Thesis Thomas Nieves Asensio 10839267 MSc BA
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1 Master Thesis Merger and acquisitions in small to medium sized enterprises A Quantitative study at the link between pre-merger preparation and post-merger success. MSc Business Administration – Track International Management Name: Thomas Nieves Asensio Student number: 10839267 Date of submission: 25-03-2016 Thesis supervisor: Dr. Ilir Haxhi Second reader: Dr. Erik Dirksen
Transcript of Thesis Thomas Nieves Asensio 10839267 MSc BA
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Master Thesis
Merger and acquisitions in small to medium sized
enterprises
A Quantitative study at the link between pre-merger preparation and post-merger success.
MSc Business Administration – Track International Management
Name: Thomas Nieves Asensio
Student number: 10839267
Date of submission: 25-03-2016
Thesis supervisor: Dr. Ilir Haxhi
Second reader: Dr. Erik Dirksen
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Statement of originality
This document is written by, Thomas Nieves Asensio, who declares to take full responsibility
for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources
other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of
completion of the work, not for the contents.
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Abstract
This thesis investigates the post-merger performance of merger and acquisitions from a
representative sample of all Merger and acquisitions in the European Union occurring in
2009, all taken place between small to medium sized enterprises (608 SME’s). Using the data
gathered, this thesis was able to investigate the impact of pre-merger factors on post merger
performance in SME’s. Four factors in pre-merger planning are studied through a quantitative
analysis. The results show that some factors in the pre-merger phase do indeed differ in
SME’s compared to large corporations when observing post-merger performance in those
SME’s. This study makes a theoretical contribution to existing literature in post-M&A
performance and pre-merger planning to prove that SME do indeed behave differently in
some areas after they have merged. Our findings showed that there is an indication that an
SME with no previous experience in M&A’s actually has an increased post-M&A
performance. Our main result though was that increased cross-national distance has a strong
negative effect on the performance after a SME has merged. This is consistent with existing
research done on large corporations. Subsequently our findings provide valuable insight for
managers in the field of M&A by recognising the effect of some pre-merger factors and SME
M&A performance. Through this study it became apparent that managers of SME’s who
announce deals, in most instances generally conclude the transaction, which is not the case in
large corporations. . Foremost this thesis is an indication to academics that further research is
needed on this subject, specifically other factors that affect post-merger performance.
Keywords: Merger and acquisitions, SME’s, Pre-merger planning, Post-merger performance
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Table of Contents
1. Introduction .......................................................................................................................... 7
2. Literature Review ............................................................................................................... 11
2.1 Merger and Acquisitions ........................................................................................................... 11
2.2 SME’s and M&A’s ..................................................................................................................... 12
2.3 M&A performance in an SME ................................................................................................. 14
2.4 The Pre-merger phase ............................................................................................................... 16
3. Theoretical Framework ..................................................................................................... 19
3.1 The public take over process and SME M&A performance .................................................. 19
3.1.1 Time between announcement and deal closure and SME performance ............................... 20
3.1.2 Cancelling an announced deal and SME performance ......................................................... 22
3.2 Cultural and Cross-national distance and SME M&A performance ................................... 23
3.3 Previous M&A Experience and SME M&A performance ..................................................... 25
3.4 Industry similarity and SME M&A performance .................................................................. 26
3.5 Conceptual model ....................................................................................................................... 28
4. Data and Method ................................................................................................................ 29
4.1 Sample and Data collection ....................................................................................................... 29
4.2 Measurement of variables ......................................................................................................... 31
4.2.1 Dependent variable ............................................................................................................... 31
4.2.2 Independent variables ........................................................................................................... 31
4.3 Method and model specification ............................................................................................... 33
5. Results and Data Analysis ................................................................................................. 35
5.1 Descriptive Statistic Analysis and Correlation test ................................................................. 35
5.2 Regression Analysis .................................................................................................................... 38
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6. Discussion ............................................................................................................................ 42
6.1 Findings ....................................................................................................................................... 42
6.2 Theoretical implications ............................................................................................................ 45
6.3 Practical implications ................................................................................................................ 46
6.4 Limitations .................................................................................................................................. 46
6.5 Further research ........................................................................................................................ 48
7. Conclusion ........................................................................................................................... 50
References ............................................................................................................................... 52
Appendices .............................................................................................................................. 62
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List of Tables and Figures
Figure 3.1: The pre-acquisition process .................................................................................. 20
Figure 3.2: Conceptual model .................................................................................................. 28
Figure 4.1: Flow chart of the working sample ......................................................................... 30
Table 4.2: Stepwise regression on post-M&A SME performance ............................................ 34
Table 5.1: Descriptive statistics: means, standard deviations and correlations ..................... 35
Table 5.2: Collinearity Statistics Post-merger SME performance ........................................... 36
Table 5.3: Model Fit of Heteroscedasticity-Consistent Regression ......................................... 39
Table 5.4: Results of Heteroscedasticity-Consistent Regression ............................................. 39
Figure I: Scatterplot of regression-standardised residual ....................................................... 62
Figure II: Histogram of regression-standardised residual ...................................................... 63
Table III: Histogram of regression-standardised residual……………………………………….64
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1. Introduction
Merger and acquisitions (M&A) has been researched for several decades in different types of
academic fields such as finance, economics, finance, law and other school of thoughts1. M&A
together with Joint ventures and Strategic alliances have been popular tools for businesses to
find a source of outward growth and development. Investors are particularly interested in
M&A because combining two companies generally expands market share and helps to contain
and or control costs. Even though M&A’s are popular for business and investors alike, they
seem to deliver at best a mixed performance to the large range of stakeholders involved
(Cartwright & Schoenberg, 2006; Epstein, 2004; Bauer & Matzler, 2014; Gosh, 2001).
Although the amount of transactions that have taken place have declined considerably
due to the most recent financial crisis, there is strong evidence to suggest there will be a
resurgence in M&A activity as of 2015, this new M&A wave is predicted to be driven by
innovation. This is because firms are focusing on acquisitions that will help move the scope of
their business, sometimes even in a new industry sector (McCrostie, 2015). Cross border
transactions are set to be the basis of these transactions in this new wave, with 86% of the
planned deals to be set in the international market. (Gillespie, 2015;EY report, 2015)
Most theories on M&A were developed almost entirely on large deals involving large
corporations; however, most of the M&A activity valued at $3.5 trillion in 2014 is derived
from Small and medium enterprise2 (SME) transactions (Jansen, 2008). Thus, the previous
research mainly focused on M&A deals of large organisations, neglecting the majority of
M&A’s taking place in the European Union (and the USA). So even though SME’s play a
significant part in the total amount of M&A transactions worldwide, it is unclear whether the 1 Although it is technically incorrect, the term merger, acquisition and M&A will be used synonymously in this 2 According to Extract of Article 2 of the Annex of Recommendation 2003/361 of the European Commission. The category of micro, small and medium-sized enterprises (SMEs) is made up of enterprises which employ fewer than 250 persons and which have an annual turnover not exceeding 50 million euro, and/or an annual balance sheet total not exceeding 43 million euro.
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same rationales may also apply to small to medium size businesses (Weitzel and McCarthy,
2009). Therefore, in the current study, we will look at factors that influence an M&A in the
context of SMEs.
There are many factors one can consider to have an effect on M&A success. Epstein
(2004) identifies seven critical factors that contribute to the success of post-merger
performance (e.g., is pre-merger preparation) and argues that the actual implementation of
merger strategy through pre-merger preparation (together with post-merger integration)
appears to be least understood with stakeholders involved in a M&A transaction. The effect of
pre-merger phase is seen as a missing element in existing M&A research (Dikova et al., 2009)
Building on previous literature, in this study, we identify four factors that can be considered
factors of success in the pre-merger phase; the public take over process, culture, industry and
experience. Due to this lack of research on pre-merger preparation, this research paper will
take factors in the pre-merger phase that have an effect on M&A performance in large
corporations and see what effect they have on M&A performance in an SME, by trying to
establish if these factors for success in M&A’s also hold for SME’s.
Pre-merger activities affect the performance of the newly merged SME’s. These
factors, that have a known effect on M&A performance in large corporations, may have a
different effect on SME’s. (Weitzel & McCarthy, 2009; Bauer & Matzler, 2014). Experience
in M&A for example is more prevalent in large corporations and is not a given for SME’s,
and this could contribute to a difference in outcome. This leaves an important gap and this
means the relation of M&A’s to SME’s performance needs to be investigated further. As most
research has been done with data regarding large corporations, this research is an exploration
of the factors that influence post-merger performance for SME’s.
This study attempts to investigate to what extent known pre-merger phase factors of;
cross-national distance, experience, industry and time between deal announcement and deal
completion have, on the outcome of post-merger performance in a SME. Performance will be
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measured in terms of total asset growth of the SME. From a theoretical perspective, the
overall effect of all previous topics mentioned is unclear, and clarification depends upon
empirical investigation because the behaviour and success of M&A’s by SMEs may differ
significantly to large firms.
