The effect of host-country institutional strength on the
location decision of emerging market MNC acquisitions:
an analysis of BRICS EM-MNCs’ cross-border
acquisitions
Word count: 15217
B.M. (Bart) Postma
S2556375
University of Groningen
Faculty of Economics and Business
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THE EFFECT OF HOST-COUNTRY INSTITUTIONAL STRENGTH ON THE LOCATION DECISION OF EMERGING MARKET MNC ACQUISITIONS:
AN ANALYSIS OF BRICS EM-MNCS’ CROSS-BORDER ACQUISITIONS ABSTRACT
Emerging markets multinational corporations (EM-MNCs) are increasingly making cross-border investments. EM-MNCs and their internationalisation process have therefore received increased scholarly attention in recent years. The applicability of existing theories on internationalisation processes on the internationalization of EM-MNCs is questioned by researchers. This study examines institutional strength moderated by psychic distance in influencing the location choice of cross-border investments done by EM-MNCs. Studying 1075 cross-border acquisitions done by 823 unique EM-MNCs originating from the BRICS countries over the time period of 2010-2015, it was found that strong host country institutions have a positive effect on the amount of acquisitions done by EM-MNCs. A moderating effect of psychic distance on the relationship between institutional strength and amount of
acquisitions was also found. EM-MNCs were found to follow different internationalisation patterns than DM-MNCs. The results of this study highlight antecedents to consider in extending existing theories to predict EM-MNC internationalization in the current dynamics of the world economy. Furthermore, the five BRICS countries were remarkably found not to react in a homogeneous way to the influence of psychic distance on host country location choice, with different variables driving their choices. As such, future research should be cautious in generalizing across emerging markets and their EM-MNCs.
INTRODUCTION
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markets are known as the BRICS countries (Brazil, Russian Federation, India, China and South Africa). Together, these countries constitute of 41 per cent of the world population, receiving 15 percent of global FDI outflows and holding 9 per cent of the total world FDI stock (UNCTAD, 2016b). This has called for a shift in the research in the field of
globalisation of multinationals. From the 1960s till the 1990s most research focused on the globalisation of Western multinationals, from the 1990s this shifted to a subsidiary
perspective, and the last decade research has focused on the rise of EM-MNCs (Kostova, Marano and Tallman, 2016).
Nowadays, MNCs are competitors of developed market multinationals.
EM-MNCs increasingly make cross-border acquisitions (Stucchi, 2012), and increasingly so in more developed economies (Buckley, Yu, Liu, Munjal and Tao, 2016). Well known
examples of companies from emerging markets gaining global presence and competitiveness are Lenovo acquiring IBM in 2005 growing to the number four PC manufacturer worldwide (Rabbiosi et al, 2012) and Huawei that has rapidly grown into the world’s number three smartphone manufacturer, selling 139 million phones in 2016, with net profits of 37.1 billion yuan (5.3 billion USD) in the year 2016 (Reuters, 2017).
Existing literature on internationalization of MNCs however, is mostly looking at internationalization of MNCs from developed countries (Chikhouni, Edwards and Farashahi, 2017). Researchers are conflicted on the applicability of existing theoretical models for research on EM-MNCs; some see EM-MNCs as a new type of multinational, whereas others believe they are the same as DM-MNCs (Ramamurti, 2012). Cuervo-Cazurra (2012)
describes the existing literature on EM-MNCs as three streams of research; ‘hot’, ‘cold’ and ‘just right’.
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frameworks are also applicable to research on EM-MNCs (Cuervo-Cazurra, 2012). One of the main contributors to this stream of thought is Rugman. Rugman (2010) explains that his theoretical framework on firm-specific advantages (FSA) and country-specific advantages (CSA), (also known as the FSA/CSA matrix), explains how EM-MNCs behave, stating that EM-MNCs lack FSA apart from economies of scale, but instead get their advantages from CSA such as cheap labour, natural resources and finance. Dunning, Kim and Park (2008) similarly compare the globalisation of DM-MNCs from a few decades ago to the more recent globalisation of EM-MNCs based on Dunning’s (1988) OLI framework, also known as the eclectic paradigm. OLI stands for ownership (intangible assets), internalization (managerial, organisational and institutional capabilities) and location (benefits of locating in a particular foreign country) advantages (Dunning, 1988). Dunning et al., (2008) found that EM-MNCs relatively lack ownership advantages, such as for example global brands when they are compared to DM-MNCs.
The third and final ‘just right’ stream consists of authors who believe that research on EM-MNCs can help elaborate the existing theoretical frameworks (Cuervo-Cazurra, 2012). Ramamurti (2009) notes that the international environment nowadays differs from the international environment in which DM-MNCs internationalised and that the home country influences the way EM-MNCs expand internationally, but believes that existing theories can still be relevant to EM-MNCs when they are elaborated on.
Many recent studies on EM-MNCs have focussed on the reasons behind outward FDI
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However, primary reasons to enter a market, such as market opportunities for economies of scale and scope or gaining access to resources are often prioritised in entering new markets (Hitt, et al., 2006).
Within international business research, a concept that has gained popularity over the last few decades, is the concept of distance (Hutzschenreuter, Kleindienst and Lange, 2013). Distance is the extent to which two things differ from each other in one or multiple ways, in international business literature it is mostly used to make cross-country comparisons
(Hutzschenreuter et al., 2013). Many fundamental international business papers have used investigated several types of distance, such as institutional distance (Kostova, 1999) and cultural distance (Hofstede, 1980; Kogut and Singh, 1988). These yielded explanations for international business behaviour were found, including foreign market entry choice and mode of entry, but also internal aspects such as the management of cultural diversity within a firm and the needed human resource practices for that (Hakanson and Ambos, 2010). Research on internationalization patterns has acknowledged the barriers that distance between home and foreign environment brings (Johanson and Wiedersheim-Paul, 1975). The concept of psychic distance looks at variables that hamper the extent to which a foreign environment is
understood (Johanson and Vahlne, 1977). Existing research (Johanson and Vahlne, 1977; Kogut and Singh, 1988) on internationalization patterns of DM-MNCs has therefore suggested incremental internationalization, increasing psychic distance between home and host environment over time as a means to reduce uncertainty.
The primary interest of this research is to understand if and how EM-MNCs cross-border acquisitions are influenced by institutional strength of the host country. As existing literature is not unanimous on whether EM-MNCs’ investment patterns differ from
traditional, DM-MNCs (Cuervo-Cazurra, 2012), it is needed to examine the cross-border acquisition deals and look at EM-MNCs’ corporate diversification strategies into new
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internationalisation of EM-MNCs, additional research is required to understand both the forces that drive (e.g. market entry, resources, etc.) as well as the variables that refrain EM-MNCs from choosing a particular target country.
The research scope of this paper is set to the world’s largest emerging markets (BRICS countries) by examining a sample of 1075 cross-border acquisitions during a time period of six years – from 2010 to 2015 – carried out by 823 unique EM-MNCs from the BRICS countries to a total of 97 target countries.
