CONTENT
Abstract ... 2
1.Introduction ...3
2. Theoretical Background ... 5
2.1 Literature Review ... 5
Culture Distance and Culture Measurement ... 5
Culture Distance and M&A Performance ... 9
2.2 Problem Statement and Research Question ... 13
Abstract
The relationship between culture distance and Post M&A performance has attracted scholars and consulting companies’ attention recently. However, as of yet the results are still unclear. Some scholars believe that culture distance can create a clash when two organizations merge together. Others believe that culture diversity can provide a routine pool for organizational learning activities and specialization which will enhance the post M&A performance. Therefore, the contributions of this paper in the field of Business Science include: (1) Empirical results that confirm culture distance as being closely related to company business performance after M&A; (2) The regression results also identify that when culture diversity is high, culture distance will hinder the company’s future business after M&A. Meanwhile, if culture diversity between the acquiring and acquired company is low, it will then be positive to post M&A performance (based on the different levels of national culture diversity of the acquiring and acquired company, I sort the original database into two groups).
Key Words
1.Introduction
reports by consulting firms have also confirmed that from one half to two-thirds of M&As do not come up to the expectations of those whom are transacting them and many resulted in divestitures (Schweiger 2003).
Recently, a series of research indicated that the culture gap between acquiring and acquired companies is relevant to cross-border M&A performance. (Morosini, 1998; Harbir Singh, 1998; Ester Barinaga, 2007; Deepak K. Datta, 2001) Different from prior study which only focuses on the corporation’s culture diversity, Piero Morosini (1998) points out that in the context of a cross-border acquisition, national cultural distance represents distance in the norms, routines and repertoires for organizational design, new product development, and other aspects of management that are found in the acquirer’s and the target’s countries of origin. Furthermore, all these routines and repertoires are shown to be critical to acquisition performance, and vary in post-acquisition performance significantly across countries that are directly associated with the national cultural distance between them (Jemison and Sitkin, 1986; Hofstede, 1980). This is the case with routines and repertoires related to innovation effectiveness (Shane, 1993), degree of entrepreneurship (McGrath et al., 1992), decision-making practices (Kreacic and Marsh, 1986; Bourgoin, 1989), and the power and control structures of an organization (Brossard and Maurice, 1974).
The structure of this article will be organized as following. After the introduction, I will illustrate relevant theoretical backgrounds and provide a literature review. Afterwards my formal research question will be put forward. This is then followed by the methodology which will be used in this research. Finally, the last part contains the results and conclusion of this paper.
2. Theoretical Background
2.1 Literature Review
Culture Distance and Culture Measurement
National cultural distance is defined as the degree to which the cultural norms in one country are different from those in another country (Kogut and Singh, 1988). In their article about national culture diversity and entry modes choice, similar to that of Hofstede’s theory, they estimated national cultural distance as a composite index which is composed of four dimensions: Power distance, uncertainty avoidance, masculinity/femininity, and individualism. Following this approach I will measure the national culture distance between acquiring and acquired companies using Hofstede’s (1980) four culture dimensions.
In the latter 20th century, a series of surveys were conducted by Dutch writer Gerard
is an introduction into the four criterions to measure this common culture diversity (Table 1):
Table 1 Description of Hofstede’s Culture Dimension
Culture Dimensions
Power Distance Index (PDI)
PDI is the extent to which the less powerful members of organizations and institutions (like the family) accept and expect that power is distributed unequally. This represents inequality (more versus less), but defined from below, not from above. It suggests that a society's level of inequality is endorsed by the followers as much as by the leaders. Power and inequality, of course, are extremely fundamental facts of any society and anybody with some international experience will be aware that 'all societies are unequal, but some are more unequal than others'.
Individualism (IDV)
unquestioning loyalty. The word 'collectivism' in this sense has no political meaning: it refers to the group, not to the state. Again, the issue addressed by this dimension is an extremely fundamental one, regarding all societies in the world.
Masculinity (MAS)
MAS versus its opposite, femininity, refers to the distribution of roles between the genders which is another fundamental issue for any society to which a range of solutions are found. The IBM studies revealed that (a) women's values differ less among societies than men's values; (b) men's values from one country to another contain a dimension from very assertive and competitive and maximally different from women's values on the one side, to modest and caring and similar to women's values on the other. The assertive pole has been called 'masculine' and the modest, caring pole 'feminine'. The women in feminine countries have the same modest, caring values as the men; in the masculine countries they are somewhat assertive and competitive, but not as much as the men, so that these countries show a gap between men's values and women's values.
Uncertainty Avoidance Index (UAI)
situations are novel, unknown, surprising, or different from usual. Uncertainty avoiding cultures try to minimize the possibility of such situations by strict laws and rules, safety and security measures, and on the philosophical and religious level by a belief in absolute Truth; 'there can only be one Truth and we have it'. People in uncertainty avoiding countries are also more emotional, and motivated by inner nervous energy. The opposite type, uncertainty accepting cultures, are more tolerant of opinions different from what they are used to; they try to have as few rules as possible, and on the philosophical and religious level they are relativist and allow many currents to flow side by side. People within these cultures are more phlegmatic and contemplative, and not expected by their environment to express emotions.
Source: http://www.geert-hofstede.com/
Piero Morosini, Scott Shane and Harbir Singh (1998) state in their article about culture distance and post M&A performance that the reasons why we can follow Hofstede’s research are:
Firstly, the validity and reliability of Hofstede’s (1980) national cultural scores have been identified by many other researchers (Morosini and Singh 1994; Shane 1992; Kogut and Singh 1988). Secondly, there are significant advantages to using Hofstede’s scores as a measure of national cultural distance over administering a questionnaire on national culture to the managers of the companies in the sample. Thirdly, the use of Hofstede’s scores avoids the problem of common method variance in which the same individuals answer questions about firm performance in the same way as answering questions about national culture (see Shane, 1995 for a discussion of the problem). Fourthly, the use of Hofstede’s scores avoids the problem of retrospective evaluation of national culture. Since people tend to be ethnocentric and prefer similarity (Hofstede, 1980), if surveyed after the acquisition, members of the acquiring firms might “remember” the national culture of target firms as being more similar than they really were. The design of this study avoids the problem of retrospective rationalization by using national culture scores from a source external to the sample and not dependent on the memory of the respondents. (Piero Morosini, Scott Shane and Harbir Singh, 1998)
Therefore, following their study, in this research I will utilize Hofstede’s four dimensions theory to measure national culture distance.