The purpose of this research study is to fill the gap by testing known theory on M&A
performance in large corporations and putting it into practise for SME’s, to explore possible
factors in the pre-merger phase that positively influence post-merger performance by SME
companies.
RQ: To what extent do selected known pre-merger success factors affect post-merger SME
performance?
In this study we analyse if there is a relationship between factors that have an outcome
on the growth in total assets in an SME and therefore also on the post-merger performance
using a dataset from Zephyr, a database from Bureau van Dijk. This is the most
comprehensive database on deal information globally with information on a 120 million un-
listed companies worldwide, making this database suitable for the data on SME’s. (Bureau
van Dijk). The sample includes 608 SME’s in the EU that have gone through a merger and/or
acquisition in the period 2009-2015. The aim is to identify the effect of selected factors in the
pre-merger phase on post-merger performance. Our main findings are that some pre-merger
factors have a different effect in SME’s. Although some pre-merger factors have much less
effect on post-SME M&A performance than others, these findings will be discussed in detail.
Even though many academics that have studied M&A generally portray M&A success
as complex and multidimensional, most research focuses only on a few performance
indicators (Meglio & Risberg, 2011), while excluding possible salient factors. Additionally
there are only limited studies regarding pre-merger activities with SME’s, even more so the
period from deal announcement to deal completion. In this phase, if prolonged deal making
occurs certain complications arise that influence the success of the merger. It offers more
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room for competitors to initiate a bidding contest resulting in a deferment of efficiency gains
of the potential deal. (Bainbridge, 1990; Luo, 2005)
Furthermore, given that SME’s play such a big role in the European economy and that
the pre-merger process during the M&A deal has the least understanding by stakeholders,
better insights into this, and the resultant on the effects on the M&A performance are required
(Epstein 2004, Weitzel & McCarthy 2009)
The thesis is organised as follows: First, we give an overview of the literature on
M&A’s, and the pre-merger phase in particular by developing a set of hypotheses on how it
may relate to the performance of SMEs. Further, we present the data and method followed by
a discussion of results and main implication of our research. Finally, we conclude with
possible further research on M&A performance and SME’s.
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2. Literature Review
2.1 Merger and Acquisitions
Merger and acquisitions continue to be a highly popular form of corporate development. In
2014 M&A activity was valued at $3.5 trillion (Thomson and Reuters). This value represents
the biggest year for M&A activity since 2007, the last year before the financial crisis hit the
world. As of April 2015 the global M&A volume stood at $1 trillion, up 19% from the
previous year on year period, according to Dealogic, an international financial software
company. In early 2015 the 8th annual Brunswick proprietary database survey consisting of
115 M&A practitioners across Europe, North America and Asia also concluded that, when
looking at these figures, that there is an indication that M&A activity is expected to grow in
the forthcoming years (PRNewswire, 2015).
However, there is a paradox that remains, whilst M&A deals are a popular tool for
development in a firm, there has been a mixed performance in results to the broad range of
stakeholders involved in these deals (Cartwright & Schoenberg, 2006). Agrawal and Jaffe
(2000) found that shareholders of the target company generally enjoy positive short-term
returns but the long-run benefit to investors acquiring firms is more uncertain. Furthermore it
was found that managers of target firms depart more quickly after an acquisition (almost 70%
leave within 10 years) than managers that joined the firm after the acquisition (Krug, J. and
Aguilera, 2005). It has been reported by managers of acquiring firms, that more than half of
M&A are considered unsuccessful against the original objective set to them (Schoenberg,
2006).
Academics have been forced to ask why despite their high rate of failure, M&A waves
keep on occurring with such a magnitude. A cause for this, by Kummer and Steger (2008), is
that corporations are constantly under pressure to realise growth (both internally and
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externally) together with the arrogance of executives, who have unrealistic expectations,
themselves, about a potential merger or acquisition transaction. Themes that are common in
M&A literature are; identifying specific factors that create value during each of the M&A
phases, reasons why firms/managers choose to undergo M&A and reasons why M&A fail or
succeed.
2.2 SME’s and M&A’s
The SME plays a central role in the European economy. They are a major source of
entrepreneurial skills, innovation and employment. In the enlarged European Union of 28
countries, some 23 million SMEs represent 99% of all enterprises in the EU, the equivalent of
28% of the EU GDP. They also provide around 90 million jobs - 67 % of total employment in
the EU (Muller et al., 2015).
The sixth merger wave, characterised by shareholder activism3, private equity4 and
leveraged buy out5 emerged in 2003 and ended in 2007 due to the financial crisis, was mainly
driven by SME’s (Salvato et al., 2007). The most obvious reason why little attention has been
devoted on SME’s is that they are not publicly traded and therefore it is difficult to obtain
reliable data for academics to do research.
It is relevant and important to focus on SME’s because they are the backbone of the
European economy and M&A theories established to date almost exclusively represent the
other 1 % of enterprises of the EU economy, which are the large global corporations. This
thesis will incorporate this important but often overlooked sector of the EU economy, by
explicitly considering the activity by SME’s within the M&A industry.
3 Shareholder activism: is a way in which shareholders can influence a corporation's behaviour by exercising their rights as owners (investopedia) 4 Private equity consists of investors and funds that make investments directly into private companies or conduct buyouts of public companies that result in a delisting of public equity (investopedia) 5 LBO: The acquisition of another company using a significant amount of borrowed money (bonds or loans) to meet the cost of acquisition.(investopedia)
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Large Corporation and SME’s differ in many aspects such as; they often have a much
simpler governance structure because often the manager or CEO of the firm is also the main
shareholder. This difference immediately lessens agency problems, which generally happens
in M&A integration (Jensen, 1986). The agency problem generally refers to a conflict of
interest between the firm’s management and the firm’s stockholders. Furthermore,
corporations undergo larger coordination problems then SME’s. (Williamson, 1975).
According to Weitzel and McCarthy (2009) the three main differences of SME’s
compared large cooperation’s in terms of M&A activity are as follows; 1) they are more
likely to rely on M&A as external growth, 2) they are more likely to withdraw from a deal as
SME’s are more flexible, 3) and that SME M&A are more likely to be financed with debt.
Until now there has been a considerable amount of literature that looks at the
differences between the size of corporations and post-merger performance. Gugler et al.
(2003) based on a large research panel of more than 45 thousand global and US mergers in
the year 1981 to 1998 examined the post-merger performance effects in terms of profitability
and sales. These authors concluded, “ One might expect mergers between small firms to be
more likely to increase efficiency by creating economies of scale and scope”. Their research
findings suggested that sales decreased when large firms merged and increased when small
firms merged. In a later study of Gugler et al. (2012) they found that post M&A performance
during the different merger waves are considerably different for listed and un-listed
companies. In a study done by Moeller et al. (2004), where they took a sample of over 12.000
acquisitions by listed firms during the period 1980 till 2001, they concluded that smaller
businesses perform better after M&A’s than larger ones. A serious limitation to this study is
that it only incorporates listed firms and therefore neglects SMEs
Similarly, another study from Moeller et al. (2005) found that mergers whose values
exceed $1 billion decreased the acquirer shareholders value by a staggering $7.38 per $100
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invested. Dutta and Jog (2009) found out that firms of a relative large size that make an
acquisition, underperform in the long run, by a negative 49% over three years.
To summarise, empirical evidence states it is quite clear that there is a difference in
post merger performance when regarding the size of the company. The results in most of the
papers provide evidence that there is a negative relationship between the company size of the
acquirer and M&A performance. Large corporations can destroy the synergy of a newly
formed firm, as they often bring more integration and management problems with them.
The relationship between company size and performance has been a subject of study,
but small corporations are not the same as SME’s. The performance of SME’s in M&A has
been largely neglected by academics. Therefore this paper would like to bring a focus on even
smaller unlisted firms and the effect on post-merger performance.
2.3 M&A performance in an SME
M&A performance and success, the dependent variable of this study, is a largely discussed
topic in M&A literature. Strategic managers, corporate financial managers and organisational
behaviour academics have studied it for decades. For example Kaplan (2007) describes and
evaluates in his paper the different measures used by financial economists to evaluate the
success of M&A performance by looking into a range of studies.
The fact that most M&A fail during each M&A wave is well documented in research
findings. This success inconsistency with M&A’s prompts academics to investigate further on
M&A performance. Zollo and Singh’s paper (2004) is a study conducted primarily in the US
banking industry. This study tests how different approaches to the post acquisition
management and different levels of knowledge in managing the integration process of the
firm affects different types of performance outcomes.
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They found that there is much discrepancy between academics and both their definition and
measurement of performance. Meaning that even today there is still much disagreement
within many academic disciplines how to measure M&A performance (Zollo & Meier, 2008).