Existing literature has mixed opinions on the applicability of internationalization theories on the current wave of internationalization by EM-MNCs (Cuervo-Cazurra, 2012; Chikhouni et al., 2017). Therefore, this research aims to contribute to the ongoing debate of the applicability of existing internationalisation theory for EM-MNCs and thereby exploring whether it is necessary to expand existing theory or develop new theory. This research however takes an exploratory step beyond this comparison between DM-MNCs and EM-MNCs, by looking into EM-MNCs from different home countries (namely, the five BRICS countries) and comparing how these EM-MNCs react to a set of variables that affect host country decision for cross-border deals. More specifically, this is done by taking a closer look at cross-border acquisitions conducted by EM-MNCs and looking at the effect of host
country institutional environments and in addition by looking at the effect of psychic distance on the decision-making process of selecting target countries for cross-border acquisitions. The context of the global economy today is vastly different from when DM-MNCs started internationalizing as todays’ global economic landscape is more interconnected through the so-called IT unbundling (Baldwin and Evenett, 2015) in which EM-MNCs internationalize (Ramamurti, 2012).Canal, 2009). This increased global competition in the global economy requires DM-MNCs to react with appropriate strategic responses in order to maintain their competitive edge over EM-MNCs (Deng, 2012). By investigating EM-MNC cross-border acquisitions, this study adds to the understanding of the dynamics of the global economy and internationalization patterns of emerging market firms, thereby extending the information availability for DM-MNC managers necessary to implement adequate strategic responses to the growing threat of EM-MNCs for their competitiveness in the global
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The next section of this paper provides an overview of existing literature to define the concepts used in this study, as well as the conceptual model and the hypotheses. The theory section is followed by the methodology, results and lastly the discussion and conclusion section.
LITERATURE Emerging markets and emerging market MNCs
The term emerging market was first coined in 1981 by van Agtmael (a former World Bank economist) as an optimistic view towards a new wave of development, rather than the more negative term ‘third world’ which implied the lack of development of such countries (Neville, 2014). There are many different terms used for (groups of) countries that are economically developing, like less developed countries, developing countries, newly
industrializing countries, transitioning economies, and emerging economies (Luo and Zhang, 2016). According to Luo and Tung (2007), emerging markets are markets with high
economic growth in which industries have gone – and are still going – through significant structural changes and a propitious market regardless of having a weak legal system.
Hoskisson, Eden, Lau and Wright (2000) define emerging market economies as countries that have rapid economic development and have government policies geared towards economic freedom and a free-market system. Peng and Meyer (2011) define emerging markets as economies with above average economic growth that only recently established institutions that enable international trade and investment and with low to medium income levels.
The abovementioned definitions of emerging markets show a few similarities, namely; high economic growth and significant recent and/or current changes. Therefore, in this research emerging markets are defined as markets with high growth rates that have
recently made changes in their governmental policies and institutions in order to open up to integration into the international business environment.
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from emerging markets and are engaged in outward FDI, where they exercise effective control and undertake value-adding activities in one or more foreign countries.” (Luo and
Tung, 2007: 482). This definition purposefully excludes certain types of companies, (e.g. import/export companies, MNCs with minority positions in joint venture relationships and state-owned corporations with only a political purpose for the home government) (Luo and Tung (2007). Notably, Luo and Tung (2007) also exclude corporations that mostly or only invest in countries with tax benefits (‘tax havens’) as their purpose does not fulfil the requirement of engaging in value-adding activities abroad.
The strong increase in internationalization by EM-MNCs shows that firm-specific advantages are not a necessity to internationalize, conversely internationalization can actually be used as a means to gain such advantages (Athreye and Godley, 2009). EM-MNCs often lack firm-specific advantages as compared to DM-MNCs (Rugman, 2010), giving them relative weaker positions in alliances with partners that have more bargaining power due to knowledge or technology spill overs (Rabbiosi et al., 2012). By choosing an entry mode such as acquisitions, such EM-MNCs can however get more power in such relationships, as opposed to for example a joint venture (Athreye and Godley, 2009). Furthermore,
acquisitions have also become a more feasible option for international expansion due to the globalization of financial markets, making it easier to get financing (Athreye and Godley, 2009). Among EM-MNCs, a popular way of internationalizing is through mergers and acquisitions, accounting for 30.7 per cent of outward FDI from developing markets, while this was only 25.5 per cent for developed markets (Rabbiosi et al., 2012). Another aspect that affects internationalization is the strength of the intellectual property rights (IPR) system, so that benefits reaped from (technological) assets are protected. It is therefore also not that surprising that asset-seeking outward FDI from both China and India has increased after minimum standards for intellectual property (IP) were set for World Trade Organization member nation by signing the Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement (Athreye and Godley, 2009). Therefore, so called south-north acquisitions (i.e. EM-MNCs acquiring DM-MNCs) are a favourable mode of international expansion when EM-MNCs seek assets (Rabbiosi et al., 2012).
BRIC(S) emerging markets
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introduced by former Goldman Sachs chairman O’Neill in 2001. O’Neill (2001) stressed the importance of four large emerging markets Brazil, Russia, India and China (BRIC), as these countries would contribute to a significant portion of world growth in the near future. Emphasizing on the economic potential of these markets, he predicted an economic shift away from the G7 countries towards the four BRIC countries, by comparing their GDP growth and relative portion in world GDP and states that the BRIC countries should be incorporated in policymaking (O’Neill, 2001). G7 stands for ‘Group of 7’, a grouping introduced by the International Monetary Fund (IMF) consisting of seven major industrial economies, namely; Canada, France, Germany, Italy, Japan, the United Kingdom and the United States (IMF, 2016). In 2006, at the United Nations General Assembly in New York, the ministers of foreign affairs of the four BRIC countries held a meeting together (Kremlin, 2009a). Meetings between the ministers of finance of the four countries to discuss global economic issues held in Sao Paolo and London, in 2008 and 2009 respectively, led to the official inception of the BRIC as a diplomatic political group (Kremlin, 2009a). Since this inception of the BRIC group, yearly summits have been held since 2009 to discuss how to deal with the financial crisis (Kremlin, 2009b).
In December 2010, the 4 BRIC countries invited South Africa to join the group the at the third annual summit in April 2011 (Guateng Provincial Treasury, 2013; South African Government, 2017). After South Africa joined, the group name was extended from BRIC to BRICS (Nevin, 2011). Surprisingly, O’Neill (2001) says that emerging economies such as South Korea, Mexico or Indonesia would fit better in the BRIC terminology (Goulding, 2013). The reason for the BRIC countries to invite South Africa to join has to do with gaining access to the continent of Africa, and using South Africa as a gateway to effectuate that (Noury, 2011). South Africa as a part of BRICS represents the entire continent of Africa and aims to create opportunities for Africa in Africa (van Niekerk, 2015).
Institutional theory
There is a vast amount of literature available on institutions. Scholars and economists found that economic explanations, such as market size, relative labour unit costs and
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Institutions form the ‘rules of the game’ in an institutional environment, which enable and constrain the behaviour and decision-making of individuals and firms within a society (North, 1990). More specifically, North (1990: 97) defines institutions as “humanly devised constraints that structure political, economic and social interaction”. From a macro-level perspective, the institution-based view (IBV) examines how institutions govern the behaviour of domestic and foreign MNCs, and from a micro-level perspective the IBV looks at how MNCs seek legitimacy from both the headquarters as well as from the institutional
environment(s) they operate in (Dunning and Lundan, 2008). Peng and Meyer (2011) divide institutions into two forms; formal and informal institutions. Formal institutions are set by authorities, such as laws, regulations and rules. In contrast, informal institutions are not formalized and not set by authorities, but constitute of norms, cultures and ethics, and shape what behaviour is seen as right or wrong within a society (Peng and Meyer, 2011).
