33.33 5.76 33.33 6.500 3.740 28.570 5.620 3.100

Create (CRE) Mean 1.081 1.262 1.049 0.877 0.932 1.082 1.266 1.214St. Deviation 0.387 0.381 0.379 0.429 0.343 0.372 0.416 0.267Min 0 0 0 0 0.16 0 0 0.69Max 20.00 5.16 20.00 3.03 3.71 7.14 5.48 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 fromthe 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 ROAand industry-adjusted ROA (IAROA) in the previous year (i.e., at the time t − 1). As shown in Table 3, there is a positiverelationship between poor past performance and subsequent CEO turnover. The turnover frequency in the lowest quintile (worstperformers) is always greater than in the highest quintile (best performers). However, the Q1–Q5 difference is only statisticallysignificant (5% confidence level) when we consider the industry-adjusted performance (IAROA). This may be a signal that thespecific performance linked to the CEO's ability affects turnover more strongly than the peer performance component. When wedisentangle successions by the origin of the new CEO, we find a very strong relationship between past poor performance and thechoice for an outsider successor (adopting two different definitions: a) someone who has not been among the top managers for atleast two years before the nomination or b) someone who did not join the company at least 2 years before the nomination). Inthis case, the Q1–Q5 difference is highly statistically significant (at the 1% confidence level) for both ROA and IAROA. The resultsare the same regardless of the chosen definition of outsider successors and are consistent with the idea that when a company usesCEO 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 ourhypotheses considering both the firm-specific and peer group components of performance as explanatory variables (see alsoBertrand 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 afirm-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 aproxy for the CEO's ability, which is obviously unobservable in a direct way. To measure performance, we use an accounting-based measure (specifically, the ROA) because short-term profit measures are better predictors for CEO turnover than stockmarket 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 groupand firm-specific performance components previously obtained, our estimates of cultural dimensions, their interactions with firmspecific-performance, and some control variables to consider the characteristics of the incumbent CEO and the firm. Our approachis specified as follows:

Pleas10.1

Pi;t−1 ¼ β0 þ β1Ppeergroup;t−1 þ vi;t−1 ð1Þ

Pr CEO changei;t� �

¼ γ0 þ γ1P̂i;t−1 þ γ2v̂i;t−1 þ γ3COLi;t−1 þ γ4COLi;t−1 � v̂i;t−1 þ γ5COMi;t−1

þγ6COMi;t−1 � v̂i;t−1 þ γ7CONi;t−1 þ γ8CONi;t−1 � v̂i;t−1 þ γ9CREi;t−1

þγ10CREi;t−1 � v̂i;t−1 þXn

j¼1δ jx j;i;t−1 þ

Xmk¼1

λkzk;i;t−1 þ ςi;t

ð2Þ

P̂i;t−1 ¼ β̂0 þ β̂1Ppeergroup;t−1 is the estimated exogenous component of firm performance common to the peer group and
wherenot attributable to the CEO's actions and v̂i;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 representedby Eq. (1).
e cite this article as: Fiordelisi, F., Ricci, O., Corporate culture and CEO turnover, J. Corp. Finance (2013), http://dx.doi.org/016/j.jcorpfin.2013.11.009



Table 2Variable descriptions.

Variable Symbol Definition and calculation method

CEO turnover CEOT CEOT is a dummy variable taking the value of 1 if the company has changed its CEO with respect to theprevious 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 theprevious year with an external successor (i.e., someone who has not been among the top managers for atleast 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 theprevious year with an external successor (i.e., someone who did not join the company at least 2 yearsbefore 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 analysisCompetition-orientedculture

COMi, t COMi, t is the competition-oriented corporate culture estimate of company i at time t obtained usingtext analysis

Collaboration-orientedculture

COLi, t COLi, t is the collaboration-oriented corporate culture estimate of company i at time t obtained usingtext analysis

