The influence of managerial power on post-merger

financial performance

Master Thesis

by

Martin Lutke

University of Groningen

Faculty Business and Economics

Msc Strategy and Innovation

23 June 2014

Verlengde Lodewijkstraat 19

9724 EK Groningen

(+ 31) 6 25420550

m.lutke@student.rug.nl

student number 1610430

First supervisor: Dr. J.Q. Dong

Second supervisor: Dr. W.G. Biemans

Word count: 15.996

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ABSTRACT

Merger and acquisition activity takes place with high peaks and deep declines over time, but even

after years of research on this topic, high failure rates for mergers and acquisitions are still

common. Many studies discuss the reasons for these high failure rates and present guidelines and

success factors for future mergers and acquisitions. Remarkably, the human factor is often

neglected and even when it is discussed, researchers argue about their influence. Most research so

far concludes that managerial power leads to value destruction for mergers and acquisitions.

However, a few studies give indications for a positive relation between the proportion of

managerial power and the success of mergers and acquisitions, in this research seen as post-

merger financial performance. Therefore, this study uses contradictory hypotheses and will

contribute to help resolving the paradox in the discussion about whether there is a positive or

negative influence of managerial power on post-merger financial performance. However, this

effect is stronger in some situations than in others. Therefore, this study takes two moderating

effects into account. First of all, the period of the wave is believed to influence the effect of

managerial power on post-merger financial performance. Secondly, the acquisition rate of the

target’s stocks (the proportion of target's stocks acquired) is believed to influence the effect of

managerial power on post-merger financial performance. Data was collected from databases

ZEPHYR and COMPUSTAT and the sample consist of 5.625 U.S. publicly listed deals in the

financial sector which were completed in the period 1997-2008. Empirical results show a positive

effect of managerial power on post-merger financial performance. These empirical results also

show positive effects for the moderating variables period of the wave and acquisition rate of the

target’s stocks. That means it is shown that the period of the wave and the acquisition rate of the

target’s stocks both positively influence the relation of managerial power on post-merger

financial performance. In conclusion, the proportion of managerial power positively influences

post-merger financial performance. Besides that, this effect is stronger in the fifth merger wave

and in cases where the acquisition rate of the target’s stocks is high.

Keywords: managerial power, success of-, mergers and acquisitions, post-merger financial

performance, merger waves, acquisition rate of the target’s stocks

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INDEX

1. Introduction 3

1.1 Problem statement 6

1.2 Importance of this research 7

1.3 Structure of the paper 9

2. Theory Development 10

2.1 The role of managerial power 12

2.2. Hypotheses development 15

3. Empirical Methodology 23

3.1 Data collection 23

3.2 Independent variable: managerial power 24

3.3 Dependent variable: post-merger financial performance 25

3.4 Moderating variables 27

3.5 Control variables 27

4. Results 30

4.1 The regression model 30

4.2 Descriptive statistics 32

4.3 Regression results 32

5. Discussion & Conclusions 35

References 39

Appendix I 49

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1. INTRODUCTION

In recent decades many large organizations have been developed created out of two or more

companies. A well-known example is the financial institution ING which is a merger of Postbank

and Nationale Nederlanden. But there are more examples in this financial sector, like the

takeover of ABN AMRO bank by the consortium of Royal Bank of Scotland, Fortis and Banco

Santander.

Both examples are categorized as mergers and acquisitions. Sherman & Hart (2006) define a

merger as two companies joining together (usually through the exchange of shares) as peers to

become one. Most of the time a new company develops, either with a new name, like ING, or

with a combination of both the names. An acquisition is defined as one company – the buyer –

which purchases the assets or shares of the seller, with the form of payment being cash, the

securities of the buyer, or other assets of value for the seller. An acquisition can be friendly, as in

the case of ING. That means that the buyer and seller negotiate. Or, an acquisition can be hostile.

In this case, one company buys the other company without cooperation or negotiation, like the

example of ABN AMRO. These authors (Sherman & Hart, 2006) have already mentioned that

the distinction in meaning between mergers and acquisitions may not really matter, since the net

result is the same: two (or more) companies that had separate ownership are now operating under

the same roof, usually to obtain some strategic or financial objective. Other authors also state that

mergers and acquisitions do have differences but they use only one definition. For example,

Weston, Mitchell and Mulherin (2004) state that mergers mostly occur between companies with

approximately the same size and work in the same industry, while with acquisitions the buying

company is in most cases larger than the selling company. Despite the differences they use

mergers and acquisitions as one term, including all types like mergers, acquisitions, divestures,

alliances, joint ventures, restructuring, minority investments, licensing and franchising.

Therefore, I will do the same and in this study call all these types mergers and acquisitions.

As stated above many authors have already covered the topic of mergers and acquisitions in their

research because the number of mergers and acquisitions has been growing significantly over the

last decades (Ravichandran, 2009; Straub, 2007; McCarthy & Dolfsma, 2012; Sudarsanam &

Mahate, 2003). Between 1995 and 1999 nine thousand billion U.S. dollars was spent by North

American and Western European firms on mergers and acquisitions, exceeding the Gross

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Domestic Product of several large countries (Schenk, 2003). Around 2000 approximately 40.000

transactions were counted worldwide (Straub, 2007; Ravichandran, 2009).

But, is this number of mergers and acquisitions rising endlessly? If some other data is

investigated, a whole different scenario could be outlined. For example, in 2008 a record number

of cancelled deals could be seen, more than 1100 versus 870 a year earlier (Vranceanu, 2008).

These figures should give some warnings to different companies who are willing to enter the

process of merging and acquisitioning. However, these dropping figures could be a negative

effect of the financial crisis. Moreover, it is only a comparison between 2008 and 2007 and

therefore it does not have to mean anything. If we take a broader view another pattern could be

seen.

Many authors have investigated the amount of merger and acquisition activity and concluded that

they come in waves (Martynova & Renneboog, 2008; Martynova & Renneboog, 2011; Andrade,

Mitchell & Stafford, 2001; McCarthy & Dolfsma, 2012; Gaughan, 2010, Straub, 2007). The

following figure, FIGURE 1, shows the waves even more clearly. It shows the number of

mergers and acquisitions on the vertical axe and the years 1897-2003 on the horizontal axe.

FIGURE 1 Total number of mergers and acquisitions 1897-2003 (Source: Martynova &

Renneboog, 2008)

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In this figure the waves are relatively easy to discover. In the chart there are six peaks which

represent the six takeover waves. In chapter 2.2 I will describe these six merger waves more

precisely.

FIGURE 1 shows that the number of mergers and acquisitions can fluctuate throughout a decade,

so a decline in the number of mergers and acquisitions in some years is historically logical. But

even in years with a large number of mergers and acquisitions, not all the deals are successful.

Considering research that has been conducted in the past, approximately half of all the mergers

and acquisitions have proven to be unsuccessful (Kitching, 1974; Covin, Kolenko, Sightler &

Tudor, 1997; Gadiesh & Ormiston, 2002; Gadiesh, Ormiston & Rovit, 2003; Weber, Shenkar &

Raveh, 1996). But what exactly is a successful merger or acquisition? In this article success of

mergers and acquisitions will be defined in financial terms, like Napier (1989) did. She chose to

combine all the definitions of success of mergers and acquisitions into two main categories in her

article. She mentioned that the success of a merger and acquisition could be measured by 1)

financial or other objective performance measures and 2) by employee reaction or morale

measures. Because the use of objective secondary data in this research is very important, the

definitions in the area of employee reaction or morale measures are less applicable. Therefore the

focus will lie on financial or other objective performance measures. Because this research deals

with completed deals only, in this article, success of mergers and acquisitions will be described as

post-merger financial performance.

Because, due to time and data limitations, it is not possible to investigate all the factors that

influence post-merger financial performance this research will only investigate one factor. For

three reasons the focus of this study will lie on the influence of managerial power on the post-

merger financial performance. The first reason is that the role of human factors has been

neglected in the literature for a long time. Past research focused on processes and firm- and deals-

specific characteristics instead of human factors (McCarthy & Dolfsma, 2012; Trautwein, 1990).

For a long time the same topics were discussed, for example: failures on strategic, financial and

economic decision-making processes and characteristics like size, relatedness, structure, methods

of payment, and liquidity. King, Dalton, Daily & Covin (2004) even gave researchers the advice

to incorporate other variables in the models than the one mentioned above, when investigating

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success of mergers and acquisitions. The second reason for choosing managerial power is that the

few authors who did investigate the role of managerial power on post-merger financial

performance did not agree whether this managerial power could positively or negatively

influence the post-merger financial performance (Covin et al., 1997; Cartwright & Cooper, 1990;

Roll, 1986; Haywood & Hambrick, 1997; Grinstein 7 Hribar, 2003; Dutta, MacAulay & Saadi,

2011; Harford & Li, 2007; Daily & Johnson, 1997). The third and last reason for choosing

managerial power is that managers’ decisions are one of the most important motives for starting a

merger and acquisition process (Trautwein, 1990).