Multinationals have to deal with multiple host environments, which differ in
requirements to gain legitimacy within the environment, making the institutional environment a particularly important concept for MNCs (Kostova and Zaheer, 1999). Organisational legitimacy means that the organisation is accepted by the environment and gaining legitimacy is seen as a necessity for firm survival and success (Kostova and Zaheer, 1999). Legitimacy influences organisational behaviour, decision-making and structure and such organisational adaptations to obtain legitimacy are defined as institutional isomorphism Ang, Benischke and Doh (2015). DiMaggio and Powell (1983) found three institutional isomorphic processes that can explain and legitimize certain firm behaviour and decision-making, namely coercive, mimetic and normative pressures. Coercive pressures are pressures from the authority in a certain institution that legitimize behaviour. Mimetic pressures are pressures that explain firms mimicking successful firms within that specific institutional environment to reduce uncertainty. Lastly, normative pressures consist of the established (patterns of) behaviour that are expected by society.
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behaviour has to oblige to, the normative pillar constitutes of moral and ethical behaviour that you are ought to do and lastly the cognitive pillar stands for cultural behaviour in values, beliefs and assumptions that you want to carry out (Palthe, 2014). Studies on multinational activity and market entry have used the work of Scott’s (1995) conceptualization of
institutions in studying firm strategy and behaviour, with focus on the normative and regulative institutional pillars (Ang et al, 2015). This study emphasizes on Scott’s (1995) regulative pillar, i.e. the formal institutions.
Hypotheses
What is the relationship between institutions and foreign investments in a target country? Do MNCs from developed markets differ from MNCs from emerging markets in the requirements they set for an institutional environment prior to making their decision for cross-border investments? According to North (1990), institutions are one of the most
important factors contributing to economic development because effective formal institutions limit both uncertainty and opportunistic behaviour. Doing business in a certain country means having to deal with challenges and opportunities that stem from the institutional profile (the institutional environment) of a country (Van Hoorn and Maseland, 2016). As such, the opportunities available in a certain country differ from other countries and therefore affects business activities (Wan and Hoskisson, 2003) Formal institutions limit modes of entry in a foreign environment, such as for example legislation posing equity stake limitations for foreign investors, whereas informal institutions can for example set norms for (dis)approval of corruption within that institutional environment (Meyer, Estrin, Bhaumik and Peng, 2009). A strong institutional framework plays a pivotal role in lowering the costs of doing business, as information asymmetries and opportunistic behaviour between business partners reduce in stronger institutional frameworks (Meyer et al., 2009). Host countries with a good
institutional framework have reduced political risk (Buckley et al., 2016). An environment with lower political risk increases the stability of the market (Peng et al., 2008), which in turn attracts international business (Buckley et al., 2016). Therefore, a positive relationship
between institutional strength and the amount of investments done by EM-MNCs is expected.
Hypothesis 1
EM-MNCs are more likely to invest (through acquisitions) in host countries with
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Measures of institutional strength. This section provides an overview of measures of
institutional strength. Institutions consist of different aspects, firstly in their different aforementioned forms of for example formal or informal (Peng and Meyer, 2011) or normative, cognitive and regulative pillars (Scott, 1995), but also within these types of institutions. As stated before, the scope of this research paper is set to Scott’s (1995) regulative pillar, or formal institutions in the terminology of Peng and Meyer (2011).
World Governance Indicators. A widely-used measure of strength of governance are
the World(wide) Governance Indicators (WGI) developed by the World Bank (Pinar, 2015; van Hoorn and Maseland, 2016; Huang and Ho, 2017). For example, Cooray (2009) found that government quality is important for economic growth. The data that is used to compose the WGI is collected through surveys conducted with organisations, individuals, as well as experts in the private sector, nongovernmental organisations (NGOs) and expert in the public sector (Apaza, 2009; Kaufmann, Kraay and Mastruzzi (2011). The large coverage of the WGI has made these indicators the industry standard, as other indicators cannot compete with the WGI’s comprehensiveness (Ward and Dorussen, 2015).
Kaufmann et al. (2011: 3) define governance as “the traditions and institutions by
which authority in a country is exercised”. The WGI are thus a measurement of institutional
quality of countries (Pinar, 2015). The WGI consist of three areas with two governance dimensions each, thus a total of six governance dimensions. The indicators are built upon hundreds of variables derived from 31 different data sources (Kaufmann et al., 2011). In a survey on governance indicators by OECD, Arndt and Oman (2006) consider the WGI as
“the most comprehensive publicly available set of governance indicators”. The WGI
indicators are widely respected, because they have a few advantages over other indicators. First, the number of sources used for the WGI reduces the measurement error of the
indicators (Berden, Bergstrand and van Etten, 2014). Secondly, Kaufmann et al. (2011) state that most other governance datasets do not report on uncertainty in measurements. Besides the WGI, only Transparency International also mentions the importance of taking margin of error into account (Arndt and Oman, 2006). Lastly, the available WGI data cover a
significant number (212) of countries and territories making it particularly useful for cross-country comparisons (Thomas, 2010).
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Similarly, Andrews (2008) criticizes the WGI for being a combination of measures with different underlying theories, perspectives, and viewpoints. Andrews (2008) continues by stating that the WGI dimensions reflect inadequacy of definition.
The six dimensions of the WGI were introduced almost twenty years ago by Kaufmann, Kraay and Zoido-Lobatón (1999). However, over the years Kaufmann and colleagues have released several papers in which the definitions of the WGI have been adjusted over time (Thomas, 2010). Therefore, in this research we use the latest available definitions for the six world governance indicators by Kaufmann et al. (2011). As mentioned earlier, the WGI variables are a very comprehensive measure of institutional strength and thus consisting of a multitude of aspects of institutional strength. Therefore, Kaufmann et al. (2011) divided their WGI variables into three different areas, each measuring a different aspect of institutional strength.
The first area is “the process by which governments are selected, monitored, and
replaced” (Kaufmann et al., 2011: 4). The corresponding governance indicators are; voice and accountability and political stability and absence of violence/terrorism. Voice and
accountability measures “perception of the extent to which a country’s citizens are able to
participate in selecting their government, as well as freedom of expression, freedom of association, and a free media” (Kaufmann et al., 2011: 4). Political stability and absence of
violence/terrorism measures “perceptions of the likelihood that the government will be
destabilized or overthrown by unconstitutional or violent means, including politically-motivated violence and terrorism” (Kaufmann et al., 2011: 4).
The second area is “the capacity of the government to effectively formulate and
implement sound policies” (Kaufmann et al., 2011: 4). The corresponding governance
indicators are; government effectiveness and regulatory quality. Government effectiveness measures “the quality of public services, the quality of the civil service and the degree of its
independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies” (Kaufmann et al., 2011:
4). Regulatory quality measures “perceptions of the ability of the government to formulate
and implement sound policies and regulations that permit and promote private sector development” (Kaufmann et al., 2011; 4).