Culture Distance and M&A Performance
cultures “collide” during the post-acquisition period (Jemison and Sitkin, 1986; Buono et al., 1985). Firstly, this is because higher levels of culture distance will lead to a higher degree of conflict during the daily post-acquisition integration time period (Jemison and Sitkin, 1986). Meanwhile, Barinaga and Ester (2007) argue that “Although there is a scarcity of literature on multinational group work, studies concur in maintaining that national culture influences group behaviour, different cultures resulting in different patterns of group interaction (Cox et al., 1991; Earley, 1993). Secondly, performances of national homogeneous workgroups differ if compared to heterogeneous ones. Such differences are acknowledged in terms of individual effectiveness: group productivity, creativity, ability to make decisions, group cohesiveness, etc. (see Bochner & Hesketh, 1994; Kirchmeyer & Cohen, 1992; Maznevski, 1994; Maznevski & Chudoba, 2000; Milliken & Martins, 1996; Thomas, 1999; Watson et al., 1993).” Furthermore, all these common characters for national culture difference will bring inter-group bias which leads to negative group outcomes (Pelled, 1996). Additionally, Thomas (1999) argues that cultural differences inherent in a multinational workgroup may be so distracting as to inhibit its potential benefits.
Meanwhile as in broader organizational contexts, people find that organizational culture is an important “internal-variable” in M&A situations. (Smircich, 1983) It means that culture is critical in the configuration of a total organizational system, influencing the organization’s effectiveness in its environment (Pablo, 1994). Thus, cultural integration and cultural compatibility are commitment, satisfaction, productivity, and longevity within a group or organization (O'Reilly et al. 1991; Holland 1985, and Kilmann et al. 1985). This is because individuals tend to select groups that they perceive as having values similar to their own, while trying to avoid dissimilar others (Schneider and Goldstein 1995). When a good fit happens, a psychological bond is created that is not easily broken (Ashforth and Mael 1989). For Hambrick and Cannella (1993), culture fit can only be observed when two different organizational cultures meet together. This is typical for M&As because they are always considered as an integration process that is both physical and psychological.
On the contrary, besides the dark side of culture distance effectiveness, some scholars also notice some advantages. For example, an empirical research conducted by Piero Morosini, Scott Shane and Harbir Singh illustrate to us that national culture distance may also enhance post M&A performance by providing access to the target's and/or the acquirer's diverse set of routines and repertoires embedded in national culture (Piero Morosini, Scott Shane and Harbir Singh,1998). Inside this article, authors explain that:
advantage, they must not be easily imitated by other firms. This is the case for
Organizational routines developed in interaction with a firm’s history and institutional environment (Collis, 1991). However, firms that operate on a multinational scale may need to possess a diverse set of routines and repertoires if they are to compete in a diverse world. In an uncertain environment, it is difficult for managers to know exactly what routines and repertoires will provide sustainable competitive advantage and performance over time. Given the difficulty of forecasting valuable future routines and repertoires, it may be in a multinational firm’s best interest to access a relatively large and diverse pool of routines and repertoires, thus increasing the probability that it will possess those that prove to be valuable in the future. Cross-border acquisitions provide a mechanism for accessing valuable routines and repertoires embedded in other national cultures without having to follow the developmental path that leads to them (Jemison and Sitkin, 1986). Acquisitions across national cultures could enhance firm performance by providing access to a valuable pool of critical routines and repertoire previously not available to the firm” (Ghoshal, 1987).
cultural values than to have them carry out tasks in ways which are not compatible with their cultural beliefs (Shane, 1993).
2.2 Problem Statement and Research Question
Arising from previous literature study, it becomes clear that culture clash in M&As have been mentioned frequently from both practitioners and academics (Cartwright and Cooper 1993; Chatterjee et al. 1992(a); Weber and Shenkar 1996, and Davis 1968). While the limitations of these studies still exist:
1. Most of them are based on practitioners and consultants’ observations, with little theoretical or empirical support (Barrett 1973; Davis 1968, and Levinson 1970). 2. The empirical work always focuses on single case study or concentrates on some specific industries or countries. (Buono and Lewis 1985; Graves 1981,
Sales and Mirvis 1984)
3. The results of previous research are contradictory. Some of them confirm that culture distance will weaken down post M&A performance by different norms and higher transaction costs when two organizations combine together. Oppositely, a recent study by Piero Morosini, Scott Shane and Harbir Singh shows us that culture distance can also have a positive influence on post M&A performance.
Originally the study on “culture clash” in M&As always focused on what happens between companies with a significant culture distance such as Asian and west European companies, or an M&A between companies that are not in the same national culture cycle. (W. Richard Frederick, 1994; Mansour Javidan, Giinter K. Stahl, Felix Biodbeck, and Celeste P.M. Wilderom, 2005). Meanwhile the database of the study by Piero Morosini, Scott Shane and Harbir Singh (1998), only concentrates on western countries. Hence, this is perhaps the reason why they can get opposite results from previous studies.
post merger and acquisition performance, and follow people’s previous research. I suppose that minimal culture diversity is positive to M&A performance, but that significant culture diversity will be negative to M&A performance.
