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The influence of CEO Power on
acquisition outcomes and the moderating
effect of national culture
MScBA SIM Thesis by Deon Frans de Beus s1681915
Supervisor dr. K.J. McCarthy Second supervisor R. A. van der Eijk Rijksuniversiteit Groningen
ABSTRACT
A CEO has a lot of, if not the most, influence on strategic firm decisions, acquisition deals included. Acquisitions can lead to firm growth and are means to entering new markets, and show to be of more importance to firms the last decades. To keep CEOs actions in line with shareholders interest, boards of directors govern and monitor firms. Some CEOs have more influence over the board than others, and can therefore choose for personal gains over firm interest. With data on 1142 acquisitions deals over a 10 year timeframe (2002-2012), along with acquirer firm specifics, CEO and board data, this study examines the differences in acquisition decisions and firm performance around the
announcement date between distinct CEO power groups. The findings suggest that CEOs with more influence over the board of directors will tend to pursue less risky acquisition deals in general than CEOs that have a small amount of power, which is in line with agency theory, frequently used by scholars in previous literature on CEO power. There is also a significant lower firm performance in the least powerful CEO group compared to the rest of the sample, based on the abnormal cumulative returns. To account for the influence of national culture, Hofstede’s cultural dimensions (1984) are integrated. Two out of the four Hofstede’s cultural dimensions moderate the relation of CEO power and M&A choices, emphasizing the importance of accounting for national culture when dealing with powerful CEOs.
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1. Introduction
With the ever increasing competition in nearly every industry, firms are constantly on the lookout for growth and expansion to secure the firm’s revenue and its future. Research on acquisitions during the last decade of the previous century shows an exponential increase in growth through acquisitions, across several - if not all - industries (Hollowell & Bossen, 2013; Boateng et al, 2011). The nature of the acquisitions also changed over time, resulting in more and more cross-border M&A activities in the last decades, due to several enabling factors such as the internet communication technology, the loosening of market regulation policies (Zou & Simpson, 2008) and the establishment of economic unities such as the EU (Coeurdacier et al, 2009). These changing circumstances simplified the cross-border acquisitions for acquiring firms, by easing the process itself, as well as the risk accompanied with a foreign takeover. Although the financial crisis of 2007-08 has caused a decline in the M&A volume globally (as can be seen in the diagram below), M&A is still a very important activity for firms in recent years (Ferris et al, 2013).
Source: Thomson Reuters, 2013
1.1 Ambiguous findings
Multiple empirical evidence shows no consensus on the impact on firm’s financial performance through acquisitions; Stiebale & Trax (2011) find cross-border acquisitions to improve the firm domestic performance in the U.K. and France, while others point out that besides the financial performance gain, there is also a boost in productivity and efficiency (Siegel & Simons, 2010). However, negative relations with post-acquisition firm performance are also abundantly found by scholars; Leepsa & Mishra (2013) discover more failures than successes in companies who adopt M&A strategies, by looking at post-M&A return over a three year period. Earlier research of Bekier et al (2001) also shows this negative relationship with very low success rates of acquisitions of only 12 %, based on revenue growth compared to their peers and industry average over a period of three years post M&A. Firms might even use acquisitions as a tool to counterattack competitors that pose a threat to the firm. Keil et al (2013) their results show that different types of acquisitions can be incorporated in strategic decisions, based on the actions of rivals and the preferred outcome.
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& Conroy, 2013; Billett & Qian, 2008) emphasize the importance of soft-coded characteristics of a CEO, particularly overconfidence. But factors linked to the CEO will only be evident if the CEO has the ability (power) to implement his or her preferences. And even so, having the ability might not always mean that CEOs actually act on their preferences; previous scholars (Hofstede, 1993; Berson et al, 2008; Lertxundi and Landeta, 2011) provide evidence that national culture has an impact on the actions of individuals, which is why this research includes national culture as a possible moderating factor on the relationship of CEO power and M&A decisions and performance, in the form of Hofstede’s four cultural dimensions (1984). This reasoning leads to the following research question:
In what way does CEO Power influence the acquisition decisions a CEO
pursues, and (how) is this effect moderated by a CEO’s cultural background?
There are limited empirical studies on the effect of CEO power on the M&A decisions and their subsequent effect on firm performance caused by these M&A’s. These studies are mostly on North-American and Australian firms (Brown & Sarma, 2007; Bugeja et al, 2012; Dutta et al, 2011; Seth et al, 2000). This paper addresses this research gap by empirically researching this phenomenon across mainly European markets, to test whether results shown in previous empirical studies also hold up for the selected firms in European countries and industries and to identify potential new relations that are of influence, accounting for the possible moderating effect of national culture, as argued by Hofstede (1984; 1993).
This paper is structured as follows: in the next section the previous literature on CEO power and M&A decisions and performance is reviewed and hypotheses are constructed based on multiple dimensions of acquisition decisions. Chapter 3 contains the methodology of the research, with information on the data set, sample, and measures. Then, the results are presented and hypotheses tested. Next is the discussion of the results, leading up to the conclusion of this paper.
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2. Theory
2.1 Why CEO’s matter
From day-to-day activities to long term strategic planning, CEOs are the decision makers and are in the end responsible for the targets attained and results achieved of their firm. In publicly traded companies, corporate governance in the form of a board of directors is the mechanism with which CEOs are kept in line and can be held responsible for their actions. However, not every board of directors has the same influence over a CEO, due to the relation and linkages a CEO has with the board. Boards with a high percentage of insiders, a chairman role for the CEO and a long-sitting CEO for example, exhibit less power over a CEO than more sovereign boards (Core et al, 1999; Haynes & Hillman, 2010; Zhang, 2013), thus resulting in less influence on CEO decisions and more powerful CEOs being able to exert their will better than their less powerful colleagues. Powerful CEOs are assumed to impact firm performance, but the direction of this impact is not conclusive (Daily & Johnson, 1997). There is even a possibility that, through his or her actions, achievements and press coverage, a CEO might turn overconfident. This can lead to the CEO celebrity effect, shown by Hayward et al (2004), which is often detrimental to the firm performance through poor decisions caused by hubris. All in all, CEOs are important agents that influence or even fully determine a firm’s future path and therefore the extent to which CEOs can exert their will over others, such as the board of directors is highly important.
2.2 CEO power
To determine the power a CEO has over its board and resulting decisions, previous research uses a CEO power index, as is done by Grinstein & Hribar (2004), Henderson et al (2010) and Morse et al (2011). This CEO power index is constructed out of multiple (usually 3 or more) dichotomous variables relating to the CEO and his or her influential relations with the board. Grinstein & Hribar (2004) label this ‘managerial power’ and construct their index based on CEO duality (1), whether or not the CEO is on the nominating committee of new board members (2), the ratio of inside directors to total directors(3) and the total number of board members in relation to the median of the sample size(4). Beiner et al (2004) also show board size to be a corporate governance mechanism to keep a CEO in check. Henderson et al (2010) also use CEO duality and complement this with CEO tenure and CEO centrality. They define CEO tenure as the number of years the CEO has been in office, which according to them ‘represents the CEOs accumulated ability to influence the board’. The final variable Henderson et al use is the CEO centrality – the compensation of the CEO as a percentage of the top 5 directors on the board. However, they argue that CEO centrality is more of a complementary variable, as the power of a CEO might already be reflected in their compensation, through CEO power stemming from previous years compensation negotiations with the board. Similar to Grinstein & Hribar (2004) and Henderson et al (2010), Morse et al (2011) solely use CEO duality as an indicator for their CEO power index, but expand CEO duality as they include an extra index point when the CEO is chairman and also the company’s president. They argue that this way, ‘the board is unable to have an in-training successor that they might tap if disagreement with the CEO ensues’. However, in Morse et al (2011) their research, the CEO power index is just one part of the CEO power construct. Just as Grinstein & Hribar (2004), the inside director ratio is another determinant of CEO power in the research performed by Morse et al (2011). A new variable is also introduced, having partial links with CEO tenure; the percentage of the board appointed during the CEOs tenure. They argue that board members appointed during a CEOs sitting term might feel obligated toward the current CEO, and will therefore be more inclined to agree with the CEO. Previous research (Grinstein & Hribar, 2004; Henderson et al, 2010; Morse et al, 2011) shows that these power measures are conclusive
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H1 The CEO power measures are correlated and are determinants for the degree to which a CEO can exert his or her will over the board of directors.