It seems reasonable, due to these three reasons, to further investigate managerial power. But,

what exactly is meant with managerial power? In this study managerial power will be described

by using the framework of Finkelstein (1992), who stated that managerial power has four

dimensions. The structural power dimension is the one which describes managerial power best.

This power dimension is based upon the fact that managers who have a legislative right to exert

influence are more influential than other managers. It is about formal organizational structure and

hierarchical authority. The greater a manager’s structural power, the greater the control will be

over colleagues’ actions and the less he or she will be dependent on other members within the

organization. So managers who have managerial power will have control over colleagues’ actions

and can take decisions independent of other members in the organization based on their

hierarchical authority. In chapter 2.2 the whole framework and the reason why I chose structural

power as the most important dimension for this study will be discussed.

1.1 Problem statement

Figure 1 showed that the number of mergers and acquisitions can fluctuate throughout a decade,

so a decline in the number of mergers and acquisitions in some years is historically logical. But

even in years with a large number of mergers and acquisitions, not all the deals are successful.

Considering research that has been conducted in the past, approximately half of all the mergers

and acquisitions have proven to be unsuccessful (Kitching, 1974; Covin, Kolenko, Sightler &

Tudor, 1997; Gadiesh & Ormiston, 2002; Gadiesh, Ormiston & Rovit, 2003; Weber, Shenkar &

Raveh, 1996). It is striking that for so many years it has been clear that half of the mergers and

acquisitions are unsuccessful but that nothing has changed. One explanation could be that success

factors are not correctly interpreted. For example, Martynova & Renneboog (2008) already

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mentioned that success factors vary from period to period. Another explanation is that some

success factors have been neglected for a long time. Past research focused on processes and firm-

and deal-specific characteristics instead of on human factors (McCarthy & Dolfsma, 2012;

Trautwein, 1990; King et al., 2004). A final explanation is that multiple studies did not reach an

agreement about whether the influence of a particular factor was successful or less successful for

mergers and acquisitions. The purpose of this research therefore is to incorporate these three

issues and so it will contribute to help resolving the paradox in the discussion whether there is a

positive or negative influence of managerial power on post-merger financial performance.

Hopefully, this research can therefore contribute to the literature which describes the problems of

unsuccessful mergers and acquisitions.

In summary, the main question of this research will be: “How does the role of managerial power

influence the post-merger financial performance?”

1.2 Importance of this research

First of all, this research can help to get a better understanding of the processes of mergers and

acquisitions. So far we have seen that many mergers and acquisitions still fail, sometimes failure

rates of fifty percent were found. Therefore, it is important that all the causes for failures are

intensively investigated and that managers are aware of these causes so they can better steer the

processes within mergers and acquisitions. Although a lot of research has been conducted

already, the high failure rates still remain, so better understanding of the causes for failure is

necessary. This research will contribute to that by investigating the success of mergers and

acquisitions.

Secondly, this research helps to fulfill a gap in the literature. It has been shown that the topic of

human interference has been neglected for a long time, while it has been proven that managers

destroy or create value in many mergers and acquisitions (McCarthy & Dolfsma, 2012;

Trautwein, 1990; King et al., 2004). Therefore, this research will focus on the role of managerial

power and its influence on post-merger financial performance.

Thirdly, this study will contribute to the research by providing an empirical test of contradictory

perspectives. By doing that, this research will contribute to help resolving the paradox in the

discussion whether there is a positive or negative influence of managerial power on post-merger

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financial performance. Prior research shows no agreement on the nature of the relation and so this

leaves a gap in the literature. This article will fill this gap by testing whether this relation is

positive or negative.

In the fourth place, this research will build further on earlier research. Daily & Johnson (1997)

were one of the few who found a significant positive relation between managerial power and

post-merger financial performance. However, they only investigated the relation between basic

pay and post-merger financial performance. By using the total compensation of the CEO, the

limitations of their study will be overcome. Therefore, this study will have a higher

generalizability.

In the fifth place, this research will contribute to the literature and follow the advice of King et al.

(2004) by taking two moderators into account. The first one is the period of the wave. Because

earlier research showed that success factors vary from period to period (Martynova &

Renneboog, 2008) it seems logical that the relation between managerial power and post-merger

financial performance is stronger or weaker between the different merger waves. Test results

should prove the nature (positive or negative) of this effect. Prior research leaves a gap in the

literature that will be filled by this article by testing the relation in different periods. As a result,

the generalizability of the study will be higher. The second moderator is the acquisition rate of

the target’s stocks. Fowler & Schmidt (1989) used the acquisition rate of the target’s stocks as an

independent variable and found a significant positive relationship between the percentage of

stocks acquired and the post-merger financial performance. However, it was another part of their

research which gave an interesting insight into using the acquisition rate of the target’s stocks as

a moderator instead of an independent variable for this study. They stated that if a relationship

exists between the percentage of stocks acquired and the degree of influence over a target, the

effectiveness of integration presumably would be affected. This could be a reason for using the

acquisition rate of the target’s stocks not as an independent variable, but as a moderator. Because

they saw the effectiveness of integration as an indicator of the success of mergers and

acquisitions and influence as an indicator of managerial power, the variable acquisition rate of the

target’s stocks is applicable for my study. So far prior research did not test this moderating effect,

that is why this research can contribute to the literature. Moreover, the article gives substantiation

for using the acquisition rate of the target’s stocks as a moderator instead of an independent

variable for my own study.

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Finally, this research gives some managerial implications. Because this research gives an answer

to the question whether managerial power leads to more or less successful mergers and

acquisitions, the organizations concerned will be able to make a better choice in searching for the

right CEO.

1.3 Structure of the paper

In this section I will outline the structure of this paper. In chapter two the theory development

will be described. In this overview the existing literature about success factors will be reviewed

first. Furthermore, in 2.1 the reason for choosing managerial power as the most important

variable for investigation is given. In part 2.2 the hypotheses will be developed. Therefore, all the

important studies about the subject of managerial power, post-merger financial performance,

period of the waves and acquisition rate of the target’s stocks will be covered. At the end of

chapter 2.2 a conceptual model will be given with all the constructs and relations in it.

The third chapter of this paper will be the empirical methodology. In this part I will first lay out

the strategy for collecting data in 3.1. Secondly, I will give the objective operational definitions

of all the variables that are important in the conceptual model, independent (3.2), dependent (3.3),

moderating (3.4) and control (3.5).

In the fourth chapter of this paper I will discuss the results. Firstly, in 4.1 the test itself will be

explained. Secondly, in 4.2 and 4.3 the results of the regression analysis will be shown and

conclusions about rejecting or accepting the hypotheses can be made.

The fifth and last chapter will be the discussion & conclusions part. In this section the results of

the regression test will be analyzed and discussed. On the basis of earlier research I will discuss

whether there are similarities or differences in the results. Possible explanations for the

differences will be given. Furthermore, the limitations will be mentioned and suggestions for

further research will be given.

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2. THEORY DEVELOPMENT

The literature about success factors of mergers and acquisitions is very comprehensive and

elaborate. For many years authors from a variety of management disciplines investigated mergers

and acquisitions and their success factors. Some authors only investigate one success factor, like

size (Moeller, Schlingemann & Stulz, 2004). This article explains that smaller mergers perform

better than larger mergers.

Other authors focus on failures in the process (Child, Pitkethy & Faulkner, 1999; Schweiger &

Very, 2003). The process of a merger can be divided into three stages: the pre-merger

(identification & planning), the during-merger (negotiation & realization), and the post-merger

(integration) stage (Appelbaum, Gandell, Yortis, Proper & Jobin, 2000; Cartwright & Cooper,

2000; Chatterjee, 2009). For example, Straub (2007) focuses on the strategic failures and

describes three types: choosing the wrong target, paying too much for the target and integrating

the target poorly. These types correspond to the three-stage model with one failure in every stage.

Therefore, it is also important to look at the process by describing successes, because different

failures arise in different stages of the M&A process. ‘Paying too much for it’ is something which

is mentioned in many other articles (Jensen, 1986; Hitt, Harrison, Ireland & Best, 1998;

Haunschild, 1994; Hayward & Hambrick, 1997; Shimizu, Hitt, Vaidyanath & Pisano, 2004).

They all conclude that the more is paid, the weaker the post-merger financial performance will

be. Especially when there is an excess of liquidity and when premiums are paid.