As such, two hypotheses for this study can be expressed as follows:
Hypothesis 1: Low level culture diversity will be positive to post M&A performance
Hypothesis 2: High level culture diversity will be negative to post M&A performance
3. Research Methodology
3.1 Sample Scale
Based on the report of the UNCTAD 2007 (United Nations Conference on Trade and Development) there are 987 M&As that have happened from 1995 to 2005 (trade value of over 1 billion US dollar) all around the world. More than 1270 companies, belonging to 37 countries, have been involved in these M&As activities. Therefore, the target sample of my research is these 1270 companies. All the detailed information is available on the official website of the UNCTAD.1
Furthermore, I will sort all these cases into two groups which are based on the nationality of acquiring and host Company. When the nationality of acquiring and Host Company both belong to the Anglo-Saxon culture cycle (The United States, The United Kingdom, Canada and Australia), then it will be sorted into group 1(Appendix 1). Meanwhile, if the target company’s nationality does not belong to the Anglo-Saxon culture cycle, and the acquiring company is inside the Anglo-Anglo-Saxon cycle, then
this company will be put into group 2 (Appendix 2). The reasons why I chose Anglo-Saxon culture as the standard of my research:
Firstly, based on the 1995-2005 database of UNCTAD, over 79% cross border M&A cases are conducted inside nations which belong to the Anglo-Saxon culture cycle. Secondly, compared with India or the Philippines, the market of America and the UK showed more health and transparency. The data will be easier to acquire and also more reliable. Finally, the precondition to use stock price as a measure for performance of the company is that the market should be a perfectly competitive market2. Comparing with other stock markets such as China and India, all
Anglo-Saxon countries’ markets are more suitable for this research.
Thus, for this paper there will be 231 M&A cases in group1 and 117 in group2. However, because the data of some companies are unavailable and some companies have been merged by other corporations or became bankrupt or are inactive now, my final database will contain 124 cases in group 1 and 79 in group 2.
With regards to group 1, graph 1 shows us that from 1995 to 2005, more than 50% of M&A cases were concentrated between the United States and the United Kingdom. Meanwhile, because of the geographic factor and free trade agreement between America and Canada, over 30% of M&As have been conducted within these two counties. The number after the nationality means the culture distance between acquiring and target countries. Obviously, the culture between the United States and Australia is most similar (culture distance = 6.557), whilst the diversity between the United Kingdom and New Zealand is the highest (culture distance = 23.000).
Graph 1 Nationality Constituent (group 1)
The situation in group 2 is a little bit different from the first graph. Graph 2 tells us that when M&A cases, acquiring companies outside the Anglo-Saxon cycle, are only from 3 countries (Australia, United Kingdom and United States). Among these 3 countries, nearly 50% are American and over 30% are British.
Graph 2 Nationality Constituent for Acquiring Companies (Group 2)
(9 acquiring countries and 20 target countries) have been involved into these M&A actions from year 1995 to year 2005. The table 1 below shows us all these 20 target countries for group 2.
Table 1 Nationality for Target Companies (group2) Nationality Number Turkey 1 Switzerland 1 Spain 3 Puerto Rico 1 Philippines 1 Norway 2 Netherlands 9 Mexico 5 Luxembourg 1 Japan 9 Italy 7 Hong Kong 3 Germany 18 France 5 Denmark 3 Czech Republic 1 Colombia 2 China 3 Brazil 2 Belgium 1
In Terms of culture distance in group 1 and group 2, United States and Germany’s cultures are most similar to each other (Culture distance= 31.270). Compared with them, culture distance between United Kingdom and Colombia is 93.972 which is the highest difference of all these 20 countries.
3.2 Dependent Variable
countries. Hence there are two research approaches in recent M&A performance studies. One approach is to employ share price data to establish the distribution of gains and losses to shareholders. The other approach is to focus on the profitability of company studies based on the analysis of accounting based data. These research tools have attempted to assess the economic impact of acquisitions by testing for changes in profitability of the combined firm. (T. Mallikarjunappa and Panduranga Nayak, 2007)
The first approach has the advantage of ease in data collection and analysis. Furthermore, compared with accounting based data, stock price can represent the company’s performance more comprehensively. Meanwhile, the disadvantage of this method is that the stock price can easily be influenced by the outside environment and closely rely on the situation of home country’s stock market. Therefore, this approach can only work properly under the assumption that stock prices can exactly represent the performance of the company. With regards to this paper, due to the matured stock market and transparent information exchange issuing activities in Anglo-Saxon countries, the stock price of companies are representative of their business performance.
The stock prices of each company will be retrieved from the DataStream database, spanning the years 1995-2007. Considering the differences of these stock markets and the exchange rate fluctuation from 1995-2005, I will employ the change rate of stock prices rather than the direct stock price change.
: Stock Price’s Change Rate
3.3 Independent Variables
Dutch writer Geert Hofstede introduced a model in his 1980s cross culture study. Based on his study, the culture distance can be measured by five dimensions which are:
Power Distance; this dimension relates to the degree of equality/inequality between people in a particular society.
Individualism: this dimension focuses on the degree to which a society reinforces individual or collective achievement and interpersonal relationships.
Uncertainty Avoidance; this dimension concerns the level of acceptance for uncertainty and ambiguity within a society.
Masculinity; this dimension pertains to the degree societies reinforce, or do not reinforce, the traditional masculine work role model of male achievement, control, and power.
Long-Term Orientation: people with Long Term Orientation are thrift and perseverance; values associated with Short Term Orientation are respect for tradition, fulfilling social obligations, and protecting one's 'face'.3
The Hofstede Score, which values 55 countries on his five dimensions, is available on his personal website4. In my study however, I will only employ the first 4 dimensions
because the fifth dimension is still incomplete. Following T. Mallikarjunappa and Panduranga Nayak’s study, the final culture distance will be calculated as:
Where:
: Culture Distance between acquiring country j and host country k.
: Hofstede’s score: i means culture dimension, j means acquiring company’s nationality
Hofstede’s score: i means culture dimension, k means Host Company’s nationality
3.4 Control Variables
Change Rate of Stock Index: As we know, the company's stock price is sensitive to
all volatility from the outside environment. All this external information will cause people to overreact and thus lead to the change of company’s stock price. Khelifa Mazouz (2008) argued that several empirical studies on short-term price changes or “shocks” show that investors overreact to the arrival of new information about stock prices. Specifically, Bremer and Sweeney (1991) find that large negative price changes give rise to overreactions in U.S. stocks. Bowman and Iversion (1998) also find evidence for the overreaction hypothesis following large weekly price changes in New Zealand stocks, whilst Ferri and Chung-Ki (1996) observed a similar pattern following large one day price changes in the S&P500 index. Meanwhile, a large number of literatures have begun to explain stock market reactions to changes in the stock index. These include the price pressure hypothesis (Harris and Gurel, 1986; Woolridge and Ghosh, 1986; Lamoureux and Wansley, 1987; Lynch and Mendenhall, 1997) and the downward-sloping demand curve hypothesis (Shleifer, 1986; Arnott and Vincent, 1986; Dhillon and Johnson, 1991; Beneish and Whaley, 1996; Lynch and Mendenhall, 1997; Morck and Yang, 2001); Hence, In order to diminish the influence of the outside environment, I introduce 4 different well known stock indexes (S&P 100, S&P AXE, S&P TSX and FTSE 100)5 into my study as control
change rate instead of a direct stock index change.