2.3 M&A decisions
CEOs and the agency problem
A CEO is, as an individual, responsible for the well-being of a firm and its shareholders, but also for satisfying his or her own needs. This can often lead to personal conflicts of interest, balancing between personal priorities and shareholder/firm goals. Drawing on agency theory (Eisenhardt, 1989), I argue that CEOs will act out of self-preservation. This is likely to conflict with the interests of other
stakeholders of the firm. CEOs tend to choose high personal (bonus) compensation with the least risk possible to endanger their own position and future in a firm. These practices of CEOs have an impact on the decisions regarding M&A, and might lead to favouring some specific deals over others. With known high agency problems within a firm, boards tend to use incentives aligned with preferred M&A activities, to trigger powerful CEOs to act in the interest of the shareholders, even though that is not the CEO’s main motive – the incentive is (Bodolica & Spraggon, 2009). Combs et al (2007) show that CEO Power is a powerful moderator on the relation of board composition and firm performance. The influence a CEO has is therefore of high importance for the acquisitions decisions made and
subsequent firm-results attained.
Frequency
Building on the agency theory (Eisenhardt, 1989), CEOs will always be on the search for opportunities to secure personal gains, also (or especially) through corporate opportunities such as acquisition activities. In essence, acquisitions enlarge firm size and the bigger the firm the higher the CEO compensation (Hallock, 2011); a 10% increase in the size of a firm will result in a 3% increase in the compensation of the CEO. Thus if CEO get their way, I expect more acquisitions when a CEO has a higher influence over the board of directors. Therefore I hypothesize that:
H2 Powerful CEOs pursue more acquisitions than less-powerful CEOs
But there is also another argument regarding agency theory, which suggests that CEOs minimize risk in order to maintain status quo (Jensen & Meckling, 1976). Acquisitions are inherently accompanied with firm-risk; first of all there is the risk of unsuccessful acquisitions, resulting in failure or
divestment of the acquisition, which might lead to poor performance of the acquiring firm. A CEO can be held responsible for the attained results and this can jeopardize his or her position. Second, even if the acquisition itself is successful, shareholders might not agree with the chosen path and lose their confidence in the current chief executive. Finally, even if shareholders agree and the acquisition is proven to be in the interest of the acquiring firm, the structuring (financing) and the consequences of an acquisition might hinder the operating strength and or core business of a firm. In light of the agency theory, I argue that CEOs tend to choose risk-averse, and therefore avoid any acquisitions if possible: H3 Powerful CEOs pursue less acquisitions than less-powerful CEOs
Building the agency theory, I would generally expect CEOs to avoid the most risk if possible when making M&A decisions. On the one hand this can be tracked back to the number of acquisitions they make, but also in what kind of acquisitions they choose to pursue. For determining the exact risk of an acquisition, I look at three different aspects of an acquisition that highly impact the risk accompanied with an acquisition (Kroll et al, 2007; Ferris et al, 2013; Peng & Fang, 2010); diversification,
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Diversification
Acquisitions can be made for different purposes; the acquirer tends to acquire a larger market share in the current industry through related acquisition or might venture into new unknown territory through diversifying acquisitions, by acquiring targets in different sub-industries or entirely different industries than the acquiring firm operates in currently. Kaplan & Weisbach (1992) show there is a higher divesture rate of diversifying acquisitions than related acquisitions. Although they argue that
diversification is not by definition less successful, a higher divesture rate in diversifying acquisitions shows the risk of this type of acquisition is higher than that of related acquisitions. This effect is somewhat moderated by the experience of the CEO; Custodio & Metzger (2013) show significant higher abnormal announcement returns for diversifying acquisitions made by experienced CEOs than by inexperienced CEOs in the target industry. Experienced CEOs are better in capturing the deal’s surplus and/or paying a low premium for the target firm. Brown & Sarma (2007) argue that dominant CEOs are more likely to pursue diversifying acquisition, due to the higher personal benefits. Although the higher risk accompanied with non-related acquisitions moderates this effect, the incentive linked to diversifying acquisitions remains for CEOs, therefore I hypothesize that:
H4 Powerful CEOs pursue more diversifying acquisitions than less-powerful CEOs
Globalization
Foreign acquisitions lead to higher CEO compensation packages than domestic acquisitions (Ozkan, 2012). This relation is not moderated by the actual performance of the acquisition, which might favour CEOs to choose foreign M&A activity over domestic, due to the higher personal rewards concerned with acquisitions across borders. In this line of thought, I argue that CEOs will always go for foreign acquisitions if possible, instead of domestic. Fortunately for the shareholders of public companies, the board of directors govern the organisation and review the performance of the CEO, and can also hold the CEO accountable for his or her actions regarding M&A activity. The power a board has over its CEO is therefore argued to be a moderating factor in the actual executing of a CEO’s preference for a foreign acquisition over a domestic one. However, this does not mean a less powerful CEO will never take on a foreign acquisition, but will only do so if the board of directors agrees with this choice of foreign acquisition target. Seth et al (2000) point out that the most important motive for foreign acquisition the synergy effect is. Overconfidence and the actual ability of the CEO to exert his or her will is a second motive for acquiring firms abroad. This is mostly fuelled by the empire/legacy building intention of the CEO. There is a slightly higher risk inclined with foreign acquisitions, which – when the acquisition fails – leads to higher CEO turnover post-acquisition than with domestic acquisitions (Krug & Hegarty, 1997). This risk can be countered by CEOs through measures such as employment contracts and might therefore diminish. More powerful CEOs are expected to be able to exert their will over the board of directors better than less powerful CEOs and go for more foreign acquisitions, therefore I hypothesize that:
H5 Powerful CEOs will pursue more foreign acquisitions than less-powerful CEOs
Hostility
In a perfect world, every acquisition would be executed with both the target as the acquiring firm in agreement. However, not every target firm is waiting to be taken over by the acquirer. In hostile takeovers, often the acquirer uses take-over bids or the acquisition negotiations do not result in an agreement, leading to an acquisition without consent of the target firm. This can be done by purchasing 100% percent of the publicly traded stocks of the target firm, with the approval of
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H6 Powerful CEOs will pursue less hostile acquisitions than less-powerful CEOs
Risk
Overall, in line with agency theory, I expect CEOs to be risk-averse in general, motivated by self-preservation (Lewellen et al, 1989). As discussed above, the risk of an acquisition is composed by different factors related to the type of acquisition. Looking at these factors separately, the risk of each factor can be compensated, countered or overthrown by the potential benefits of the specific factor. When looking at risk in general, Zhao (2013) states that CEOs will only pursue riskier deals when an employment contract for the CEO is in place, regardless of the success or failure of the acquisition. Earlier research of Lehn & Zhao (2006) also points out that CEO turnover post-acquisition through poor CEO performance might scare off CEOs to pursue risky deals. Powerful CEOs are better able to avert risk by having more influence over the board and ultimate executive decisions, therefore I hypothesize that:
H7 Powerful CEOs pursue risk-averse acquisitions than less-powerful CEOs
Previous research has pointed out that more powerful CEOs do not necessarily pursue acquisitions with higher absolute values than their less powerful counterparts (Grinstein & Hribar, 2004), but the deal value ratio to the total assets of the acquiring firm is found to be significantly higher with powerful CEOs. Grinstein & Hribar (2004) also found that an increase in deal value results in a significant increase in CEO compensation. Based on the agency theory, I argue that CEOs prefer higher compensation and will therefore choose larger relative deals over smaller ones. Powerful CEOs are better able to exert their will, therefore I hypothesize that:
H8 Powerful CEOs pursue acquisitions with a higher deal value to total assets than less-powerful CEOs
Performance
CEOs are expected to maximize short- to medium- performance post-acquisitions, due to the fact that their compensation is largely correlated with the (positive) results of their decisions. So although the agency problem arises when CEOs have to choose between their own compensation and the
performance of their firm, this is in practice never this black and white. Daily & Johnson (1997) already showed that CEO power and firm performance are interrelated and in some cases the former causes the latter and vice versa. Others, such as Harford & Li (2007) have found that CEOs might not be harmed by poor performance, in terms of compensation. But on the contrary, they are rewarded through compensation whenever there is positive performance of an acquisition.