Essentially there are five-performance evaluation measures a used in the M&A field:
• Stock price analysis measures
• Accounting-based measures
• Managers’ subjective assessments (Homburg & Bucerius, 2006);
• Expert informants’ assessment (Hayward, 2002);
• Divesture (Mitchell and Lehn, 1990)
As of 2010, 92% of all empirical studies regarding M&A performance reviewed by Cording
et al. (2010) either used the stock price analysis method and/or the accounting-based methods.
Furthermore Zollo & Meier (2008) also stated that 41% of all articles they reviewed used the
stock price analysis method and 28% used the accounting based method. What is also
apparent in the Meglio & Risberg (2011) paper is that most studies measure economic
performance after the M&A has taken place through firms’ share performance in the market.
The stock price analysis method uses share prices to evaluate the performance, which
means that it can only be used on firms that are listed on a stock exchange. For the purpose of
this study the stock price analysis cannot used for evaluating the M&A performance of
SME’s, for the obvious reason that SME’s are not listed companies. The focus on the stock
price analysis to measure M&A performance is another example that previous M&A research
has mainly focussed on large corporations and not on SME’s. Therefore this research paper
further assesses the accounting based method.
Accounting based measures
When discussing about post-acquisition performance, the accounting-based measure is often
used. The use of financial statements, income statements and cash slow statements that are
available publicly is an advantage for managers, as they are easily obtainable and simply used
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to calculate the firm’s performance. This method usually consists of a comparison of
accounting measures prior and subsequent to a takeover. The basis of this measure is that a
firm’s strategic aim is to get a suitable return on equity (ROE), which will be reflected in the
accounting statement, e.g.: growth in turnover or total assets (Tuch & O’Sullivan, 2007). An
issue with this method though is that it still does not solve the isolation problem that the stock
price analysis also has. A further implication is that it has issues evaluating performance in a
certain time window, such as a one financial year (Zollo & Singh, 2004).
Researchers vary on the definition of operating performance, ratios chosen,
benchmarks constructed, time frame and methodology design when using the accounting
based method (Zollo&Meier, 2008). This means that even within the accounting based
measure there is much disagreement on how exactly this method should be used to measure
M&A performance, thus, this makes comparison difficult.
The quantitative study of this research paper focuses on SME performance measures.
Keeping in mind what the differences between SME’s and large corporations are, a choice as
a performance evaluation needs to be made. As the stock price analysis cannot be used, this
research paper will therefore use the accounting based method to evaluate to M&A
performance of the SME’s in our sampled data. Which one exactly, will be discussed in
section Four.
2.4 The Pre-merger phase
Most academic research that has studied the success of M&A’s, typically examine the
financial performance of a firm after the M&A has taken place (Porth, 1992; Ramaswamy
1997). Although examining post-M&A performance is definitely beneficial, one could argue
that more attention is needed on pre-M&A activities and the affect this has on the post-merger
performance.
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There are many influences that can affect the performance, success or even failure of
an M&A. As mentioned in page 8, 2nd paragraph, Epstein (2004) defines seven determinants
of success; strategic vision, strategic fit, deal structure, due diligence, pre-merger planning
and post merger integration. Epstein stated in his paper that pre-merger planning and
integration have the least understanding by stakeholders involved in the M&A process and is
not researched enough by academics as well. Academics regularly haven’t contemplated the
hurdles that arise in the bargaining process after the initial agreement is signed in relation to
the M&A deal (Hotchkiss et al., 2005). Even though this is the case, the phase after the
preliminary M&A deal and before the deal resolution has up to now not been the focus to
many scholars of the International Business world (Dikova et al., 2009).
Studies typically identify two or three phases in the M&A process. Research by Kim
(1998) recognised three phases; pre-acquisition management, the post acquisition integration
and the post acquisition performance. The paper looks at what success factors have
considerable value-added impact on corporate acquisition in the hotel industry. It concludes
by saying that management should put much more emphasis on pre-acquisition integration
process than to the post acquisition processes. The pre-acquisition management phase entails
the time frame from the initial development strategy until M&A deal resolution. One of the
essential objectives this paper describes as being critical in the pre-acquisition phase is to
evaluate the target’s fit with the firm’s goals, objectives, culture and potential synergies.
DiGeorgio (2002) concurs with this and says that before the deal is completed the acquirer
should identify the right methods to be used to integrate the newly acquired firm into the
existing business. A range of factors were named that should be considered including people,
culture, political, financial, administrative and organisation strategies (DiGeorgio, 2002).
Gomes et al (2013), like Kim (1998), identifies the three phases in the M&A process.
Similarly they also show a whole list of critical success factors in the pre-merger phase. Here
emphasis is put on similarity between organisational culture and industry, good
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communication in the pre-merger phase (which directly affects the time taken in the pre
merger phase) and overall strategy and accumulated experience of the acquirer on M&A. The
paper concluded by saying that if the mentioned pre-merger factors are known, and are taken
into consideration in the choice of integration approach post-merger, M&A success
performance is greater when compared to those deals that did not consider these pre-merger
factors. In a similar study by Schmidt and Fowler (1990), they added one more factor that
previous studies did not mention, which is industry commonality.
We can conclude that although there is no consensus in M&A literature on the exact
definitions for this phase, what variables are included and when the process exactly begins or
ends, the overarching definition that determines the pre-merger phase is that it takes place up
to the point where the ownership transfer from target to acquirer is completed.
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3. Theoretical Framework
Considering the literature in the previous chapter, this research paper will look at the pre-
merger phase of a Merger and/or Acquisition and its relationship to post merger success in
SME’s.
Although there are many factors to consider, this paper identifies four most publicly
disclosed factors for SME’s that exist in the pre-merger phase and have a known influence on
M&A performance. These would ultimately influence the overall success of the M&A. These
factors are consistently mentioned in previous studies done on the pre-merger phase
(Trautwein, 1990; Schmidt and Fowler, 1990; DiGeorgio, 2002; Gomes et al., 2013;Stahl et
al., 2013).
These are important factors that acquirers will have to take into account before taking
ownership of target firms:
• The length of the public take over process
• Culture & Cross-national distance between acquirer and target
• The type of industry where the M&A takes place
• The previous experience of the SME in M&A’s of the acquirer
Each factor will be explained in more detail as well as other determinants that literature has
identified has an effect on post-merger performance.
As research of M&A performance with SME’s is limited, this research paper will look at
previous research of each of these determinants regarding large corporations. Further analysis
in Section 4 of this research paper, will show if the same is accurate for SME’s.
3.1 The public take over process and SME M&A performance
Boone and Mulherin (2007) explain that the pre-acquisition process seen in Figure 3.1
consists of two periods, first the private takeover process and then the public takeover
process. The private takeover process instigates when a firm is keen on acquiring, selling or
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merging. The company enters initial negotiations or bargaining between several interested
parties. When this is done and an agreement is settled between two parties, a buyer and a
seller, and they announce the deal publicly. This is when the acquiring process enters the
public takeover period. The public takeover process starts with an announcement in the press
and ends with the resolution date, where the M&A will be completed or abandoned by the
parties involved. This research paper will focus on the public takeover process in the pre-
acquisition process.
Figure 3.1: The pre-acquisition process
(Boone and Mulherin, 2007)
This paper identifies two aspects in the public take over process that have an effect on
performance of the acquirer. The time taken in the public take over process (time between
deal announcement and deal completion) and the effect of cancelling on deal when it is
announcing it publicly.
3.1.1 Time between announcement and deal closure and SME performance
In the Dikova et al. (2009) paper, they study how formal and informal institutional features
influence the probability a cross-border M&A deal will be accomplished as well as the time
taken in the public take over process until completion. They suggest that closer examination
of the period between M&A deal announcement and deal completion is needed. Their reason
behind this is that it could provide valuable understanding into potential deal breakers of
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international firms that announce possible M&A transactions. In the article’s study they find
that deals financed with cash are more easily completed that stock-financed ones.
Furthermore largely owned public companies take longer to complete as the transaction tends
to be much larger and complex.
An explanation for why negotiations during the public take over process can take up
time is because of hold-up problems during re-negotiations. Initial contracts that are designed
in the private take over process, which are improperly made, cause these hold ups. According
to Hotchkiss et all (2005): “These type of contracts grant an option to the target to terminate
the merger, while the strike on the option compensates the acquirer’s effort without imposing
excessive costs on the target for pursuing non-merger alternatives. The option strike can be
implemented by the use of deal protection devices, such as a target termination fee6 or an
acquirer lockup7” (Hotchkiss et al 2005).
Other studies explain that it produces additional legal expenses and creates a
distraction of further investment prospects and the attention of managers from other gainful
M&A deals (Bainbridge, 1990; Dikova et al., 2009). Also, financial market conditions might
change, making deal financing more difficult. Finally, a better understanding of time to
completion matters not only for firms that merge but also for their competitors and investors.