: Stock index’s Change Rate
: Stock Index when M&A conducted
: Stock Index 2 years after M&A
j: Nationality
3.5 Time lagging
As the results of M&As can’t be shown immediately, the time lagged after M&As should be added into consideration. In this paper I measure performance following two years after M&A activities. The reasons are:
Firstly, a large amount of literature maintains that the first two years after an acquisition are essential to its performance (Jemison and Sitkin, 1986; Balloun and Gridley, 1990). Secondly, the process of acquisition can’t be finished immediately. Two years period is adequate time for the two companies to merge (Jemison and Sitkin, 1986).
3.6 Research Model
to post M&A performance. So, my first model can be shown as:
Y: Business performance (change rate of stock price) when culture distance is low : Culture distance (CD)
: Control variable
Coefficient
Consequently, when national culture diversity between acquiring and acquired companies is high, the influence from culture diversity will be negatively linear to performance. Hence the second model should be:
Y: Business performance (change rate of stock price), when culture distance is high : Culture distance (CD)
: Control variable
Coefficient
4. Results
Statistical Analysis
Table 2 Descriptive Statistics Mean S.D. CD CR SIC CD 14.189 3.1519 1.0 CR 2.1239 59.5910 0.101 1.0 SIC 1.5108 30.3386 0.064 0.155 1.0 Key:
CD: National Culture Distance from acquiring and acquired company
CR: 2 years Stock price’s change rate before and after M&A
SIC: 2 years stock index’s change rate before and after M&A
Table 3 Descriptive Statistics Mean S.D. CD CR SIC CD 56.6061 19.8926 1.0 CR -8.812 42.0916 -0.232 1.0 SIC 7.6396 27.9928 -0.017 0.377 1.0 Key:
CD: National Culture Distance from acquiring and acquired company
CR: 2 years company’s stock price’s change rate before and after M&A
SIC: 2 years stock index’s change rate before and after M&A
The table2 and table 3 both show us that the highest correlation among all these variables is that between company’s stock price’s change rate and stock index’s change rate before and after M&A. This result is coincide with my former suppose. Meanwhile, I also notice that the correlation coefficient between culture distance and company stock price change rate in table 2 is positive but negative in table 3. This phenomenon identify my previous suppose that high culture distance will block company performance after M&A and low culture distance will enhance company performance after M&A.
After that I also conducted tests about heteroskedasticity and autocorrelation to ensure the robustness of the regression model. None of these problems were found here in the data. Plots of the independent variable against the dependent variable indicated that a linear model was the suitable model to fit the data.
The results of the regression analyses for group 1 and group 2 are shown in Table 4 and Table 5 respectively.
Table 4
Result of Regression Analyses
Variables Coefficient T-Value
Culture Distance 3.148 2.006
Adjust R square 0.024
*Significant at the p< .05 level or better in a two-tailed test
Based on the result I acknowledge that the independent and dependent variables are correlated. But none of the control variables are correlated to the dependent variable in group 1 (Sig.> 0.05). Hence, in the regression, I only test the relationship between culture distance and stock price change rate by using enter/remove way (independent and dependent variable for this model). As can be seen in table 4, the sig level is 0.047<0.05 and the B value is 3.148 indicate that culture distance had s positive effect on post-acquisition performance in group 1. In other words low culture diversity can enhance acquiring company’s performance. This result is coincide to the study by Piero Morosini, Scott Shane and Harbir Singh (1998).
The model can be shown as:
Y: Business performance (change rate of stock price) when culture distance is low : Culture distance (CD)
Coefficient
Table 5
Result of Regression Analyses
Variables Coefficient T-Value
Culture Distance -0.476 -2.185
Stock Index’s change
rate 0.562 3.624
Constant 13.868
Adjust R square 0.172
*Significant at the p< .05 level or better in a two-tailed test
However, when culture distance is high the result is opposite. First of all the result illustrates that the stock price’s change rate is affected by culture distance. (Sig. = 0.04<0.05). Meanwhile, the result (Sig. = 0.01 between Stock index’s change rate and change rate of each company’s stock price) also indicate that the company’s stock price can
addition, there is no correlation between Stock_index_changrate and culture distance (Sig. = 0.881). Therefore, it is certain that the stock index change rate is suitable for this study and thus can be introduced as control variable. The most important information contain in table 5 is that B value for culture distance in group 2 is -0.476. It means that high culture distance had negative effect to post-acquisition performance. Hence our model can be presented as:
: Change rate of Company’s stock price : Culture distance (CD)
: Change rate of national stock market index
Coefficient
5. Conclusion
Former research maintained that national culture distance between countries has in turn been linked to significant differences between these countries’ norms, routines and repertoires (Hofstede, 1980; Kogut and Singh, 1988) The first contribution of this paper is that I provide an empirical support to scholars’ research and confirmed that culture distance is closely related to companies’ post M&A performance (Sig=0.047 with group1 and Sig=0.040 with Group2).
(Hypothesis 2). The results from the regression confirmed both hypotheses (B=3.148 with low culture distance group and B=-0.476 with high culture distance group). It indicates that when culture diversity is high, culture will be negative to post M&A performance. The linear model is reasonable for both group 1 and group 2.