There are however others (Jiraporn et al, 2012) that argue that dominant CEOs negatively affect firm performance and value, due to agency costs. But these studies do not account for CEO ownership and might therefore have skewed results. Bhagat & Bolton (2013) show that director ownership is of importance when looking at the relation between power and performance. It might not come as a surprise that when a CEO profits from strong firm value (share prices) through ownership
constructions, he or she might be more driven to secure value-enhancing acquisition for the entire firm, instead of just his or her personal win. Therefore I hypothesize that:
H9 Powerful CEOs pursue more value-enhancing acquisitions than less-powerful CEOs
Cultural dimensions
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extensively on his work to identify the impact of national culture on various managerial issues, also regarding CEO choices and firm performance; Grenness et al (2011) use the Power distance and the Individualism dimensions to explain salary gaps and CEO remuneration in different countries, which is backed up by earlier work of Tosi & Greckhamer (2004), who conclude that ‘cultural dimensions can contribute to understanding cross-national CEO compensation. Others, such as Berson et al (2008) and Lertxundi & Landeta (2011) link national culture with firm performance in terms of sales growth, efficiency and employee satisfaction. Jackofsky et al (1988) also state the importance of national culture on a CEOs behaviour and emphasize that previous research somewhat neglects the apparent relations. To account for this possible moderator, this study includes the four Hofstede’s cultural dimensions.
Individualism
This first dimension is ‘the degree to which people in a country prefer to act as individuals rather than as members of groups’ (Hofstede, 1993). A high degree of individualism is associated with ‘I’
thinking, rather than ‘We’. CEO’s that have a high degree of power in their organization are to a great extent able to act on their own belief. Pursuing personal benefits however, can be moderated by the degree of individualism the CEO’s national culture has, and therefore taking into account the needs of the stakeholders of an organisation.
H10 The degree of Individualism will affect the M&A decisions that powerful CEOs make. Power Distance
Power among organizations and institutions is often unequally distributed. The extent to which the members of a society accept this distance in power, is the second cultural dimension (Hofstede, 1984). Behaviour of members is affected by this power distance through the justification people seek. If there is a large power distance, people accept the fact that a hierarchical order exists and that power is divided unequally. In societies with a lower power distance, members tend to attain power equality and they do not easily accept hierarchical orders in society, organizations and institutions. CEO’s with a high degree of power, operating in a society that strives for power equality (low power distance culture), might spend a lot of time battling individuals on their decisions, because people do not acknowledge the CEO’s authority.
H11 The degree of Power Distance will affect the M&A decisions that powerful CEOs make. Uncertainty avoidance
This dimensions accounts for ‘the degree to which members of a society feel uncomfortable with uncertainty and ambiguity’ (Hofstede, 1984). In societies with a strong uncertainty avoidance, people tend to enforce codes and procedures that diminish the uncertainty of the future. Persons or
organizations that deviate from these codes are frowned upon and intolerated by society, which might cause the board or other members of the organisation to disagree with the decisions a CEO makes regarding the (uncertain) future of their firm. Therefore I argue that:
H12 The degree of Uncertainty avoidance will affect the M&A decisions that powerful CEOs make. Masculinity
Hofstede (1984) concludes with the Masculinity versus Femininity cultural dimension, where masculinity stands for a preference for achievement, heroism, assertiveness, and material success. Femininity on the other hand, emphasizes the importance of relationships, modesty, caring for the weak, and the quality of life. As Hofstede in 1984 already argued, an organization and especially the top management of an organizations is comprised of men, and therefore often already leaning towards masculinity. Masculinity also has a preference for achievement and material success, which leads me to argue that
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However, it is important to note that men can also be feminine, and women masculine, but as
masculinity shares some of its characteristics with powerful CEOs (heroism, assertiveness), I suspect that the impact of this cultural dimension is more difficult to measure in this study, as CEOs are through their position inherently leaning towards masculinity.
2.4 Conceptual model
As argued, CEO Power is expected to have a particular effect on the decisions regarding acquisitions. High CEO Power is expected to yield less risky acquisitions, based on a composite of globalization, diversification and hostility. However, these single variables may vary among CEO Power groups, therefore this study also tends to show relations for CEO Power and the single variables. Powerful CEOs are thought to go for relatively larger deals, due to the larger compensation packages and are expected to enhance firm performance. Firms performing well, allocate larger bonuses to top
management as well as prolonging of their contracts, motivating a CEO to focus on short- to medium-term performance. Previous literature has ambiguous findings on the number of acquisitions more powerful CEOs pursue. This study aims to find results on the acquisition frequency related to CEO Power to further clarify this relation. Hofstede’s (1984) four cultural dimensions are included as moderating variables, together forming the construct national culture. The impact of each cultural dimension on the relations between CEO Power and the dependent variables are tested, to determine the moderating effect of a CEO’s cultural beliefs.
CEO Power
Acquisition risk
Firm performance
National culture
Acquisitions frequency
Globalization
Diversification
Hostility
+/-
+/-
+/-
+
Relative deal size
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3. Methodology
3.1 Data
From the Thomson Reuters Securities Data Company’s database, I collected a sample of acquisition announcements, with the following selection criteria: (1) The announcements were between January 1, 2002 and December 31, 2012; (2) regarded publicly disclosed transactions; (3) with a deal value equal to or greater than 10 million USD; (4) with the acquirer taking a 100% stake in the target firm; (5) including all deal statuses (completed/pending/withdrawn); (6) excluding acquiring firms from the north-American region and (7) those operating in the financial industry, because high-leverage, risk factors and corresponding high betas are often a common practice in the financial industry (Foerster & Sapp, 2005), skewing the results. This sample contained over 10,000 acquisitions deals for the chosen timeframe. These deals were matched with the data from the BoardEx database, based on the year the acquisition was announced. If the BoardEx database contained complete data on the CEO and board of directors’ characteristics of the acquiring firm in the year report for the same year the acquisition was announced, the data was paired to the acquisition deal data. For the determining of the firm
performance related to the acquisition announcement, I used Datastream to collect the securities data (stock price and beta) of the acquiring firms and Yahoo Finance for the historical prices of the corresponding reference indices, related to each security. Finally, I used Orbis to complement the dataset with company information (such as size, total assets, CEO and BoD compensation), along with manually searching for missing, easily available data, such as firm size and revenue for missing years. This resulted in a final sample size of just over 1140 announced acquisition deals in the chosen timeframe, of which the most prominent variables are outlined and summarized in table 1.