Creation-oriented culture CREi, t CREi, t is the creation-oriented corporate culture estimate of company i at time t obtained using text analysisReturn on assets ROA ROA is obtained by the ratio between Earnings Before Interest, Tax, Depreciation, and Amortisation

(EBITDA) and Total AssetsIndustry-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)ROA firm-specificperformance component

v̂i;t−1 v̂i;t−1 is the estimated firm-specific performance component. We follow Jenter and Kanaan (forthcoming)to disentangle the peer group component and the estimated residual component of ROA

ROAexogenous component P̂i;t−1 P̂i;t−1 is the estimated exogenous component of firm performance common to the peer group and notattributable to CEO actions. We follow Jenter and Kanaan (forthcoming) to disentangle the peer groupcomponent and the estimated residual component of ROA

Size SIZE SIZE is the industry-adjusted natural log of Total AssetsCapital expenditure CAP_EXP CAP_EXP is the industry-adjusted ratio between Total Capital Expenditure and Total AssetsLeverage LEV LEV is the industry-adjusted ratio between Total Assets and Total Common EquityFirm 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 otherwiseAge AGE AGE is the age of the CEOTenure TENURE TENURE is duration of the CEO's chargeEquity incentives EQ_INC EQ_INC is the proportion of the CEO's total compensation represented by equity incentivesCEO in the compensationcommittee

CEO_COMP_CTTE CEO_COMP_COM is a dummy variable taking the value of 1 if the CEO is listed in the compensation committeeand 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 otherwiseDuality DUALITY DUALITY is a dummy variable taking the value of 1 if the CEO is also chairman and 0 otherwiseOwnership 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 otherwiseCrisis 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 corporateculture plays a moderating role in the relationship between firm-specific performance and CEO turnover. Regarding theprediction of estimated coefficients, we expect the following. 1) γ1 = 0. We assume that the exogenous performance componentwill not affect CEO turnover, consistent with the prediction of the strong-form relative performance evaluation hypothesis (seeJenter and Kanaan, forthcoming). 2) γ2 b 0. To be a credible corporate governance instrument, the probability of CEO turnovermust be inversely related to firm-specific performance, so we expect to find a negative coefficient. 3) γ3,5,7,9 ≠ 0. Consistent withour research hypotheses, we expect that, on average, companies with a competition-, creation-, or collaboration-oriented culturehave a stronger orientation to change CEOs than companies with a control-oriented culture. At the same time, we assume thatcompanies with a competition-oriented culture have a stronger orientation to change CEOs than companies with a creation- orcollaboration-oriented culture. As a consequence, the coefficient γ5 should be positive and greater than both γ3 and γ9. At thesame 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 theprobability 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-, andcollaboration-oriented cultures have a stronger “incremental” incentive to change CEOs than companies with a control-orientedculture. At the same time, companies with a competition-oriented culture have a stronger “incremental” incentive to change CEOsthan companies with a creation- or collaboration-oriented culture. We cannot directly consider the coefficients γ4,6,8,10, but wecan analyse the value of the correct mean interaction effects. As outlined by Powers (2005), the interpretation of the interactionterm coefficients in logit and probit models (in our case, γ4,6,8,10) requires great care. Specifically, in logit and probit models of thetype turnover = f(performance, firm type, firm type ∗ performance, controls), Powers (2005) shows that the significance of the




Table 3Univariate analysis.