The last area is “the respect of citizens and the state for the institutions that govern
economic and social interactions among them” (Kaufmann et al., 2011: 4). The
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measures “perceptions of the extent to which agents have confidence in and abide by the
rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence” (Kaufmann et al.,
2011: 4). Control of corruption measures “perceptions of the extent to which public power is
exercised for private gain, including both petty and grand forms of corruption, as well as ‘capture’ of the state by elites and private interests” (Kaufmann et al., 2011: 4).
The concept of institutional strength is a very broad concept, which has led to a large number of definitions for institutions, ranging from very broad and conceptual definitions, such as North’s (1990) ‘rules of the game’ to more specific definitions, such as the
subdivision of institutional strength into three different areas by Kaufmann et al. (2011). The definition by Kaufmann et al. (2011) clearly shows the different areas institutional strength consists of, including corruption, law and regulation, but also political stability and absence of violence/terrorism. Therefore, this research also looks at the effect of underlying constructs of institutions strength by separately testing the effect of the six underlying variables the WGI measure of institutional strength comprises. Therefore, following the argumentation leading to hypothesis 1, it is expected that the higher a country scores on the underlying variables of the WGI construct, the more likely it is that EM-MNCs will make cross-border investments in that country.
Hypothesis 2
The number of acquisitions done by EM-MNCs is positively related to strong: a. Voice and accountability (VA)
b. Political stability and absence of violence and terrorism (PS) c. Government effectiveness (GE)
d. Regulatory quality (RQ) e. Rule of law (RL)
f. Control of corruption (CC)
Psychic distance. Within international business literature, distance has grown into an
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institutional distance (Kostova, 1999) and cultural distance (Hofstede, 1980; Kogut and Singh, 1988; Shenkar, 2001). Uniting these concepts, the psychic distance concept was introduced for the first time by Beckerman (1956) and popularized by Johanson and Wiedersheim-Paul (1975). As a broader concept that considers variables that hamper the extent to which a foreign environment is understood (Johanson and Vahlne, 1977), psychic distance consists of factors that negatively impact information flows between a firm and the market (Johanson and Wiedersheim-Paul, 1975; Johanson and Vahlne, 1977). Examples of the multiple measures of distance it takes into account include distance in education, industrial development, culture and political systems (Johanson and Wiedersheim-Paul, 1975). In a study by Hakanson and Ambos (2010), geographical distance, economic factors and cultural distance were considered as antecedents of psychic distance. Hakanson and Ambos (2010) found that psychic distance from country A to country B is not the same as psychic distance from country B to country A. The reason why psychic distance is not equal in both directions is because it takes into account variables on both the firm and the country level, and thus psychic distance between two countries is asymmetrical (Hakanson and Ambos, 2010). Other researcher approach the concept of psychic distance from a different perspective, namely from the manager’s point of view, as the perception held by the manager is crucial in their choices and behaviours (Evans, Treadgold and Mavondo, 2000).
Dow and Karunaratna’s (2006) psychic distance stimuli can be seen as an overarching comprehensive definition of distance. Taking both Hakanson and Ambos (2010) and Evans, Treadgold and Mavondo’s (2000) perspectives into consideration, the psychic distance
stimuli include measures of geographical distance, economic factors, cultural distance and the managerial perspective. Psychic distance stimuli consist of a set five variables measuring differences, namely; language, religion, industrial development, level of education and political systems (which in turn can be subdivided into differences in degree of democracy and differences in political ideology), which are highly influential on the perceived psychic distance (Dow and Karunaratna, 2006). Perceived psychic distance in turn can be seen as the psychic distance as perceived by key decision-makers, such as the perception of the manager which influences decision making related to psychic distance (Dow and Karunaratna, 2006). Psychic distance has provided explanations for choice of entry and entry mode into markets (Hakanson and Ambos, 2010), arguably due to its ability to account for liability of
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Countries that are similar in terms of culture are more likely to be similar in their institutions, and therefore keeping this in mind when deciding on which markets to enter is expected to reduce the liability of foreignness when entering new markets (Hitt et al, 2006). Liability of foreignness consists of all the costs that are associated with doing business abroad that a domestic firm would not incur (Zaheer, 1995). Four sources of liability of foreignness posited by Zaheer (1995) are spatial distance, firm-specific costs, lack of legitimacy for foreign companies, and costs stemming from the home country environment. Firstly, spatial distance can cause costs in terms of travel, transport and the complexity of coordination. Secondly, foreign firms can incur firm-specific costs due to lack of knowledge and roots in the environment. Thirdly, liability of foreignness can stem from the host country environment can lead to lack of legitimacy for foreign companies. Lastly, costs stemming from the home country environment, for example restrictions on high-tech sales (Zaheer, 1995). Liability of foreignness increases as psychic distance increases, as having an understanding of a foreign market through experience, either at home or through earlier international expansion, can help alleviate such liabilities that foreign firms incur. For example, foreign investors that have experience with corruption because it is a commonality in their home institution, face fewer costs of doing business abroad in institutions that also have high corruption (Cuervo-Cazurra, 2006). Due to home country experience, the liability of foreignness is thus lower (Cuervo-Cazurra, 2006). This highlights the importance of considering psychic distance as perceived by firm managers, as they are the decision-makers for investment acquisition decisions.
In this research, the psychic distance conceptualisation by Dow and Karunaratna (2006) is used, because their psychic distance stimuli measures give insight in managerial perceptions on home-host country distance and in turn in the attractiveness of foreign markets for investments. Managerial perceptions of distance are key in the decision-making process for which markets to enter (Sousa and Lages, 2011).
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On the other hand, a higher psychic distance would deter managers from investing in that market (Blomkvist and Drogendijk, 2013) due to the liability of foreignness incurred by the foreign firm (Zaheer, 1995). Target countries that show similarities to the home country are expected to cause less liability of foreignness and thus lower cost of doing business in comparison to dissimilar markets (Hitt et al., 2006). That would make such target countries more attractive to invest in. This is also the reason why the ‘Uppsala model’ of
internationalization (Johanson and Vahlne, 1977) has been a popular way of
internationalising by DM-MNCs for decades. By gradually increasing the psychic distance between home and host country, risk of internationalisation is minimized, and firms learn from these incremental adjustments that the firm makes to understand foreign markets. Lack of market knowledge and the difficulties of obtaining such knowledge creates uncertainty for managers in markets at a greater psychic distance (Johanson and Vahlne, 1977). As such, MNCs build up their international experience, which in turn can be used to understand markets at greater psychic distance from their home country (Blomkvist and Drogendijk, 2013). Through this learning, managers gain experience in managing a particular institutional environment (Cuervo-Cazurra and Genc, 2008).