Table 1
Variable name Description
Deal characteristics Announcement date
7-1-2002 to 31-12-2012, ranging from 57 deals (5%) in 2002 to 157 (14%) in 2007
Target region
552 (48%) Europe, 317 (28%) Americas, 226 (20%) Asia-Pacific (ex Central Asia), 37 (3%) Africa/Middle East/Central Asia and 10 (1%) Japan
Across industry
773 (68%) deals across industries looking at all 4 SIC digits (main and sub-industries), of which 464 (41%) fully diversifying (across main industry) and 309 (27%) partially diversifying (across sub-industry)
Across region 711 (62%) deals across borders, of which 415 (36%) also across region Deal value
ranging from 10 million USD to 145 billion USD, with a mean deal value of 890 million USD and a median of 80 million USD
Acquirer firm characteristics
Acquirer region
813 (71%) Europe, 12 (1%) Americas, 257 (23%) Asia-Pacific (ex Central Asia), 32 (3%) Africa/Middle East/Central Asia and 28 (2%) Japan Acquirer nation firms from 37 different countries, see appendix A
Acquirer size
11 Acquirer total assets
ranging from $2.3 million to $331 billion, mean value $24.6 billion and a median of $5.1 billion
Acquirer industry firms from 33 different industries, see appendix A
Acquirer corporate
characteristics
Total number of board members ranging from 1 to 34, with an average of 11 (10.96) board members Insider ratio
The percentage of internal (executive) directors on the board, ranging from 0 to 100%, with an average of 26,4%
Board tenure
The average tenure of all members on the board, ranging from 0.2 years to 28 years, averaging 4.5 years among all boards with a standard deviation of 2.5 years
CEO tenure
The time in role for a CEO, ranging from 0 to 39.5 years, with an average of 5.1 years
CEO duality
Whether or not the CEO is also the chairman of the board; this is the case in 450 (39.4%) of the 1142 acquisitions.
CEO centrality
Whether the CEO compensation exceeds the median of the sample (adjusted for firm size; Hallock, 2011)
CEO Power Index
An index based on CEO tenure, duality and centrality, to describe the relative power a CEO has to the board, ranging from 0 to 3
Hofstede’s cultural dimensions
Individualism
The degree of individualism in a society, Hofstede’s (1984) index scores, ranging from 17 (Taiwan, low) to 90 (Australia, high), with a median of 71 Power Distance
The degree of Power Distance in a society, Hofstede’s (1984) index scores, ranging from 11 (Austria, low) to 81 (Mexico, high), with a median of 36 Uncertainty avoidance
The degree of Uncertainty avoidance in a society, Hofstede’s (1984) index scores, ranging from 8 (Singapore, low) to 112 (Greece, high), with a median of 53
Masculinity
The degree of masculinity in a society, Hofstede’s (1984) index scores, ranging from 5 (Sweden, low) to 95 (Japan, high), with a median of 61
3.2 Dependent variables
Acquisition decisions - diversification & globalization
The act of acquiring other firms, can have different goals for the acquiring firm. Therefore, the determining of the target firm will largely depend on the strategic intentions of the acquiring firm. First of all I account for diversification with the variables Cross sub-industry and Cross industry. Cross sub-industry – This variable is dichotomous and is coded 0 if all the 4 digits of the SIC code of both acquirer and target are the same and is coded 1 if the last 2 digits of the SIC code of acquirer are different than the target’s. A value of 1 for this variable would mean that the acquirer and target operate in the same main-industry, but not in the same sub-industry; partial diversification.
Cross industry – This variable is dichotomous and is coded 0 if the first 2 digits of the SIC code of both acquirer and target are the same. This means the main industry the target operates in, is the same as the acquirer. If the first 2 SIC digits differ, the variable is coded 1, which is labelled as a
diversifying acquisition.
Another acquisition decision level is the degree of globalization of an acquisition, which is measured by variables Cross border and Cross region.
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Cross region – Acquiring firms located in another region than the target firm are coded 1 and intra-region acquisitions 0.
Hostile – Acquisitions based on an agreement between the acquiring firm’s management and the target firm’s management are coded 0, while hostile takeovers are coded 1.
Risk index – An index based on the previous five variables regarding diversification, globalization and hostility. This index is constructed through using the sum of the five dichotomous variables Cross sub-industry, Cross sub-industry, Cross border, Cross region and Hostile. The index ranges from 0 (least risk) to 5 (most risk) and the distribution is shown in the graph below.
Deal to Assets – This variable represents the deal value of the acquisition in terms of a percentage of the total assets of the acquiring firm.
Graph 1 – Risk index distribution
Acquisition decisions – frequency
For the timeframe of the sample, I also looked at the number of acquisitions for each acquiring firm and CEO, to be able to draw conclusions on the frequency of acquisitions and the predictor variables. Number of acquisitions per firm – This variable reflects the total number of acquisitions of an
acquiring firm in the data set.
Number of acquisitions per CEO – This variable represents the number of acquisitions announced by the sitting CEO of an acquiring firm, after the acquisition announcement. Hence, it accounts for the number of previous announced acquisitions in the dataset by the CEO, including the current announced acquisition (>=1).
Firm performance
To measure the performance of the publicly traded acquiring firm around the acquisition announcement date, the cumulated abnormal return of the acquiring firm securities is used, as prescribed by Brown & Warner (1985) when dealing with event studies.
Cumulated abnormal return (CAR) – For every acquisition, the security prices of the acquiring firm have been identified, for a period of 3 days around the announcement date of the acquisition: 1 trading day (-1) before announcement date, day of announcement, 1 trading day (+1) after the announcement. If the acquisition was announced on a non-trading day (weekends, holidays), the security information for the announcement date was determined to be that of the first subsequent trading day. Resulting was the cumulated return for each acquiring firm’s security for a 3 day window around the announcement date, calculated as follows:
(security price day +1) – (security price day -1)
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(Actual) Cumulated security return(%)= ______________________________________ security price day -1
Next, the market’s return for the same 3 day window was calculated in a similar fashion.
(reference index day +1) – (reference index day -1) (Expected) Cumulated market return(%)= ______________________________________
reference index price day -1
Finally, to determine the CAR, the actual return was adjusted for the security’s beta and detracted from the expected return:
Cumulative abnormal return (%)= (Actual return * beta) – Expected return
3.3 Independent variables
CEO Power Index – This index is built using the three dichotomous variables CEO tenure, CEO duality and CEO centrality. Based on the sum of these variables, a CEO Power index is created, ranging from 0 (least powerful) to 3 (most powerful). CEO tenure is coded 1 if the CEO’s tenure is longer than the median of the sample. CEO duality is 1 when the CEO is also the chairman of the board. The complementing CEO centrality variable is coded 1 if the CEO compensation - adjusted for firm size (Hallock, 2011) - exceeds the sample median. The distribution of the CEO Power index is graphed below.