Q1 Q2 Q3 Q4 Q5 Q1 vs. Q5

Performance quintiles based on delta ROA in t + 1P (CEO turnover in t) 11.6% 11.0% 10.0% 10.2% 10.1%P (CEO turnover in t & Outsider_a) 42.8% 40.8% 36.2% 31.6% 29.4% ***P (CEO turnover in t & Outsider_b) 44.8% 39.7% 36.5% 31.9% 31.2% ***

Performance quintiles based on delta industry-adjusted ROA in t + 1P (CEO turnover in t) 12.4% 11.0% 9.4% 10.6% 9.9% **P (CEO turnover in t & Outsider_a) 47.8% 33.8% 33.4% 35.3% 30.6% ***P (CEO turnover in t & Outsider_b) 48.6% 34.1% 33.1% 35.6% 32.8% ***

This table presents CEO turnover and outsider succession frequencies by performance quintiles in US companies over the period 1994–2011. Performance ismeasured 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 forcompanies in the same industry group, considering the SPINDEX code in the Execucomp database). Companies without an assigned industry group are notconsidered. The outsider succession is classified based on two different definitions: a) someone who has not been among the top managers for at least two yearsbefore 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 wereobtained from Compustat and Execucomp.


interaction term coefficient may be misleading. One possibility is that the true difference in the relationship could be strongerthan is indicated by the estimated coefficient, potentially generating Type 1 errors. Alternatively, the true difference in therelationship could be weaker than is indicated by the estimated coefficient, potentially generating Type 2 errors. To overcomethis problem, we use the methodology developed by Norton et al. (2004) to compute the correct marginal effects and theirstandard errors (as in Bushman et al., 2010; Lel and Miller, 2008; Loureiro, 2010). The Norton approach allows us to obtain anunbiased estimation of the mean interaction effect and its level of statistical significance. Consistent with our researchhypotheses, 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 isreinforced) and greater in absolute value than both the mean effect for the interactions with the creation and the collaborationcultures. At the same time, all these three effects should be greater in absolute value than that relative to the control-orientedculture.

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 themodel 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 severalcultural dimensions, we also run models in which cultural variables (and their interaction with the specific performancecomponent) are included one by one. b) To account for a potential crisis effect, we also consider the performance registered by thefirm at the time t − 2. The underlying idea is that the CEO should experience more severe consequences if the poor performanceis continuative. To explore this issue, we include in the model an additional dummy variable, named CRISIS, taking the value of 1 ifthe 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 andmarginal 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 tointerpret directly in logit and probit models. As outlined in Bushman et al. (2010), the economic significance should be computedas the product of three different terms: the estimated coefficient times mean turnover density (i.e., the marginal effect) times onestandard deviation of the variable. Since our independent variables have been standardised, the economic significance is directlyobservable from the marginal effects shown in Tables 4 and 5. For interaction terms, the marginal effect is the cross-partialderivative with respect to the two interacted variables, as calculated using the delta method (Powers, 2005). In Tables 4 and 5, theinformation 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 marginaleffects calculated following Norton et al. (2004) and their significance at every predicted probability (see Fig. 2). For brevity, wefocus 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 poorperformance, 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 introductionof cultural variables as a group (model 1, Table 4) or one by one (models 1a–1d, Table 5). Furthermore, it is worth noting thatwhen we introduce the variable CRISIS (model 2), it assumes a positive coefficient, statistically significant at the 10% confidencelevel, 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.




Table 4Multivariate analysis.

CEOT = 1 (1) Coefficient (1) Marginal effect (2) Coefficient (2) Marginal effect

P̂i;t−1 −0.03557 −0.00283 −0.02855 −0.00227(0.04869) (0.00388) (0.04897) (0.00389)

v̂i;t−1 −0.15448*** −0.01229*** −0.14353*** −0.01142***(0.03563) (0.00282) (0.03593) (0.00285)

COLt − 1 −0.01690 −0.00134 −0.01602 −0.00127(0.03200) (0.00255) (0.03201) (0.00255)

COMt − 1 0.07181** 0.00571** 0.07158** 0.00569**(0.03605) (0.00287) (0.03604) (0.00287)

CONt − 1 −0.00470 −0.00037 −0.00849 −0.00068(0.03635) (0.00289) (0.03644) (0.0029)