As EM-MNCs emerge in weaker institutional environments, it is expected that managers from EM-MNCs will have less difficulty understanding other weak institutional environments, as they are familiar with the way business is done (Cuervo-Cazurra and Genc, 2008). An example of this is familiarity with corruption (Cuervo-Cazurra, 2006). Experience in a market gives managers confidence to enter other markets that are similar, as the liability of foreignness is reduced (Ellis, 2008). Therefore, it is expected that lower psychic distance (thus, more similarities between home and host country) would weaken the effect between institutional strength and amount of acquisitions by EM-MNCs (as proposed in hypothesis 1). EM-MNC’s experience with weaker institutional environments due to their home country’s weak institutional environment is expected to offset the political risks and uncertainty that comes with doing business abroad in weaker institutional settings.
Thus, a negatively moderating effect is expected; the effect of psychic distance is expected to weaken the relationship between institutional strength and amount of acquisitions by EM-MNCs.
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Hypothesis 3
Psychic distance between home and host country negatively moderates the
relationship between institutional strength and amount of EM-MNC acquisitions in that host country, when the home country is:
a. Brazil b. Russia c. India d. China e. South Africa
Figure 1: conceptual model
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METHODOLOGY Procedure and sample
Procedure. The data was collected from a number of secondary data sources. Firstly,
the data on acquisitions was collected using Bureau van Dijk’s Zephyr database, a comprehensive database that contains information on mergers and acquisitions deals. Secondly, for measuring institutional strength, the popular World Governance Indicators were used as they are very comprehensive with data for over 200 countries and measurements over a larger period of time. The last available update (September 2016) of WGI data was retrieved from the World Bank’s official website (World Bank, 2016). Lastly, gross domestic product per capita (GDPC) was collected from the United Nations Conference on Trade and Development (UNCTAD) for the years 2010-2015 (UNCTAD, 2016c).
Sample. The data sample in this study was retrieved from the Zephyr database on
March 10, 2017. A number of search steps were used to create the sample used in this study. The first search step was selecting the time period for the deals, which is the period from January 1, 2010 up to and including December 31, 2015. All the deals in the sample had the status of being both completed and confirmed. The next search step included selection of only cross-border deals as well as selecting Brazil, China, India, Russian Federation and South Africa as the acquirer countries. The third step filtered the search results on company type to companies only for both the acquirer and target side of the deals (excluding for example governments and individuals). Within Zephyr, several deal types can be selected, such as acquisitions, joint-ventures, mergers and demergers. The final step narrowed down the deal types to acquisitions only. The sample size used in this study was N= 1075
acquisitions, conducted by 823 unique EM-MNCs to 97 target countries. The distribution of deals and EM-MNCs can be found in table 1 below. The data sources for GDPC, WGI and psychic distance were cross-compared to include the maximum possible amount of measures.
Table 1: Number of acquisitions and EM-MNCs per BRICS country BRICS country Total number of
acquisitions
Unique number of EM-MNCs
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Variables
Dependent variable: Amount of cross-border acquisitions by EM-MNCs from BRICS countries. The amount of cross-border acquisitions by EM-MNCs from BRICS
countries was measured by counting the amount of deals per target country. The range of the dependent variable was 116, with a minimum of zero and a maximum of 116. The mean number of acquisitions was 5.46 with a standard deviation of 13.84. Two control variables were taken into account to control for the amount of acquisitions per target country, namely GDP per capita of the target country and tax havens.
Independent variable: World Governance Indicators (WGI) variables. The six
independent variables in this study were developed by the World Bank. The WGI measures were constructed as aggregated indicators of institutional strength based on data collected from over 30 underlying sources divided over four categories; surveys of households and firms, commercial business information providers, NGOs and public-sector organizations (Kaufmann et al., 2011). Data from these underlying individual sources was first assigned to each of the WGI variables. Secondly, they rescaled the individual sources to a scale from 0 to 1. Lastly, a weighted average of the individual sources is constructed through the means of an Unobserved Components Model (UCM), which assigns higher weighs to strongly correlated data sources, and improving the statistical accuracy of the WGI (World Bank, 2017). Lastly, each WGI dimensions was measured from -2.5 to 2.5. The dataset of the World Bank
comprised 214 countries. However, cross-comparison with other measures used in this study made it necessary to exclude countries that did not have data for all the different measures and N = 198 countries. As this study did not use the entire WGI dataset, the six WGI variables were standardised prior to running analysis for readability purposes so that the mean is zero and the standard deviation is one for all the WGI variables.
Moderator: Psychic distance stimuli. Psychic distance was measured as a composite
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Control variables
GDP per capita. In order to control for the size of the market as a variable influencing
the amount of acquisitions done in a market, gross domestic product per capita (GDPC) was used as a control variable. Gross domestic product data per target country was retrieved from the UNCTAD statistics database (UNCTADstat). The data was measured as (GDPC) at current prices in US dollars. In this study, GDPC data for the years 2010-2015 was used by calculating the sum of GDPC over this period divided by the amount of years, thus the average GDPC for 2010-2015.
Tax havens. In this research, tax havens were selected based on a ranking by
OXFAM International on corporate taxes. OXFAM International (2016) collected a list of 59 jurisdictions from existing lists on secrecy as well as corporate tax havens. Through
screening, OXFAM identified the most problematic corporate tax jurisdictions. The next filtering step was ranking the fifteen ‘most aggressive’ corporate tax havens based on scores assigned on six variables (OXFAM International, 2016). The following criteria were taken into account to identify the fifteen worst corporate tax havens in the world; 1) size of tax haven, 2) corporate income tax (CIT) rate as a proportion of the global average rate, 3) no withholding tax, 4) aggressive tax planning indicators, 5) lack of controlled foreign company (CFC) rules and 6) lack of commitment to international efforts against tax avoidance. In this study, the control variable tax havens was dummy coded as ‘0 = no’ and ‘1 = yes’. See table 9 in the appendices for the tax havens included in this research.
Analytical approach
Exploratory reliability and correlation analyses. Reliability analyses and correlation
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Table 2: Correlations worldwide governance indicators
M SD 1 2 3 4 5 6 7 8 9
1. Control variable:
GDP/capita 14798.49 20486.74 1 2. Control variable: tax
havens1
.06 .24 .45** 1
3. DV: Number of acquisitions 5.46 13.84 .36** .26** 1 4. IV: Voice and
accountability
0 1 .51** .27** .29** 1 5. IV: Political stability and
absence of violence/terrorism
0 1 .54** .29** .19** .73** 1
6. IV: Government
effectiveness 0 1 .73** .38** .41** .75** .70** 1 7. IV: Regulatory Quality 0 1 .69** .35** .40** .75** .62** .94** 1 8. IV: Rule of Law 0 1 .73** .36** .39** .81** .78** .95** .90** 1 9. IV: Control of Corruption 0 1 .75** .41** .37** .78** .77** .93** .86** .95** 1
1 Dummy coded, 0 = no, 1 = yes
** p < .01 * p < .05
The psychic distance stimuli education, industrial development and religion were collected from secondary sources by Dow and Karunaratna (2006) and therefore the scales of the psychic distance stimuli were first standardized prior to running analyses. The political ideology psychic distance dimension was removed because of a combination of reasons. First, political ideology was not known for many countries in comparison to the other five psychic distance stimuli variables, and would therefore dramatically decrease the sample size for the analyses. Second, in factor analysis this variable loaded noticeably weaker as
compared to the other variables. After removal of political ideology, the variance explained by the factors extracted from the factor analysis increased from 54.54 cumulative per cent to 61.98 cumulative per cent. In order to keep the sample size acceptable, it was thus decided to not take into account the political ideology variable in the analyses. Psychic distance stimuli had a Cronbach’s alpha of .46.
