The Effect of Cultural Distance on Acquirer Performance in Cross-Border Acquisitions

University of Groningen

Faculty of Economics and Business

The Effect of Cultural Distance on

Acquirer Performance in Cross-Border

Acquisitions

Master thesis

Groningen 2011

András Kerekes (2050013)

Supervisor:

e-mail:deusbandi@gmail.com

dr. P. Rao Sahib

Abstract

This study aims to measure the effects of cultural distance on acquirer performance post- cross-border acquisition. There is a lot of debate about the effects of cultural distance on acquisition performance, and the empirical results so far are quite contradictory. This paper focuses on reviewing the relevant literature, and based on former studies carrying out a research, namely the effect of large national cultural distance between on the acquirer performance. Consequently, the model applied in the study uses a sample of 197 acquirers originating from either Europe or North America. The cross-border acquisitions in the three years period 2008–2010 carried out by these firms were taken into consideration, controlling for several factors. The empirical results show that cultural distance has a significant negative effect on acquirer performance post-acquisition, though this effect is quite marginal. This paper shows that the role of cultural distance in terms of cross-border acquisitions still requires further research, and also illustrates the importance of several factors that might play a role in achieving better firm performance post-acquisition.

Table of Contents

I. Introduction... 3

II. Literature review... 5

III. The Sample... 15

IV. The Variables... 18

V. Control variables... 19

V.1. Firm level control variables ...19

V.2. Country level control variables ...22

VI. Results... 24

VI.1. Statistical Analysis... 24

VII. Discussion... 34

VIII. Conclusion... 36

IX. Implications for future research... 39

I. Introduction

Cultural differences between acquiring firms and their targets are thought to be one of the main causes ruining cross-border acquisitions (Morosini et al., 1998; Chakrabarti et al., 2009; Reus et al., 2009; Malhotra et al., 2010). However, most of the recent studies focus on the allocation of firm resources and portfolio diversification. The aim of this paper is the relationship between national cultural differences between acquirer firms and their targets and firm performance post-acquisition. Thus, we make an assumption that the national culture of a country highly influence the behaviour of firms as well, as Chakrabarti et al. (2009) also point out. The role of national culture in cross-border acquisitions has been researched several times so far, but mainly measuring cross-border acquisitions between culturally similar countries (Morosini et al., 1998). Morosini and his collegues (1998) base their research on european countries and 52 cross-border acquisitions. Moreover, they distinguish between national cultural distance and corporate cultural distance, the latter they measured through interviews at firms and field-study. Corporate culture is not part of this study but it focuses on national cultural distance itself and measures whether it has any effect on acquisition performance. The latter one has been discussed often among international economics and business scholars, since it focuses on the question whether multinational enterprises (MNEs) are spreading their activities equally across the world or concentrating them in specific regions (Beugelsdijk and Maseland, 2011).

acquisitions are taking place between culturally similar countries. Looking at the data they provided it seems that MNEs rather avoid taking the risk of acquiring in culturally distant countries.

When firms cross borders they have to adapt to the local conditions which are believed to be different from the home country of the firm. This explains why a number of scholars believe that larger cultural distance hinders post-acquisition performance. Thus researchers tried to find cultural explanations of the geography of MNE activity. Scholars of international economics and business are trying to explain the aggregate patterns of foreign direct investment (FDI). Navaretti et al. (2004) use home and host country characteristics as explanatory variables in their model to explain the determinants of FDI. They and Beugelsdijk et al. (2011) point out that FDI is quite well approximated by the gravity relationship. This refers to the similarities between the country of the acquirer and the target in terms of income, the distance between them, and also other factors such as sharing a common language and similar culture. Beckerman (1956) was the first to argue that cultural distance is also one of the main determinants of international investment flows. Culturally more distant countries are thought to be less familiar with one another. According to Beugelsdijk and Maseland (2011) countries trade less with each other if they do not share the same dominant religion or official language. They cite several scholars who have shown the significant negative effect of cultural distance on FDI flows, among them Loree and Guisinger (1995) and Siegel et al. (2008). However, we should distinguish between different types of FDI. In terms of cross-border acquisition, which is in the focus of this paper, the effects of cultural distance on horizontal FDI (HFDI) are important. As HFDI is also driven by market access, the new market shares can also contribute to better firm performance. Yet, as cultural distance increases, firms may choose to export instead of local production.

II. Literature review

Stahl and Voigt (2008) argue the negative effect of cultural differences on mergers and acquisition (M&As). They point out that the literature about the effects of cultural differences on mergers and acquisition performance are often shown to be negative. On the other hand, there are those who emphasize the potential gains from cultural disparity. Morosini et al. (1998) also share this view saying that cultural distance improves cross-border acquisition performance by providing access to the target’s and acquirer’s diverse set of routines and repertoires derived from the national culture. They also find significant positive relationship between national cultural distance and firm performance, but their sample is quite limited and they measure firm performance in sales growth two years following the acquisition. The main objective of this study is to find out whether high cultural distance relates negatively or positively to acquirer performance.

Cultural distance is measured in several different ways. Hofstede (2001) defines culture as “the collective programming of the mind which distinguishes the members of one category of people from another”.1 Hofstede’s work has a significant role even nowadays in terms of measuring cultural differences. He found that people having the same national background working for a specific organization tend to behave similarly. Developing his theory he defined four dimension to rank the countries (Beugelsdijk and Maseland, 2011; Hofstede, 2001):

1. Power distance which means the extent to which the less powerful members of organizations and institutions (like the family) accept and expect that power is distributed unequally.

2. Uncertainty avoidance refers to the extent to which people are uncomfortable with uncertain and unknown situations.

3. Individualism versus its opposite, collectivism, is the degree to which individuals are integrated into groups. It reflects the degree to which individuals are loose in the group; they have to look after themselfes or they are strongly integrated into a group instead.

4. Masculinity refers to the extent to which the traditional masculine values are emphasized in a society, for example competitievness, assertiveness, achievement, ambition and material posessions. On the

other side stand the feminine values, like nurturing, helping others, valuing the quality of life.