CREt − 1 0.06316* 0.00503* 0.06318* 0.00503*(0.03230) (0.00257) (0.03229) (0.00257)

v̂i;t−1∗COLt−1 −0.03970 −0.00340 −0.03970 −0.00342(0.03477) (0.00294) (0.03469) (0.00294)

v̂i;t−1∗COMt−1 −0.00257 −0.00092 −0.00383 −0.00099(0.03277) (0.0029) (0.03261) (0.00288)

v̂i;t−1∗CONt−1 −0.08700** −0.00771** −0.08727** −0.00770**(0.04077) (0.00315) (0.04066) (0.00316)

v̂i;t−1∗CREt−1 0.06842** 0.00548* 0.06795** 0.00548*(0.03478) (0.00306) (0.03464) (0.00306)

GENDERt − 1 −0.07853 −0.00625 −0.08085 −0.00643(0.22485) (0.01789) (0.22526) (0.01791)

AGEt − 1 0.61140*** 0.04866*** 0.61143*** 0.04863***(0.05033) (0.00362) (0.05038) (0.00363)

TENUREt − 1 −0.06727** −0.00535** −0.06870** −0.00546**(0.03069) (0.00242) (0.03068) (0.00242)

EQ_INCt − 1 −0.32132*** −0.02557*** −0.32259*** −0.02566***(0.03249) (0.00255) (0.03252) (0.00255)

CEO_COMP_CTTEt − 1 −0.17845 −0.0142 −0.18374 −0.01461(0.14897) (0.01185) (0.14932) (0.01187)

EXECDIRt − 1 −1.71783*** −0.13671*** −1.71779*** −0.13663***(0.13464) (0.01084) (0.13481) (0.01084)

DUALITYt − 1 0.20614*** 0.01641*** 0.20630*** 0.01641***(0.06583) (0.00525) (0.06582) (0.00524)

SHARE_5%t − 1 −0.93436*** −0.07436*** −0.93725*** −0.07454***(0.11703) (0.00903) (0.11691) (0.00902)

SIZEt − 1 0.06848* 0.00545* 0.07075* 0.00563*(0.03665) (0.00291) (0.03667) (0.00291)

CAP_EXPt − 1 0.10604*** 0.00844*** 0.10215*** 0.00812***(0.03797) (0.00301) (0.03796) (0.00301)

LEVt − 1 −0.03047 −0.00243 −0.02982 −0.00237(0.03406) (0.00271) (0.03367) (0.00268)

FIRM_AGEt − 1 −0.04364 −0.00347 −0.04298 −0.00342(0.03340) (0.00266) (0.03345) (0.00266)

CRISIS - 0.11378* 0.00905*- (0.06545) (0.0052)

Year effects Yes YesIndustry effects Yes YesConstant −0.80484* −0.82134**

(0.41423) (0.41445)Observations 14,347 14,347R-squared 0.0821 0.0824

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 oncontemporaneous industry ROA. The predicted values and errors from this regression are used to disentangle firm performance into specific and systematiccomponents. 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 theprobability of a CEO turnover for a unit change in the explanatory variable, holding other variables at the mean values. For interaction terms, margins arecalculated 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 CEOsincreases).

The most interesting result we show is that different corporate cultures have a different impact on the probability of changinga CEO. First, we find that both H2 (companies with a competition-, creation-, or collaboration-oriented culture have a strongerorientation to change CEOs than companies with a control-oriented culture) and H3 (companies with a competition-oriented culturehave a stronger orientation to change CEOs than companies with a creation- or collaboration-oriented culture) are substantiallyconfirmed. The coefficients for the competition- and creation-oriented cultures are positive, statistically significant (at the 5% and