Finally, as regarding the limitation of this research:
Firstly, this research only concentrates on countries which belong to the Anglo-Saxon culture cycle, which means that the next step we should expand this research into other countries and other culture cycle. Secondly, a fifth dimension has been recently added into Hofstede’s research names as Long-term Orientation. However because the study about this part is still in progress, I wasn’t able to collect enough data for all target countries in my study. Thirdly, there might be some problems existing in Hofstede’s culture dimension theory. I noticed that some people still criticize his findings and one of the most critical voices comes from Dr. Brendan McSweeney.
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Appendix 1
Company Name and Nationality for Group 1 Acquiring Companies Name Nationality of Acquiring companies Industry Name of Target companie s Nationali ty of Target Companies Year Owens-Illinois United States
Glass,plastic containers BTR PLC- Australia 1998 AEP Resources
I
United States
Electric utility Citipowe Australia 1998 Newmont Mining United
States
Gold ores Normandy Australia 2002 News Corp Ltd Australia Printing, Publishing,
and Allied Fox/Libe United States 1999 Foster 抯 Brewin
Australia Malt beverages Beringer United States
2000 News Corp Ltd Australia Newspapers: publishing,
or publis
Chris-Cr United States
2001 News Corp Ltd Australia Newspapers: publishing,
or publis Hughes E United States 2003 Southern Compan United States South We United Kingdo 1995 Avon Energy (GP United States Midlands United Kingdo 1996 Coca Cola Enter United States Coca-Col United Kingdo 1996 Merrill Lynch & United States
Investment & commodity firms, dea Mercury United Kingdo 1997 EI du Pont de N United States
Chemicals and allied products Imperial United Kingdo 1997 Caterpillar Inc United States
Machinery Perkins United Kingdo
1997 Xerox Corp. United
States
Computer and office equipment
Rank Xer United Kingdo 1997 Texas Utilities United States
Electric and gas utility Energy G United Kingdo
1998 Coca-Cola Co United
States
Food and beverages Cadbury United Kingdo
1998 Enron Corp United
States Own,operate gas pipelines Wessex W United Kingdo 1998 Texas Utilities United States
Electric and gas utility Energy G United Kingdo 1998 Marsh & McLenna United States
Insurance Sedgwick United Kingdo
1998 Edison Mission United
States
Electric, Gas, and Water Distribu
PowerGen United Kingdo
1999 AES Corp United
States
Electric, Gas, and Water Distribu
National United Kingdo
States passenger car Kingdo Chase Manhattan United States National commercial banks Robert F United Kingdo 2000 AOL Time Warner United States Television broadcasting stations
IPC Grou United Kingdo 2001 Aquila Inc(Util United States Combination utilities, nec
Avon Ene United Kingdo
2002 Goodrich Corp United
States
Guided missiles and space vehicle TRW Aero United Kingdo 2002 United Technolo United States
Aircraft engines and engine parts
Chubb PL United Kingdo
2003 Carnival Corp United
States
Deep sea transportation of passen
P&O Prin United Kingdo 2003 General Electri United States
Power, distribution, and specialt Amersham United Kingdo 2004 Songbird Acquis United States
Investors, nec Canary W United Kingdo
2004 Cendant Corp United
States
Real estate agents and managers Gulliver United Kingdo 2005 Honeywell Inter United States
Motor vehicle parts and accessori Novar PL United Kingdo 2005 Tomkins PLC United Kingdom Gates Ru United States 1995 Cadbury Schwepp United Kingdom Dr. Pepp United States 1995 Farnell Electro United Kingdom Premier United States 1996 Amvescap PLC United Kingdom
Investment & commodity firms, dea Chancell United States 1997 Reed Elsevier P United Kingdom
Publishing Matthew United States
1998 Amvescap PLC United
Kingdom
Financial services Chancell United States 1998 British Petrole United Kingdom
Petroleum expl/ref/dist Amoco Co United States
1998 Scottish Power United
Kingdom
Electric utility PacifiCo United States 1998 British Telecom United Kingdom
Telecommunications AT&T-Wor United States 1998 National Grid C United Kingdom
Electric utility New Engl United States 1998 British Telecom United Kingdom
Telecommunications Concert United States 1998 Cable & Wireles United Kingdom Telecommunications services
MCI Comm United States
1998 Pearson PLC United
Kingdom
Publishing Simon & United States 1998 General Electri United Kingdom
Electronics Tracor I United States 1998 Stagecoach Hold United Kingdom Transportation and Shipping (exce Coach US United States 1999 Scottish Power United
Kingdom
Electric, Gas, and Water Distribu
PacifiCo United States
1999 Vodafone Group United
Kingdom
Telecommunications AirTouch United States
1999 Royal & Sun
All
United Kingdom
Insurance Orion Ca United States 1999 HSBC Holdings P United Kingdom
WPP Group PLC United Kingdom
Advertising agencies Young & United States 2000 National Grid G United Kingdom
Electric services New Engl United States
2000 BP Amoco PLC United
Kingdom
Petroleum refining ARCO United States
2000 BP Amoco PLC United
Kingdom
Petroleum refining Vastar R United States 2000 Cadbury Schwepp United Kingdom
Candy and other confectionery pro Snapple United States 2000 Unilever PLC United Kingdom
Creamery butter Bestfood United States
2000 Rexam PLC United
Kingdom
Sanitary paper products American United States 2000 SmithKline Beec United Kingdom