Hostede gave each country a score on each cultural dimension that varies between zero and 100, which indicates the people’s feeling about the aforementioned societal issues. He extended these scores to a large number of countries and his work has been cited and confirmed also in replication studies. The scores of Hofstede were used in this paper for several reasons. The Hofstede scores are cited in almost all of the papers measuring the effects of cultural distance. Hofstede believes that cultural differences do not change rapidly but remain constant over time, that is his scores are applicable even nowadays.

His work has been criticized as well, and there have been new approaches to measure cultural distance like the Globe project or Schwartz. Schwartz (1994) has critisized Hofstede’s work on several methodological issues. He also developed an alternative culture framework using three dimensions. The most recent concept of measuring culture is the Globe project, which is applied by several scholars, among them Reus and his collegues (2009). Bhagat et al. (2002) use two dimensions:

horizontal/vertical and individualism/collectivism. However, most of the methods are based on Hofstede’s work (1983). According to Clerc (1999) the national culture determines the behavior of an individual in an organization, that is he also determines that cultural differences can affect firm performance after the acquisition took place. However, Schwartz and Globe are not used extensively as Hofstede in international business literature. When building a model to explain economic effects, the scores of Hofstede are more applicable, whereas in cross-cultural psichology and international management Schwartz and Globe are applied more often (Beugelsdijk and Maseland, 2011). This paper focuses on the economic effects of cultural distance, since the model applied in the study also uses country level variables.

(2009) claim that the financial crisis might have fueled international acquisitions, that is the firms might have taken actions to restructure their activities through cross-border acquisitions lately. The acquisition portolios of the firms are measured in this time period. The firms that are being investigated are random in a way that any firm from North America or Europe which had acquisitions in culturally distant countries in the examined period could be in the sample. Culturally distant countries were defined as countries from East Asia and South America. Yet gathering the sample did not ensure that the acquirer firms only had acquisitions in culturally distant countries in the measured period. They might had domestic acquisitions or those in culturally non-distant countries. Consequently, looking at the portfolios of the acquirer firms proved to be useful to see whether domestic acquisitions, acquisitions in culturally distant or close countries dominate.

Knoben et al. (2008) argue in their paper that firms are mobile, as they can relocate their activites easily. They also find that the effect of distance between the original location and the investment location on firm performance is mixed. On one hand their findings indicate that firms investing over long distances experience high employee growth in the first year (which implies growing profitability), on the other hand they measure a decline in the number of employees two years later. In the long-run however they also see that firms investing over longer distances show increased profitability. They conclude that the characteristics of the region in which a firm is located play a relatively minor role in explaining the firm’s performance. In addition, knowledge spillovers, resulting from being located in a highly research and development (R&D) intensive region affect only marginally the innovative performance of firms. This refers to the fact that whether an acquisition takes place in a develepod region or not, it has only a marginal effect. One of their other findings is that in the medium and long term, most firms benefit from relocating. They mention organizational embededness, what they define as “a firm’s participation in interorganizational relationships and networks, and thereby its access to external resources controlled by other organizations”.2 _{Based on this they hypothesize that the}

larger the number of direct interorganizational relationships a firm has, the greater its performance. In terms of geographic distances they show that organizational proximity seems to be the safeguard against the negative effects of relocating over

large distances. However, their findings about geographical distance are mixed. They find that firms that move over large distances experience a growth in the number of employees in the first year, but this is mostly dute to the physical constraints at the old location, that is the firms were not able to grow before. On the other hand, they find for a subset of firms with one or more inter- organizational relationships, that relocation over longer distances leads to a decline in employee growth two years after relocation. On longer time horizon, the findings indicate that firms relocating over large distances show increased profitability. They also show that relocations over longer distances are positively associated with the percentage of sales that are generated by products that are new to the firms, but negatively associated with the generation of products that are new to the market. In the end they find no clear pattern to the effects of geographic distance on firm performance. Consequently, geogpraphic distance as a control variable was not applied in this study.

The evaluation of the empirical results is of great importance to the paper. Provided that there is a significant relationship between firm performance and cultural distance the question is what cultural distance truly stands for. In their paper Reus et al. (2009) argue that cultural distance affects negatively the cross-border acquisition performance because it hinders integration capabilities. Moreover, their results include zero-near correlation between cultural distance and firm performance. However, they also mention the possibility of learning, though it is only possible with strong integration capabilities. According to King (2002) the mergers and acquisitions do not raise the value of the firm. Yet, why do the firms insist on exercising such activities? On the other hand, if we accept Milton Friedman’s idea that the rationality of mankind is constrained (Friedman and Savage, 1948) the answer is obvious: an M&A transaction is such a complex task that the actors involved are not able to take into account all the possible factors and their effects. However, the problem can be also the way of measuring the value or performance growth, which differs among studies.

reap the benefits of international acquisitions. Markides and Ittner (1994) call this “the nature of the bidding firm’s industry”.3 _{Using a sample of 276 US firms in the}

period 1975–1988 they show that on average international acquisitions create value for acquiring firms. Thus, one of the presumption of this study is that firms prefer cross-border acquisitions to exports. Yet, it is still not known how international acquisitions over large cultural distances affect acquirer performance.

Although Dikova et al. (2010) argue that more attention to pre-merger activities is needed, they also point out the importance of institutional differences and organizational learning. They focus on the fact that according to empirical research firms abandon 25% of their announced acquisitions. They conclude that institutions are nation specific, that is the uncertainty in economic activity vary across national borders. We might expect firms to take this into account when considering acquisitions in culturally distant countries. The authors find that the more different the formal institutional environments of the home and host country are, the more likely it is that the announced acquisition will be abandoned. They argue that larger institutional differences would have a negative effect on deal-completion likelihood. This refers to the fact why acquirers are still not likely to invest only in culturally distant countries, but to have a more diverse portfolio of acquisitions instead. On the other hand, if managers do not have the knowledge and skills necessary to fully understand and carry out a cross-border acquisition transaction, they can rely on local consultants and overcome the negative effects. They also find that the more experience with completed acquisitions a firm has, the higher the likelyhood of focal deal comletion in institutionally non-distant countries. This implies that higher number of acquisitions refer to more experience, more completion, and therefore might cause higher profitability. The fact that the latter one they only find for institutionally non-distant countries means that firms tend to dissolve acquisitions, when it comes to higher risks in distant countries. The high percentage of dissolved acquisitions was also a constraint while collecting data for my study.