10% confidence levels, respectively), and greater than that for the collaboration-oriented culture (not significantly different fromzero), as predicted by H2. However, the effect of the collaboration-oriented culture is negative and not statistically significant at the10% 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 thehypotheses 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, companieswith a competition-oriented culture have a stronger “incremental” incentive to change CEOs than companies with a creation- orcollaboration-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- andcompetition-oriented cultures. As shown in Fig. 2, the corrected interaction effects for the control-oriented culture areoverwhelmingly negative across predicted probabilities and also significant for most probabilities. Being negative, the interactionreinforces the inverse relationship between firm-specific performance and CEO turnover. In addition, the coefficient and the meaninteraction effect for the creation-oriented culture are positive and statistically significant at the 10% confidence level. As shownin Fig. 2, the corrected interaction effects for the creation-oriented culture are overwhelmingly positive across predictedprobabilities and also significant for most probabilities. Because the interaction effect is generally positive, and then of oppositesign 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% confidencelevel: 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 tenyears). 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 anexecutive 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) andthe 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 themain 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 performanceconsequences of top executive successions and, more recently, under which circumstances succession benefits or disrupts firmperformance (see Ansari et al., forthcoming for a recent paper and Karaevli, 2007 for a review). Our perspective is different from thatof 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 predictedthat external CEO succession would be chosen when organisations perform poorly and need a strategic change, while internal CEOsuccession is preferred when organisations desire continuity (for a review, see Karaevli, 2007). As such, our hypothesis is that, asfirm-specific performance declines, the probability of external CEO succession increases. This hypothesis is somehowmediated by theorganisational culture.

The collaboration-oriented culture is based on cohesion and support and, as such, the board would be reluctant to replace theleaderwith an outsider, even in the case of poor performance. Similarly, in high-control firms, the boardwould be reluctant to addressproblems by replacing the leader of a very hierarchical system. Turning to external-oriented cultures, competition-orientedcompanies should tolerate change and instability and even trumpet these values, especially in case of poor performance, e.g., byselecting 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, thebusiness of these companies is founded on creativity, knowledge, and agility that are often firm-specific and cannot be easily found inother companies, so that the boardmay not be inclined to replace the leaderwith anoutsider, whomay have a different view,8 even inthe case of poor performance.9

To test these hypotheses, we conduct a further empirical investigation. With reference to the subsample of year-observationsin which a CEO turnover has occurred, we construct two different dummy variables (Outsider_a and Outsider_b), which take thevalue 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.8 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 managersto 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 atournament succession. In addition, in comparison with firms with tournament succession, firms with a successor-incentive promotion are more likely toexperience a turnover, but the turnover is less sensitive to performance, consistently with the greater difficulty in replacing the CEO.




Table 5Multivariate analysis: Robustness check.

CEOT = 1 (1a) Coefficient (1a) Marginal effect (1b) Coefficient (1b) Marginal effect (1c) Coefficient (1c) Marginal effect (1d) Coefficient (1d) Marginal effect

P̂i;t−1 −0.03616 −0.00289 −0.03402 −0.00272 −0.04028 −0.00322 −0.03208 −0.00256(0.04797) (0.00384) (0.04840) (0.00387) (0.04811) (0.00384) (0.04784) (0.00382)

v̂i;t−1 −0.15517*** −0.01241*** −0.15342*** −0.01226*** −0.15187*** −0.01214*** −0.15233*** −0.01216***(0.03429) (0.00273) (0.03509) (0.00279) (0.03453) (0.00275) (0.03404) (0.00271)

COLt − 1 0.02219 0.00177(0.02862) (0.00229)

COMt − 1 0.08010*** 0.0064***(0.02978) (0.00238)

CONt − 1 0.02341 0.00187(0.03437) (0.00275)

CREt − 1 0.08561*** 0.00683***(0.02846) (0.00227)

v̂i;t−1∗COLt−1 −0.03369 −0.00324(0.03063) (0.00264)

v̂i;t−1∗COMt−1 −0.01460 −0.00208(0.02825) (0.00274)

v̂i;t−1∗CONt−1 −0.09043** −0.0083**(0.04057) (0.003401)

v̂i;t−1∗CREt−1 0.04417* 0.00312(0.02486) (0.00265)