The Competitors may profit from this in the product-market setting from the prolonged
takeover process due to increased perceived uncertainty by suppliers, customers and delays in
innovative undertakings by both the merging firms. Financiers on the other hand may gain by
more rapid deal completion by speculating on deal completion8, by benefitting from faster
settlement of the deal in question (Luypaert & Measeneire, 2015).
6 Termination fee: A common fee used in takeover agreements if the seller backs out of a deal to sell to the purchaser. This fee is required to compensate the prospective purchaser for the time and resources used to facilitate the deal (Investopedia), 7 Acquirer Lock up: A legally binding contract between the underwriters and insiders of a company prohibiting these individuals from selling any shares of stock for a specified period (Investopedia) 8 Also called merger arbitrage
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Lengthy duration of the acquisition process indicates problems, like those mentioned
above, in closing the deal. The problems might impact future returns for the newly merged
firm and therefore impede growth.
Former studies take acquisition duration and performance indirectly into consideration, such
as Dikova et al.’s (2009) paper that displays a whole list of variables that affect the
acquisition duration. This list included; type of financing, public status of acquirer and target
and cross-border distance. Even though it concludes by saying that SME’s take less time in
the public take over process, it remains to be found if within SME’s, acquisition duration has
a direct effect on post merger performance. One could therefore look closer at the time taken
between the deal announcement and the deal closure and investigate if it has any relation to
the performance in an SME.
H1: The more time taken between announcement time and deal closure, the lower post-
merger performance is for the acquirer
3.1.2 Cancelling an announced deal and SME performance
Empirical evidence suggests that firms cease up to 25% of their merger and/or acquisition
attempts at some point in the negotiation process (Holl & Kyriazis 1996). Observed reasons
for this are opposed decisions by courts of law or regulatory agencies (Hotchkis et al., 2005).
Cancelling a deal that has been announced publicly can severely damage the credibility and
the reputation of any company, due to loss of faith. When an announced deal does not
succeed, it can also entail a breach of contract, which could incur heavy penalties (Luo,
2005).
Dikova et al (2009) found that in their sample, a significant percentage of deals that
are announced in the public take- over process are abandoned; this only concerned large
corporations and SME’s. Furthermore the following pre-merger factors still to be discussed
all too have an effect on the probability of deal completion. As this study only looked at
public companies, this paper hypothesis the following; as the effects of cancelling a deal are
23
universal and influence SME’s in the same way as corporations, incurred penalties and a loss
of credibility for stakeholders have a similar effect for SME’s as corporations; therefore we
hypothesise the following;
H2: When a deal is announced but cancelled, it will affect the acquirer’s performance
negatively
3.2 Cultural and Cross-national distance and SME M&A performance
Cultural distance has often been argued, but not so often researched to be an influence in
M&A. Cultural distance can be the cause of confusion, distress and even hostility between
merging parties (Stahl & Voigt, 2005). Cultural difference is also a factor that affects M&A
performance. Some research schools believe that cultural differences between firms going
through an M&A could create major complications in integration, whilst others believe that
cultural differences can be a source of value creation and learning (Stahl & Voigt, 2008).
King et al. (2004) considered that cultural distance is a major contributor to the high failure
rate in M&A, which is often reported in literature. The ability to integrate culturally is even
considered by some executives of major European multi-nationals to be of more importance
to the success of an M&A than strategic and financial factors (Cartwright & Cooper, 1996).
It is a fact that countries differ from one another; these differences include cultural,
political and economic differences. Academics have called this cross-national distance.
Cross-national distance is a key concept in the field of management and is important that it
considered in the pre-merger phase when it decides to merge with a firm across it own borders
(Berry et al. 2010).
A study done by Gugler et al. (2003) did not find significant difference in return (i.e.
performance) between cross-border M&As and domestic M&As. However Moeller and
Schlingemann (2004) found an indication there is a difference amongst international and
national M&A’s. Particularly their findings showed that the acquirer’s previous M&A
24
experience considerably decreases return on their shares and operating performance for
international transactions than for domestic ones. This is an indication that acquirers are not
properly valuing or seizing synergies in cross-border M&A’s.
In consonance with the previous two papers Chari et al. (2010) also state that normally cross-
border transactions experience a negative post-merger performance. Only if they have
intangible asset advantages that can be exploited abroad, can they increase their firms’
performance. One can therefore presume that an increase in cross-national distance, affects
post-merger performance negatively with large corporations.
Cross-national difference is measured by using the matrix of Berry et al. (2010). A
critic of the Hofstede and the Ghemawat9 approach is Berry et al. (2010), they mention that
previous research has conceptualised cross-national differences mostly in terms of dyadic
cultural distance, because it is measured using a Euclidean10 approach. They use a more
multi-dimensional approach by combining a range of measures. Although up to now there has
not been a theoretical agreement on how to measure cultural and cross border distance
(Teerikangas and Very, 2006). This paper feels that by using their matrix, it is the best
approach to measure the cultural cross-border distance between merging firms.
All previous studies have not taken into consideration the affect of cultural distance and SME
performance. One study done did however mention that smaller acquirers outperform larger
ones, irrespective of the country where the acquirer is based (Alexandridis et al., 2010).
Although this study considers smaller corporations, we consider the same is true for SME’s:
H3: A higher cross-border distance between acquirer and target will have a negative effect
on post merger performance in an acquirer 9 One of the first academics that created a measurement to calculate cultural distance is Hofstede (1994) In his paper “the business of international business culture” it defines culture as the collective programming of the mind with distinguishes the member of one category of people to another. These five factors were given a rating for each country, so that a combined measure of comparison could be created, Ghemawat (2001) also built a framework to calculate distance, to help managers identify and assess the impact of distance of various industries. 10 Euclidean distance: is a metric is the "ordinary" distance between two points that one would measure with a ruler, and is given by the Pythagorean formula.
25
3.3 Previous M&A Experience and SME M&A performance
This thesis will also consider the effect on post M&A performance as a result of previous
acquisition experience by an acquiring firm. Learning from acquisitions suggests the transfer
of a firm’s experience from one event to the following, plays a crucial role in determining the
success or failure of the newly formed M&A. A substantial volume of previous studies show
that firms with an overall strategy and experience of M&A are more prosperous than those
that are less experienced in M&A (Barkema & Schijven, 2008).
Lubatkin (1983) stated that firms with considerable experience in former acquisition
experience are more proficient in implementing any necessary structural changes needed after
a merger or acquisition and thus avoid any sort of administrative costs that may have a
negative impact on performance. An example of this could be differences in managerial
styles, fear of layoffs and increased size of the company. Two other studies reveal that
learning from prior engagements in M&A may be critical in future performance of that
particular company any stage of the process of buying or merging with a firm (Lei et al.,
1996; Vermeulen & Barkema, 2001).
Only a few studies discovered that the post merger performance of consecutive M&A
acquirers decline from deal to deal (Ismail, 2006; Aktas et al., 2009). But overall the notion is
in line with other academics in that there is a positive relationship between experience and
performance (Bruton et al. 1994; Vermeulen & Barkema, 2001).
Williams et al. (2008) state that a lot SME’s lack previous relevant M&A experience,
that might help generate efficient created synergies, so therefore because of this lack of
experience, post merger performance is affected negatively. To conclude from the literature,
firms can become more capable at managing specific types of complex organisational
undertakings, such as being involved in M&A’s, this is because they gain more experience in
such type of transactions. Similarly they should be more capable to negotiate and buy the
target at a low premium.
26
What this research paper set out to do is to see if SME’s that actually have previous
M&A experience also has a positive post merger performance like large corporations:
H4: Previous M&A Experience of the acquiring SME has a positive outcome on post-merger
performance
3.4 Industry similarity and SME M&A performance
A factor that can affect firm performance after an M&A is industry similarity. An
M&A occurring in a different industry then its acquirer is also called diversification.
In the paper of Mantravadi & Reddy (2008), they do a study on post-merger
performance of acquiring firms in different industries. The result of the study is that there are
slight deviations in operating performance following mergers of public traded companies in
India. So one has to ask the question, as the type of industry does seem to make a difference
in M&A performance, what would it do the post-merger operating performance of acquiring
firms when they diversify into different industries?
A number of research works have brought up significant interests in performance
differences with various forms of diversification. Several delivered findings signifying that
businesses that engaged in M&A with firms of the same industry experienced greater
performance gains (Schmidt and Karen, 1990). One of those studies, such as that of Singh &
Montgomery (1987) for example showed that mergers in a related industry give better
abnormal return than that of mergers in unrelated industries. The reason given, why related
mergers are more successful, is that they are able achieve operating efficiency and market
power more effectively. This is because the opportunity occurs to accomplish economies of
scope and scale, to manage the price and amount of the goods sold, and to form some type of
collusion.
27
On the contrary Chatterjee (1986) exposed in their study that M&A deals that happen
in industries that are unrelated are more profitable for both the acquiring and the target.
Unrelated M&A’s can create value by reducing risk via diversification.