Gubbi et al. (2010) measure Indian cross-border M&As and conclude that cross-border M&As often fail to deliver shareholder value. However, their empirical research has also shown that cultural, administrative and economical factors are

3 _{Markides, C.C. and Ittner, C.D. 1994. Shareholder benefits from corporate}

important in the value creation of FDI. They also take into account the role of institutions, though they focus on emerging economies, that is they do not measure the performance of those acquisitions originating from developed countries. Based on their study, economic disparity between acquirers and targets are also controlled in this study. Consequently, this paper tries to extend the previous literature by adding a variable to the model that captures the effect of economic disparities, namely, the difference in GDP per capita between the acquirer and its targets.

Nevertheless, most of the studies explaining international activity use data on developed countries. Dunning et al. (2008) talk about the internalization theory in their book as one of the explanations of FDI. Internalization means that the combined ownership of domestic and foreign activities is more beneficial than export for the firm. MNEs choose internalization (acquisition) in those cases where the market functions poorly, so transaction expenses of exporting are high. Consequently, we would expect firms to take the risk of acquiring new counterparts even in culturally distant lands, instead of supplying through export. Moreover, firms originating from developed countries are more likely to own internalization and integration advantages (Reus et al., 2009).

Beugelsdijk and Maseland (2011) contributed to the liturature about culture in economics in their recent book, Culture in Economics: History, Methodological

Reflections and Contemporary Applications. They provide a broad overview of

interaction between different cultures which might explain the learning processes of cross-border acquisitions. The latter one is quite relevant since it is in the focus of researchers when looking at cross-border acquisitions over large distances (either cultural or geographic).

Jun-Koo Kang and Jin-Mo Kim (2010) argue that as cultural distance inrcreases, it becomes more difficult and expensive for headquarters to obtain accurate information about foreign subsidiaries. Thus, cultural differences can be an important source of information asymmetry which implies less governance activities by the acquirer in the target’s acivities. Krug et al. (2001) show that cultural distance between the foreign acquirer and the US target (they based their study on US firms) is one of the most important determinants for post-acquisition management turnover in US manufacturing firms bought by foreigns. Jun-Koo Kang and Jin Mo Kim (2010) also applied Hofsede’s (1980) four cultural dimensions (power distance, uncertainty avoidance, masculinity and individualism) to show how high cultural distance hinders post-acquisition performance.

Lee et al. (2008) find that cultural distance shows no significant relationship with the degree of control sought over the cooperative ventures, whereas cultural distance is significantly related with a preference for ventures in domestic or foreign markets. The impact of cultural distance was found to be greater in inward investment than in outward investment. If the effect of cultural distance on outward investment is marginal, we might expect less relevance of cultural distance in terms of cross-border acquisitions. My study attempts to measure the latter.

acquirers with high levels of integration capabilities in their sample. Furthermore, Malhotra et al. (2010) conclude that U.S. firms consider cultural distance a big constraint when deciding which market to enter. In my paper I try to extend their study, and address the problems of the study of Morosini et al. (1998). Nonetheless, it is not easy to collect a sample where the acquirers do not own high levels of integration capabilities, since most of the FDI activity originates from developed countries.

The theory of Sarala et al. (2010) is in line with the formerly discussed facts. They argue that cultural convergence and crossconvergence affect knowledge transfer in acquisitions. They also examine the role of cultural distance between firms from a new point of view. They try to find out why organizational cultural convergence occurs in some acquisitions, crossvergence in others, and no cultural integration or divergence at all in others. Slangen (2006) argues that acquirers must keep their acquired counterparts in distant cultures autonomous to some extent. Too tight integration comes with lower firm performance post-acquisition. However, if we keep in mind other scholars’ reasoning, without tight integration there is less possibility of knowledge transfer. Several studies do not support the idea of large cultural differences in cross-border acqusition being beneficial nor the opposite. Based on the previous studies so far we cannot conclude that one result is more likely than the other. The evidence of empirical studies is still unclear. Yet Zollo et al. (2002) conlude that acquisition performance is positively related to the codified knowledge of the acquirer about the target. To sum up the previously mentioned ideas, we see that the negative view stesses that cultural distance is a challange posed by acquiring firms in distant cultures, whereas the positive view points out the benefits of new learning possibilities which were not available to the acquirer prior-acquisition. We should note that there are differences between the firms in terms of acquisition abilities.

acquisition.”4 _{They find that most studies about M&A performance are short-term}

event studies and use stock price measures. However, stock price variation is the expectation of the market after the acquisition took place. They also question the reliablility of the short-term methods. Other scholars, like Morosini et al. (1998) use the firm sales to measure firm performance two years after the acquisition. Yet Zollo et al. (2008) argue the importance of the variation in return on assets (ROA) and the long-term measures which is also applied in this study. Though it is still not clear over what time period after the acquisition shall we measure the change in ROA, most studies advice two and three years long time periods to measure the effects.

Ragazzino and Reuer (2010) put on a hypothesis which says that the greater the dissimilarity between the acquirer’s and target’s knowledge, the worse these new ventures will perform. Nevertheless, they use a different method to measure cultural distance between the acquirer and the target, namely the knowledge distance, and they also compute it differently than Kogut and Singh.