Graph 2 CEO Power index distribution
Insider ratio – The number of inside board members in relation to their external colleagues. According to Core et al (1999), a CEO has more influence over the board when there are relatively more internal board members than when there are less.
0 10 20 30 40 F re q u e n cy % 0 1 2 3
14 Graph 3 Insider ratio distribution
Total number of board members – The total number of members on the board of the acquiring firm. Previous scholars (Morse et al, 2011; Chikh & Filbien, 2011) have shown that the less members a board has, the more influence a CEO has over the board. Boards with a high number of members, are more difficult for a CEO to steer and influence. The mean number of board members is 11, which is in line with previous findings (Lehn et al, 2009).
Graph 4 Total number of board members distribution
3.4 Moderating variables
The index scores of Hofstede’s (1984) four cultural dimensions are determined based on the nationality of the CEO. With these relative indices of the cultural dimensions in the sample of powerful CEOs (CEO Power Index 2 and 3), every observation is categorized either low, medium or high regarding the degree of the cultural dimensions. Every dimensions has its specific characteristics on either end of the spectrum:
Individualism – The degree to which a society prefers individuals to mainly care and provide for themselves or their direct relatives/family only. The opposite of individualism is collectivism, which finds caring for ‘group’ more important than one’s own needs.
Power Distance – The degree to which a society is accustomed to and tolerant of inequality of power in individuals, organisations and institutions. A low degree of Power Distance will result in
questioning authority and impeding those in power, e.g. CEOs.
Uncertainty avoidance – The degree to which a society is uncomfortable with the uncertainty of the future. High uncertainty avoidance results in risk-averse behavioural preferences.
0 5 10 15 F re q u e n cy % 0 0.20 0.40 0.60 0.80 1 Insider Ratio 0 5 10 15 F re q u e n cy % 0 10 20 30 40
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Masculinity – The degree a society has masculine beliefs, which stands for achievement, heroism, assertiveness, and material success (Hofstede, 1984). The opposite of masculine is feminine, which is characterized by preference for relationships, modesty, caring for the weak and the quality of life.
3.5 Control variables
Deal value – The value (in $ millions) the acquiring firm is agreed to transfer to the target’s shareholders in return for a 100 % stake in the target firm.
Firm size – The size of the acquiring firm in number of employees
Total assets – The book value of the current total assets of the acquiring firm (in $ millions)
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4. Results
A concise overview of the descriptive statistics for the variables of the entire the sample size is shown in table 3, followed by a correlation matrix to detect suspected, interesting and/or surprising
correlations among variables. This chapter continues with a regression analysis and a group
comparison of means for the degree of power the CEO has, concluding with the moderating effect of national culture.
4.1 Descriptive statistics
Table 3 - Descriptive statistics
Variable Mean Std. Dev. 25% Median 75%
Deal Value ($ millions) 890,18 5462,18 27,84 80,00 348,84
Size (N of employees) 43883,61 71426,61 2852,00 15674,50 50668,00
Total Assets ($ millions) 24589,96 44817,69 1199,92 5114,84 27929,06
Risk Index 2,1112 1,1860 1 2 3 Cross-border 62,26% Cross-region 36,34% Cross sub-industry 67,69% Cross industry 40,63% Hostile 4,20% Deal to Assets 0,1133 0,4665 0,0064 0,0236 0,0827 Winsorized (5-95%) 0,0756 0,1146 0,0064 0,0236 0,0827
Number of acquisitions (firm) 4,9597 3,9829 2 4 7
Winsorized (5-95%) 4,8573 3,7037 2 4 7
Number of acquisitons (CEO) 2,3205 2,0619 1 2 3
Winsorized (5-95%) 2,1708 1,5416 1 2 3
3 day CAR (%) 0,4458 4,6883 -1,2277 0,2694 1,9676
Winsorized (5-95%) 0,4431 2,8677 -1,2277 0,2694 1,9676
CEO Power Index 1,3779 0,8285 1 1 2
Total board members 10,9641 4,7689 8 10 13
Insider ratio 0,2641 0,1758 0,1250 0,2381 0,3750
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A simple linear regression is used to detect relationships between the CEO power and every single dependent variable up front. This method of analysis is however not sufficient due to the non-normally distributed nature of some dependent variables. Another issue is the phenomenon that some
relationships are not linear and tend to show high variance in outcome in specific CEO Power groups, either with high, low or medium power. Therefore, to test the hypotheses, the sample means and medians for each individual CEO Power index group is calculated, to be able to identify significant differences between power groups of CEOs. Because the majority of the variables are not normally distributed, a two samples independent t-test cannot be used for the comparison of these groups. Instead, the Wilcoxon-Mann-Whitney test is used to test significant difference between group means, as this test is the non-parametric version of the independent samples t-test. The following assumptions also hold for the data set:
1. The dependent variable at the measured at the interval or ratio level
2. The independent variable consists of two independent unrelated groups, categorically divided (group 0 versus 3, group 0 versus groups 1,2,3 and group 3 versus groups 0,1,2)
3. There is independence of observations, this is the case as every observation is a different acquisition.
4. Significant outliers are not present in the data set as I manually checked for data errors and outliers through graphing and boxplotting variables. Dependent variables are winsorized for the lowest 5% and the highest 5% of the variable’s value, for the robustness of the research. 5. Dependent variables are not normally distributed for each category of the independent
variable. I ran a Shapiro-Wilk-test for all dependent, independent and control variables. All variables showed p= 0.00 values, except for Cross border (p=0.99), Cross region (p=0.71), Cross sub-industry (p=0.78) and Cross industries (p=0.98), as these are dummy variables, coded 0 or 1, thus not suited for a normality test.