The exploratory correlation analysis for the psychic distance stimuli was based on distance stimuli data with Countryi = BRICS and Countryj = all available countries that were
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significant negative correlation with psychic distance in education and strong, strong and weak significant positive correlations with psychic distance in language, religion and industrial development respectively.
Table 3: Correlations psychic distance stimuli
M SD 1 2 3 4 5 6
1. Differences in Education 0 1 1
2. Differences in Language 0 1 .03 1
3. Differences in Religion 0 1 -.00 .18** 1
4. Differences in Industrial Development 0 1 .58** .00 .10* 1
5. Differences in Degree of Democracy 0 1 -.10* .22** .35** .09* 1 6. Differences in Political Ideology 0 1 .15** .06 .11* .21** .10* 1
** p < .01 * p < .05
Factor analyses. Factor analyses were run for the institutional strength (WGI)
variables as well as psychic distance to determine whether they measure the same underlying construct. The threshold for factors extracted from the factor analyses was eigenvalue > 1.0.
World Governance Indicators (Cronbach’s alpha = .96). Principal components
factor analysis with varimax rotation extracted one factor (institutional strength) with an eigenvalue of 5.08, explaining 84.72 per cent of the variance. Six items that reflect the institutional strength of a country. The factor loadings for each variable can be found in table 4 below. The regression and moderation analyses were conducted using this factor as the Cronbach’s alpha and the factor loadings of the individual variables were very high.
Table 4: Factor analysis worldwide governance indicators
Construct and item wording Factor Loadings Institutional strength
Rule of law .98
Control of corruption .96
Government effectiveness .96
Regulatory Quality .92
Voice and accountability .87
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Psychic distance stimuli (Cronbach’s alpha = 0.46). Two factors with an
eigenvalue > 1 were extracted through principal components extraction with varimax rotation. Factor 1 (psychic distance in education and industrial development) and factor 2 (psychic distance in degree of democracy, religion and language) had an eigenvalue of respectively 1.60 and 1.49, cumulatively explaining 61.98 per cent of the variance. The factor loadings per component can be found in table 5 below. The regression and moderation
analyses were conducted with the two extracted factors.
Table 5: Factor analysis psychic distance stimuli
Construct and item wording Factor loadings Psychic distance in education and industrial
development
Difference in education .89
Difference in industrial development .88 Psychic distance in degree of democracy, religion and
language
Difference in degree of democracy .78
Difference in religion .74
Difference in religion .58
Explanatory correlation analyses. Due to the relational nature of the psychic distance
stimuli measures (distance from country A to country B), the explanatory correlation analyses and the moderation analyses were run separately for each of the five BRICS countries to avoid the need of using an average psychic distance measure when conducting these analyses for all the five BRICS countries in a single analysis.
Correlation analysis was conducted for the institutional strength factor, the two psychic distance stimuli factors, the control variables and the dependent variable. The results for the separate correlation analyses for each BRICS country can be found in table 10 in the appendices.
Regression and moderation analyses. To further test the results from the correlation
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(table 11). Next, six separate regression analyses were run to test hypothesis 2a to 2f, as testing the predictors in the same analyses led to high correlations between the independent variables (table 12 to table 16). After that, the moderating effect of the two factors of psychic distance stimuli was tested in five separate moderation analyses, one for each of the five BRICS countries, just like the explanatory correlation analyses. A prerequisite for moderation analysis was standardisation of the independent variable and the moderation variables, as cross-product variables have to be computed for the moderation analysis.
RESULTS
First, the results of the regression analysis between institutional strength and number of acquisitions will be presented. Second, the outcome of the regression analyses for the individual WGI variables will be presented to test hypothesis 2a to 2f. Lastly, the moderation analyses for hypothesis 3a to 3e will be presented. Two control variables were taken into account in all regression and moderation analyses conducted, namely the GDP per capita of the host country as well as tax haven status of the host country.
Regression analyses
Regression analysis institutional strength. In this regression analysis, the main effect
was tested, namely the expected positive effect of the strength of target country institutions on the number of acquisitions done in that target country by EM-MNCs. As expected, there was a significant positive relationship between institutional strength of the target country and the amount of acquisitions done by EM-MNCs, β = .23, p < .05. Thus, the stronger the institutions of a particular country are, the more likely it is that EM-MNCs from the BRICS countries will invest in that country through acquisitions. Therefore, hypothesis 1 is
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Table 7: Regression analysis institutional strength
Regression analyses WGI variables. Hypothesis 2 looked at the effect of the six
individual WGI variables on the dependent variable to test whether each individual
dimension has a significant effect. Similar to hypothesis 1, a stronger governance on the WGI dimensions was expected to have a positive effect on the amount of acquisitions done by EM-MNCs from BRICS countries in that country. The dimension voice and accountability had a weak significant positive effect (β = .14 and p < .10), so weak support is found for hypothesis 2a. For hypothesis 2b no support was found, the variable political stability and absence of
violence and terrorism had a negative (β = -.10) but non-significant effect. The dimensions government effectiveness, regulatory quality and rule of law were all significant at the p < .01
level and had a positive effect on the number of acquisitions (β = .30, .28 and .27
respectively), supporting hypotheses 2c, 2d and 2e. Lastly, control of corruption was found to be both significant and positive (β = .23 and p < .05), confirming hypothesis 2f.
In the factor analysis, the WGI dimensions loaded very high on the first factor (institutional strength), where rule of law had the highest factor loading (.98) and political stability and absence if violence and terrorism had the lowest factor loading (.83). As support for hypothesis 1 was found, it was surprising that political stability and absence of violence and terrorism turns out to be a negative effect, albeit not significant.
Model 1 Model 2
Steps and variables Beta SE Beta SE
Intercept (1.14)* (1.31)***
1 Control
GDP per capita .30*** (.00) .14 (.00)
Tax havens1 .12 (4.31) .11 (4.27)
2 Main effects
IV: Institutional strength .23** (1.32)
F 15.61*** 11.69***
Degrees of freedom 193 192
R Square .14 .17
Δ R Square .14*** .03**
1 Dummy coded, 0 = no, 1 = yes
Standard errors are reported between parentheses *** p < .01
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Moderation analyses
Despite the BRICS being very similar in the aspect of being emerging markets with large domestic markets (O’Neill 2001), and all holding a large portion (9 per cent altogether) of the FDI stock in the world (UNCTAD, 2016b), the results of this study show that EM-MNCs from BRICS countries react differently on psychic distance between home and host country. Institutional strength when moderated by psychic distance variables, influences their cross-border acquisition location decision. The moderation analyses yielded different results for each of the BRICS countries. Furthermore, the main effect was no longer significant when adding the moderating variables which is potentially because the sample size for the
moderation analysis was only N = 110 countries, whereas the sample size for the regression analysis was N =198 countries.