GENDERt − 1 −0.08359 −0.00669 −0.08498 −0.00679 −0.09146 −0.00731 −0.07929 −0.00633(0.22424) (0.01793) (0.22422) (0.01791) (0.22425) (0.01791) (0.22352) (0.01784)

AGEt − 1 0.60564*** 0.04844*** 0.61044*** 0.04878*** 0.60271*** 0.04816*** 0.60717*** 0.04847***(0.05005) (0.00363) (0.05025) (0.00364) (0.05019) (0.00364) (0.05024) (0.00363)

12F.Fiordelisi,O

.Ricci/JournalofCorporate

Financexxx

(2013)xxx–xxx

Pleasecite

thisarticle

as:Fiordelisi,F.,Ricci,O

.,Corporateculture

andCEO

turnover,J.Corp.Finance(2013),http://dx.doi.org/

10.1016/j.jcorpfin.2013.11.009



TENUREt − 1 −0.06489** −0.00519** −0.06762** −0.0054** −0.06366** −0.00509** −0.06258** −0.005**(0.03043) (0.00242) (0.03055) (0.00242) (0.03053) (0.00242) (0.03053) (0.00242)

EQ_INCt − 1 −0.31809*** −0.02544*** −0.31884*** −0.02548*** −0.31841*** −0.02544*** −0.31978*** −0.02553***(0.03244) (0.00256) (0.03246) (0.00256) (0.03243) (0.00256) (0.03242) (0.00255)

CEO_COMP_CTTEt − 1 −0.17911 −0.01433 −0.18205 −0.01455 −0.18070 −0.01444 −0.17168 −0.01371(0.14956) (0.01195) (0.14935) (0.01193) (0.14931) (0.01192) (0.14907) (0.01189)

EXECDIRt − 1 −1.71707*** −0.13734*** −1.71552*** −0.1371*** −1.71348*** −0.13693*** −1.71354*** −0.13679***(0.13445) (0.01088) (0.13499) (0.01092) (0.13470) (0.01089) (0.13377) (0.01079)

DUALITYt − 1 0.20565*** 0.01645*** 0.20533*** 0.01641*** 0.20707*** 0.01655*** 0.20334*** 0.01623***(0.06587) (0.00528) (0.06587) (0.00527) (0.06586) (0.00527) (0.06577) (0.00526)

SHARE_5%t − 1 −0.93455*** −0.07475*** −0.93423*** −0.07466*** −0.93613*** −0.07481*** −0.94681*** −0.07558***(0.11675) (0.00905) (0.11671) (0.00904) (0.11670) (0.00904) (0.11715) (0.00906)

SIZEt − 1 0.06167* 0.00493* 0.07099* 0.00567* 0.06899* 0.00551* 0.06011* 0.0048*(0.03642) (0.00291) (0.03654) (0.00292) (0.03650) (0.00291) (0.03629) (0.00289)

CAP_EXPt − 1 0.10706*** 0.00856*** 0.10681*** 0.00854*** 0.10319*** 0.00825*** 0.10196*** 0.00814***(0.03787) (0.00302) (0.03779) (0.00301) (0.03784) (0.00301) (0.03749) (0.00298)

LEVt − 1 −0.03368 −0.00269 −0.03021 −0.00241 −0.03287 −0.00263 −0.03089 −0.00247(0.03714) (0.00297) (0.03335) (0.00267) (0.03688) (0.00295) (0.03483) (0.00278)

FIRM_AGEt − 1 −0.04250 −0.0034 −0.03873 −0.0031 −0.04791 −0.00383 −0.04131 −0.0033(0.03303) (0.00264) (0.03307) (0.00264) (0.03314) (0.00265) (0.03298) (0.00263)

Year effects Yes Yes Yes YesIndustry effects Yes Yes Yes YesConstant −0.81462** −0.78839* −0.79420* −0.86211**

(0.41250) (0.41277) (0.41264) (0.41296)Observations 14,347 14,347 14,347 14,347R-squared 0.0801 0.0806 0.0805 0.0809

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 anderrors 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 standarderrors are in parentheses. ***, **, * indicate statistical significance at the 1, 5, and 10% levels, respectively. Source: Authors' elaboration of Execucomp data.