Medicinal chemicals and botanical Block Dr United States 2001 Reed Elsevier P United Kingdom Periodicals: publishing, or publi Harcourt United States 2001 National Grid G United Kingdom
Electric services Niagara United States 2002 HSBC Holdings P United Kingdom
Banks, non-US chartered Househol United States 2003 Cadbury Schwepp United Kingdom
Candy and other confectionery pro Pfizer I United States 2003 Associated Brit United Kingdom
Bread and other bakery products, Burns Ph United States 2004 WPP Group PLC United Kingdom
Advertising agencies Grey Glo United States 2005 Shire Pharmaceu United Kingdom Pharmaceutical preparations Transkar United States 2005 Union Pacific R United States
Petroleum expl/ref/dist Norcen E Canada 1998 Bowater Inc United
States
Paper and lumber Avenor I Canada 1998 Weyerhaeuser
Co
United States
Wood Products, Furniture and Fixt MacMilla Canada 1999 Electronic Data United States
Business Services MCI Syst Canada 1999 Uniphase Corp United
States Electronic and Electrical Equipme JDS Fite Canada 1999 Smurfit-Stone C United States
Paperboard mills St Laure Canada 2000 Anadarko
Petrol
United States
Crude petroleum & natural gas Berkley Canada 2001 Devon Energy Co United States
Crude petroleum & natural gas Anderson Canada 2001 Burlington Reso United States
Crude petroleum and natural gas
Canadian Canada 2001 Newmont Mining United
States
Gold ores Franco-N Canada 2002
EI du Pont de N United States Industrial inorganic chemicals, n DuPont C Canada 2003 General Dynamic United States
Aircraft GM Defen Canada 2003
RR Donnelley & United States Commercial printing, lithographic Moore Wa Canada 2004 GE Commercial F United States Personal credit institutions Bombardi Canada 2005 Kinder Morgan I United States
Natural gas transmission and dist Terasen Canada 2005 Kohlberg Kravis United States
Investors, nec Masonite Canada 2005 Weatherford
Int
United States
Oil and gas field machinery and e
Precisio Canada 2005
of States The Thomson
Cor
Canada West Pub United
States
1996 Placer Dome
Inc
Canada Mining Getchell United
States
1998 Canadian
Nation
Canada Railroad services Illinois United States
1998 Quebecor
Printi
Canada Printing, Publishing, and Allied World Co United States 1999 Placer Dome Inc
Canada Mining Getchell United
States
1999 Thomson Corp Canada Newspapers: publishing
or publish
Primark United States
2000 Thomson Corp Canada Newspapers: publishing,
or publis
Harcourt United States
2001 Sun Life Finl
S
Canada Life insurance Keyport United States
2001 Barrick Gold
Co
Canada Gold ores Homestak United
States
2001 Domtar Inc Canada Paper mills Georgia- United
States
2001 Canadian
Nation
Canada Railroads, line-haul operating Wisconsi United States 2001 George Weston L
Canada Bread and other bakery products, Bestfood United States 2001 Royal Bank of C
Canada Commercial banks Centura United States
2001 Royal Bank of
C
Canada Commercial banks Dain Rau United States 2001 Cinram Internat Canada Phonograph records,prerecorded au Warner M United States 2003 TransCanada Cor
Canada Electric services Gas Tran United States
2004 Manulife
Financ
Canada Life insurance John Han United States
2004 EnCana Corp Canada Crude petroleum &
natural gas
Tom Brow United States
2004 Nexen Inc Canada Crude petroleum &
natural gas EnCana(U United Kingdo 2004 Toronto-Dominio
Canada Banks Banknort United
States 2005 Standard Charte United Kingdom
Investment advice ANZ Grin Australia 2000 Billiton PLC United
Kingdom
Miscellaneous metal ores Reynolds Australia 2001 BHP Ltd Australia Steel works, blast
furnaces, and Billiton United Kingdo 2001 Origin Energy L
Australia Electric services Contact New Zealand 2004 Woolworths Ltd Australia Variety stores Foodland New Zealand 2005 Tesco PLC United
Kingdom
Retail trade-general merchandise
Associat Ireland 1997 Vodafone Group United
Kingdom Radiotelephone communications Eircell Ireland 2001 Royal Bank of S United Kingdom
Banks First Ac Ireland 2004
Billiton PLC United Kingdom
Miscellaneous metal ores, nec
Rio Algo Canada 2000 Amdocs Ltd United Kingdom Computer programming services Solect T Canada 2000 Amvescap PLC United Kingdom
Investment advice Trimark Canada 2000 British
America
United Kingdom
GlaxoSmithKlin e United Kingdom Pharmaceutical preparations ID Biome Canada 2005 International P
Canada Canary W United
Kingdo
1995 Petro-Canada Canada Crude petroleum and
natural gas
Veba Oil United Kingdo 2002 International P United States
Carter H New Zealand 1995
Shell Overseas United Kingdom
Petroleum bulk stations and term
Fletcher New Zealand 2001
Appendix 2
Company Name and Nationality for Group 2
Name of Acquiring Companies National ity of Acquirin g Companie s
Industry Name of Target Companies Nationali ty of Target Companies Year European Directories SA
Australia Investors, nec Yellow Brick Road Netherlands 2005 Vodafone Group PLC United
Kingdom
United Kingdom Oskar Mobil as Czech Republic
2005 SABMiller PLC United
Kingdom
Malt beverages Bavaria SA Colombia 2005 SABMiller PLC United
Kingdom
Malt beverages Bavaria SA Colombia 2005 GS Capital Partners
LP
United States
Investors, nec Pirelli SpA-Cables & Sys Div
Italy 2005 eBay Inc United
States
Information
retrieval services
Skype Technologies SA Luxembourg 2005 Colony Capital LLC United
States Real estate investment trusts Accor France 2005 Mohawk Industries Inc United States
Carpets and rugs Unilin Holding NV Belgium 2005 GE Consumer Finance United
States Short-term business credit insti Turkiye Garanti Bankasi AS Turkey 2005 Yahoo! Inc United
States
Information
retrieval services