Moderation analysis Brazil. Both psychic distance in education and industrial
development, and psychic distance in degree of democracy, religion and language did not
significantly moderate the relationship between institutional strength and number of acquisitions. Thus, hypothesis 3a is not supported. Psychic distance stimuli therefore do not seem to influence the effects of host country institutional strength on amount of acquisitions done by Brazilian EM-MNCs. Interestingly, psychic distance in degree of democracy, religion and language has a highly significant direct effect on the number of cross-border acquisitions by Brazilian EM-MNCs. The top 10 target countries for Brazil (table 17) confirms this effect, as Brazil’s top target countries list consists for a large part of countries with similarities in language.
Moderation analysis Russia. Psychic distance in degree of democracy, religion and
language had a significant positive moderating effect in the relationship between institutional strength and number of acquisitions for the Russia sample, however psychic distance in education and industrial development did not have a significant moderating effect. Therefore, hypothesis 3b is partially supported. Higher psychic distance in degree of democracy, religion and language was `expected to cause a weaker relationship between institutional strength and number of cross-border acquisitions. Russian EM-MNCs thus favour stronger institutional environments even more as distance increases. Seemingly the institutional strength of a host country thus weighs stronger than the liability of foreignness caused by higher psychic distance.
Moderation analysis India. In the India sample, a significant negative interaction effect
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the relationship between institutional strength and number of acquisitions, partially supporting hypothesis 3c. Bigger differences in degree of democracy, religion and language weaken the importance of the strength of host country institutions. When looking at the top target countries for Indian EM-MNCs in table 17, it stands out that the United States and the United Kingdom are by far the number 1 and number 2 targets respectively, Germany being far behind as number 3. India shares the same language as the United States and the United Kingdom, thus this result seems to be caused by the importance of language similarities for EM-MNCs from India.
Moderation analysis China. The moderation analysis for China showed a notably higher
R square value in both model 2 (R2 = .37) and model 3 (R2 = .50) as compared to the analyses of the other BRICS countries. Full support was found for hypothesis 3d. Psychic distance in education and industrial development had a strong significant positive interaction effect in the relationship between institutional strength and number of acquisitions for Chinese EM-MNCs. The top target countries for China consists of highly developed markets (table 17). Buckley et al. (2012) found a similar list of high developed countries being China’s top destinations. As psychic distance in education and industrial development positively moderates the relationship between institutional strength and amount of acquisitions (i.e. the higher the distance, the stronger the relationship between institutional strength and amount of acquisitions), it seems that Chinese EM-MNCs seek education and industrial development abroad in strong institutional environments. Nicolas and Thomsen (2008) found that EM-MNCs from China invest in strong, highly
developed economies in search of strategic assets. The choice for developed markets for China is a result of China’s ‘Go Global’ policy (Buckley et al., 2012), which motivates EM-MNCs from China to improve their technological capabilities (Pei and Zeng, 2015). This shows in the statistics foreign R&D investment, as China is good for 2.8 per cent of the total amount of such projects in Europe (Nicolas and Thomsen, 2008).
A strongly significant negative moderation effect was found for psychic distance in degree of democracy, religion and language. Thus, this type of psychic distance weakens the relationship between institutional strength and amount of acquisitions.
Moderation analysis South Africa. No significant moderations from psychic distance on
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African continent. This aligns with the reason for the BRIC countries to invite South Africa as the fifth member of the BRICS group as a gateway to gain access to Africa and the future business opportunities on the continent of Africa (Noury, 2011).
DISCUSSION AND CONCLUSION
The institutional environment of a country matters (Van Hoorn and Maseland, 2016) for internationalisation. Stronger host country institutions attract international business as less political risk is faced in an institutional environment with good (strong) governance (Buckley et al., 2016). Many aspects of institutions can influence entry choice and entry modes, for example commonality of bribery, opportunistic behaviour or information asymmetry are all elements that increase the costs of doing business and might refrain foreign firms from entering or more strongly lean towards entry modes that carry lower risk, such as joint
ventures (Meyer et al., 2009). Entering a market through acquisitions is therefore sensitive for how effective a market is governed (Meyer et al., 2009). Recent literature has looked at outward FDI flows from EM-MNCs, but found mixed results on the motives of EM-MNCs for their location choices for cross-border acquisitions (Jindra et al., 2016). The institutional environment in itself is not a good enough reason to conduct business somewhere and acquire companies in that country, but other aspects such as natural resources, a means to enter the host market or accessing to strategic assets are also potential driving forces that influence the location decision for acquisitions (De Beule and Duanmu, 2012; Dunning, 2000). Existing literature is scattered rather than unanimous on whether EM-MNCs show similar behaviour to cross-border acquisition of DM-MNCs (Cuervo-Cazurra, 2012). Therefore, based on existing theory, EM-MNCs were also expected to seek strong institutions in their cross-border acquisition location choices and the first hypothesis in this study confirms that for the BRICS countries.
Some papers have already pointed out that EM-MNCs do not always internationalise the way as described in theories based on DM-MNCs. for example Johanson and Vahlne (1977)’s ‘Uppsala model’ of incremental internationalisation does not always hold true for EM-MNCs, however this might also partially be a manifestation of the increased
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internationalized in several decades ago. Traditional international business theory based on DM-MNCs poses that firms first expand countries similar to their home country (Ramamurti, 2012), however hypothesis 1 of this study shows that host country institutional strength has a positive relationship with the amount of acquisitions, whereas the emerging markets such as the BRICS countries are characterised by weaker institutions.
A remarkable finding in this study is that the BRICS countries as a group themselves are not driven by the same forces in their location decisions. In table 17 you can see the top 10 target countries per individual BRICS country. Interestingly, approximately 70 per cent of all deals across all the BRICS countries are conducted in the top 10 countries. As can be seen, the countries are notably different in their choice of target countries. An important
implication of this and the different results found in the five moderation analyses, is that the EM-MNCS from BRICS countries should not be seen as a homogeneous group, but are driven by different forces. Caution is therefore required when generalising EM-MNCs as one group as they show dissimilarities in the forces that drive their location decision for cross-border acquisitions.
Theoretical and Managerial Implications
Theoretical implications. Existing literature and theories in the field of international
business have often taken a developed country/MNC perspective (Chikhouni, 2017).
The results in this study show that EM-MNCs not only internationalize differently as compared to DM-MNCs (Guillen and Garcia-Canal, 2009), as increasingly questioned by recent papers (Chikhouni et al., 2017), but also that EM-MNCs from different emerging markets seem to have different internationalization motives and patterns. Globalisation has changed the dynamics of the global economy and requires existing theory to be extended beyond the DM-MNCs perspective. Home country aspects and a different global context in which EM-MNCs internationalize today cause EM-MNCs to internationalise in a particular way (Ramamurti, 2009).
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variance in decisions made by EM-MNCs. This would be a significant first step towards extending DM-MNCs theories in the spirit of the ‘just-right’ stream, as such models would make more accurate and robust predictions about EM-MNC acquisitions.