13F.Fiordelisi,O

.Ricci/JournalofCorporate

Financexxx

(2013)xxx–xxx

Pleasecite

thisarticle

as:Fiordelisi,F.,Ricci,O

.,Corporateculture

andCEO

turnover,J.Corp.Finance(2013),http://dx.doi.org/

10.1016/j.jcorpfin.2013.11.009



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.



image of Fig.�2




has not been among the top managers for at least two years before the nomination or b) someone who did not join the companyat 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 hasbeen a turnover, there might be a sample selection problem. To overcome this issue, after the OLS regression decomposes firmperformance into specific and systematic components, we adopt an Heckman procedure in which both the selection and theprincipal 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 inthe 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 theincumbent 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, confirmingour hypothesis that, as firm-specific performance declines, the probability of external CEO succession increases. With reference tocultural dimensions, we show that, on average, companies oriented toward creation are more likely to select an insider. Linkingthis result with findings from the turnover analysis, this suggests that innovative companies encourage changes in top manage-ment but prefer that the successor is someone grown inside the company, with the same culture and know-how. This isreasonable if we consider that the way of doing business and the necessary knowledge can be very specific in such companies. Atthe same time, we find statistically significant evidence that the creation-oriented culture weakens the relationship between thepoor performance of the incumbent CEO and the choice of an outsider successor. This may be a further signal that innovativecompanies 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 theopposite 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 andperformance pre-turnover. Our paper is the first to provide empirical evidence using a large dataset (US listed companies from1994 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 ROAcomponent 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 ofchanging CEOs. First, the probability of CEO turnover, on average, increases in the case of a corporate culture oriented towardcompetition (i.e., focusing on emphasising organisational effectiveness and fast response) or creation (i.e., focusing on generatingfuture opportunities through innovation). Second, we show that companies with a competition-oriented culture have the strongestorientation to change CEOs. When we assess what happens in the case of poor past performance, we find that the negativerelationship between firm-specific performance and CEO turnover is reinforced by a culture oriented toward control (i.e., focusing oninternal improvements in efficiency through the implementation of better processes) and reduced by a culture oriented towardcreation. We also find that CEO turnover is more likely as the CEO becomes older (and thus closer to retirement age) and when theCEO is also a chairman (e.g., duality has been discouraged by most corporate governance rules and best practices, especially over thelast 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 equityincentives is less probable.

We complement our analysis of CEO turnover by adding a further investigation on succession type (internal vs. external). Weshow a negative relationship between the past performance of the incumbent CEO and the choice for an outsider, confirming ourhypothesis that, as firm-specific performance declines, the probability of external CEO succession increases. We also show thatcompanies oriented toward creation are more likely to select an insider. At the same time, the creation-oriented culture typeweakens 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 havevery limited information on both the predecessor and the new CEO, e.g., their origin, education, and previous experience. Thistype of data might help to better explain the moderating role of corporate culture. In addition to this limitation, we believe thatcultural variables are likely crucial in not only determining the probability of dismissal for poor results but also influencing theopinions on the current CEO, regardless performance, and directing the choice for a successor that best fits the corporateorientation. Further investigations should be devoted to enriching the database and exploring these issues. Second, it would beinteresting 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 isprobable that a cultural approach is able to offer interesting results if applied to top managers other than the CEO, as the upper-echelons perspective suggests.

In conclusion, this study represents a first step toward opening a new perspective in the literature, contributing to studiesexamining 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.




Table 6Investigating succession type: Insider vs. outsider.