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4.2 Correlation matrix
Observations = 1132 CEOP o we rIn d ex In sid erra ti o To tal n u m b er o f b o ard m em b ers De al v alu e F irm siz e To tal ass ets Risk In d ex Cro ss Bo rd er Cro ss Re g io n Cro ss In d u stry 4 D Cro ss In d u stry 2 D Ho stil e De al Va lu e to As se ts Cu m u lativ e ab n o rm al re tu rn N o f ac q u isi ti o n s p er firm N o f ac q u isi ti o n s p er CEO In d iv id u ali sm P o we r Dista n ce Un ce rtain ty A v o id an ce M asc u li n it y CEOPowerIndex 1,00 Insiderratio 0,10 1,00 Total n of boardmembers -0,11 -0,15 1,00 Deal value -0,03 -0,03 0,09 1,00 Firm size -0,27 -0,13 0,51 0,08 1,00 Total assets -0,25 -0,09 0,40 0,26 0,52 1,00 RiskIndex -0,05 -0,01 0,18 0,02 0,18 0,11 1,00 CrossBorder 0,00 -0,07 0,24 0,02 0,16 0,11 0,59 1,00 CrossRegion -0,06 -0,01 0,06 0,01 0,10 0,08 0,61 0,59 1,00 CrossIndustry4D -0,05 0,00 0,09 -0,02 0,09 0,04 0,60 -0,06 -0,02 1,00 CrossIndustry2D 0,00 0,05 0,06 -0,07 0,08 0,01 0,58 -0,07 -0,06 0,57 1,00 Hostile -0,05 0,01 -0,03 0,26 0,00 0,07 0,17 0,00 0,00 0,02 -0,02 1,00 Deal Value to Assets 0,14 0,13 -0,28 0,22 -0,24 -0,21 -0,13 -0,18 -0,12 -0,05 -0,05 0,21 1,00 Cumulative abnormal return 0,05 0,06 -0,04 -0,08 -0,09 -0,08 -0,02 0,02 -0,01 -0,02 -0,01 -0,07 0,02 1,00 N of acquisitions per firm -0,17 -0,06 0,28 0,02 0,32 0,24 0,26 0,22 0,18 0,12 0,11 -0,01 -0,28 -0,03 1,00 N of acquisitions per CEO 0,05 -0,04 0,12 0,03 0,14 0,13 0,19 0,19 0,19 0,06 0,04 -0,03 -0,17 -0,01 0,62 1,00 Individualism -0,04 0,00 -0,35 -0,06 -0,17 -0,27 -0,12 -0,21 -0,04 -0,05 0,01 0,01 0,15 0,03 0,07 0,05 1,00 Power Distance 0,15 -0,02 0,09 0,04 0,15 0,14 0,01 0,03 0,03 0,01 -0,05 0,00 -0,05 -0,03 -0,14 -0,13 -0,43 1,00 Uncertainty Avoidance 0,17 -0,09 0,23 0,06 0,16 0,24 0,09 0,12 0,09 0,01 -0,03 0,03 -0,11 -0,04 -0,10 -0,09 -0,46 0,68 1,00 Masculinity -0,07 0,36 -0,10 0,00 -0,07 0,07 0,01 -0,11 0,01 0,05 0,07 0,03 0,03 -0,03 -0,01 0,01 0,09 -0,05 0,08 1,00Bold = moderate to strong relation
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First of all, I would like to note that as some relations are non-linear, the correlation matrix does not show the exact relation direction and strength of most of these non-linear relations. CEO Power shows modest negative correlation with firm size and total assets. This is anticipated as the larger the firm size, the higher the number of board members (which even has a moderate to strong correlation with firm size (0.51 and 0.40), making it more difficult for a CEO to control the board, resulting in less CEO Power. Other mentionable modest relations are those between deal value to assets and the power measures (CEOPowerIndex, Insiderratio and total number of boardmembers), all show correlations as hypothesized; more CEO Power shows higher relative acquisition deal values. A surprising correlation is that of N of acquisitions per firm with CEO Power; higher CEO Power has a negative relation with the number of acquisitions pursued by the firms in the dataset. This phenomenon is further discussed in the CEO Power group comparison subchapter. Looking at the correlations of Hofstede’s cultural dimensions, no moderate or strong relations are found, except among the cultural dimensions themselves, which is also evident in research by other scholars (Smith et al, 1996)
Correlation categorisation used (Dancey & Reidy, 2004): 1 being a perfect linear relation, 0.8 to 0.9 very strong, 0.5 to 0.8 strong, 0.3 to 0.5 moderate, 0.1 to 0.3 modest, >0.1 weak
4.3 Regression
In table 5, the regression results are shown for the independent variables and their relation with the CEO Power Index. The regression is controlled for deal value, firm size and total assets and displays 2 significant relations on the 0.01(**) level; Powerful CEOs tend to pursue deals with deal value to assets ratio than their less powerful colleagues (coefficient 0.0197, p-value 0.00), however the firms that house powerful CEOs also pursue acquisitions less often (coefficient -0.7467, p-value 0.00). The other apparent relations are those between CEO power and the Risk Index (0.07), Cross Region (0.05), Hostility (0.09) and the performance around the announcement date (0.07). These relations are only significant at the 0.10(*) level, which asks for a more precise method of analysis, to be able to adopt or reject the hypotheses. As mentioned in the Methodology chapter, some relations are not linear and are only more apparent in CEOs with a certain amount of power. For example, a CEO that has very little to a medium amount power over the board, will be a lot less able to pursue and execute his or her preferences, whereas a mighty CEO should have very few difficulties and therefore show more apparent relations. To be able to detect phenomena that are CEO power group specific, I compare the weak and strong CEO power groups with each other and with the rest of the sample.
Regression of M&A decisions and performance on
CEO Power Risk Index Cross Border Cross Region
Cross
sub-industry Cross industry CEO Power Index Coef. -0,0757 -0,0049 -0,0332 -0,0254 0,0000
t-stat -1,7900 -0,2800 -1,9300 -1,5200 0,0000 p-value 0,0740 * 0,7790 0,0540 * 0,1290 0,9996
Hostile Deal to Assets ACQ firm ACQ CEO 3 day CAR CEO Power Index Coef. -0,0123 0,0197 -0,7467 0,0835 0,0018
t-stat -1,7100 4,8600 -5,7200 1,5200 1,7900 p-value 0,0870 * 0,0000 ** 0,0000 ** 0,1299 0,0734 * observations 1142 *,** significant at the 0,1;0,01 level
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4.4 CEO Power group comparison
Based on the CEO Power Index, the sample is split up into 4 different groups with each their own mean and median for all the variables. By testing whether or not the difference in the distribution per variable for each distinct is significant, I can draw conclusions regarding the impact of CEO power on the dependent variable. First I look at the least powerful CEO group versus the most powerful ones. Second the least powerful CEO group is compared to the rest of the sample and finally I look at the most powerful CEOs versus the rest of the sample. The results are shown in table 6.
Table 6 M&A decisions and performance based on CEO power variables
Variable Statistic CEO Power Index
WMW group 0 vs group 3 WMW group 0 vs groups 1,2,3 WMW group 3 vs groups 0,1,2 0 1 2 3 Observations 162 469 417 94 Value
Deal Value ($ millions) Mean 1035,5 980,7 863,7 305,7 z 3,2750 2,2640 2,7080 Median 113,9 93,4 76,4 43,3 p 0,0011 * 0,0236 * 0,0068 *
Size Mean 80037 50022 31671 5127,1 z 12,9120 10,9890 7,9480 Median 49496 17130 6997 2710 p 0,0000 * 0,0000 * 0,0000 *
Total Assets ($ millions) Mean 53939 22374 20173 4661 z 8,4810 8,2090 5,1500 Median 22403 5115 4553 2246 p 0,0000 * 0,0000 * 0,0000 *
Risk Index Mean 2,2901 2,049 2,1847 1,7872 z 3,0490 2,0070 2,7240 Median 2 2 2 2 p 0,0023 * 0,0447 * 0,0064 *
Cross-border Mean 0,679 0,5864 0,6475 0,5657 z 1,3420 1,5990 0,5600 Median 1 1 1 1 p 0,1795 0,1099 0,5753
Cross-region Mean 0,4383 0,339 0,3933 0,2234 z 3,4470 2,1380 2,9440 Median 0 0 0 0 p 0,0006 * 0,0325 * 0,0032 *
Cross sub-industry Mean 0,6975 0,6823 0,6882 0,5638 z 2,1560 0,6060 2,4460 Median 1 1 1 1 p 0,0211 * 0,5443 0,0145 *
Cross industry Mean 0,4136 0,3945 0,4245 0,3723 z 0,6480 0,2030 0,7000 Median 0 0 0 0 p 0,5167 0,8388 0,4842
Hostile Mean 0,0617 0,0469 0,0312 0,0319 z 1,0450 1,3480 0,5100 Median 0 0 0 0 p 0,2959 0,1776 0,6100
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Median 11 10 10 9 p 0,0000 * 0,0000 * 0,0085 *
Insider ratio Mean 0,2511 0,2475 0,2757 0,3175 z -3,2850 -2,1640 -3,1660 Median 0,2308 0,2 0,25 0,3038 p 0,0010 * 0,0305 * 0,0015 *
*significant at the 0.05 level
Power measures
Looking at the control power measures (Total board members and Insider ratio) for every CEO Power Index group comparison, the differences between groups are significant. For the Total board members variable this suggests that the smaller the board size, the more power a CEO has over the board. Less-powerful CEOs in this sample deal with boards of 12 to 13 board members on average, while their more powerful colleagues only have to deal with boards with 10 members on them. The ratio of insiders on a board is significantly higher for powerful CEOs (0.3175) than for the CEOs with the least power (0.2511). Based on these significant results I adopt H1 and argue that CEO Power Index, Total board members and Insider ratio are all sound power measures, which can be used interchangeably to determine the power a CEO has over the board.