Other authors try to make a more comprehensive overview. For example, Gadiesh and Ormiston

(2002) list five major causes of merger failure: poor strategic rationale, mismatch of cultures,

difficulties with communication and leading the organisation, poor integration planning and

execution, and paying too much for the target company. Cartwright & Schoenberg (2006) have

made a reflection on the advances in research in the topic of mergers and acquisitions of the last

thirty years. They summarized all the strategic and behavioral literature in three primary streams:

issues of strategic fit, organizational fit and the process itself. The organizational fit is cited as

relatedness most of the times. Merging firms may be considered related when a common skill,

resource, market or purpose applies to each of them, i.e. if they employ similar production

techniques, serve similar markets, use similar distribution systems, or employ science-based

research (Rumelt, 1974). Relatedness is one of the most discussed variables in mergers and

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acquisitions successes (Nahavandi & Malekzadeh, 1988; Shimizu, Hitt, Vaidyanath & Pisano,

2004; Hitt, Harrison, Ireland & Best, 1998; Salter and Weinhold, 1978; Porter, 1980; Lubatkin,

1983; Gugler, Mueller & Yurtoglu, 2003), although its results are very often inconsistent

(Lubatkin, 1987; Seth, 1990; Wansley, Lane and Yang, 1983).

The reason that relatedness is cited so much is because past research focused on processes and

firm- and deals-specific characteristics instead of human factors (McCarthy & Dolfsma, 2012).

For a long time the same topics were discussed, for example: failures on strategic, financial and

economic decision-making processes and characteristics like size, relatedness, structure, methods

of payment, and liquidity. King et al. (2004) conclude that past researchers almost all focused on

the same factors and gave researchers the advice to incorporate other variables in the models than

the one mentioned above, when investigating success of mergers and acquisitions. However,

King et al. (2004) did mention that some authors tried to focus on different factors, but those

authors needed more support. One example of authors who tried to focus on other factors is the

research of Seth, Song & Pettit (2002). They state that value creation by mergers and acquisitions

can be more or less successful depending on the motives behind the merger or acquisition.

Therefore, it is important to gain a deeper insight of these motives behind mergers and

acquisitions.

In general, theories concerning motivation can be divided into two broad streams. Of these

streams, the first presumes that managers of the merging companies seek to maximize profits or

shareholder wealth. Under this assumption any merger must be expected to either increase the

market power of the merging companies or reduce their costs. The second stream assumes other

managerial goals than profits, for example the growth of the firm, or quasi-irrational behavior

that might occur because managers are overcome by hubris, which is a form of overconfidence

(Gugler et al, 2003). Firth (1979) made the same distinction but named it differently. He

describes one stream as the profit maximizing and growth purpose and the other as the

management utility maximizing purpose. Trautwein (1990) is one of the few authors who made a

comprehensive overview of the different motives. He came up with seven motives for mergers

and acquisitions. The first motive is called the efficiency theory. This theory is based upon the

idea that mergers and acquisitions are planned and executed to achieve synergies. The second

motive is called the monopoly theory. This theory is based upon the idea that mergers and

acquisitions are planned and executed to achieve market power. The third motive is called the

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valuation theory. This theory is based upon the idea that mergers and acquisitions are planned

and executed by managers who have more knowledge of the value of the targeted firm than the

stock market. The fourth motive is called the empire-building theory. This theory is based upon

the idea that mergers and acquisitions are planned and executed by managers who thereby

maximize their own utility instead of their shareholders’ value. The fifth motive is called the

process theory. This theory is based upon the idea that the reasons behind mergers and

acquisitions are not rational choices but outcomes of processes influenced by the limited

information processing capabilities of individuals, the organizational routines and the political

power “games” of organization subunits and outsiders. The sixth motive is called the raider

theory. This theory is based upon the idea that the motive behind mergers and acquisitions is the

wealth transfer a person or company received from the stockholders of the firms bided for. The

seventh motive is called the disturbance theory. This theory is based upon the idea that economic

disturbances causes mergers and acquisitions. Trautwein (1990) gives a lot of criticism on many

of the motives in his article. According to him some theories are more important than others. He

cites other research to refute most of the theories above. The valuation theory, process theory and

empire-building theory can explain the motives behind mergers and acquisitions best according

to Trautwein (1990). Striking is the fact that all these theories include the role of human power.

Because human power plays such a huge role in the motives behind mergers and acquisitions it

seems logical that the role of human interference should get more attention, which is already

mentioned earlier. Human factors have been neglected for a long period, because it was always

assumed that mergers and acquisitions were a closed system with little room for human influence.

But, this part shows that the managers play a huge role in the motives for mergers and

acquisitions. Therefore, due to the important role managerial power has in the motives of mergers

and acquisitions and the fact that is has been neglected in the literature for a long time, there is

enough evidence to investigate managerial power further. I will do this in the next part.

2.1 The role of managerial power

As was stated above the desire for managerial power, prestige and empire could be a motive for

mergers and acquisitions. Many CEOs are striving for more control over resources, often because

of the linkage between company size and reward. The role of managerial power is even more

important because the targeted firm is chosen by the CEOs or by a select group of non-executives

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on the top management team most of the time. But, how is (managerial) power described in the

literature? The theory of power has been investigated over so many years, because people have

possessed power over other people ever since they existed (Dahl, 1957). Many wars have started

because of a search for (more) power, such as World War II or the wars of ancient Rome. But

power is not always a negative thing. In certain domains we accept the fact that people possess

power over us because it is laid down by law. Policemen, for example, have the authority to

intervene if necessary, and parents possess some power over their children, although it is not

explicitly written down. Because scholars in so many fields have investigated the subject of

power, a lot of different definitions exist. Dahl (1957) sees it as a social theory and he comes up

with the idea that “A has power over B to the extent that he can get B to do something that B

would not otherwise do.” He describes power as a relation between people. To describe that

relation best, four elements should be included. First, it should include references to the source,

domain or base of the power. This consists of all the resources – opportunities, acts, objects, etc.

– that someone can exploit in order to affect the behavior of others. Secondly, it should include

references to the means of power. This consists of the instruments that were actually used.

Thirdly, it should include references to the amount of power. This consists of the extent to which

the power is used. Lastly, it should include references to the scope of power. This means to what

extent it is possible to influence someone else.

This social theory about the base, means, amount and scope of power is supported by Foucault

(1982). He also says that power is a relationship between people, but he goes further by saying

that power only exists when it is put into action. If it is, of course, integrated into a disparate field

of possibilities brought to bear upon permanent structure, for example an organization. Because

that is much more interesting for this study than all the social definitions of power, the focus will

be on managerial power in organizations. One of the theories that discuss that role is the research

of French & Raven (1959). The reason why this theory is chosen is because French & Raven

discuss power in the context of change, which fits the topic of mergers and acquisitions. In their

original work they discuss five bases of power. By the basis of power they mean the relationship

between A and B, which is the source of that power. The first base of power is the reward power.

This is defined as power whose basis is the ability to reward. The second base of power is the

coercive power. This is defined as power whose basis is the ability to manipulate the attainment

of valences. It seems almost the same as reward power, because it is both about the ability to

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manipulate the attainment of valences. But in the case of reward power this is done with rewards

and in the case of coercive power this is done with punishments. The third power base is

legitimate power. This power base stems from the fact that internalized values in the subordinate

determine that the manager has a legitimate right to influence the subordinate. These values are

dependent of age, intelligence, social structure, or psychological characteristics. The fourth base

of power is the referent power. This power base stems from the fact that some people feel a

strong identification with another person. The last power base is expert power. The strength of

expert power varies with the extent of knowledge or perception that the subordinate attributes to

the manager within a given area. So it is not about ‘real knowledge’ but the perception of

knowledge.

These bases of power are very useful in getting more information about where power comes

from, but it does not describes managerial power in particular. Finkelstein (1992) changed the

framework a little and found four different power dimensions. These dimensions together should

describe the topic of managerial power completely. This framework is more specifically

developed with top managers in mind and therefore better usable than the framework of French &

Raven (1959). Besides that, in the article of Daily & Johnson (1997), which was one of the

motives for my own research, this framework was used in describing managerial power too.

Therefore, a deeper insight in this framework is necessary for this study. The four managerial

power dimensions Finkelstein (1992) uses are:

1) Structural power. This power dimension is based upon the fact that managers who have a

legislative right to exert influence are more influential than other managers. It is about

formal organizational structure and hierarchical authority. The greater a manager's

structural power, the greater the control will be over colleagues actions and the less he or

she will be dependent on other members within the organization.

2) Ownership power. This power dimension is based upon the fact that managers who have

significant shareholding within the organization have more managerial power than other

managers.

3) Expert power. This power dimension is based upon the fact that managers with relevant

expertise may have significant influence on a particular strategic choice and therefore

possess more managerial power than other managers. This managerial power will even be

higher when this expertise is critical to an organization.

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4) Prestige power. This power dimension is based upon the reputation of a manager in the

institutional environment of the organization and among stakeholders. The more he or she

stands in the ‘managerial elite’ or the more he or she interacts with other high valued

persons, the more managerial power he or she will have.

