1
Faculty of Economics and Business
Master Thesis
The influence of cultural distance and global cities on ownership intensity of
MNEs from advanced and emerging economies for realizing their strategic asset
seeking motives
Author: Marius Hoogeveen Student number: 11606304
MSc Business Administration: International Management University of Amsterdam
Date of submission: 25-01-2018 Supervisor: Dr. Mashiho Mihalache Second reader: Dr. Vittoria Scalera
2
Statement of originality
This document is written by Marius Hoogeveen who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
3
Table of content
Abstract ... 4 1. Introduction ... 5 1.1 Research gap ... 6 2. Literature review ... 82.1 MNEs in advanced and emerging economies ... 8
2.2 Internationalization motives ... 9
2.3 Ownership intensity ... 12
2.4 Cultural distance ... 13
2.5 Global cities ... 15
3. Theoretical framework ... 17
3.1 Internationalization motives and the ownership intensity ... 17
3.2 Moderating role of cultural distance ... 19
3.3 Moderating role of global cities ... 21
4. Methodology ... 24
4.1 Sample ... 24
4.2 Data collection ... 25
4.3 Variables ... 25
5. Results ... 30
6. Discussion and contributions to the literature ... 38
6.1 Findings and academic relevance ... 38
6.2 Managerial and policy implications ... 41
6.3 Limitations and recommendations for future research ... 42
6.4 Conclusion ... 43
4
Abstract
Emerging markets have become more influential in the world economy; their economic growth and their foreign direct investments (FDIs) outflows are steadily increasing (UNCTAD, 2017). Simultaneously, a remarkable increase in the literature written on activities in and from emerging markets, such as Luo & Tong (2007), is recognized. The four different motives introduced by Dunning (2000) underlying the FDIs performed by MNEs, are of different values to MNEs from advanced economies compared to MNEs from emerging economies. In this research strategic asset seeking is considered to be the main motivation for doing a FDI, since its importance is reflected in the rapid growth of intellectual capital as the key wealth-creating asset in most industrial industries (Dunning, 2009). However, the relation between strategic asset seeking motives and the ownership intensity of emerging market multinational enterprises (EM-MNEs) is underexposed, since most authors focus on FDIs undertaken by advanced market multinational enterprises (AM-MNEs) (Brouthers et al., 2003; Chen & Hennart, 2004; Hitt, & Lester, 2009). The purpose of this thesis is to create a better insight into strategic asset seeking motives and ownership intensity of both AM-MNEs and EM-MNEs and the differences between them. This research offers a combination of well-known theories on internationalization (Dunning, 1998) and on cross-cultural distance by Hofstede (1980), with new theories on global cities as an attractive location for MNEs (Goerzen et al., 2013). By using a sample of 159 strategic asset seeking FDIs from AM-MNEs as well as EM-MNEs in a period from 2010 until 2017, a better insight is created in the influence of strategic asset seeking on ownership intensity. The results of the hierarchical linear regression analysis show that AM-MNEs and EM-MNEs do not significantly differ in their ownership intensity when involved in a strategic asset seeking FDI. Neither is there a significant moderating effect found of the presence in global cities nor of the level of uncertainty avoidance.
Keywords: advanced multinationals enterprises, emerging market multinational enterprises, ownership choices, ownership intensity, uncertainty avoidance, global cities, strategic asset seeking motives, strategic asset seeking foreign direct investments, BRIC countries.
5
1. Introduction
International expansion and the motivations for expansions are a well-discussed topic in the field of international business. Expanding across borders gives multinational enterprises (MNEs) the possibility to tap into new markets (Hymer, 1976) and to achieve economies of scale and scope (Porter, 1986). Furthermore, cross-border expansion offers learning opportunities (Hitt et al., 1997) and can realize low-cost factor inputs (Makino et al., 2002). The most internationalization theories are focused on Advanced Market Multinational Enterprises (AM-MNEs) from developed markets, however, we also see new theories that explain the rapid growth and transformation process of internationalization from MNEs in emerging markets. Emerging markets are defined as low income and high growth economies, that use market liberalization as their main means of growth (Kedia et al., 2012). MNEs in Emerging Markets (EM-MNEs) have increasingly internationalized in a triad between Europe, North-America and Japan to create and gain intangible resources through strategic asset seeking Foreign Direct Investments (FDIs) (Rugman & Verbeke, 2004). For example Tata Steel, an agglomerate from India, undertook several acquisitions in the UK, they acquired companies such as Jaguar and Land Rover (Elia & Santagelo, 2017). The actual numbers of the United Nations Conference on Trade And Development (UNCTAD, 2015) show striking patterns of outflowing FDIs from emerging markets. For example, the developing Asia region is dominated by China with an FDI outflow of 128 billion dollar and an economic growth of 3.6% in 2015. Latin America is dominated by Chili with an economic growth of 31.4% and an FDI outflow of 15.5 billion dollars. The strong increase in FDI outflows of the BRIC countries is influenced by the case that EM-MNEs have benefited tremendously from inward FDIs from AM-MNEs, which gave them positive spillovers such as technological knowhow. These spillovers arose through Original Equipment Manufacturing (OEM) and joint ventures between MNEs and EM-MNEs. The AM-MNEs have transferred technological and organizational skills to emerging economies, that allowed EM-MNEs to learn from these skills and technological knowhow (Luo & Tung, 2007).