Alibaba.com Corp Hong Kong, China 2005 Developers Diversified Realty United States Real estate investment trusts Caribbean Property-PR Assets Puerto Rico 2005 HSBC Holdings Plc United Kingdom
Banks BoCOMM China 2004
Blackstone Group LP United States
Investors, nec Celanese AG Germany 2004 Blackstone Group LP United
States
Investors, nec WCM-Residential Ppty Germany 2004 GE Capital Real Estate United States Lessors of real property, nec Sophia SA France 2004
Procter & Gamble Co United States
Soap & other detergents, except
Procter & Gamble-Hutchison Ltd China 2004 British American Tobacco PLC United Kingdom
Cigarettes Ente Tabacchi Italiani SPA
Italy 2003 Procter & Gamble Co United
States
Soap & other detergents, except
Procter & Gamble Co United States
Soap & other detergents, except Wella AG Germany 2003 State Street Corp,Boston,MA United States Offices of bank holding companie Deutsche Bank-Securities Div Germany 2003 Blackstone Group LP United
States
Investors, nec Deutsche Bank-Real Estate(51) Germany 2003 General Electric Co{GE} United States Power, distribution, and special
Instrumentarium Oyj Finland 2003 UnitedGlobalCom Inc United
States
Cable and other pay television s
UGC Europe Inc Netherlands 2003
AIG United
States
Fire, marine, and casualty insur
GE Edison Life Insurance Co
Japan 2003 Amcor Ltd Australia Setup paperboard
boxes Schmalbach-Lubeca-PET Assets Germany 2002 Imperial Tobacco Group PLC United Kingdom Cigarettes Reemtsma Cigarettenfabrik GmbH Germany 2002 BP PLC United Kingdom
Petroleum refining VEBA Oel AG (E.On AG) Germany 2002
BP PLC United
Kingdom
Petroleum refining VEBA Oel AG(E.On AG) Germany 2002 Kingfisher PLC United
Kingdom
Hardware stores Castorama Dubois France 2002 HSBC Holdings PLC United
Kingdom
Banks Grupo Financiero Bital SA
Mexico 2002 Ball Corp United
States
Metal cans Schmalbach-Lubeca AG Germany 2002 Morgan Stanley,
Pirelli-Real
United States
Real estate agents and managers Telecom Italia-Real Estate Italy 2002 Bunge Ltd United States
Grain and field beans
Cereol France 2002
Microsoft Corp United States
Prepackaged software Navision A/S Denmark 2002 Telstra Corp
Ltd(Australia)
Australia Telephone communications, except
Pacific Century Cyber-Wireless
Hong Kong, China
2001 Vodafone Group PLC United
Kingdom Radiotelephone communications Swisscom Mobile(Swisscom AG) Switzerland 2001 British Telecommunications PLC United Kingdom Telephone communications, except
Viag Interkom GmbH & Co
Germany 2001 Vodafone Group PLC United
Kingdom Radiotelephone communications Airtel SA(Vodafone Airtouch) Spain 2001 Vodafone Group PLC United
Kingdom
Radiotelephone communications
Japan Telecom,J-Phone Japan 2001 Vodafone Group PLC United
Kingdom
Radiotelephone communications
Japan Telecom Co Ltd Japan 2001 Vodafone Group PLC United
Kingdom
Radiotelephone communications
Japan Telecom Co Ltd Japan 2001 Abbott Laboratories United
States
Pharmaceutical preparations
Knoll AG(BASF AG) Germany 2001 OM Group Inc United
States Industrial inorganic chemicals Degussa Metals Catalysts AG Germany 2001 Prudential Insurance Co United States
Life insurance Kyoei Life Insurance Co
Japan 2001 Citigroup Inc United
States
Commercial banks Banacci Mexico 2001 Vodafone PLC United Kingdom Radiotelephone communications Mannesmann AG Germany 2000 British Sky Broadcasting Group United Kingdom
Vodafone PLC United Kingdom Radiotelephone communications Airtel SA Spain 2000 Standard Chartered PLC United Kingdom
Investment advice Chase Manhattan-HK Banking
Hong Kong, China
2000 Corning Inc United
States Telephone and telegraph apparatu Siemens AG-Optical Fiber,Cable Germany 2000 Corning Inc United
States Telephone and telegraph apparatu Pirelli SpA-Optical Components Italy 2000 General Motors Corp United
States
Motor vehicles and passenger car
Fiat Auto SpA (Fiat SpA)
Italy 2000 Cisco Systems Inc United
States Computer peripheral equipment, n Pirelli-Fibre Optic Operations Italy 2000 Morgan Stanley Real
Estate United States Real estate investment trusts Fonspa-Non-Performing Loans Italy 2000 Reliant Energy United
States
Electric services Energieproduktiebedrij f UNA NV
Netherlands 2000 Intel Corp United
States
Semiconductors and related devic
Giga A/S (NKT Holding) Denmark 2000 General Electric Capital Corp United States Personal credit institutions
Toho Mutual Life Japan 2000 General Motors Corp United
States
Motor vehicles and passenger car
Fuji Heavy Industries Ltd
Japan 2000 AES Corp United
States
Electric services Gener SA Chile 2000 British American
Tobacco PLC
United Kingdom
Tobacco Products Rothmans Intl BV(Richemont)
Netherlands 1999 Reckitt & Colman
PLC
United Kingdom
Pharmaceuticals Benckiser NV Netherlands 1999 National Power PLC United
Kingdom
Electric, Gas, and Water Distrib Union Fenosa Generacion SA Spain 1999 EI du Pont de Nemours and Co United States
Chemicals and Allied Products Herberts Paints(Hoechst AG) Germany 1999 General Electric Capital Corp United States
Credit Institutions Japan Leasing Corp Japan 1999 Imperial Tobacco
Group PLC
United Kingdom
Food and beverages Douwe Egbert Van Nelle Tobacco Netherlands 1998 EI du Pont de Nemours and Co United States Chemicals Herberts Paints(Hoechst AG) Germany 1998 Universal Studios Inc United States
Media PolyGram NV(Philips Electrn) Netherlands 1998 Monsanto Co United States Chemicals Cargill-International Seed Ope Mexico 1998 Coca-Cola Amatil Ltd
Australia Food and kindred products Coca-Cola Bottlers Philippines Philippines 1997 ICI PLC United Kingdom