Not all these dimensions are within the scope of this research. For example, the dimension of

ownership power is difficult to investigate within my research. During the process of mergers and

acquisitions the amount or ratio of shares of both companies could change. Top managers who

possess a large number of shares in the pre-merger phase could possess a lot more or a lot fewer

shares in the post-merger phase after the aggregation. Data unavailability is therefore the main

reason for not using this dimension.

Because the proportion of expert power or prestige power a manager possesses is independent of

the hierarchical function of this manager, these two managerial power domains are less suitable

for this research. First of all, because it was stated earlier that the CEO plays a huge role in the

merger and acquisition process, it turns out that structural power is more important than expert or

prestige power. The targeted firm is very often chosen by the CEOs, simply because he or she is

the leader. Other managers could possess a lot of expert of prestige power, but the final decision

is made by the CEO. Secondly, and even more importantly, it was stated earlier that the desire for

managerial power, prestige and empire could be a motive for mergers and acquisitions. This is

why the CEO will decide what will happen, probably without listening to other managers, the

CEO’s only aim is empire-building. This shows that they make decisions independent of other

members within the organization, and this is exactly the definition of structural power. They can

strive for empire-building because, due to their hierarchical function ,they are in the position to

do that. These two arguments support the choice for taking the structural power dimension as the

most important aspect of managerial power for this study.

2.2. Hypotheses development

Managers have to use different bases of power to influence and motivate employees, especially in

processes of mergers and acquisitions when people have to change. However, prior research has

found different outcomes when the relation managerial power and post-merger financial

performance is investigated. Many studies show that the role of managerial power is not that

16

successful. For example, Covin et al. (1997) identified the leadership styles that influence post-

merger satisfaction of employees positively or negatively. They found, based on a single-case

study, that the different bases of power were not all that successful for post-merger satisfaction.

But in large-scale samples it is also concluded that managers destroy value (Cartwright &

Cooper, 1990). They state that managers are responsible for one third to one half of all the

failures of mergers and acquisitions. One of the reasons for managers’ failures is explained by the

hubris theory. In the pre-merger stage managers pay too much for their targets due to

overconfidence, which is called hubris. This overpricing leads to a higher failure rate of mergers

and acquisitions (Roll, 1986; Haywood & Hambrick, 1997). The article of Grinstein & Hribar

(2003) is even more suitable because, just like in this research, they incorporate the role of

managerial power. But their conclusion gives an even more dramatic impression. They found that

mergers and acquisitions which were led by CEOs with a significant proportion of managerial

power, were received more negatively by the market. In conclusion, it leads to the following

hypothesis.

Hypothesis 1a: The higher the proportion of managerial power, the less successful the

post-merger financial performance will be.

One can conclude that a powerful CEO is not a positive resource in the organization. But why

then do all companies still search for strong powerful CEOs? If these powerful CEOs only

destroy value they would never again be considered for a vacancy. Therefore, it sounds rather

unbelievable that managers only have a negative influence on post-merger financial performance.

Dutta, MacAulay & Saadi (2011) asked themselves the same question. They did not believe

either that managers only destroy value for two reasons. They said: “First, in an effective and

competitive labor market, CEOs are likely to be concerned about their reputation. Therefore, they

are not likely to make an acquisition which might hurt their reputation in the future without

rational analysis. Second, most of the CEOs have long-term performance incentive (such as stock

options and profit sharing schemes) in a firm. Therefore, they might not be interested just in

short-term M&A bonuses. Rather, they might be interested in acquiring a good target, which will

give long-term benefits to them (in terms of a total CEO compensation package).” (p, 258).

Harford & Li (2007) also investigated the relation of managerial power and post-merger financial

17

performance. They found that in companies with a strong board a relation exists between

negative post-merger performance and pay. In other words, in such companies CEOs will search

the best targets because their compensation is dependent on the financial results. So in these

organizations CEOs do not have the possibility to strive for their own interest. This result

supports the idea that managerial power could lead to better post-merger financial performance.

Furthermore, in the same article they found that only those firms that have extremely good post-

merger stock performance continue with additional acquisitions. And because the size of the

organization influences the amount of compensation for the CEO (Jensen, 1986; Grinstein &

Hribar, 2003), it is implied that managers will search for targets which have a positive influence

on the post-merger stock performance because then the basis for further merger & acquisition

activity is higher.

The most interesting assumption for further investigation can be found in the article of Daily &

Johnson (1997). These authors tested the relation between managerial power and the post-merger

financial performance. They took the relative compensation of the CEO as an objective

measurement for managerial power. They found a significant and positive relationship between

this relative compensation of the CEO and the post-merger financial performance. However, only

the basic compensation was included in the relative compensation of the CEO. Because most

CEOs have a lot of options, grants, bonuses, et cetera, this result could be different if the entire

compensation package is incorporated in the relative compensation of the CEO. If the

relationship between managerial power and post-merger financial performance is still significant

under this condition, a much better generalizable and valid research conclusion could be drawn.

That is an interesting challenge for this study. In conclusion, it leads to the following hypothesis.

Hypothesis 1b: The higher the proportion of managerial power, the more successful the

post-merger financial performance will be.

However, King, Dalton, Daily & Covin (2004) state that in research of post-merger financial

performance the role of moderating effects often is neglected. Therefore, they advise future

researchers to incorporate moderating variables into their models for better results. That is why I

will take these moderating effects into account. Here, period of the wave and the acquisition rate

of the target’s stocks will be used as a moderator. First, the reason for choosing the period of the

18

wave as a moderator will be outlined, but for a better understanding, the topic of merger waves

has to be shortly discussed.

As mentioned before mergers and acquisitions come in waves. A takeover wave, as these waves

are called, reflects the wave pattern of the number and the total value of takeover deals over time

(Martynova & Renneboog, 2008). Each takeover wave begins after a number of economic,

political, and regulatory changes. For a long time, five completed waves have been examined in

the literature. But lately more evidence was found for the existence of a sixth wave.

The first wave, which is also called the Great Merger Wave, started around 1890 in the United

States. This period was characterised by radical changes in technology, economic geographic

expansion, innovations in industrial processes, the introduction of new state corporate legislation,

and the development of industrial stock trading on the New York Stock Exchange. The main

characteristic of this wave was its horizontal character. By far, most of the mergers were

characterized by horizontal consolidation of industrial production. Due to the horizontal mergers

the first monopolies appeared in this time. It is therefore that Stigler (1950) called this pattern

merging to form monopolies. This wave came to an end at the beginning of the 20th

century,

when the equity stock market crashed.

The second wave started around 1918, when the First World War ended and economic recovery

was necessary. The main characteristic of this wave was its vertical character. Many small

companies merged to achieve economies of scale and build strength to compete with the

dominant monopolies, which were created in the first wave. Therefore, Stigler (1950) describes

this wave as a move towards oligopolies, because through this merging pattern more larger

companies were created. The large monopolies did not attempt to regain power through new

mergers. Stigler (1950) suggest that the lack of sufficient capital to finance the mergers and the

antimonopoly laws which were developed in the first years of the 20th

century were the reasons

for this. This second wave ended with the stock market crash and the subsequent economic

depression in 1929. In the following decades there was little merger and acquisition activity due

to the worldwide recession and the Second World War.

The third wave started around 1960 and lasted for almost two decades. The beginning of this

wave was initiated by the economic recovery and the anti-trust regime in the United States in

1950. The main feature of this wave was a very high number of diversifying takeovers that led to

the development of large conglomerates. The reason why companies started these large

19

conglomerates was to benefit from growth opportunities in new product markets unrelated to

their primary business. This allowed them to increase value, reduce their earnings uncertainty,

and to overcome imperfections in external capital markets. Another characteristic of this wave

was that the geographical scope widened beyond the United States for the first time, namely to

the United Kingdom. The third wave ended in 1973, when the oil crisis started and the world

economy fell into a recession.

The fourth wave started in 1981, when the stock market had recovered from the economic

recession. The start of the fourth wave was initiated by changes in anti-trust policy, the

deregulation of the financial services sector, the creation of new financial instruments and

markets, and by technological progress in the electronics industry. The conglomerate structures

created during the third wave had become inefficient by the 1980s and so companies were forced

to reorganize their businesses (Shleifer and Vishny, 1991). Therefore, this wave was

characterised by a huge number of divestitures, hostile takeovers, and privatization. The

geographical scope of this wave stretched beyond the United States and the United Kingdom and

also influenced the corporate structures in Western-Europe. The fourth wave ended with the stock

market crash of 1987.

The fifth takeover wave started in 1993. It was initiated by the increasing economic globalisation,

technological innovation, deregulation and privatisation, as well as by the economic and financial

markets boom. A main characteristic of this fifth wave is its international character. The

European takeover market was about as large as the market in the United States in the 1990s, and

an Asian takeover market also emerged. A second characteristic was that a substantial proportion

of the merger and acquisition activity consisted of cross-border transactions. Previously

domestically-oriented companies started takeovers abroad as a means to survive the international

competition created by global markets. The dominance of industry-related (both horizontal and

vertical) takeovers and the decline in the relative number of divestitures during the fifth wave

suggests that the main takeover motive was growth to participate in globalized markets.