In the King et al. (2004) paper, part of their study is on industry related and unrelated
acquisitions. They conclude by saying that neither related/unrelated industries explain the
effect of post-merger performance and “thus, despite decades of research, what impacts the
financial performance of firms engaging in M&A activity remains largely unexplained”(King
et al., 2004).
How industry similarity truly affects post-merger is still unclear, as there are still
contradictory positions amongst academics regarding this topic. Research is still missing
concerning industry similarity and post-performance for SME’s. This research paper takes the
stance off all research named by Schmidt and Karen, 1990 and considers that there is a
positive outcome on post-merger performance when an acquirer merges with a firm in the
same industry. As according to Weitzel and McCarthy (2009) SME’s use M&A for external
growth, this is done more easily in the same industry and less costly for a firm (Lubatkin,
1983; Giuseppe, 1995), the study will determine if this is true. .
H5: A merger & acquisition between parties in the same industry has a positive outcome on
post-merger performance in an SME.
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3.5 Conceptual model
In the previous section, five hypotheses have been established. Figure 3.2 shows the
conceptual model containing the relationship between the dependent and independent
variable. The model refers to the direct relationship between “ Pre- merger Factors that affect
performance” and Post merger performance in SME’s. The individual pre-merger factors that
affect performance have been graphically illustrated in the small boxes. Each small box has
an effect on post-merger performance and is hypothesised.
Figure 3.2: Conceptual model
Post-mergerperformanceinSME's
H1,H2:Thepublictakeoverprocess
H3:culturaldistance
H4:PreviousM&A
experience
H5:Industrysimilarity
29
4. Data and Method
In this section the methodological part of the thesis is presented. First the way the data was
obtained will be described. Second the variables used in this research will be presented and
finally, the data analysis that was conducted including regression models will be explained.
4.1 Sample and Data collection
In this research, the compounded average growth rate (CAGR) of the total assets of the SME
between 2009 until 2015 is the dependent variable. Cultural distance, Previous experience in
M&A’s, Industry similarity and Length in the pre-merger phase are the independent variables.
Data was collected from 608 firms within the EU (all 27 member states). The reason the study
was conducted only in the EU is that the definition of an SME is a term established by the
European commission and its criteria differs in other regions. An SME is a firm with a
turnover that does not exceed 50 million Euros, 43 million Euros in total assets and does not
have more than 250 employees (European Commission). The data gathered (608 companies)
are all SME’s, in the EU, that acquired or merged with a firm anywhere else in the world in
the year 2009.
Data was gathered and investigated on all merger and acquisitions that occurred after
the financial crisis i.e. 2009 onwards. M&A data that occurred during the financial crisis
(2007-2008) would be unreliable as M&A activity significantly decreased, congruently
marking the end of the 6th Merger wave. As mentioned in Section 2, there is evidence that in
2009 M&A activity started to recover. The data originates from a database called Bureau van
Dijk, where company data was obtained through Orbis and M&A data from Zephyr, both
subsidiaries of Bureau van Dijk. Orbis is a database that contains extensive financial
information from millions of companies worldwide. Whereas Zephyr is a database that
30
3184 SME’s that undergo
an M&A in 2009 in EU (27)
Missing data on important
independent variables
N=2305
Missing financial data from
2009 to 2014
N=271
879 SME’s with data to
calculate TA CAGR
Final sample
608 SME’s
contains information on M&A, IPO, private equity and venture capital deals, announcements
and rumours from firms worldwide.
The data from Zephyr has been merged with Orbis to recover more financial information on
the companies participating in the deal. The data was collected on Bureau van Dijk and stored
to Microsoft excel. To perform the statistical analyses, the Statistical software Package for
Social Sciences (SPSS) version 22 was used. Looking at Figure 4.1 you can see how the final
sample was obtained. According to Orbis there were 3.184 SME’s that went through a merger
and/or acquisition in 2009 that released some type of information of their financial statements
and M&A deal. Four types of independent variables were needed. As often SME’s did not
disclose one or two variables of this important M&A data, this left us with 879 SME’s.
Financial information of the SME’s total assets over five consecutive years was needed to
calculate the performance growth rate compounded annually (2009-2014). 271 SME’s did not
disclose some or all of this essential information. Therefore, this gave us the final sample of
608 SME’s used for our quantitative study.
Figure 4.1: Flow chart of the working sample
31
4.2 Measurement of variables
4.2.1 Dependent variable
This study has one dependent variable and it represents the post-merger performance of the
SME. Previously it was decided that to measure post-merger performance that the accounting-
based method should be used. As it was difficult to obtain elaborate financial data from
SME’s, because these type of companies do not need to declare their financial statements, two
type of performance indicators were considered that were obtainable in the database; Revenue
or Total assets. Although revenues are a good indicator of results, they do not show the added
value to the organisation. A growth in total assets would indicate that an organisation adds
value. When testing for normalcy, it was decided to use total assets exclusively, since the data
was a better fit for this specific study, as revenue did not portray consistent results.
When total assets were chosen as a performance indicator, a decision needed to be
made on the most accurate way to measure returns in total assets from the year 2009 to 2014,
two were identified; compounded annual growth rate (CAGR) and average growth rate. The
CAGR 11 represents one of the most accurate ways to calculate and determine returns for
individual assets, investment portfolios and anything that can rise or fall in value over time
(PWC, 2007).
4.2.2 Independent variables
There are four independent variables that need to be considered; Time taken in the public take
over process, Culture & cross-border distance, previous M&A experience and industry
similarity.
Time taken in the public take over process
11 CAGR represents the year-over-year growth rate of an investment over a specified time period. And as the name implies, it uses compounding to determine the return on the investment, which is a more accurate measure when returns are more volatile. Source: investopedia
32
Time taken in the public takeover process was measured in the amount of days taken from
deal announcement until deal completion. Dikova et al. (2009) define it as “acquisition
duration”. This value was calculated by looking at the difference between the announcement
date and deal closure of each SME, on the Bureau van Dijk database, Zephyr. In the sample it
became clear that SME’s often skip the public takeover process and close the deal straight
after the private takeover process identified in page 20, paragraph 1.
Culture & cross-border distance
The distance between companies was calculated based on the cultural cross-border distance
matrix from Berry et al. (2010). They use a multi-dimensional approach by combining a range
of measure, including economic, financial, political, administrative, cultural, demographic,
knowledge, global connectedness and geographic distance. These researchers made their
distance available for all managers and scholars. The matrix gives a value representing the
cross-border distance between two countries. The higher the value, the higher the cross-border
distance. A value of zero means that the SME is engaged in a domestic M&A transaction.
Previous M&A Experience
Previous M&A experience was measured using data from Bureau van Dijk. A SME was
considered experienced if it had done more than one previous M&A in its existence. In the
sample it was evident that SME’s had less M&A experience then its large corporations
counterparts. A point scale was used ranging from 1 (previous M&A experience) to 0 (No
previous M&A experience).
Industry similarity
This was simply measured by differentiating between SME’s that are engaging in a deal
together which are in a similar industry or each from a different industry. The classification of
industries follows the industry classification code established by Zephus. Zephus is a
subsidiary of the database this research paper uses, Bureau van Dijk, whose main task is to
collect information on M&A deals. Information is collected from different sources and
33
complemented with news, market research, and information from official bodies. A point
scale was used ranging from 1 (different industry) to 0 (similar industry).
4.3 Method and model specification
The hypotheses in this study are relational hypotheses; therefore a correlation analysis
was conducted to establish whether there is a relationship between the dependent and
independent variables, as seen in Table 5.1. The data is normally distributed and therefore the
Pearson correlation value was used. This data is two-tailed, since this study isn’t related to
one specific direction (see Figure II).
The planned hypotheses were tested through a regression analysis; a linear regression
technique determines whether the independent variables explain a significant amount of the
variation in the dependent variable. The most apparent straight line through sets of variables
is created by the regression analysis; this association can be formulated with the following
formula:
Y = β0 + β1 * X1i + β2 * X2i + β3 * X3i + … + βn * Xni + ε
In this case Y represents the dependent variable post-M&A performance, measured by growth
in total assets. β0 and β1,2,3,n are the regression coefficients, where β0 represents the intercept
and β1,2,3,n the pre-merger success factors represented, which are the four independent
variables. The ε stands for the error that describes the change between the estimated X1i and
the actual X1i (Field, 2009).
Homoscedasticity is an important assumption in ordinary least squares (OLS)
regression. The homoscedasticity assumption states that the variance of the regression errors
is σ2 regardless of which set of values of the p predictor variables is used to generate those
errors. When this assumption is violated, we say that the errors are heteroscedastic (Hayes &
Cai, 2007). The dataset for this research showed heteroscedasticity (see Figure II& Table III).
34
To correct for this the model by Hayes & Cai (2007) has been used.