Y = OUT_A Y = CEOT Y = OUT_B Y = CEOT

P̂i;t−1 −0.05491 −0.01579 −0.04309 −0.01578(0.05678) (0.02438) (0.05636) (0.02438)

v̂i;t−1 −0.19219*** −0.07280*** −0.18527*** −0.07282***(0.03676) (0.01673) (0.03669) (0.01673)

COLt − 1 0.00370 −0.00792 0.00731 −0.00790(0.04189) (0.01763) (0.04185) (0.01763)

COMt − 1 0.03635 0.03933** 0.04719 0.03931**(0.04345) (0.01913) (0.04344) (0.01913)

CONt − 1 0.00374 0.00031 0.00096 0.00034(0.04690) (0.01968) (0.04682) (0.01968)

CREt − 1 −0.08667** 0.03210* −0.08841** 0.03214*(0.04159) (0.01816) (0.04173) (0.01816)

v̂i;t−1∗COLt−1 −0.03784 −0.01851 −0.03864 −0.01855(0.03635) (0.01690) (0.03628) (0.01690)

v̂i;t−1∗COMt−1 0.05291 −0.00365 0.04982 −0.00361(0.03606) (0.01592) (0.03600) (0.01592)

v̂i;t−1∗CONt−1 0.00096 −0.04766** 0.00061 −0.04765**(0.04596) (0.02002) (0.04578) (0.02002)

v̂i;t−1∗CREt−1 0.06417* 0.03254* 0.06419* 0.03253*(0.03904) (0.01756) (0.03905) (0.01756)

AGEt − 1 0.28051*** 0.28074***(0.01759) (0.01758)

GENDERt − 1 −0.01792 −0.01726(0.11245) (0.11246)

TENUREt − 1 −0.01833 −0.01803(0.01634) (0.01634)

EQUITY_INCt − 1 −0.16497*** −0.16448***(0.01609) (0.01611)

CEO_COMP_CTTE t − 1 −0.07987 −0.07906(0.07549) (0.07545)

EXECDIRt − 1 −0.93556*** −0.93512***(0.08091) (0.08081)

DUALITYt − 1 0.12026*** 0.12054***(0.03349) (0.03348)

SHARE_5%t − 1 −0.45049*** −0.45040***(0.05445) (0.05443)

SIZEt − 1 −0.14721*** 0.03538* −0.14013*** 0.03527*(0.04181) (0.01857) (0.04182) (0.01857)

CAPITAL_EXPt − 1 0.05461 0.04781** 0.04768 0.04775**(0.04370) (0.01873) (0.04376) (0.01873)

LEVERAGEt − 1 0.57340** −0.02029 0.55609** −0.02025(0.25238) (0.04216) (0.25229) (0.04211)

FIRM_AGEt − 1 −0.05505 −0.02486 −0.03032 −0.02491(0.04041) (0.01782) (0.04042) (0.01782)

CRISIS 0.00076 0.05865* 0.00779 0.05863*(0.07923) (0.03483) (0.07913) (0.03483)

Year effects Yes Yes Yes YesIndustry effects Yes Yes Yes YesConstant −0.01657 −0.51926** −0.03907 −0.52041**

(0.43660) (0.21096) (0.43620) (0.21093)Observations 14,347 14,347Uncensored observation 1540 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 predictedvalues and errors from this regression are used to disentangle firm performance into specific and systematic components. Second, we run a selection probit modelpredicting CEO turnover. Finally, we run a probit model predicting succession by an outsider based on two different definitions: a) someone who has not beenamong 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. Allregressors 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 veryconstructive 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, andTom Weyman Jones, for their helpful comments. We are also grateful to the Financial Intermediation Network of EuropeanStudies (FINEST) seminar participants at the University of Rome III and the Free University of Bozen. We would like to give specialthanks to Anjan Thakor for his continuous support and great suggestions. Franco Fiordelisi also wishes to acknowledge the





support of the Fulbright Commission and the Olin Business School of Washington University in St. Louis, US. We alone areresponsible for any remaining errors.

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