Compared to the fourth takeover wave, this fifth wave had fewer hostile bids in the United Stated

and the United Kingdom. However, a huge number of hostile takeovers was started in

Continental Europe. The fifth wave ended with the attacks on 9/11 and the subsequent equity

market collapse in the beginning of the 21st century.

20

Some authors (Martynova & Renneboog, 2008) believe that a sixth wave emerged in 2003

because of the rise of cheap credit. This wave continued were the fifth wave stopped. A large

number of cross-border deals are still being made and thus the international industry

consolidation which started in the 1990s is continued. Remarkably, this sixth wave was the first

wave that was not led by the United States and had more activity in Europe. Recent acquirers

seem to prefer friendly negotiations to the aggressive bidding, as the number of hostile bids is at a

modest level. This sixth wave ended with the financial crisis around 2008.

Not all these merger waves are interesting for my study. For two reasons only the last two waves

will be included in this research. Firstly, because more recent information is more interesting for

research than older information. Secondly, and much more importantly, only in these two waves

does the financial sector belong to the industries with the most merger and acquisition activity.

And because I take a sample from the financial sector, only the fifth and sixth wave are

interesting for my study. Evidence is found that mergers and acquisitions in the sixth wave were

more successful than their predecessors in the fifth wave (McCarthy & Dolfsma, 2012). These

authors based their assumptions on the fact that the sixth wave has a number of factors acting in

its favour, compared to the fifth wave. Firstly, in the sixth wave more mergers and acquisitions

were financed with cash. Earlier research found that cash-financed deals are more beneficial to

the bidder’s shareholders (Carow, Heron & Saxton, 2004; Huang & Walkling, 1987; Loughran &

Vijh, 1997; Travlos, 1987; Goergen & Renneboog, 2004; Franks, Harris & Titman, 1991).

Secondly, McCarthy & Dolfsma (2012) found that in the sixth wave the number of hostile bids

had declined. Because hostile mergers and acquisitions lead to poorer performance and wastes

resources (Gaughan, 2010; Dong, Hirshleifer, Richardson & Teoh, 2006; Croci, 2007), the results

of mergers and acquisitions in the sixth wave had to be better. Lastly, the mergers and

acquisitions in the sixth wave tended to be more related. The opposite of related mergers and

acquisitions are diversifying mergers. Evidence is found that these diversifying mergers destroy

value (Gaughan, 2010; Chatterjee, 1986; Datta, 1991; Salter & Weinhold, 1978; Hitt, 1998;

Wansley, Lane & Yang, 1983). Furthermore, and more interesting for this research, these

diversifying mergers and acquisitions are more likely to be pursued by managers who strive for

more prestige, empires and self-entrenchment (Shleifer & Vishny, 1991; Mueller, 1969). So by

conducting more unrelated mergers and acquisitions in the fifth wave, the role of powerful

21

managers will be higher in that period and so their possibility to influence the post-merger

financial performance. Therefore the expectation is that:

Hypothesis 2: The effect of managerial power on post-merger financial performance will

be stronger in the fifth wave than in the sixth wave.

The other moderator in this study will be the acquisition rate of the target’s stocks. As stated

earlier the usage of the acquisition rate as a moderator stems from the article of Fowler &

Schmidt (1989). In their article they state that if an acquirer buys twenty percent of the target’s

stocks, it is presumed that the acquirer has the possibility to have influence over the target to

some extent. That means CEOs can use their power to influence post-merger performance and it

seems logical that the possibility to influence post-merger performance will increase if a higher

percentage of the target’s stocks is acquired. Fowler & Schmidt (1989) further stated that if a

relationship exists between the percentage of stocks acquired and the degree of influence over a

target, the effectiveness of integration (in their study an indicator of success of mergers and

acquisitions) presumably would be affected. So the firms that acquired a significant portion of a

target firm’s stocks may be able to exert more influence during integration than firms that

acquired a smaller percentage. This part of their study could prove that a relation between a

proportion of influence and the success of mergers and acquisitions will be influenced by the

degree of acquisition. Because managerial power is all about influence, I assume that the degree

of acquisition, also called the acquisition rate of the target’s stocks, influences the relation

between managerial power and post-merger financial performance. This assumption is also in

line with conclusions in earlier research, which stated that future researchers should use more

variables as moderators, because interaction effects could explain a lot of the so far unidentified

variances (King et al., 2004; Hitt et al., 1998). Therefore the expectation is that:

Hypothesis 3: The effect of managerial power on post-merger financial performance will

be stronger in cases with a higher acquisition rate of the target’s stocks

than in cases with a lower acquisition rate of the target’s stocks.

22

In short, in this research the effect of the role of managerial power on post-merger financial

performance will be investigated. The period of the wave and the acquisition rate of the target’s

stocks will act as moderator. The relations that will be tested are shown in FIGURE 2. It is not

sure whether the relations are positive or negative, therefore this is a neutral model.

FIGURE 2 Conceptual model

23

3. EMPIRICAL METHODOLOGY

Before collecting data for investigating the relation between managerial power and post-merger

financial performance, some issues of empirical methodology have to be discussed. Firstly, in

section 3.1 the strategy for collecting data will be outlined. Secondly, it is explained what is

understood by the independent (section 3.2) and dependent variables (section 3.3) within the

conceptual model. Thirdly, in section 3.4 it is explained in which way the moderating variables

will be measured. Finally, in section 3.5 the role of the control variables within the conceptual

model will be explained and theoretically supported.

3.1 Data collection

As mentioned before this research will make use of secondary data. The data source for mergers

and acquisitions that will be used is called the ZEPHYR database, which is a variant of ORBIS.

The extensive database contains all sorts of business deals including mergers, acquisitions and

international joint ventures. In making a sample some changes had to be made to make the

database more applicable for this research. Firstly, only mergers and acquisitions that are 100%

completed are incorporated in the sample, because this research is only focused on post-merger

financial performance. Secondly, as mentioned before, only mergers and acquisitions that are

completed in the fifth and sixth wave will be investigated. Because ZEPHYR only has data from

1997 onwards, the sample consists of mergers and acquisitions which are completed between

1997-2008. Thirdly, some studies found that cultural differences influence the success of mergers

and acquisitions (Lodorfos & Boateng, 2006; Morosini, Shane & Singh, 1998; Morosini, 2004;

Chatterjee, Lubatkin, Schweiger & Weber, 1992). To exclude the effects of culture, only US

firms are used in the sample. In the fourth place, because of greater data availability, only

mergers and acquisitions which were performed by companies who are publicly listed are

included in the sample. Finally, some studies found that industry differences influence the

success of mergers and acquisitions (Zollo & Singh, 2004; Kusewitt, 1985). Therefore, to exclude

the effects of industrial differences, this research will focus exclusively on one particular

industry. Because over the last decades a lot of mergers and acquisitions have taken place in the

financial sector (Martynova & Renneboog, 2008; Bliss & Rosen, 2001; Ramaswamy, 1997) only

24

mergers and acquisitions within this industry will be included in the sample. After all these steps

10.102 mergers and acquisitions were left in the sample.

The data for measuring the variables were extracted from the database of COMPUSTAT. With

use of SQL codes the different variables were linked to each other by TICKER symbol and

combined into one dataset. With use of SPSS all the data could be analyzed to test the hypothesis.

3.2 Independent variable: managerial power

Firstly, the independent variable, managerial power, will be described. The measurement of

managerial power causes some problems. One of the major problems has been an overreliance on

perceptual indicators of managerial power and a lack of objectivity in the resulting measures

(Finkelstein, 1992). Managerial power is a sensitive subject for many managers; the word itself is

heavily laden with meaning. Finkelstein (1992) refers in his article also to other authors (March,

1966; Pfeffer, 1981) who found the measurement of the concept managerial power as a major

obstacle in their investigations. Because perceptual measures of managerial power have a

questionable validity due to difficulties in measurement the importance of objective measures

within a research is high. That is one of the reasons why this research will rely on secondary data.