Nadolska and Barkema (2007) use data on Dutch companies and argue that firms engaged in international acquisitions can benefit from foreign acquisition, domestic acquisition, and international joint venture experiences, but their learning process is prone to biases. They also point out the importance of cross-border acquisition in gaining market power and building up foreign presence. They expect that experience with international acquisitions leads to routines that help to economize on cognitive efforts devoted to acquiring abroad, that is better acquisition performance over time. Their evidence supports the idea the idea that the frequency of acquiring abroad increases with a company’s experience – that is, with its past international and domestic acquisitions. They show that as time, attention and cognitive effort devoted to acquiring abroad increases, the efficiency of the process of acquisitions increases as well, and firms acquire more frequently. Building on their findings I assume that as the number of acquisitions increases in the measured period, the performance of acquirers might increase as well, as it implies more experience.

Based on the aforementioned studies we cannot put on a clear hypothesis regarding the effect of cultural distance on acquisition performance. The results have been mixed so far, thus it is difficult to state that cultural distance has significant positive or significant negative effect on acquisition performance. Consequently, the

4 _{Zollo M., Meier D. 2008. What is M&A Performance? Academy of Management,}

aim of this paper is to find out what effect has average national cultural distance between the country origin of targets and the country origin of acquirer on acquirer performance post- cross border acquisition. The model applied in the study attempts to measure whether cultural distance has any significant effect on acquirer performance post-acquisition, but also includes several other factors that might play a role in affecting performance in the case of cross-border acquisitions. In the appendix table 1 summarizes the most relevant papers for my study in the literature. The table shows the authors, the year of publishing the paper, the sample, the dependent variable(s), the explanatory variables and the major findings.

The next section describes the sample and methodology used in the study. Following this the results are presented with some tests. This is followed by the conclusion and some suggestions for future research.

III. The Sample

Defining a reasonable sample of firms undertaking M&As recently was important to make the research relevant. The past three years has been chosen (2008– 2010) for the time-period to make the study more up to date, although if we look at the data or figures about FDI activity around the world we see a decline in the last three years.5 _{Nevertheless, this specific time period has been chosen, because the}

recent financial crisis might motivate firms to restructure their activities. Since the focus is on firms from culturally distant countries, the main criteria was to find firms which performed acquisitions in culturally distant nations. Other criterias were that the acquirer’s origin country had to be in Europe or North America, and the target countries had to be either in Central and South America or Far East Asia. The Zephyr database was used to find the acquisition deals. The Zephyr database is a comprehensive M&A database with integrated detailed company information, though the company information provided there did not prove sufficient. Zephyr is part of the Bureau Van Dijk company that provides databases of company information and business intelligence for individual countries, regions and the world. Their global database called Orbis (which was also used later on, and compatible with Zephyr)

5 _{World Bank database, [online] Available at}

covers information from around 100 sources and covers approximately 65 million companies. The sample consists of 197 acquirer firms (observations). Only listed acquirers were picked from the past three years, for is it only possible for listed companies to find sufficient information about them via their BVD number. The BVD number is the the Bureau van Dijk identification number and has three parts:

1. The first two of the characters stand for the Country Code which identifies where the firm is domicilied.

2. Next a six-to-fourteen character identification (ID) number is assigned by the appropriate national agency.

3. The last character of the ID number depends on the financial reports of the firm. If the reports are consolidated, then a "C" is assigned. If the reports are either unconsolidated or have limited financial information, then a "U" is assigned. Otherwise, nothing is assigned. However, I only picked western firms with consolidated information to see their financial indicators and acquisition deals.

Table 1

Steps taken collecting the sample

Number of observations left 1. Searching for listed acquirers in the BVD database 206,308 2. Dropping out the non-completed acquisitions 134,455 3. Setting the time period for acquisitions to 2008–

2010 31,597

4. Setting acquirer country origin* 18,752 5. Setting target country origin** 1,105 6. Sorting out firms from specific industries*** 560 7. Sorting out acquirers and acquisition due to

missing data 199

8. Dropping outliers**** 197

* Country origins of acquirers were: Austria, Belgium, Bulgaria, Canada, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, United Kingdom, United States

** Country origins of targets were: Argentina, Bolivia, Brazil, Chile, China,

Colombia, Ecuador, Guatemala, Guyana, Hong Kong, Indonesia, Japan, Republic of Korea, Malaysia, Mexico, Nicaragua, Paraguay, Peru, Singapore, Suriname, Taiwan, Thailand, Uruguay, Venezuela, Vietnam

*** The sample consists of firms operating in the following industries: services; machinery, equipment, furniture, recycling; chemicals; food, beverages, tobacco. **** Two outlier acquirer firms were dropped because of really high firm sales compared to the rest of the sample, namely The General Motors Company and the British Petrol PLC.

Acquirer’s country of origin Number of firms Industries Number of firms United States 126 Machinery 67 United Kingdom 21 Services 67 France 15 Chemicals 36

Germany 10 Food, bev.

tob. 27 Sweden 7 Total 197 Italy 4 Luxemburg 4 Findland 3 Austria 2 Belgium 2 Ireland 2 Spain 2 Total 197

IV. The Variables

Dependent variable: Performance was measured as the the return on assets

(ROA) of the acquirer, based on Zollo et al. (2008) after the three-years period, thus in 2010. The information about the ROA of the acquirer firms was collected from Orbis. Stock price measures were not applied, since it is more convenient when looking at short-term effects. Stock price reflects mostly the pricing of the market which is sometimes misleading. Some research about the topic use sales as the main dependent variable, that is for measuring the performance (Morosini et al., 1998). Instead of using firm sales as main dependent variable it was applied in the model as a control variable for measuring firm size.

Independent variable: The key independent variable in this study is the

score of the cultural distance between the acquirer and its targets and becomes the main independent variable in the model. For example, the Eurasian Natural Resources Corporation Plc from the United Kingdom had acquisitions in the Netherlands in 2010, in China and in Brazil in 2008. Even though the Netherlands is not so distant in cultural terms from the UK, China and Brazil are quite different, thus the average cultural distance will be quite high, in this case 71,3. Kogut and Singh’s (1988) formula based on Hofstede to determine the average of the national cultural distance between the acquirer and its targets is the following:

Where CDj is the cultural distance for the jth country, Iij is Hofstede’s score for the ith cultural dimension and jth country. In this case the subscript ’C’ indicates the countries. This particular form of the formula was taken from the paper of Morosini et al. (1998). Hofstede’s original four dimensions were utilized, even though there is two new dimensions in his model. These two new ones are not included because by several countries Hofstede and his collegues have not indicated the new scores yet. Reus et al. (2009) and Chakrabarti et al. (2009) also used this formula to calculate the cultural distances. Hofstede’s scores were acquired from his official website.