Managerial implications. The findings of this research suggest that the international
expansion patterns of EM-MNCs show dissimilarities. While the BRICS countries are similar in the fact that they are emerging markets (and therefore have above average growth rates) with large domestic markets and (O’Neill, 2001), EM-MNCs from the BRICS countries seem to have different driving forces for their cross-border acquisitions. As EM-MNCs are now also competitors of DM-MNCs in both less-developed markets (Stucchi, 2012) as well as developed markets (Buckey et al., 2016), it is necessary for managers to understand their internationalisation process and to understand which factors influence the cross-border acquisition decisions of EM-MNCs to take this information into account when deciding on their own cross-border investments and to thus remain competitive.
An important contribution this study thus makes is that managers should not
generalise EM-MNCs, as this study shows that besides EM-MNCs being different from DM-MNCs (Guillen and Garcia-Canal, 2009), emerging markets are not a homogeneous group in cross-border acquisition behaviour. Rather, they should take into consideration how
institutional strength and psychic distance drive EM-MNCs from BRICS countries in a different way, and thus look at each of these emerging markets separately. Being able to predict internationalization patterns of EM-MNCs from these five big markets can be a great asset in the decision-making process for strategic responses for DM-MNC managers.
Limitations and Future Directions
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The scope of this research was set to (completed and confirmed) cross-border acquisitions only, given the popularity of this mode of entry for EM-MNCs. Other forms of
internationalisation, such as greenfield investments, joint ventures or mergers were thus not taken into account. Despite the narrowed down scope of this research, data collection yielded a very acceptable sample size of 1075 cross-border investments conducted by 823 unique EM-MNCs. Future studies can investigate whether the results of this study also hold true for the different aforementioned modes of entry, as the mode of entry also has implications for the amount of risk involved.
The main effect of institutional strength in this study explained 17 per cent of the variance in the number of cross-border acquisitions done by EM-MNCs from BRICS countries. Due to the complex nature and the many different factors affecting the
internationalisation process, not all variables can ever be taken into consideration in research, rather only a portion of the empirical truth can be examined. A potential future research could for example compare the effects of institutions and psychic distance based on the underlying reason of EM-MNCs to internationalize. Examples of such motives are for example
economies of scale and scope or access to resources (Hitt et al., 2006).
Gross domestic product per capita was used to take into account the size of the market as one of the variables influencing the amount of acquisitions done in a particular
market/country. This study however had an international scope, focussed on cross-country differences. Further specifics of markets, such as market dynamics, were not taken into account. Future research could, based on table 17, focus on specific markets that are popular target countries for EM-MNCs to invest in and investigate the effects of market dynamics, for example with the use of Porter’s five forces of competitiveness that shape strategy (Porter, 1979).
This research has focussed on country level characteristics influencing acquisition behaviour. It is not known whether these companies actually conduct their commercial activities in these countries or that they only have a mailing address for tax purposes
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are conducted in the target countries. This would also help getting a better understanding of what EM-MNCs seek in the companies they target for their acquisitions.
Additional future research suggestions. The top target countries differ for each of the
five BRICS countries (see table 17). A potential future direction is looking at the relationship between the home and host countries to get a better understanding of why these countries are the top targets for EM-MNCs from the BRICS countries. For example, what history do these countries have with each other (e.g. colonial ties) and what trade treaties are active that might be an incentive for these countries to be considered as target countries?
Conclusion
Host countries with high institutional strength are preferred locations for cross-border acquisitions done by EM-MNCs from the BRICS countries. However, institutional strength is only one of many factors influencing cross-border investment decisions. This study shows that psychic distance stimuli show an interaction effect on the relationship between host country institutional strength and number of cross-border acquisitions. The BRICS countries are affected differently by psychic distance stimuli and should therefore, in the context of cross-border acquisitions, not be seen as a homogeneous group. Fleury and Fleury (2009) similarly mentioned that the BRICS countries, despite their similarities, have taken different roads. The results of this study show that the BRICS countries also show differences in the way they react to influencing variables on internationalisation location choice. This research has tried to clarify whether existing international business theory is applicable to EM-MNCs or not (Cuervo-Cazurra, 2012) and to thus gain a better understanding of the different nature of EM-MNCs as compared to DM-MNCs. The results of this study provide a first step to building new theory based on EM-MNCs in the current dynamics of the world economy. However, this research has researched some of the host country characteristics that influence cross-border acquisition decisions. Future research should also take into consideration home country characteristics as well as deal level characteristics besides host country
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REFERENCES
Andrews, M. (2008). The good governance agenda: beyond indicators without theory. Oxford
development studies 36(4), 379-407
Ang, S.H., Benischke, M.H. and Doh, J.P. (2015). The interactions of institutions on foreign market entry mode. Strategic Management Journal 36, 1536-1553
Apaza, C.R. (2009). Measuring governance and corruption through the Worldwide Governance Indicators: critiques, responses, and ongoing scholarly discussion. Political
science and politics 42(1), 139-143
Baldwin, E. and Evenett, S. (2015). Value creation and trade in 21st century manufacturing: what policies for UK manufacturing? Journal of regional science 55(1), 71-128
Beckerman, W. (1956). Dist ance and the pattern of intra-European trade. The review of
economics and statistics, 31-40
Berden, K., Bergstrand, J.H. and van Etten, E. (2014). Governance and Globalisation. The
World Economy 37(3), 353-386
Blomkvist, K. and Drogendijk, R. (2013). The impact of psychic distance on Chinese outward foreign direct investments. Management International Review 53(5), 659-686 Buckley, P.J., Yu, P., Liu, Q., Munjal, S. and Tao, P. (2016). The institutional influence on the location strategies of multinational enterprises from emerging economies: evidence from China’s cross-border mergers and acquisitions. Management and Organization review 12(3), 425-448
Chikhouni, A., Edwards, G. and Farashahi, M. (2017). Psychic distance and ownership in acquisitions: direction matters. Journal of International Management 23(1), 32-42
Cooray, A. (2009). Government expenditure, governance and economic growth. Comparative
35
Cuervo-Cazurra, A. (2006). Who cares about corruption? Journal of international business
studies 37, 807-822.
Cuervo-Cazurra, A. and Genc, M. (2008). Transforming disadvantages into advantages: developing-country MNEs in the least developed countries. Journal of international business
studies 39, 957-979
Cuervo-Cazurra, A. (2012). Extending theory by analysing developing country multinational companies: solving the goldilocks debate. Global Strategy Journal 2, 153-167
De Beule, F. and Duanmu, J. (2012). Locational determinants of internationalization: A firm-level analysis of Chinese and Indian acquisitions. European Management Journal 30, 264-277
Deng, P. (2009). Why do Chinese firms tend to acquire strategic assets in international expansion? Journal of world business 44, 74-84
Deng, P. (2012). Accelerated internationalization by MNCs from emerging economies: determinants and implications; Organizational Dynamics 41, 318-326
DiMaggio, P.J. and Powell, W.W. (1983). The Iron Cage Revisited: Institutional
Isomorphism and Collective Rationality in Organizational Fields. American Sociological Review 48(2), 147-160
Dow, D. and Karunaratna, A. (2006). Developing a multidimensional instrument to measure psychic distance stimuli. Journal of international business studies 37(5), 578-602
Dunning, J.H. (1988). The eclectic paradigm of international production: a restatement and some possible extensions. Journal of international business studies 19, 1-31