To test the stated theoretical framework, one linear regression is conducted that is
corrected for heteroscedasticity; which is done by using method HC3 (heteroscedasticity-
consistent 3) in the macro designed by Hayes for SPSS. This regression is used to test the
relationship between post-M&A performance and four pre-merger success factors. This
regression was tested as one model (see Table 4.2).
Table 4.2: Stepwise regression on post-M&A SME performance
Model Dependent Independent
Total asset Time Distance Experience Industry
Model 1 X X X X X
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5. Results and Data Analysis
In this section the outcomes of the statistical analysis of the data is presented. Firstly, an
outline of the descriptive statistics, correlations between the variables and a test for
multicollinearity will be analysed. Secondly the regression analysis will be described in the
method section. The results will be used to draw conclusions regarding the proposed
hypothesis of this study.
5.1 Descriptive Statistic Analysis and Correlation test
Five hypotheses were made to measure this relationship. The descriptive statistics of
the depended variable and independent variables can be found in Table 5.1. As shown the
average growth in total assets of all SME’s in the sample is a mean of 7,05%. Which is in line
with the average growth rate of SME’s in the European union, the average annual growth rate
by SME’s as stated by the “annual report on European SME’s 2014/2015” was just over 6%.
This is a great indication of the data sample of the research paper being representative
Table 5.1: Descriptive statistics: means, standard deviations and correlations
Variable Mean S.D. 1 2 3 4
1. Total Assets (%) 7,05 17,47
2. Experience (# deals) 4,04 7,02 -,054
3. Cross-border distance 1,59 4,74 -,105** ,054
4. Industry similarity 0,58 0,49 .35 , 040 -,041
5. Time taken in pre-merger
(days) 132,33 269,28 -.150** -,037 ,110** -,046
* p < .05, **p <.01, *** p < .001
36
Table 5.2: Collinearity Statistics Post-merger SME performance
Standardised coefficients Collinearity Stats
Variable Beta t Tolerance VIF
1. Time in pre-merger -,144 -4,611 ,984 1,016
2. Cross-border distance -,087 -2,619 ,983 1,017
3. Previous M&A exp. -,053 -1,643 ,993 1,007
4. Industry Similarity -,043 -1,094 ,996 1,004
a. Dependent variable total assets
* p < .05, **p <.01, *** p < .001
A Pearson correlation was used indicating that the data is normally distributed, which
shows a linear relation between predictors and the dependent (see Figure II). Moreover, Table
5.1 displays correlations between the dependent and independent variables of this study to test
for linearity. To prevent the regression analysis from any multicollinearity, two methods were
used. Looking at Table 5.1 again one can see that none of the correlations are particularly
high, which is anything above 0,80 (Field, 2009). This is the primary indicator that no
multicollinearity exists between the variables. Furthermore, the Variance inflation factor
(VIF) is used as second method to test whether there is multicollinearity. Given closer
examination at Table 5.2 the VIF showed a range of 1,004 and 1,017 and a tolerance range of
0,983 and 0,996. Which is well below the VIF standard cut off level of above 10 and
tolerance cut off level below 0.1 respectively according to Field (2009). Therefore both
factors even reinforce the correlation and there is no concern for multicollinearity in this
analysis.
37
Looking at Table 5.1 the following can be deduced. Time, shows an overall mean of
123 days with a standard deviation of about a 270 days, This means that overall in this
sample, SME’s take about 4 months to complete their acquisitions from announcement time.
With a Pearson correlation of -0,150 and an associated p-value of 0,000, one can conclude
that the less time taken between announcement time and deal closure, the greater post merger
performance is in an SME at the 1% level of significance. The Pearson correlation is a
relatively weak negative correlation.
With the variable concerning Cancelled deals, in the sample of 608 SME’s not enough
data was gathered to be able to test this variable. In the sample, most SME’s that announced
to merge or acquire a firm actually went through it. Therefore the correlation of this
hypothesis in this study is unknown.
For Cross-border distance, there is a mean of 1,59 meaning that in the sample, most
SME’s on average perform an M&A domestically or in countries with minimal cross-national
distance compared to their own, the SD of 4,74 confirms this. With a Pearson correlation of -
0,105 and an associated p-value of 0,010, we can therefore say that cultural distance
influences post-merger performance in an SME at the 1% level of significance. The Pearson
correlation is a weak negative correlation.
Previous M&A Experience has a mean of 4 previous acquisitions before they acquire
a firm in the year 2009, making the average SME in the sample reasonably experienced in
M&A’s, there is a standard deviation of 7 previously acquired firms. With a Pearson
correlation of -0.054 and an associated p-value of 0,105 one can conclude that experience
does not have an outcome on M&A performance at the 10% level of significance. However it
can be seen as indicative since it is close to the 10% level of significance.
Industry has a mean of 0,58 and a standard deviation of 0,49. This represents that in
this sample acquiring firms have almost equal distribution regarding horizontal (which was
coded as 0) and vertical merger (which was coded as 1). With a Pearson correlation of 0,035
38
and an associated p-value of 0, 2745 one can conclude that the type of industry the Merger or
Acquisition is involved in does not have an effect on the post-merger performance in an SME
at the 5% level of significance.
5.2 Regression Analysis
The results of the Heteroscedasticity-Consistent Regression between the independent
variables and dependent variable can be seen in Table 5.4. We aimed to test the dependency
between four factors as independent variables (Time, Distance, Experience and Industry), on
the growth rate in total assets i.e. the performance of the SME, as the dependent variable with
a discrete outcome. One linear regression technique was applied for the purpose of this
research, corrected for heteroscedasticity and can be outlined as follows:
Post-M&A SME performance= β0 + β1 * Time + β2 * Distance + β3 * Experience +
β4 * Industry+ ε
The intercept β0 and the slope β1 to β4 present the pre-merger success factors measured by %
growth Post-M&A SME performance (Field, 2009).
As this analysis is done using an OLS regression analysis, the model fit must be
determined. The fit of the regression model is expressed by R2, the coefficient determination.
The R2 indicates the strength of the relationships, the extent to which the independent
variables explain a significant amount of the variation in the dependent variable. The R2
shows the amount of variation in total asset growth that can be explained by the model (Field,
2009). Looking at Table 5.3, the model fit of this study’s regression is portrayed. . The model
has a R2 value of 0.0351 indicating that the independent variables count for 3,51% of the
variance of post-M&A performance (growth in total assets). Meaning that the model does not
have a perfect fit and thus relatively low strength of the coefficients together. This is a very
low number, but this can be expected since there are a lot of variables that could influence
total asset growth. Further looking at Table 5.3, the F-test tests the overall significance of the
39
model. The F-stat has to be significant to be able to perform the regression analysis. With an
F-stat of 7,9703 and an associated p-value of 0.000 we can conclude that the overall model is
a good fit at the 5% level of significance, which means we can proceed with analysing the
linear regression.
Table 5.3: Model Fit of Heteroscedasticity-Consistent Regression
R-square F Df1 Df2 Sig.
,0351 7,970 4,000 595,000 ,000
a. Dependent Variable: Total Assets, Compounded Asset Growth Rate
Table 5.4: Results of Heteroscedasticity-Consistent Regression
Model
Unstandardized Coefficients
Sig. Coeff Std. Error(HC)
1 (Constant) 10,224 1,1738 ,000
Experience -,1312 ,0798 ,100
Distance -,3283 ,1253 ,009
Industry -1,5259 1,3951 ,274
Time -,0094 ,0020 ,000
a. Dependent Variable: Total Assets, Compounded Asset Growth Rate
b. Andrew F. Hayes HC method 3
H1: The more time taken between announcement time and deal closure, the
lesser post merger performance is in an SME
Analysing the linear regression (Table 5.4) one can see that Time (b4= -0,0094) is
highly significant at the 5% and the 1% level of significance with an associated p-value of
0,00. Therefore Hypothesis H1 can be accepted, the least amount of days taken in the public
take over phase (period between deal announcement and deal completion), the higher post
40
merger performance is in an SME. A coefficient of -0,0094 indicated that there is weak
relationship between the time taken and post-merger performance. This means although there
is a definite relationship between the two variables, the effect of the independent variable is
minor.
H2: When a deal is announced but cancelled, it will affect the SME’s
performance negatively
A Cancelled deal has no correlation with post-merger performance and therefore
could not be included in the regression. A there was not enough data available to test the
association between performance and a deal that was announced however cancelled.
Therefore one must reject Hypothesis H2.
H3: A higher cross-border distance between acquirer and target will have a
negative effect on post merger performance in an SME
Cross-border distance (b2= -0,3283) is highly significant at the 5% and the 1% level
of significance with an associated p-value of 0,009. A coefficient value of -0,3283 means that
there is a relatively strong correlation between cross-border distance and post-merger
performance in an SME. This is the variable that contributes most to the model, as is the
strongest correlation out of all the significant variables in this study. The result shows that the
lower the cross-border distance between two SME’s that merge, the greater performance is in
the period from 2009 until 2014. Hypothesis H3 can be accepted.