V. Control variables

The model consists of firm level and country level control variables. The firm level variables control for the firm specific characteristics, whereas the country level variables control for those nation specific characteristics which are not included in Hofstede’s scores, and for those which might affect post-acquisition performance.

V.1. Firm level control variables:

Industry relatedness: Industry relatedness was defined according to the

industries the acquirer and target comes from. If an acquirer comes from the same industry as the target, it might affect positively the performace of the acquirer after the acquisition. The knowledge of the same industry might enhances the performance. Industry relatedness appears as a ratio in the model. The more acquisition targets in the portfolio of the acquirer are from the same industry as the acquirer, the higher the

CDij = (Iij −IiC)

2

i=1 4

ratio gets. For example, let us consider a case where a firm made four acquisitions in the three years period. Three of these firms are from the same industry as the acquirer, one of them is from a different one. In this case the industry relatedness score is 0,75. The information about the industries was collected from Orbis.

Firm size: The firms sales is a good indicator for measuring firm size. The

Orbis database proved useful to see the net sales of the firm in the year(s) of the acquisition (if the firm had acquisitions in all three years an average was calculated). Zollo and Meier (2008) argue that higher firm sales might imply more international experience. Consequently, more international experience might lead to better acquirer performance post-acquisition. The coefficient of firm size shows whether there is significant relationship between the sales of the acquirer and its performance post-acquisition. The firm size (as measured in net sales) is shown in million dollars and was taken from the detailed financial information of Orbis.

Industry of the acquirer: A number of scholars have shown that industries

have some specific characteristics which impact the firms operating whithin. Caves (1982) argues that industries determine the preference of acquisitions as an entry mode. Morosini et al. (1998) and Reus et al. (2009) also controls for this in their research. Kogut and Singh (1988) conclude that acquisitions are more frequent in the manufacturing and services industries. Not just the acquisition strategy, but also the pace of integration, the development of performance might differ across industries, ergo it is inevitable to control for the industries in the model. In this case the industry of the acquirer has been taken into consideration, since the industry relatedness also controls for the industry of the target. In the final sample dummy variables were assigned to the acquirers according to the industries they operate in. The industries were chosen based on the level of cross-border activity. The industries are:

• Services

• Machinery, equipment, furniture, recycling

• Chemicals

• Food, beverages, tobacco

Average stake: Acquirer firms not only undertake fully acquistions but also

their study and they find significance. Nevertheless, scholars do not usually include the acquired stake in their models as control variable. Consequently, both full and non-full acquisitions are present in the sample to see whether the stake of acquisitions has any effect on acquier performance. An average stake variable has been created based on the acquirer’s shares in the target companies. For instance, if the acquirer had four acquisitions, two of them with minority stake of 50% and the rest 100% acquisitions, the average stake takes the value of 75%. The data about the stake of acquisitions was collected from Orbis and Zephyr.

Domestic acquisition: Controlling for domestic acquisitions proved necessary

because a lot of firms in the sample carried out acquisitions in their country of origin during the examined period, which might have an impact on the firm-performance after the acquisitions took place. It is also important to see whether these firms preferred domestic investments to cross-border ones in the measured period. A ratio of domestic investment over the total value of the acquisitions of an acquirer was created in the measured three years period. This is particulalry important since some acquirer firms in the sample had most of their acquisitions in their home country. So in this case we might see a good post-acquisition performance with a relatively high cultural distance, but we also see that most of the acquisition took place in the home country of the acquirer, that could have more effect on good performance than high cultural distance. The Orbis and Zephyr databese provided the value of the acquisitions which was used to compare the value of domestic and international acquisitions in the measured time period and calculate the ratio. The domestic acquisition variable was calculated the following way:

Domestic acquisition= value of domestic acquisitions2008– 2010

total value of domestic and foreign acquisitions_{2008– 2010} Number of acquisitions: The number of acquisitions controls for the fact that some acquisition portfolios are more diverse than others. Nadolska and Barkema (2007) also emphasize the importance of the frequency of acquisitions. Some acquirers had only two or three acquisitions in three years, while others more than ten. The number of acquisition takes the form of a number after collecting the comleted acquisitions of the acquirers from Orbis.

decline in the number of emloyees two years after the acquisition. The time period that they defined for looking at employee retention is similar to the timeframe in my study (2–3 years). However, in some cases acquirers experienced growth in the number of employees over the three years period measured in the study. Thus, the variable takes the form of a change measured in percentage, both negative and positive. Information about the number of emloyees was collected from Orbis. The

variable is calculated the following

way:

change in the number of employees= number of employees2010−number of employees2008

number of employees₂₀₀₈

V.2. Country level control variables

Trade openness: According to Chakrabarti et al. (2009) trade oppennes of the target countries can influence post-acquisition performance and it is therefore controlled in this study. Based on their study trade oppenness is calculated the following way:

The gross import, export and GDP values were collected from the official World Trade Organization (WTO) website. In the case of more target countries the target openness takes an average from. In any case, it is presented as percentage.

Economic disparity: Chakrabarti et al. (2009) also controls for economic differences between the country origins of the acquirer and the targets, therefore it was applied in this study as well. The formula is the following:

Just as in the case of trade openness in the case of more target countries the economic disparity takes the form of an average. The GDPacq is the GDP per capita of the acquirer’s nation and the GDPtar is the GDP per capita of the target’s nation. GDP per capita values were collected from the WTO website.

