Merger and acquisitions in small to medium sized entreprises : a quantitative study at the link between pre-merger preparation and post-merger success

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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.

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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

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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.

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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}

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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 pre-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

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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)

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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 takeover process are abandoned; this only concerned large corporations and SME’s. Furthermore the following pre-merger factors still to be discussed

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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

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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

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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.

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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.

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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

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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-merger

performance

in SME's

H1,H2: The public take over process

H3: cultural

distance

H4: Previous

M&A

experience

H5: Industry similarity

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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

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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

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.

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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

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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

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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).

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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

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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

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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.

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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

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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

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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

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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

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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.

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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,

Merger and acquisitions in small to medium sized entreprises : a quantitative study at the link between pre-merger preparation and post-merger success

Master Thesis