H4: Previous M&A Experience of the SME has a positive outcome on post-
merger performance
Experience (b1= -0,1312) is indicative at the 10% level of significance with an
associated p-value of 0,10. Even though the coefficient value of -0,1312 means there is a
medium to low effect on the dependent variable. The effect of experience on post-merger
performance is merely indicative. By means of this study the result on the relationship of an
SME’s previous M&A experience and post-merger performance is not conclusive. An
41
interesting note is that the result shows the opposite of what is hypothesised; An SME with no
previous experience in an M&A undergoes more success over the 5-year period after the
merger took place. Nevertheless H4 must be rejected
H5: A merger & acquisition between parties in the same industry has a positive
outcome on post-merger performance in an SME
Industry (b3= -1,5259) is not significant at the 5% or 10% level of significance with
an associated p-value of 0,2745. Thus we must reject H5, there seemed to be no significant
relationship between industry commonality in M&A transaction and post-merger
performance.
To conclude, in the regression analysis there were significant results to be reported.
This indicates that pre-merger success factors do indeed have a direct effect on post-merger
SME performance. This study has several limitations, which influence these results. This will
be discussed further in the following section.
42
6. Discussion
Below the most apparent findings are discussed, together with the implications of these
findings with respect to the literature and practical implications for managers. Moreover,
limitations and possible suggestions for further research in this study are reviewed.
6.1 Findings
The main aim of this thesis is to determine if post-merger performance is experienced
similarly by SME’s as with large corporations, by looking at pre-merger factors. The results
of the study underline that when looking at pre-merger factors and post-merger performance,
there is indeed a difference between large corporations and SME’s. The findings of each
factor will be discussed.
Firstly this thesis attempts to establish what effect culture and cross-border distance
have on SME performance. Empirical findings regarding public companies present somewhat
of a puzzle for many researchers. Some studies report negative effects, while other conclude
that cross-border distance is positively related to performance (Cartwright & Schoenberg,
2006; Stahl & Voigt, 2005). Although in line with a more comprehensive research on cross-
border distance (Gugler et al., 2003; Moeller and Schlingemann, 2004; Chari et al., 2010) the
result of this thesis found that a higher cross-border distance between acquirer and target will
have a negative effect on post merger performance in an SME. Meaning that SME’s perform
better in a domestic M&A transactions.
Secondly, after analysing empirical data, results show that the shorter acquisition time
is in an SME, the greater post-merger performance is. The results indicated that there is weak
relationship between the time taken and post-merger performance. This weak indication might
suggest that although acquisition duration has an affect on post-merger performance,
managers/owners of SME’s prepare the transaction with more devotion than large
43
corporations, as there is more at stake for a smaller firm when thinking of merging or
acquiring. As mentioned by Hotchkiss et al. (2005) this better preparation decreases the
acquisition time due to the decreased probability of hold-up problems during re-negotiations.
Additionally these SME’s keep in mind that they cannot afford the legal fees that come with
prolonged deal making, as well as the opportunity cost in the time taken from the manager
that could be used in other valuable operations in the small business (Bainbridge, 1990;
Dikova et al., 2009). Competitors on the other hand may benefit in the market from stretched
deal duration due to increased uncertainty in the eyes of consumers as well as suppliers.
Considering the result of this factor, it seems that acquisition duration does not have a notable
influence on post-merger performance. This is remarkable, taking into account there is
considerable theoretical evidence that prolonged acquisition deal making is not beneficial for
firms, especially SME’s.
Thirdly, although even an indicative measure, when an SME has no previous
experience in an M&A it has positive outcome on future returns. This result is the opposite of
what is hypothesised. The paper of Ismail (2008) and Aktas et al. (2009) also do not agree
with the hypothesis of this study and say that the more experience a firm has in M&A the
worst their post-merger performance is. The result of this study is interesting though, as it
says that an SME with no previous M&A experience has better growth in total assets than that
of an SME having M&A experience. An explanation could be that compared to large firms,
acquiring SME’s are more likely to rely on M&A as an option for external growth. Meaning
that an SME’s owner with no experience carefully plans before going into a M&A deal,
unlike some CEO’s that sometimes allow their egos to cloud their commercial reasoning on
the reason for a M&A. transaction. An SME with no previous experience could also mean
that it is not in the financial services sector and therefore initiates in an M&A carefully for
external growth and not for profit. Further statistical investigation needs to prove this theory.
44
Fourthly, Industry commonality had no effect on post merger performance in an SME.
Further explanation could establish that the articles used to hypothesise on industry
commonality and post-merger performances might be out-dated and therefore no satisfactory
result was possible. This study had to use out-dated studies about industry commonality and
diversification, due to the lack of recent studies. Attention needs to be created for
diversification and post-merger performance in SME’s. As the sources contradict each other
in stating the factors that influence growth, diversification or integration, this variable needs
to be measured more specifically.
Lastly, this study hypothesises that a cancelled deal is more likely to withdraw from a
deal, because SME’s are more flexible and better able to avoid deals that turn sour. This
hypothesis was in line with a study done by Weitzel and McCarthy (2009). But considering
the result due to the lack of cancelled deals in the sample, this paper is forced to disagree and
conclude that SME’s tend to not cancel an M&A deal when announced. A reason for this is
that SME’s are probably very careful before they enter into deal negotiations because
cancelling a deal that has been announced publicly can severely damage the credibility and
the reputation of any company, due to loss of faith (Luo, 2005). As SME’s do not have the
financial capabilities as their larger counterparts, the room for error to finance a mistake like
cancelling an announced deal is small. This could explain the lack of cancelled deals in the
sample.
One has to keep in mind that these results are valid within the certain conditions tested
in this study. When this paper mentions SME’s, it concerns small to medium enterprises in
the EU that made an acquisition in 2009 and disclosed their financial statements. The research
field of assessing post-merger performance is rich, and needs to be studied further
45
6.2 Theoretical implications
This study contributes to the theory of M&A performance in two ways. Firstly most academic
studies regarding performance in M&A almost exclusively analyses large corporations and as
stated by Weitzel & McCarthy (2009) it is uncertain if the same is true for SME’s. In this
research data is gathered of all M&A deals with SME’s in western-Europe and the US from
1996 until 2007.The empirical results of this study do indeed support these expectations that
SME’s do behave and gain M&A success differently. Similarly Bauer & Matzler (2014) tried
and develop a compressive model for SME M&A success, by studying all SME’s in German
speaking Europe. The results of their study confirm the demand for more standard factors in
M&A success. These studies are very helpful, as they have proven that SME’s do indeed
behave differently and that there is a demand in the academic world for an integrated and
comprehensive literature on M&A success in SME’s (and large corporations for that matter)
(Zollo & Meier, 2008).
A limitation though is that these studies, and others, are always used in a specific
context. There is no guarantee that the results of these previous studies would be the same in
on a different geographic location and during a different period. This quantitative study adds
to the existent scarce academic literature on M&A success in SME’s by using data in the
period of 2009 onwards, in what some academics already define as the beginning of 7th
merger wave (Vazirani, 2015).
Second, this thesis further addresses the much needed study on the overlooked pre-
acquisition phase. As stated in section 2, the pre-merger phase has up to now not been the
focus to many scholars of the International Business world (Dikova et al., 2009). Studies
such as Stahl et al. (2013) and Gomes et al. (2013) both in their own way define the pre-
merger phase. These studies and others like them often have no agreement on the exact
definitions that determines the pre-merger phase. The only understanding between academics
46
is that it takes place up to the point where the ownership transfer from target to acquirer is
completed. We try and fill the gap by using more up to date research on the topic.
6.3 Practical implications
Considering the results, this study gives valuable insight for managers in the M&A field by
refining current knowledge on M&A success in SME’s. Our study showed that, similar to
large corporations, SME’s noticeably perform better when a merger is made domestically (or
in a country similar to their own country). Secondly contrary to popular opinion in the M&A
field, the results indicate that previous M&A experience does not seem to be a factor for
M&A success for SME’s. Peculiarly, SME’s with no actual M&A experience had a tendency
to perform better than those with a track record.
In the study of Larsson and Finkelstein (1999), their empirical evidence suggests that
it is not one particular factor that enables M&A’s to become successful but rather the
interconnection of several factors that make an M&A successful. A practical implication to
consider is that managers should focus on all factors that affect post-merger performance.
Even though this study focussed on a factor that was considered to have the least
understanding (Epstein, 2004), managers should consider the interconnection of all the factors
that are decisive in the M&A process.
Further Marks and Mirvis (2011) opt for more consistency in how the results of post-
merger performance are measured. So a second managerial implication is that managers for
both SME’s and large corporations need to find a more reliable and consistent method in
calculating post-merger performance.
6.4 Limitations
Considering the test condition of this particular study, some limitations need to be mentioned.