Language relatedness: Language relatedness is included in the model because it is not part of the cultural distance measure. Chakrabarti et al. (2009) also controls for language relatedness in their study. The language takes the form of percentage, that is if the acquirer and its targets share the same language it takes the value of

Openness=import+exp ort GDP

100%, if only half of the targets share the same language as the acquirer it takes the value of 50% etc. Information about the official languages was collected from the Central Investigation Agency (CIA) World Factbook.

Religion relatedness: Religion relatedness was included in the model for the

same reason as the aforementioned language relatedness, and it is calculated the same way. Just as in the case of language relatedness, Chakrabarti et al. (2009) also included religion relatedness in their model. The religion followed by the most people was taken into consideration as the national religion in the case of every country. This data was collected from the CIA World Factbook.

In the appendix, Table 2 summarizes the variables. It includes a short description of every one of them and the sources they were acquired from.

Thus, the complete model is:

PERFORMANCE_i2010 =

α

β

β

β

j=1 J

∑

∑

+

β

β

β

J

∑

+

β

β

β

β

∑

∑

β

β

ε

∑

∑

Where the PERFORMANCE of the acquirer firm ’i’ is measured as the ROA in the year 2010. The CULTDIST is the mean of national cultural distances between the acquirer ’i’ and the target ’j’, the INDREL shows whether there is relation between the target’s ’j’ and acquirer’s ‘i’ industry (that is the aforementioned average of the industry relatednesses). The FIRMSIZE controls for the size of the acquirer as measured in sales in the year of the first acquisition, or the average of sales of the years of acquisitions in the case of acquisitions in more than one year. The

AVERAGESTAKE shows the average stake of the acquisitions of acquirer firm ’i’ in

performed by acquirer ’i’ in the three years period. The EMPLOYEE shows the change of the number of employees over the three years period at acquirer ’i’. The

OPENNESS is the average trade openness of targets. The ECODIFFERENCE

controls for the average economic disparity between the acquirer ’i’ and target ’j’. The LANGUAGE and RELIGION terms control for the language and religion relatedness between the acquirer firm ’i’ and its target ’j’. The term ∑I is the error

term and controls for those omitted effects affecting the performance of acquirer firm ‘i’.

VI. Results

VI.1. Statistical Analysis

Table 3.1 Descriptive Statistics

Variables Mean Std. Dev. Variance Skewness Kurtosis

ROA (%) -0.20 3.67 13.47 -13.96 196.28 Change in the number of employees (%) -0.19 5.75 33.08 -13.51 188.27 Firm size (million$) 6.70 11.71 137.34 3.20 16.57 Average stake (%) 0.89 0.20 0.04 -2.36 8.71 Number of acquisitions 3.87 3.86 14.88 2.50 11.08 Domestic acquisition (%) 0.23 0.33 0.11 1.08 2.60 Industry relatedness (%) 0.74 0.34 0.11 -0.99 2.72 Cultural distance 67.96 16.22 263.08 -0.18 2.04 Trade openness (%) 0.84 0.83 0.69 2.86 11.03 Economic disparity (%) 0.46 0.26 0.07 0.11 1.94 Religion relatedness (%) 0.66 0.39 0.15 -0.77 2.01 Language relatedness (%) 0.24 0.29 0.09 0.73 2.04 Chemicals industry 0.19 0.39 0.15 1.61 3.61 Food, bev., tob. industry 0.14 0.34 0.12 2.13 5.53 Machinery industry 0.34 0.48 0.23 0.67 1.45 Services industry 0.34 0.47 0.22 0.69 1.48 Acquisition countries 2.88 2.41 5.79 2.96 16.27

tested omitting the domestic stake variable as well. Overall the modest level of correlation indicates that multicollinearity is not a problem in this study. Even checking for the different industries resulted in marginal correlation coefficients.

VI.2. Regression Results

Table 4

1. 2. 3. 4.

VARIABLES ROA ROA ROA ROA

Cultural distance -0.00295* -0.00287*

(0.00164) (0.00162) Change in the number of

employees (%) 0.632*** 0.632*** 0.632*** 0.632*** (0.0142) (0.0141) (0.0142) (0.0142) Trade openness (%) -0.0516 -0.0517 -0.0478 -0.0479 (0.0978) (0.0975) (0.0988) (0.0985) Economic disparity (%) -0.181 -0.181 -0.118 -0.119 (0.125) (0.125) (0.137) (0.136) Religion relatedness (%) 0.0603 0.0621 0.0216 0.0215 (0.107) (0.106) (0.108) (0.107) Language relatedness (%) 0.111 0.0842 0.0647 0.0826 (0.143) (0.119) (0.147) (0.118) Number of acquisitions 0.0188*** 0.0184*** 0.0166*** 0.0169*** (0.00645) (0.00625) (0.00623) (0.00604) Firm size (million$) 0.00363* 0.00361* 0.00328 0.00330

(0.00202) (0.00201) (0.00200) (0.00201) Industry relatedness (%) -0.104 -0.103 -0.120 -0.121

(0.0887) (0.0875) (0.0906) (0.0902) Average acquired stake (%) -0.186 -0.186 -0.211 -0.210

(0.155) (0.155) (0.158) (0.157)

Domestic acquisition (%) -0.0312 0.0210

(0.0951) (0.0955)

Food, beverages, tobacco industry dummy

0.0325 0.0317 0.0334 0.0339

(0.0909) (0.0905) (0.0909) (0.0904) Machinery industry dummy -0.0933 -0.0938 -0.0986 -0.0981 (0.108) (0.108) (0.107) (0.106) Services industry dummy -0.0495 -0.0499 -0.0503 -0.0501 (0.110) (0.110) (0.109) (0.109)

Constant 0.171 0.170 0.411** 0.405**

(0.163) (0.162) (0.166) (0.167)

Observations 197 197 197 197

R-squared 0.980 0.980 0.980 0.980

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Nadolska and Barkema (2007), who argue that the frequency of acquisitions has a positive effect on acquisition performance. We also find that the firm size has a positive, significant effect on performance (=0.00363, p<0.05). However, this is only in the case when we omit the main independent variable from the regression. The result suggests that the effect is positive but very small. The second regression shows the results when omitting the main independent variable and the acquired domestic stake variable. Running the regressions without the domestic stake variable was necessary as well, because of the high correlation between the acquired domestic stake and language relatedness variable. Yet, the results did not change significantly, and we acquire the same significant variables with nearly the same coefficients.