The framework of French & Raven (1959) implies the existence of perceptual indicators and is

therefore less suitable to this research, although it is widely used. Finkelstein (1992) changed the

framework a little and found some objective measures for the different power dimensions. The

model itself and the reason for choosing the structural power dimension as the only dimension

that will be investigated was already discussed within section 2.1

Right now, more important is how this variable will be measured. An objective measurement

should be chosen. Finkelstein (1992) states that the amount of compensation could be an

objective measurement for structural power. Managers' compensation is an exact, but less formal

reflection of their place in an organization. It seems logical that someone on the top of an

organization, with high structural power, earns more money than someone who is placed lower in

the organizations ranking. So the more structural power a manager possesses, the more this

manager will earn. This formal hypothesis leads to two measurement errors. Firstly, large

organizations will pay higher salaries than smaller organizations. But this does not mean

automatically that managers of larger organizations possess more structural power than managers

25

of smaller organizations. That means that the impact of the scale of the organization has to be

excluded. Secondly, some organizations will pay small salaries but they offer a lot of bonuses

while other organizations pay high salaries with small bonuses. That means that the impact of the

heterogeneity in payments also has to be excluded. Therefore the operation definition of the

proportion of managerial power will be: POWER = total compensation CEO acquirer / average

compensation of all other members in the top management team of the acquirer in the completed

year. With this approach, this study will go further than Daily & Johnson (1997). They only

found a significant positive relationship for basic pay and post-merger performance. By taking

the total compensation, a better generalizable conclusion is possible.

3.3 Dependent variable: post-merger financial performance

In this part the variable ‘post-merger financial performance’ will be explained. With the selection

of a good objective measurement for this variable, a wide range of different operational

definitions emerge. Zollo & Meier (2008) give a good overview of all the different definitions of

post-merger financial performance. They state that approaches to measure post-merger financial

performance vary from subjective to objective, from short-term to long-term time horizon and

from an organizational level of analysis to a process or transactional level. For the best possible

measure all these six elements should be included. Zollo & Meier (2008) present a very

comprehensive model in which they incorporate these six elements. But, it can also be explained

in a more compact manner, like Napier (1989) did. As I already mentioned earlier, this study will

follow her definition. She chose to combine all the definitions into two main categories in her

article. She mentioned that the success of a merger and acquisition could be measured by 1)

financial or other objective performance measures and 2) by employee reaction or morale

measures. Because in this research the use of objective secondary data is very important, the

definitions in the area of employee reaction or morale measures are less applicable. Therefore the

focus will lie on financial or other objective performance measures.

The literature about financial objective performance is very extensive and therefore various

performance measures can be used. Before 1970, studies that investigated post-merger

performance focused on accounting based performance measures (Lubatkin, 1983). However,

these measures do have a lot of limitations. First, these measures do not fit with the goal of

organizations, creating maximum shareholder wealth. Secondly, these measures ignore the

26

impact of risk. For example, shareholders could gain higher returns, but if the risk burden is

increased they would be no better off in the end. Finally, these measures are biased by specific

events which also influence firms profitability. For example, it takes years before a merger or

acquisition has its effect on profitability. In those years other firm specific or market specific

disturbance could bias these results.

After 1970, due to all the limitations, market-based performance measures were used to

investigate post-merger performance. One of the most widely used market-based measures is the

stock price (Jensen and Ruback, 1983; Lubatkin, 1987; Woo, 1992; Chatterjee, 1992; Singh &

Montgomery, 1987; Datta, 1991). Many variants are used, but in general it is about a comparison

between the stock price of the individual firms before the merger or acquisition and the new stock

price of the combined firm in the post-merger phase. Morosini, Shane & Singh (1998) decided to

use the percentage rate of growth sales because stock price related measures were not suitable to

their research. Firstly, by using stock price related measures for investigating success of mergers

and acquisitions, many companies, which were not listed on the stock market, were excluded for

research. Therefore, by using stock price related measures, the total activity of mergers and

acquisitions is not measured and the research is biased. Secondly, Morosini, Shane & Singh

(1998) argue that some stock markets are known for their lack of market efficiency and are

therefore not suitable for stock price related measures. Although these arguments sound rather

credible, the percentage of growth sales as a measurement of success of mergers and acquisitions

will not be used in this research, because this measure captures only one dimension of

performance and the importance of this measure will differ across strategic contexts (Lubatkin &

Shrieves, 1986).

Due to all these limitations the ideas of Zollo & Meier (2008), Kusewitt (1985), Lubatkin (1983),

Lubatkin & Shrieves (1986) and DeLong & DeYoung (2007) will be used. They all advise to use

measures related to abnormal returns by using the Return on Assets (ROA). Therefore the

operational definition of the success of mergers and acquisitions will be in line with these

authors: ROA = net income before depreciation acquirer / total assets acquirer one year after

completed date.

27

3.4 Moderating variables

In this research the period of the wave and the acquisition rate of the target’s stocks will be used

as a moderating variable. In this part the operational definitions will be given.

The way the moderating effect of the period of the wave is measured is on a quite objective base.

The fifth wave consist of the years 1993-2001 and therefore the influence of managerial power on

the success of mergers and acquisitions will first be tested on mergers and acquisitions

throughout those years. The sixth wave comprises the years 2003-2008 and therefore the

influence of managerial power on the success of mergers and acquisitions will be tested secondly

on mergers and acquisitions throughout those years. This moderator will be called ‘Wave’ and is

measured as a dummy variable in which the mergers and acquisitions which were completed in

the fifth wave will be labelled as ‘1’ and the ones which were completed in the sixth wave will be

labelled with ‘0.’

The other moderating effect in this study will be the acquisition rate of the target’s stocks. This

moderating variable will be measured as a dummy variable and is called ‘Type’. Cases in which

the target is acquired for 100% will be labelled as ‘1’ and the ones in which the target is acquired

for less than 100% will be labelled with ‘0.’

3.5 Control variables

To control the possible effects of other variables on the dependent variable some control

variables are necessary. By doing this, my research will be much more valid, especially when the

hypothesis is still confirmed under these circumstances. Earlier research has produced a lot of

options for possible control variables in studies on merger performance. In TABLE 1, an

overview of earlier research is given. TABLE 1 is shown in appendix 1.

It is striking that some control variables show up in every study, for example (relative) size.

Because size and relative size are quite different, both control variables will be used.

Relative size may influence post-merger financial performance, although not all authors agree on

the direction of this influence. Shrivastava (1986) concludes that the larger the size of the

acquirer relative to the target, the more difficult it is for the acquirer to understand all the areas

28

where integration is needed. This process has a negative influence on the post-merger financial

performance. Kitching (1967) also found that the greater the difference between acquirer and

target, the weaker the post-merger financial performance. Alternatively, Kusewitt (1985) says

that there is a tendency of firms to investigate larger targets more consistently and more thorough

than smaller targets. In that case the greater the relative size, the better the post-merger financial

performance. Besides that, relative organizational size may have a direct influence on shareholder

gains because larger firms might acquire smaller firms to realize scale-related synergies that

would otherwise be difficult to obtain (Kusewitt, 1985). Although the direction of the influence

is not quite clear, its impact on post-merger financial performance seems obvious. That is why it

would be wise to include relative size as a control variable in this study. In respect to relative

size, the operational definition of Kusewitt (1985), Fowler & Schmidt (1989), Ramaswamy

(1997), and Zollo & Singh (2004) will be used: RELSIZE = Total assets acquirer / Total assets

target in the year before completion of the merger. The reason to choose RELSIZE in the year

before completion is because in many cases the target company is incorporated in the acquirer

and does not exist as a company by itself anymore. In that case many figures, such as total assets,

are not available after completion. Therefore, for greater data availability the figures in the year

before completion are investigated. For size the operational definition will be: SIZE =

Sales/Turnover of the acquirer in the completed year. This definition is chosen because this

definition is also used in similar studies in which a relation between managerial power and post-

merger financial performance is tested (e.g. Harford & Li, 2007).

It is also expected that experience in merger and acquisition activity influences post-merger

financial performance (Fowler & Schmidt, 1989; DeLong & DeYoung, 2007; Carow, Heron &

Saxton, 2004; Harford & Li, 2007). Just like gaining economies of scales, organizations are also

learning by being active in the business of mergers and acquisitions. The idea is that the more

mergers and acquisitions an organization completes, the smoother the process will be with the

next merger or acquisition. Therefore this control variable will also be included in this research.

The definition of Carow, Heron & Saxton (2004) is more precise than those of other authors.

Carow, Heron & Saxton (2004) use a squared term because experience is expected to have a

curvilinear relationship with performance. It has a stronger effect in the beginning, but the effect

gets weaker when experience increases. Therefore in this research their operational definition will

29

be used: EXPERIENCE = (# acquisitions made by acquirer in past three years until completed

year).2

Because some variables in TABLE 1 are already part of the sampling process (e.g. year, industry

relatedness, country, uncertainty avoidance) and some qualitative variables could not be obtained

by using secondary data of ZEPHYR and COMPUSTAT (e.g. resource quality of target, post-

acquisition strategy, type) RELSIZE, SIZE, and EXPERIENCE will be used as control variables

in this study.

30

4. RESULTS

This section will give the results of the tested relations of the conceptual model. Firstly, the test

itself will be explained. Secondly, the results of the test will be shown and with that the

hypotheses 1a, 1b, 2 and 3 can be accepted or rejected.