This study focuses on SME’s, which are usually not listed on the stock exchange or publicly
traded. In the European Union SME’s have less strict requirements for transparency as well as
47
for publicly disclosing there financials (Muller et al, 2005) Even the information on Orbis
regarding SME’s was limited, as financial information is disclosed only if the SME’ s wishes
to do so.
Looking at the sample distribution of our study (see Figure I in the appendices),
external factors that might have lead to heterogeneity of variance for the predictor variables.
This disturbance of the distributions of the predictor variables makes the OLS regression a
less reliable method. Possible external influence on the predictor variables are as follows. The
Financial crisis of 2007 might have affected the acquisition duration and the ability to
diversify for SME’s. As the SME’s performance shown in the data would have been affected
by the external macro-economic condition, this is explained in more detail below.
The Berry matrix used for cross national distance could show an intrinsic disturbance
as neighbouring countries could show a large disparity in cultural alikeness, while for
entrepreneurs it might be easy to make deals cross borders. This means that the data might not
have been a good representation of actual cross-border distance for SME’s.
Finally using experience as a dummy variable might explain some of these
disturbances created in this variable. As this continuous variable was recoded as a binary
variable, the extend of the experience in M&A’s that entrepreneurs have, gets compressed in
this variable as second-timers and seasoned acquirers get lumped together.
In this paper the accounting based method was used to measure post-merger
performance in an SME’s. To get a real accurate representation of the post merger
performance in any firm, multiple measures are essential, not only because each method has
its own restrictions, but also because post-merger performance by its nature is enormously
complicated and multidimensional, no single method can cover all the different features
(Cording et al. 2010; Zollo and Meier, 2008).
The cultural distance matrix of Berry et al. (2010) also poses some limitation as to
how the pre-merger factor, cross-border distance is measured. As mentioned there have been
48
many academics that have tried to define and give a numerical value for cross-border and
cultural distance. Although Berry et al. (2010) are confident that their calculations give the
most accurate representation of this; one cannot know this for sure.
Macro economic conditions also have had an affect on the post-merger performance
and are extremely difficult to measure especially with cross-border transactions, as each
domestic economy performs differently. The external economic environment is also one of
the major limitations of this study, as it is difficult to measure what effect the exogenous
environment has on post merger performance. In the recent economic crisis in 2008 which
drastically affected M&A activity, also meant the end of the 6th merger wave. Martynova and
Renneboog (2008) investigated the past known U.S. merger waves and proved that there is a
clear pattern that all merger waves in history coincided with economic affluence and
recovery, while the end of each merger wave coincided with an economic recession and
stock-market crash. This is a clear indication that external environment in the form of
macroeconomic factors (factors that determine the state of the economy), has a strong
influence on the existence and end of M&A waves. The reader has to keep in mind that even
if a firm adheres to all factors that lead to post-merger performance (Epstein, 2004; Gomes et
al., 2013) macroeconomic conditions in each country can have serious affect on the post-
merger performance of any firm or SME, without that it has any control of it.
6.5 Further research
There are many other variables that affect post-merger performance than those explored in
this research. Considering the seven determinants listed in Epstein’s paper (2004), this
research chose to focus on pre-merger planning as it was one of the two determinants that had
the least focus in previous academic work and management. The other determinant that was
considered to be the least understood by managers was post-merger integration; this factor is
49
mentioned in a lot of literature on pre-merger success factors but is seen as difficult to
measure (Bauer & Matzler, 2014; Gomes et all, 2003; Stahl et al., 2013)
Post merger integration is often quoted to be decisive for the success of M&A’s, but
post-acquisition integration typologies suffer from inadequate empirical support or lack of
comprehensiveness (Haspeslagh & Jemison, 1991; Stahl & Voigt, 2008; Gomez et al., 2013;
Agwin & Meadows, 2015).
Chatterjee et al. (1992), in their study, display that a lack of integration is a major
reason for M&A failure, but that to much integration can also be unfavourable, due to
potential culture clashes as a result of high cross-border distance. Hence one can see that
culture and cross-border distance has a direct relationship to integration. The degree of
integration a firm undergoes has both its advantages and disadvantages. On one hand, there is
a positive effect on synergy and prospective realisation but on the other hand a higher degree
of integration leads to higher coordination costs and more change in the business. (Larsson &
Finkelstein, 1999; Agwin & Meadows, 2015)
The effect of the speed of integration is something that has been neglected in previous
academic studies (Angwin, 2004; Homburg & Bucerius, 2005;Agwin & Meadows, 2015)
In the paper of Angwin (2004), the writer argues that the faster a firm integrates the faster that
firm can exploit its synergies and ROI. Additionally, it also minimises the duration the newly
merged firm spends in a suboptimal state.
Overall one can conclude that some degree of integration is beneficial (Zollo & Singh,
2004). Further research on the degree of integration and post merger performance of SME
would be beneficial. Since the study was based on a sample of 608 SME’s, it would be
interesting to redo the study with a larger selection of research objectives, to make the results
of this study more valid. Finally to add validity of to this research, a qualitative research on
the role of the owner in the SME would help gives specific insight in which factors
specifically contribute to success.
50
7. Conclusion
To conclude our results show that when looking at the under researched pre-acquisition M&A
success factors, we find that some do indeed behave differently in SME’s than expected,
when compared to large corporations. Previous studies mainly look at these factors towards
post-merger success in large corporations. Weitzel & McCarthy (2009) says SME’s are more
flexible when it comes to entering deals, but in our study we find that even though they are
more flexible, they are indeed more committed, they do not tend to pull out of deal
negotiations. The reason for this being that SME’s try and avoid the costs behind cancelling a
deal or prolonging deal negotiations as they usually only get one chance to finance it.. This
deal commitment effect is shown in this research in a lack of cancelled deals and a weak
impact of deal duration.
Additionally as known most SME’s lack the experience in M&A (Williams et al.,
2008), a finding that was remarkable, though, is that when an SME has no previous
experience in M&A it has a positive outcome on the M&A performance. A reasoning behind
this is that SME’s tend use M&A for external growth (Weitzel & McCarthy, 2009) and
therefore even though they have little to no experience, such a type of transaction is planned
and executed carefully. A second reason for disproving the experience trap for SME’s is the
fact that the size of SME’s makes integration and therefore growth more attainable. These
factors are contrary to most literature on this topic. In addition, SME’s that had more
experience tended to be in the financial services sector, using M&A to make profit and
therefore were less successful.
Finally, as with large corporations, cross-national distance has a significant effect on
post-merger performance of SME’s. This is a notable result as even though all the mentioned
differences in SME’s are a given, the results are equivalent with that of large corporations.
Cultural differences seem universal irrespective of company size.
51
There are many different perspectives and benchmarks that determine whether merger
and acquisitions are prosperous or not. As one can see there is no perfect measure for
performance in M&A’s (Zollo and Meier, 2008). Studies have shown that M&A success is a
function of many factors. This thesis takes only a few of many and tests if these increase the
value in an SME. For a M&A to be successful it depends on decisions made in all the phases
that the M&A goes through (Gomes et al., 2013). Managers need to comprehend this complex
relationship. The key success, for managers in SME’s, is that they need to understand that
when undertaking a M&A, their business might react differently compared to a large public
firm. This thesis suggests that further research need to be done to get a more complete
understanding on post-merger success, especially that of SME’s.
This study is a mere indication on SME’s and post-merger, further research needs to
validate the results of this research paper. SME and post merger performance is an under
researched topic in academic literature (Weitzel and McCarthy 2009). In short, this paper
contributes by showing that previous M&A experienced does not matter, but the size of the
firm does when looking at post-M&A performance.
The main question for academic and managers still remains; why do large firms and
SME’s alike keep using M&A’s for external growth, whilst the rate of success is so marginal
(Cartwright &Schoenberg, 2006).
52
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Appendices
Figure I: Scatterplot of regression-standardised residual
63
Figure II: Histogram of regression-standardised residual
64
Table III: Statistics of regression-standardised residual
*Before correction of HC-3
Revenue CAGR %
(2009-2014)
Total assets CAGR %
(2009-2014)
Acquirer total assets 2014
Acquirer revenue
2014
Pre-deal acquirer revenue
2009
Pre-deal acquirer total
assets 2009
N Valid 608 608 608 608 608 608
Missing 0 0 0 0 0 0 Mean 9,2393645521
3742 7,3058045732
9077 12933,080547
3893180 15684,70396 12945,24 11860,32
Skewness 6,034 2,271 ,896 2,741 3,439 2,863 Std. Error of Skewness
,099 ,099 ,099 ,099 ,099 ,099
Kurtosis 68,878 14,775 -,241 10,450 17,791 12,178 Std. Error of Kurtosis
,198 ,198 ,198 ,198 ,198 ,198
Minimum -72,744459268
719
-45,766279865
513
64,81700000000
4,259 2 7
Maximum 478,729867477255
191,248740576730
42541,11067193676
167239,255 196836 115085