When adding the main independent variable, in the third model the results show that the coefficient of cultural distance is significant at the level of 10% (= -0.00295, p<0.1). Thus we see a significant negative effect of cultural distance on acquirer performance. However, cultural distance has a zero-near coefficient. This is in line with the findings of Reus et al. (2009). The coefficient of the employee variable shows the same result as in the case before (=0.632, p<0.01). The coefficient of the number of acquisitions variable also shows positive significance (=0.0166, p<0.01). However, the coefficient of firm size loses its significance.

The fourth regression presents the results omitting the acquired domestic stake variable to see if we acquire different results than in the former case due to the correlation between the control variables, acquired domestic stake and language relatedness. Still, there is no significant change in the results and the coefficient of firm size remains insignificant.

included resulted in positive and significant coefficients for firm size, even with the cultural distance variable included. However, interpreting the results with the two outliers included would have been irrelevant, since the omitted acquirers had sales of 361 and 141 million dollars, which is incomparable with the mean value of firm size in the sample (6.7 million dollars). We can therefore observe that, in our sample,

running the complete model, the firm size did not have any significant effect on acquirer performance. All the country level variables have insignificant effect on the acquirer’s ROA. This was expected in the case of language and religion relatedness, as Chakrabarti et al. (2009) did not find significance either.

None of the industry dummy variables turned out to be significant. Whereas Morosini and his colleagues (1998) find significance in terms of industries, my results support the findings of Reus et al. (2009) who found the opposite. Nevertheless, Morosini et al. (1998) only find positive significant effect in the textiles and apparel industry, while the other three industries they control for turned out to be insignificant. My results on the other hand indicate that controlling for industry in studies on cross-border acquisition performance is of small importance.

Table 5

1. 2. 3. 4.

VARIABLES ROA ROA ROA ROA

Cultural distance -0.00383** -0.00366*** -0.000249 -2.25e-05 (0.00148) (0.00138) (0.000807) (0.000804) Change in the number of

employees (%) 0.648*** 0.648*** 0.0285 0.0285 (0.000814) (0.000812) (0.0231) (0.0230) Trade openness (%) -0.0140 -0.0149 0.0200 0.0219 (0.0178) (0.0177) (0.0241) (0.0237) Economic disparity (%) 0.0200 0.0138 -0.0104 -0.00550 (0.0752) (0.0730) (0.0575) (0.0572) Religion relatedness (%) -0.126** -0.126** -0.0453 -0.0515 (0.0549) (0.0545) (0.0415) (0.0413) Language relatedness (%) 0.113 0.139** -0.146* -0.0529 (0.0891) (0.0679) (0.0817) (0.0449) Number of acquisitions 0.0118* 0.0124* 0.00155 0.00252 (0.00691) (0.00700) (0.00215) (0.00231) Firm size (million$) -0.000217 -0.000184 0.00137 0.00164

(0.00129) (0.00127) (0.00104) (0.00108) Industry relatedness (%) 0.0111 0.0107 -0.0914** -0.0918** (0.0674) (0.0668) (0.0446) (0.0458) Average acquired stake (%) -0.135 -0.133 -0.0235 -0.0368

(0.0969) (0.0951) (0.0971) (0.0941)

Domestic acquisition (%) 0.0345 0.0899

(0.0718) (0.0617)

Food, beverages, tobacco industry dummy

0.0133 0.0124 0.0693 0.0766*

(0.0440) (0.0446) (0.0451) (0.0444) Machinery industry dummy -0.106** -0.106** 0.0369 0.0415

(0.0468) (0.0470) (0.0409) (0.0411)

Services industry dummy 0.0166 0.0169 0.0716 0.0715

(0.0470) (0.0471) (0.0459) (0.0459)

Constant 0.508*** 0.497*** 0.144 0.132

(0.167) (0.161) (0.113) (0.113)

Observations 102 102 95 95

R-squared 0.999 0.999 0.257 0.243

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

significance (=0.0118, p<0.1). Moreover, the coefficient of the machinery industry dummy variable shows negative significance (=-0.106, p<0.05). In model 2 we see the same regression omitting the domestic stake variable because of the multicorrelation. However, the results did not change significantly, but the coefficient of language relatedness becomes positive and significant (=0.139, p<0.5). Model 3 shows the regression results for the firms, which experienced employee growth over the measured three years period (95 observations). The coefficient of cultural distance becomes insignificant. Moreover the change in the number of employees variable also loses its significance. Language relatedness shows a negative significant effect on acquirer performance (=-0.146, p<0.1). More surprisingly, industry relatedness also shows the same effect (=-0.0914, p<0.5). Model 4 shows the results of the regression omitting the domestic stake variable for the same group of firms. We see more substantial changes. In this case, language relatedness loses its significance, while industry relatedness keeps nearly the same effect as in the case before. Furthermore, the food, beverages and tobacco industry dummy shows positive significance (=0.0766, p<0.1).

Table 6

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

VII. Discussion

In spite of a lot of research about showing the relevance of cultural distance in international acquisitions, the empirical findings of this paper do not support this theory. This study was based on several former papers, trying to sum up more methods explaining acquisition performance and find out what other factors influence this. Even though the statistical analysis does not show high correlation between the factors included in the model, theory suggests that they are linked explaining acquisition performance (Zollo and Meier, 2008). The results of this research confirm that cultural distance has no strong effect on acquirer performance post-acquisition.

1. 2.