4.1 The regression model

Because this study assumes that managerial power has an influence on post-merger financial

performance, a causal relation arises. To analyze causal relations the most common test is the

regression analysis. To make the test as valid as possible all the variables are incorporated in the

regression model. If all the variables for testing hypothesis 1a and 1b are incorporated in the

model the regression model looks like:

Y = β0 + β1 * POWER + β2 * RELSIZE + β3 * SIZE + β4 * EXPERIENCE + Ɛ

In which Y is the dependent variable post-merger financial performance, which is measured by

ROA.

Because the period of the wave acts as a moderator, this variable needs to be added to the model

also, otherwise there is no result for hypothesis 2. This hypothesis states that in the fifth wave the

effect of managerial power on post-merger financial performance will be stronger than in the

sixth wave. To add this moderating effect in the model an intersect variable had to be made. This

intersect variable will be called ‘Moderator_W’ and is computed by multiplying the dummy score

of the variable ‘Wave’ with the score on the variable POWER. Just like for hypothesis 1, to find

statistic evidence for hypothesis 2 a regression model had to be made. Because the effect will be

stronger in the fifth wave, the regression model will look like:

Y = β0 + β1 * POWER + β2 * RELSIZE + β3 * SIZE + β4 * EXPERIENCE + β5 * Wave + β6 *

Moderator_W + Ɛ

31

In which Y is still the dependent variable post-merger financial performance, which is measured

by ROA.

In the sixth wave the effect will be weaker. Because the scores of the dummy variable ‘Wave’ in

the sixth wave were labelled as ‘0,’ the interacting variable will also be ‘0.’ So in the sixth wave

the following regression model represents the situation:

Y = β0 + β1 * POWER + β2 * RELSIZE + β3 * SIZE + β4 * EXPERIENCE + β5 * Wave + Ɛ

In which Y is still the dependent variable post-merger financial performance, which is measured

by ROA.

Finally, the acquisition rate of the target’s stocks also acts as a moderator. To obtain a result for

hypothesis 3 this variable needs to be added to the model too. This hypothesis states that in cases

of a higher acquisition rate of the target’s stocks, the effect of managerial power on post-merger

financial performance will be stronger than in cases with a lower acquisition rate of the target’s

stocks. To add this moderating effect in the model, an intersect variable had to be made. This

intersect variable will be called Type_Control and is computed by multiplying the dummy score

of the variable ‘Type’ with the score on the variable POWER. Just like for the other hypotheses,

to find statistic evidence for hypothesis 3 a regression model had to be made. Because the effect

will be stronger in cases of a higher acquisition rate the regression model will look like:

Y = β0 + β1 * POWER + β2 * RELSIZE + β3 * SIZE + β4 * EXPERIENCE + β5 * Type + β6 *

Type_Control + Ɛ

In which Y is still the dependent variable post-merger financial performance, which is measured

by ROA.

In cases of a lower acquisition rate of the target’s stocks the effect will be weaker. Because the

scores of the dummy variable Type in cases of lower acquisition rate were labelled as ‘0’ the

interacting variable will also be ‘0.’ So in cases of a lower acquisition rate the following

regression model represents the situation:

32

Y = β0 + β1 * POWER + β2 * RELSIZE + β3 * SIZE + β4 * EXPERIENCE + β5 * Type + Ɛ

In which Y is still the dependent variable post-merger financial performance, which is measured

by ROA.

4.2 Descriptive statistics

Before the results of the regression analysis are shown, I will first present the descriptive

statistics in TABLE 2.

TABLE 2

Descriptive statistics

Minumum Maximum Mean

Statistic Statistic Statistic Std.

Error

ROA 0,00 1,03 0,08 0,00

Power 0,01 64,79 1,17 0,04

Wave 0 1 ,27 0,01

Relsize 0,20 37901,16 30,38 13,21

Size 0,00 345977,00 26029,63 488,95

Experience 0 626 51,09 1,47

Moderator_W 0 31,54 0,19 0,01

Type 0 1 0,43 0,01

Type_Control 0 0,81 0,03 0,00

N = 5625.

This table shows that the total number of deals is 5.625 instead of the 10.102 that was mentioned

earlier. This is because I only used the values that are above zero for the dependent variable. This

way, all the deals that do not have a value on ROA are left out the analysis, because there is no

possibility of testing an independent variable on a value that does not exist.

4.3 Regression results

In this section the results of the regression analysis will be presented. The regression method that

I have used, is the method ENTER, because I do not want to exclude any variables from the

model. All the important results are shown in TABLE 3.

33

TABLE 3

Results from Regression Analysis

Note: Dependent Variable is ROA, Standard errors are in parentheses

* p < .05, ** p < .01, *** p < .001

First, it is stated that R

2 = 0,465. That means that 46,5% of all the variance of the dependent

variable is explained by the independent variables. Although it is not an indicator of a very strong

relationship, it is enough for a valid study and further analysis of the regression model.

The results of the overall variance analysis give a significant value of F = 610,382 (p < .001) for

the whole model. That means that at least one of the variables in the regression model and the R2

differs significantly from zero. Therefore, there is enough support to look at the individual

variables in the model. By doing this, the relations stated in this study can be analyzed and the

hypotheses can be supported or rejected. For this analysis the output of the estimated regression

coefficients is needed. This output is also shown in TABLE 3.

Firstly, I will look at my main hypothesis, the relation between managerial power and post-

merger financial performance. In TABLE 3 it can be seen that POWER has a significant value of

β = .002 (p < .001). That means that there is enough evidence for supporting a relation between

managerial power and post-merger financial performance. But, because I used contradictory

hypotheses, the direction of the relation has to be analyzed. The positive value of β indicates that

there is a positive relation between managerial power and post-merger financial performance.

Therefore, there is enough evidence to support hypothesis 1b, and for rejecting hypothesis 1a.

Variables Model 1

Power .002*** (.000)

Wave -.002 (.002)

Relsize -.000 (.000)

Size -.000*** (.000)

Experience -.000*** (.000)

Moderator_W .002* (.001)

Type -.097 (.002)

Type_Control

R2

F

.996*** (.016)

.465

610,382***

34

Secondly, I will look at the moderating relations. The first moderating effect was the period of

the wave. I assumed that the effect of managerial power on post-merger financial performance

was stronger in the fifth wave than it was in the sixth wave. In TABLE 3 it can be seen that the

intersect variable Moderator_W has a significant value of β = .002 (p < .05). The positive value

of β indicates that there is a positive moderating effect of the period of the wave on the

relationship between managerial power and post-merger financial performance. That means that

there is enough evidence to support this moderating effect and therefore hypothesis 2 will be

accepted. The second moderator was the acquisition rate of the target’s stocks. I assumed that the

effect of managerial power on post-merger financial performance was stronger if the acquisition

rate of the target’s stocks was high. In TABLE 3 it can be seen that the intersect variable

Type_Control has a positive significant value of β = .996 (p < .001). The positive value of β

indicates that there is a positive moderating effect of the acquisition rate of the target’s stocks on

the relationship between managerial power and post-merger financial performance. That means

that there is also enough evidence to support this moderating effect and therefore hypothesis 3

will also be accepted.

Finally, I will look at the control variables and their effect on the dependent variable. The control

variables that I used in this study were RELSIZE, SIZE and EXPERIENCE. In TABLE 3 it is

shown that RELSIZE has a value of β = -.001, but that this result was not significant. That means

that there is not enough evidence that this control variable influences post-merger financial

performance. SIZE (β = -.001) and EXPERIENCE (β = -.001) both have a significant value that

is lower than .001. Because of the negative value of β, they both influence post-merger financial

performance in a negative way. So the bigger the size of the organization and the more

experienced they are in performing merger and acquisition activity, the less successful post-

merger financial performance will be.

35

5. DISCUSSION & CONCLUSIONS

In summary, this study addressed the topic of mergers and acquisitions. First of all, the topic was

introduced by discussing the high failure rate of mergers and acquisitions. Secondly, in the theory

development part the different failure factors were discussed and it became apparent that

managerial power needed further investigation. Earlier research discussed whether managerial

power was positively or negatively linked to post-merger financial performance. By using

contradictory hypotheses this study will contribute to help resolving the paradox in the discussion

whether there is a positive or negative influence of managerial power on post-merger financial

performance. The research question was: “How does the role of managerial power influence

post-merger financial performance?”