Chemicals and allied products Quest International,3 Others Netherlands 1997 Amersham International PLC United Kingdom
Chemicals and allied products
Nycomed ASA Norway 1997 BAT Industries PLC United
Kingdom
Tobacco products Cigarrera La Moderna SA
Mexico 1997 Ameritech Corp. United
States Telecommunications TeleDanmark A/S(Denmark) Denmark 1997 Southern Electric Brazil United States Investment & commodity firms, de
Cemig(Minas Gerais) Brazil 1997 Sonat Offshore Drilling United States Transocean Drilling A/ S Norway 1996 General Motors Corporation United States
Rocket Systems Corp. Japan 1996
Colgate-Palmolive United States
Kolynos Brazil 1995
Appendix 3
Culture Index
Nation PDI:Power
Distance Index IDV:Individualism MAS:Masculinity UAI:Uncertainty Avoidance Index LTO:Long-Term Orientation
US vs UK 12.88409873 US vs Australia 6.557438524 US vs Canada 15.03329638 US vs South Africa 27.69476485 US vs Irland 27.23967694 UK vs Australia 42.21374184 UK vs Canada 21.49418526 Uk va South africa 31.25699922 Uk vs Irland 20.34698995 UK vs New 23 UK vs Czech Republic 55.19963768 UK vs Colombia 93.96275858 UK vs China 82.52878286 UK vs Germany 37.20215048 UK vs France 67.40178039 UK vs Chile 95.83840566 UK vs Mexico 88.40248865 UK vs Japan 79.37253933 Uk vs Switzerland 31.41655614 UK vs Spain 71.44928271 UK vs Netherlands 55.83905443 UK vs HK 72.81483365 Uk vs Lux 48.44584606 Australia vs Netherlands 48.13522619 Australis vs Newzenlands 18.16590212 Australia vs HK 75.82216035 Australian vs Philip 82.37718131 South Africa vs Ghana 114
US vs Netherlands 49.77951386 US vs Denmark 58.46366393 US vs mexico 82.14012418 US vs Norway 59.13543777 US vs Brazil 68.69497798 US vs Chile 88.93255872 Canada vs Swazerland 24.35159132
Appendix 4
Stock Index for Each Country Dow Jones South Africa Index
2004 17.02918 2005 18.44123 S&P_AXE_Australia 1996 -11.4176 1997 -23.5473 1998 1.0211 1999 -34.7859 2000 -42.6572 2001 -3.57946 2002 34.70121 2003 44.3542 2004 39.97679 2005 33.09611 S&P_TSX _Canada 1995 23.4517 1996 32.132 1997 20.2132 1998 1.0211 1999 -8.78063 2000 -26.1689 2001 6.017092 2002 40.18933 2003 38.53465 2004 39.60072 2005 22.61374
Resource by DataStream and Yahoo Finance
Appendix 5
Regression Result with Group 1
Regression
Variables Entered/Removedb Model Variables Entered Variables
Removed
Method 1 Culture_distancea . Enter
Variables Entered/Removedb Model Variables Entered Variables
Removed
Method 1 Culture_distancea . Enter
b. Dependent Variable: Change_rate
Model Summary
Model R R Square Adjusted R Square
Std. Error of the Estimate
1 .179a .032 .024 54.86006901
a. Predictors: (Constant), Culture_distance
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 12109.538 1 12109.538 4.024 .047a
Residual 367174.515 122 3009.627 Total 379284.053 123
a. Predictors: (Constant), Culture_distance b. Dependent Variable: Change_rate
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients
t Sig.
B Std. Error Beta
1 (Constant) -28.544 22.807 -1.252 .213
Culture_distance 3.148 1.569 .179 2.006 .047
a. Dependent Variable: Change_rate
Correlations Value Culture_distanc e Change_rat e Stock_index_changerate Industry_variables Value Pearson Correlation 1 -.109 .018 -.199* -.003 Sig. (2-tailed) .227 .842 .027 .976 N 124 124 124 124 114 Culture_distance Pearson Correlation -.109 1 .179* .064 -.024 Sig. (2-tailed) .227 .047 .480 .799 N 124 124 124 124 114 Change_rate Pearson Correlation .018 .179* 1 .053 .040 Sig. (2-tailed) .842 .047 .557 .673 N 124 124 124 124 114 Stock_index_changerate Pearson Correlation -.199*.064 .053 1 .177 Sig. (2-tailed) .027 .480 .557 .060 N 124 124 124 124 114 Industry_variables Pearson Correlation -.003 -.024 .040 .177 1 Sig. (2-tailed) .976 .799 .673 .060 N 114 114 114 114 114
*. Correlation is significant at the 0.05 level (2-tailed).
Regression Result with Group 2
Variables Entered/Removedb Model Variables Entered Variables
Removed Method 1 Stock_index_cha ngrate, Culture_distancea . Enter
a. All requested variables entered. b. Dependent Variable: Change_rate
Model Summary
Model R R Square Adjusted R Square
Std. Error of the Estimate
1 .439a .193 .172 38.3052966
a. Predictors: (Constant), Stock_index_changrate, Culture_distance
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 26678.348 2 13339.174 9.091 .000a
Residual 111514.477 76 1467.296 Total 138192.825 78
a. Predictors: (Constant), Stock_index_changrate, Culture_distance b. Dependent Variable: Change_rate
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 13.868 13.147 1.055 .295 Culture_distance -.476 .218 -.225 -2.185 .032 Stock_index_changrate .562 .155 .373 3.624 .001
a. Dependent Variable: Change_rate
Correlations Industry_variable s Stock_index_changrate Culture_distanc e Change_rat e Billion US Dollars Industry_variables Pearson Correlation 1 .041 .213 -.119 .084 Sig. (2-tailed) .723 .064 .308 .471 N 76 76 76 76 76 Stock_index_changrate Pearson Correlation .041 1 -.017 .377** .091 Sig. (2-tailed) .723 .881 .001 .425 N 76 79 79 79 79 Culture_distance Pearson Correlation .213 -.017 1 -.232* -.109 Sig. (2-tailed) .064 .881 .040 .340 N 76 79 79 79 79 Change_rate Pearson Correlation -.119 .377** -.232* 1 -.153 Sig. (2-tailed) .308 .001 .040 .178 N 76 79 79 79 79
Billion US Dollars Pearson Correlation .084 .091 -.109 -.153 1 Sig. (2-tailed) .471 .425 .340 .178 N 76 79 79 79 79
Msc Thesis 2008- 2009
National Culture Distance and Post M&A
Performance
By Cheng Chen
University of Groningen,
Duindoornstraat 289, 9741 PP, Groningen, The Netherlands Tel: 00 31 (0)624139871