VARIABLES ROA ROA

Change in the number of employees (%) 0.648*** 0.0283 (0.000778) (0.0230) Trade openness (%) -0.0206 0.0200 (0.0183) (0.0239) Economic disparity (%) -0.0819 -0.0145 (0.0644) (0.0529) Religion relatedness (%) -0.0833 -0.0414 (0.0538) (0.0368) Language relatedness (%) 0.177* -0.142* (0.0897) (0.0812) Number of acquisitions 0.0151** 0.00170 (0.00725) (0.00229) Firm size (million$) 0.000497 0.00137

(0.00117) (0.00103) Industry relatedness (%) 0.0439 -0.0907** (0.0674) (0.0443) Average acquired stake (%) -0.0920 -0.0236

(0.0861) (0.0955) Acquired domestic stake (%) -0.0432 0.0860

(0.0655) (0.0611) Food, beverages, tobacco industry

dummy

-0.0107 0.0709 (0.0464) (0.0441) Machinery industry dummy -0.115** 0.0385

(0.0516) (0.0410) Services industry dummy 3.88e-05 0.0729

(0.0480) (0.0462)

Constant 0.203* 0.125

(0.113) (0.106)

Observations 102 95

Yet, low levels of average domestic acquisitions imply that firms prefer cross-border ones. However, the moderate level of average cultural distance in the sample indicates that firms do not take the risk of acquiring only in culturally distant lands. The data suggests that firms try to mitigate the risk by acquiring in culturally close countries as well. Furthermore, the results are in line with the findings of Malhotra et al. (2010). They show that firms from both the United States and emerging countries target countries that are culturally closer to their home countries. Fernhaber et al. (2008) argue that it is all about the capability of internalization. They emphasize the role of venture characteristics, which supports the different results for different industries. Yet, my results did not show strong patterns in terms of industries. The empirical results also confirm that running the regressions for the whole sample the cultural distance, employee and acquisition variable always turned out to be positive and significant. The firm size only showed significance though when the outliers were included in the sample. As the firm size was measured in sales, it is somehow linked to the study of Morosini et al. (1998). In their model firm sales stand for the acquisition performance. Despite that in this study firm sales control for firm size, it is still obvious that firm size has no significant effect on the acquisition performance.

play an important role in the value creation of FDI, our findings suggest economic disparity does not have a significant effect on acquirer performance post-acquisition, therefore might not influence the decision of acquirers when choosing between acquisition possibilities.

Lee et al. (2008) looked at the degree of control sought over the cooperative ventures in the case of small and medium-size Korean firms. Unlike our empirical findings they conclude that cultural distance is significantly related with a preference for ventures in domestic or foreign markets. In the analysis the stake of domestic acquisitions has shown no significant correlation to cultural distance. Moreover, the coefficient of the domestic stake variable did not show any significance in the models applied in the study.

To sum up, the zero-near coefficient of cultural distance implies that cultural distance may not have a large effect on firm performance, ergo it has a marginal role in the case of cross-border acquisitions. The results confirm that there is no simple answer to the question whether acquisitions in distant countries will result in good performance. While the empirical results support Reus et al. (2009) with the negative relationship between cultural distance and acquisition performance, this relationship has only a marginal effect according to the empirical results, just like the aforementioned researchers had shown before.

One of the main findings of this paper is that the coefficient of the change in the number of employees turned out to be positive and significant. This supports the findings of Reus et al. (2009) as well and Zollo et al. (2008). Furthermore, the number of acquisitions also showed positive significant effect on acquirer performance, except when we only looked at the acquirers with employee growth. This result supports the findings of Nadolska and Barkema (2007) who argue the importance of the frequency of acquisitions.

VIII. Conclusion

related to firm performance, and whether cultural distance matters at all. Beugelsdijk and Maseland (2011) summarize well the weaknesses of the cultural distance concept. First of all, when we look at cultural distance, we have an illusion of symmetry, that is we believe that for country A to invest into country B is the same as vica versa. We also believe that cultural distance remains constant over time. Scholars also tend to have the illusion of linearity, ergo the cultural distance affect all the phenomena of MNE activity the same way. Researchers concentrate on the effect of cultural distance, while the effect of cultural distance should be considered as a part of a broader picture, also including geopolitical distance, market size etc. When researchers use cultural distance they assume that every aspect of it matters equally, whereas in some cases this is not true. Moreover, when using national cultural distance, scholars unwillingly assume that the corporate culture does not differ among countries. Yet, corporate culture might be able to mitigate the effects of high national cultural distance.

After all, only a few studies have shown that cultural distance is directly related to FDI flows or any MNE activity. Beugelsdijk and Maseland (2011) argue that the impact of cultural distance on trade and FDI cannot be studied in isolation because trade and FDI are interrelated. Nevertheless, my research did not find any significance of trade openness. According to Navaretti et al. (2006) we would expect other results. They point out that acquisitions may serve as substitutes for trade in case of high trade costs. In the results of this study though, trade openness shows no significance. I must address though, that my study does not measure the effect of trade openness on the number or frequency of acquisitions, which would be a more appropriate to research in the latter case.

IX. Implications for future research

This study presents an overview of the relation between MNE performance and cultural distance, though it has some limitations and suggests future research. One weakness of the study is the over-representation of U.S. firms. Though most of the FDI activity originates from the U.S., future research should focus on using a more diverse sample. Furthermore, the sample of 197 firms is not broad enough to draw general conclusions for every aspect of cross-border acquisitions. The paper focused on acquirer firms from western, advanced countries acquiring over large cultural distances. As the results suggested, large cultural distances might not matter that much. Future research should also include acquirers from developing countries and find out the effect of cultural distance on their activities as well.

Future research should focus on the variance of cultural distance between the acquirer and its targets as well. If the variance of cultural distance remains low, it might indicate that firms rely on learning processes. On the other hand, average cultural distance does not show the level of variation between the targets.

In addition, the acquirer performance was measured in ROA, which is a long-term measurement, and other methods might end up with different results. However, from the control variables used in this study turned out that it is in line with the former literature. Despite the number of acquisitions turned out to be significant when looking at the whole sample, future studies should measure whether the frequency of acquisitions matters. That is, the number of acquisitions per a certain time period.

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