Frequency
CEO Power does not seem to have any relationship with the number of acquisitions a CEO pursues, at least not in this sample. The least powerful CEOs pursue on average 2 (1.9938) acquisitions in a period of 10 years’ time, versus 2.1 (2.0957) acquisitions for the most powerful CEOs. The middle 2 groups (CEO power index 1 and 2) are not far off by having respectively 2,1386 and 2,2926
acquisitions on average. Hypothesis 2 and 3 are not supported by these results. There is however a significant difference between the CEO power group when I account for the total number of
acquisitions made by firm instead of CEO. Some acquiring firms were present in the sample multiple times with different CEOs (due to CEO turnover). Looking at the firm-level instead of CEO-level, I find that firms with the most powerful CEOs tend to acquire less frequently (3.4894 times on average) than the firms with the least powerful CEOs (6.1728 times on average). These results show an
inversed relation than was hypothesized and might be explained by other factors than risk-averse CEO behaviour, such as firm culture or strategic choices. However, this is beyond the scope of my thesis and might be subject to future research.
Risk
Based on the SIC codes of the acquirer and target firm, I differentiate between related, partially related and non-related (diversifying) types of acquisitions. Comparing the different CEO Power groups based on diversifying acquisitions, there is no significant difference in means; the least powerful group of CEOs (0) have pursued diversifying acquisitions 41% percent of the time versus 39%, 42% and 37% in CEO power index group 1, 2 and 3 respectively. Looking at the partially diversifying acquisitions, there is a significant difference between the most powerful CEO group (3) and the rest of the sample. Powerful CEOs pursue on average for 56% of their time partially diversifying acquisitions (same industry, different sub-industry), while this percentage is higher for the less-powerful CEO groups; 70%, 68% and 69% for CEO power group 0, 1 and 2 respectively. Hypothesis 4 is not supported, as powerful CEOs pursue the same amount of diversifying acquisitions as their less-powerful
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Of the entire sample of acquisitions, 4,2% were hostile takeovers. In total this were only 48 of the 1142 recorded deals in the sample. The two least powerful groups (0 and 1) were above this sample average with respectively 6,2% and 4,7% of the deals being hostile takeovers, while the more powerful CEO groups (2 and 3) had less hostile deals than the sample average (3,1% for group 2 and 3,2% for group 3). Despite the differences in means for the separate groups, this difference between power groups is not significant; the p-values were all higher than 0.05 in all three comparisons between power groups, which results in Hypothesis 5 not being supported by the data. With the powerful CEO having less hostile takeovers on average and the least powerful groups more on average in this dataset, there is a possibility that with a larger sample size of hostile takeovers, this relation can be proven statistically, as the hypothesised trend is visible in the mean data in this research. Further research should give conclusive results on this issue regarding the risk-taking of CEOs in the form of hostile takeovers. Overall risk regarding acquisitions does show a significant relation with the amount of power a CEO has; the composite risk index for the entire sample averages a score of 2,11.
Comparing the least powerful CEO group (0) with the most powerful group (3) shows that the latter take significantly less risk (p=0.0023) than the former when pursuing acquisitions. This significant difference also holds when I compare the most powerful group with the rest of the sample (p=0.0064) and when the least powerful group is compared with the rest of the sample (p=0.0447). CEOs are risk-averse and this behaviour will be more apparent when they have the ability to exert their will over the board, therefore Hypothesis 7 is supported. Although CEOs prefer to minimize the risk, they are constantly trying to maximize their personal gains and those of the firm. This effect shows in the deal value of the acquisition deals as a ratio of the total assets of the acquiring firm. The average
winsorized deal value to assets ratio of the entire sample is 7.56%, which is significantly higher than the ratio measured in the least powerful CEO group (3.31%) and lower than the deal value to assets ratio of the most powerful CEO group (10,17%). The CEO power group comparisons all show significant p-values (p=0.00 for all group comparisons) and I therefore adopt Hypothesis 8 as it is supported by the data.
Performance
The final dependent variable tested is the performance of the acquiring firms measured by calculating the cumulative abnormal return of the firm’s securities around the announcement date. The least powerful CEO group seems to have very small negative cumulative abnormal returns on average (-0.02%) while the entire sample’s average CAR is 0.44%. CEO power group 1, 2 and 3 have CARs on average of respectively 0.48%, 0.56% and 0.55%. Among the more powerful groups (1 and 2) there is little to no difference in the acquirer’s performance around an acquisition announcement. Due to the small differences in group 1, 2 and 3, the rank sum comparison tests show no significant difference in group 3 versus groups 0, 1 and 2. There is however a noticeable and significant difference in the average CAR of CEO power group 0 and that of the rest of the sample, suggesting that firms that have CEOs with very low influence (group 0) will perform significantly (p=0.03) less in acquisitions than their more powerful colleagues (groups 1,2 and 3). Because only 1 of the 3 group comparisons is significantly different, Hypothesis 9 is only partially supported, with the argument that the firms with the least powerful CEOs perform worse than the rest of the sample, but the firms with the most powerful CEOs do not necessarily show better acquisition performance than the firms with CEOs of power group 1 and 2.
H1 The CEO power measures are correlated and are determinants for the degree to which a CEO can exert his or her will over others (board of directors)
Supported
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H4 Powerful CEOs pursue more diversifying acquisitions than less-powerful CEOs
Not supported
H5 Powerful CEOs will pursue more foreign acquisitions than less-powerful CEOs
Not supported
H6 Powerful CEOs will pursue less hostile acquisitions than less-powerful CEOs
Not supported
H7 Powerful CEOs pursue risk-averse acquisitions than less-powerful CEOs
Supported H8 Powerful CEOs pursue acquisitions with a higher deal value to total
assets than less-powerful CEOs
Supported
H9 Powerful CEOs pursue more value-enhancing acquisitions than less-powerful CEOs
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4.5 National culture as moderating factor
Powerful CEOs have the ability to pursue own preferences regarding M&A decisions, as they are not bound by the board of directors as much as less powerful CEOs. But having the ability and actually acting on these preferences are two different things. As argued by Hofstede (1984; 1993), the national culture might affect the actual pursuing of certain M&A decisions; CEO preferences can clash with or can be stimulated by established national cultural beliefs, affecting the relations between CEO power and M&A practices and firm performance. To account for these potential moderating cultural dimensions, the more powerful CEOs (CEO Power Index group 2 and 3) were assigned index scores for each of the 4 cultural dimensions, stemming from Hofstede’s 1984 article, based on the nationality of the acquiring firm. This resulted in a sample of 507 acquisition announcements. Next, I categorized the observations for each cultural dimensions, either high, medium or low, displayed in appendix D.