By executing a regression analysis, a significant positive relationship was found between the

independent variable managerial power and the dependent variable post-merger financial

performance. Therefore, there was sufficient evidence for supporting hypothesis 1b and rejecting

hypothesis 1a. So far most of the authors have supported the idea that managerial power leads to

value destruction (Covin et al, 1997; Cartwright & Cooper, 1990; Roll, 1986; Haywood &

Hambrick, 1997; Grinstein & Hribar, 2003). The outcomes of this research support the minority

of authors who claim that managerial power can lead to better post-merger financial

performances, but did not find any significant evidence (Dutta, MacAulay & Saadi, 2011;

Harford & Li, 2007). Daily & Johnson (1997) did find a significant positive relationship for

managerial power and post-merger financial performance. However, in describing managerial

power they only incorporated the basic pay of a CEO and they did not consider all the bonuses

and stock options of the CEO. Because CEOs make decisions based upon the impact they have

on their total compensation (Trautwein, 1990; Harford & Li, 1997) the results of this study give a

more valid and generalized result. Besides that, it gives organizations an argument to keep

searching for powerful CEOs because they can increase value in the process of mergers and

acquisitions. Furthermore, this conclusion helps organizations who are willing to enter the

process of mergers and acquisitions. After all, in the introduction the high failure rate of mergers

and acquisitions was addressed. Apparently, many organizations need some advice in dealing

with mergers and acquisitions. The results of this study indicate that CEOs who have a high

36

relative total compensation, also have a high proportion of managerial power and that is why

CEOs could positively influence post-merger financial performance. My conclusion shows that

organizations who are planning to enter a process of mergers and acquisitions could improve

their post-merger financial performances by searching for a powerful manager and give them a

high relative total compensation. Hopefully, these findings can help to decrease the high failure

rate of mergers and acquisitions.

This study also contributed to the research field by making use of two moderating variables. First,

the impact of the period of the wave on the relation of managerial power and post-merger

financial performance was tested. Earlier research showed that in the fifth wave more

diversifying and hostile mergers were conducted, and that diversifying and hostile mergers were

pursued more by managers who strive for more prestige, empires and self-entrenchment (Shleifer

& Vishny, 1991; Mueller, 1969).

By conducting a regression analysis, a significant positive moderating effect was found for the

period of the wave. Therefore sufficient evidence was presented to accept hypothesis 2. This

means that in the fifth wave the effect of managerial power on post-merger financial performance

will be higher. Firstly, this result helps to better understand the characteristics of the different

waves. The more we know about the past, the better the guidelines for future mergers and

acquisitions will be. Secondly, this result is in contradiction with most of the earlier research

which showed that the results of mergers and acquisitions in the sixth wave were better

(Gaughan, 2010; Dong, Hirshleifer, Richardson & Teoh, 2006; Croci, 2007; Chatterjee, 1986;

Datta, 1991; Salter & Weinhold, 1978; Hitt, 1998; Wansley, Lane & Yang, 1983). Therefore,

this study can activate further research on the characteristics of the different waves. A question

can be: Which characteristics of this fifth wave helped the powerful CEOs to positively influence

post-merger financial performance? An interesting starting question for future research. Lastly,

this result can be a start for further research on the role of diversifying and hostile firms. I found a

stronger effect of managerial power on post-merger financial performance and assumed that it

had to do with the relatedness or the hostility. But I did not test the real relation between

relatedness, hostility, managerial power, and post-merger financial performance.

37

The other moderating variable which was used in this study was the acquisition rate of the

target’s stocks. Fowler & Schmidt (1989) and Kusewitt (1985) stated that if a relationship exists

between the percentage of stocks acquired and the degree of influence over a target, the

effectiveness of integration (in their study an indicator of success of mergers and acquisitions)

presumably would be affected. So the firms that acquired a significant portion of a target firm’s

stocks may be able to exert more influence than firms that acquired a smaller percentage.

By conducting a regression analysis, a significant positive moderating effect was found for the

acquisition rate of the target’s stocks. Therefore there was sufficient evidence to accept

hypothesis 3. That means that in cases with a higher acquisition rate of the target’s stocks the

effect of managerial power on post-merger financial performance will be higher. This result has a

practical implication for organizations. If organizations have or search for a powerful CEO to

positively influence post-merger financial performance, it is better for these organizations to

obtain as much of the target’s stocks as possible. In that way the effect of the powerful CEO

positively influencing post-merger financial performance will be higher.

An unexpected result of this study is that experience in mergers and acquisitions has a significant

negative effect on post-merger financial performance. This is in contradiction with most of the

studies that used this variable (Fowler & Schmidt, 1989; DeLong & DeYoung, 2007; Carow,

Heron & Saxton, 2004; Harford & Li, 2007). The answer to how this is possible lies in the article

of Kusewitt (1985). He also found a negative relation between experience and post-merger

financial performance. The explanation Kusewitt (1985) gives, is that the relation is U-shaped

and can even be negative. He suggests that organizations should make a sufficient number of

mergers and acquisitions over time so that they can develop and maintain gains through expertise.

He states that this number of mergers and acquisitions over time should not be too high, because

then the attention which should be paid to a fully completed integration process cannot be given.

At the end of the article he even gives a guideline for proper acquisition programs in which he

states that a preferred number of mergers and acquisitions over time should be one with a

maximum of approximately one per year and a probable minimum of around one every four or

five years (Kusewitt, 1985). This way, the results from this study can lead to further

investigations of the role of experience within the relation of managerial power and post-merger

financial performance.

38

My work gives some additional suggestions for further research due to the limitations of this

study. First of all, this study is conducted in a very detailed setting, because only US firms in the

financial sector are incorporated in the sample. Further research should give an answer to the

question whether this result is in accordance with the situation on other markets or in other

countries. Secondly, I only used the structural power dimension of Finkelstein (1992) as an

indicator of managerial power and measured it with the relative total compensation. Future

research can build further on these results by incorporating other power dimensions of Finkelstein

(1992) in the model.

In conclusion, this study fulfills some gaps in the literature and helps resolve the paradox in the

discussion whether there is a positive or negative influence of managerial power on post-merger

financial performance. Besides that, this study gives a lot of suggestions for further research and

gives organizations some practical implications for improving their processes of mergers and

acquisitions. Therefore, this study has substantially added value to the literature about managerial

power and post-merger financial performance.

39

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49

APPENDIX I

TABLE 1

Overview of earlier studies with control variables on merger performance

Paper Control variable Formula

Chang (1996) Financial resources Total assets / Total liabilities

Size Log of total assets

Book value of long term debt to

market value of equity

Industry relatedness Average annual growth rate of

industry shipments

Carow, Heron & Saxton

(2004)

Number of firms within the target’s

industry

# firms within the target’s industry

the possibility that entry leads to more

targets

% change in the number of firms in

the target industry over the year

prior to each acquisition.

resource endowment of the early mover the log of the acquirer’s equity

market value

Experience in M&A activity (# acquisitions made by acquirer in

past three years)2

Relative size Market equity target / Market

equity acquirer

Liquidity position Acquirer cash & equivalents /

Acquirer total assets

Investment opportunity set Tobin’s Q ratio: ((Equity Market

Value + Liabilities Market Value) /

(Equity Book Value + Liabilities

Book Value))

Chatterjee, Lubatkin,

Schweiger & Weber (1992)

Relative size Total assets acquirer / Total assets

target

DeLong & DeYoung

(2007)

Geographic focus Dummy score (same country=1,

different country=0)

Size Log of total assets

50

Relative size Dummy score (same size=1,

different size=0)

Experience in M&A activity # acquisitions made by acquirer in

past three years

Type Dummy score (unfriendly=1,

friendly=0)

GDP growth % change in US GDP during

merger announcement

Fowler & Schmidt (1989) Relative size Total assets target / Total assets

acquirer

Experience in M&A activity # acquisitions made by acquirer in

past four years

Organizational age of acquirers # years

Industry relatedness Dummy score (same industry=1,

different industry=0)

Type Dummy score (unfriendly=1,

friendly=0)

% acquired % target firm outstanding common

stock owned by an acquiring firm

Harford & Li (2007) Size Total net sales

Growth opportunities Year-end market-to-book-ratio

averaged over the previous 5 years

Industry Dummy score (same industry=1,

different industry=0)

Kusewitt (1985) Relative size Total assets target / Total assets

acquirer

Acquisition rate Mean # acquisitions in a year

% acquired % of assets acquired

Industry relatedness % of acquired assets which were on

the same SIC number as the

acquirer (2-digit)

Type of payment % of asset acquisitions

accomplished with cash

Morosini, Shane & Singh

(1998)

Industry relatedness Dummy score (same industry=1,

different industry=0)

51

Size Dollar value of target’s net sales in

year of acquisition

Post-acquisition strategy Dummy score (independence=-1,

restructuring=0, integration=1)

Uncertainty avoidance National cultural score on

Hofstede’s dimension “uncertainty

avoidance”

Year Dummy score=Year

Ramaswamy (1997) Relative size Total assets target / Total assets

acquirer

Pre-merger performance Weighted average ROA pre-merger

acquirer

Zollo & Singh (2004) Relative size Total assets target / Total assets

acquirer

Market relatedness Dummy score (same industry=1,

different industry=0)

Resource quality of target Dummy score (bankrupt=-2, poor

performance=-1, average

performance=0, good

performance=1, outstanding

performance=2)