Table 7 Statistic Individualism Power Distance Uncertainty
avoidance Masculinity IDV low vs high PDI low vs high UAI low vs high MAS low vs high low high low high low high low high
Variable
N 66 167 183 121 95 192 118 182 Value
Risk Index Mean 1,79 1,98 2,15 2,11 1,98 2,12 2,13 2,20 z -1,4090 0,2220 -0,8000 -0,7330
Median 2,00 2,00 2,00 2,00 2,00 2,00 2,00 2,00 p 0,1588 0,8240 0,4235 0,4635
Deal to Assets Mean 0,06 0,12 0,10 0,08 0,14 0,07 0,07 0,09 z -4,0770 1,9180 5,2110 -1,5210
Winsorized (5-95%) Median 0,06 0,16 0,14 0,10 0,26 0,09 0,08 0,11 p 0,0000 ** 0,0552 * 0,0000 ** 0,1282 Number of acquisitions (firm) Mean 3,50 4,17 4,84 3,83 4,88 4,30 4,84 5,34 z -0,9470 2,6050 0,4680 -0,4490
Winsorized (5-95%) Median 4,00 5,00 7,00 4,00 7,00 5,00 6,00 8,00 p 0,3439 0,0092 ** 0,6395 0,6533 Number of acquisitons (CEO) Mean 1,74 2,27 2,54 1,96 2,43 2,01 2,36 2,63 z -2,1500 2,4990 0,9800 -0,9030
Winsorized (5-95%) Median 2,00 3,00 4,00 2,00 4,00 2,00 3,00 4,00 p 0,0315 ** 0,0124 ** 0,3270 0,3667 3 day CAR (%) Mean 0,00 0,01 0,01 0,00 0,01 0,00 0,01 0,01 z -0,8550 1,3070 1,6520 0,8730
Winsorized (5-95%) Median 0,02 0,02 0,03 0,02 0,04 0,02 0,02 0,02 p 0,3924 0,1913 0,0985 * 0,3824 *significant at the 0.10 level
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As each cultural dimension has opposite values at the end of each spectrum, the observations that scored medium relative to the rest of the sample, are left out of consideration, as they do not have distinct characteristics regarding the cultural dimensions. By comparing the group with a low degree of the cultural dimensions with the high degree group, significant differences in dependent variables are identified. A high degree of Individualism (IDV) results in a significant higher Deal to Assets ratio (mean low: 0.06, mean high: 0.12, p-value 0.00) and in that way, enhances the already existent
positive relation CEO Power has with the deal value to total assets ratio. However, this relation works both ways, so powerful CEOs are hindered in pursuing relatively large deals in a society with a low degree of Individualism (a high degree of Collectivism). This can be seen by comparing the earlier mentioned Deal to Assets means of the powerful CEOs with the means of CEO power index group 2 and 3 in table 5 (2=0.08, 3=0.10). Cultural dimensions Power Distance (PDI) and Uncertainty Avoidance (UAI) also moderate the relation between CEO Power and Deal to Assets ratio. A high degree of PDI negatively affects the existing relation, and the same is true for a high degree of UAI. IDV and PDI also both have an influence on the non-significant relation between CEO Power and the number of acquisitions a CEO makes; a high degree of IDV positively affects the number of
acquisitions a powerful CEO pursues (p-value 0.03), while a high degree of PDI has a reverse effect (p-value 0.01). The relation between CEO Power and the number of acquisition per firm is negatively affected by a high degree of PDI in a society and finally the firm performance for powerful CEOs is less for CEOs with a national culture that has a high degree of Uncertainty Avoidance. The cultural dimension Masculinity does not seem to affect any hypothesized relations, which might be explained by the fact that the degree Masculinity is already high in CEOs, as they show masculine characteristics through simply being a CEO. Therefore, the masculinity dimensions is difficult to capture adequately and the index points might display the societal/national degree, but this does not hold for CEOs in a society. To conclude, H10 and H12 are supported, as these dimensions (IDV and UAI) clearly moderate certain M&A decisions, while H11 needs further research, because PDI seems intertwined with the independent variable CEO Power Index. Masculinity shows no significant results as a moderator in this study, thus Hypothesis 13 is not supported. Below an overview of the hypotheses regarding the effect of cultural dimensions.
H10 The degree of Individualism will affect the M&A decisions that powerful CEOs make.
Supported H11 The degree of Power Distance will affect the M&A decisions
that powerful CEOs make.
Partially supported
H12 The degree of Uncertainty Avoidance will affect the M&A decisions that powerful CEOs make.
Supported
H13 The degree of Masculinity will affect the M&A decisions that powerful CEOs make.
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5. Discussion
Although the three different power measures are all clear determinants of the influence a CEO has over the board, the Insider ratio does not show a linear relation regarding the ratio of CEO power group 0 and group 1. Firms in both groups have on average a board consisting of 25% of insider directors. For more powerful groups (2 and 3), the ratio does increase. This observation is in line with that of Core et al (1999) and Grinstein & Hribar (2004), who both found the insiders ratio to be a ‘noisy proxy’ for CEO power and board independence. The total board members variable does
correlate with previous research; the sample shows an average board size of 10.96 with a median of 10 board members. Morse et al (2011) found this to be 10.62 on average with also median of 10, while earlier literature of Lehn et al (2009) also states a similar median (11) for board size. CEO power groups show a decline in the total number of board members as the power index increases, with the least powerful group averaging 12.4 board members and the most powerful group 9.6. As the CEO power index is based on multiple dichotomous variables determining the power relation between the CEO and the board, this is index was used as primary power proxy. This power measure construct is previously used by Henderson et al (2010), Morse et al (2011), Grinstein & Hribar (2004), Chikh & Filbien (2011) and others. There is however a slight difference among scholars regarding the exact variables of which the ultimate power index is constructed; some measures are almost always present in measuring CEO power (such as CEO duality; Henderson et al, 2010; Grinstein & Hribar, 2004; Chikh & Filbien, 2011; Li & Tang, 2010; Hagendorff & Keasey, 2012), while others are only apparent in a limited number of studies (CEO prestige power, determined by social networks, ties and
education; Chikh & Filbien, 2011/CEO is also company president, preventing the board from appointing a successor; Morse et al, 2011). Although the CEO power reflected by these different measures might be congruent with each other and therefore have similar outcomes regarding the power a CEO has, for future research it might be beneficial to have consensus among scholars on the exact variables a CEO power index is made up of and the respective weight of each variable.
5.1 Frequency
According to the sample data, there is no clear relation between the amount of power a CEO has and the number of acquisitions he or she pursues. The intermediate power groups seem to have slightly more acquisitions on average versus the most and least powerful groups, although this difference is negligible. The absence of a significant relationship is a possible consequence of agency theory (Eisenhardt, 1989); CEOs choose between risk-averse behaviour that limits the amount of pursued acquisition - as acquisitions bring along a certain risk – and personal benefit from M&A activities. There are two limitations to my research regarding the frequency of acquisitions based on CEO power; first of all I do not take in account the way of financing an acquisition (debt versus cash). Previous scholars that incorporate the financing structure (Jensen, 1986; Eisenhardt, 1989), do find significant relationships regarding preference for acquisition frequency linked with the financing structure of the actual acquisition. The second limitation is the fact that I do not look at deals with a deal value smaller than 10 million US dollar, which might skew the results for CEOs that have pursued a number of smaller acquisitions in the timeframe of the dataset. Future research based on all acquisitions pursued including the financing structure of the deal might give conclusive evidence on the number of acquisitions a CEO pursues in relation to his or her relative power to board of directors. Besides the number of acquisitions pursued by every single CEO in the sample, I also accounted for the