6
According to Dunning, a common motivation for internationalization for AM-MNEs and EM-MNEs is strategic asset seeking, characterized by the acquirement of intangible knowledge in order to reinforce the competitive position in a competitive environment (Dunning, 1996). For EM-MNEs, technological knowhow is especially important in order to overcome latecomer disadvantages and competitive disadvantages (Luo & Tung, 2007). A latecomer disadvantage is mostly formed through weak innovations systems in emerging economies. These systems are weaker because of a lack of decent education and government support. Dunning (2009) states that the growth of strategic asset seeking FDIs in the recent years is best demonstrated by the increasing role of mergers and acquisitions (M&As). Through M&As, MNEs can purchase companies to generate missing (technological) knowhow. Other opportunities to realize a strategic asset seeking FDI are greenfield investments, alliances, joint ventures or using a sales agent in a target country.
In this research the focus is on the acquired share in a target company performed by an AM-MNE or an EM-MNE to fulfill their strategic asset seeking motives. The acquired share will be measured in percent, and therefore the term ownership intensity will be used. The relation between strategic asset seeking motives and ownership intensity will be discussed with regard to EM-MNEs and AM-MNEs. In addition, the power of global cities and the impact of cultural distance will be used as moderating variables. Global cities are locations with interesting pull factors. The second moderator in this research is cultural distance, a concept often used within the international business literature, however without a real consensus about the effect on ownership intensity.
1.1 Research gap
Emerging markets have become more influential in the world economy; their economic growth is high and their FDI outflows are steadily increasing (UNCTAD, 2017). A remarkable growth in the literature written on emerging markets, such as Luo & Tong (2007), can be recognized. However, the relation between internationalizations and ownership intensity of EM-MNEs is quite underexposed, since most authors are focused on AM-MNEs (Brouthers et al., 2003; Chen & Hennart, 2004; Hitt, & Lester, 2009). As acknowledged by Contractor et al., (2014) the literature written on ownership intensity is quite underexposed.
7
The relations between strategic-asset seeking motives of AM-MNEs and EM-MNEs and ownership intensity, combined with cultural distance and global cities as moderating variables, has not been discussed in the literature on international business so far. Therefore, the main contribution of this research lies in extending the existing literature about AM-MNEs and EM-MNEs and their internationalization processes. In this research, the role of global cities in the internationalization process of both AM-MNEs and EM-MNEs exceptionally extends the literature. This is mainly because the concept of global cities is introduced quite lately by Goerzen et al. in 2013. The influence of global cities could influence the location choice of AM-MNEs and EM-MNEs, because creating and obtaining (technological) knowledge in global cities could be important for realizing strategic asset seeking motives. To bridge the gaps in the literature, the following research question has been formulated:
How does the effect of global cities and cultural distance moderate the relationship between
strategic-asset seeking motives and ownership intensity by AM-MNEs and EM-MNEs and what
are the differences between these two MNEs?
In this study a quantitative research method is used. The self-generated data exploited from the Bureau van Dijk’s Zephyr database provided input of 158 FDIs to give a statistically validated answer to the research question.
The structure of this research is as follows. In the first section, an overview will be given of the most relevant theories on internationalization motives of AM-MNEs and EM-MNEs, ownership intensity, global cities and cultural distance. In the second section the theoretical framework that underpin the hypotheses will be discussed, after which in the third section the methodology will be discussed. In the fourth section the results of the statistical analysis will be shown, and the last section covers the discussion, the limitations of this research, the managerial and policy implications, and the conclusion of this thesis.
8
2. Literature review
In this section an overview will be given of the relevant literature about AM-MNEs and EM-MNEs, internationalization motives, ownership intensity, cultural distance and global cities.
2.1 MNEs in advanced and emerging economies
MNEs are defined as groups of enterprises that have direct investments in enterprises in other countries than where their parent company is located (Buckley et al., 2002). The AM-MNEs are MNEs from advanced economies. According to the International Monetary Fund (IMF), advanced economies are defined as sovereign states that have a highly developed economy and an advanced technological infrastructure. The IMF uses the Gross Domestic Product (GDP), levels of industrialization, living conditions and the number of widespread infrastructure as determinants for assessing the position of economies. In 2017, the biggest amount of outflowing FDIs came from the United States, a highly developed economy. They had an FDI outflow of 299 billion dollars, followed by the Netherlands with an FDI outflow of 174 billion dollars (UNCTAD, 2017).
For many years, AM-MNEs were the core focus within the international business literature. However, the development of emerging markets and the growing presence of EM-MNEs brought a shift in the business literature: emerging markets and EM-MNEs gained more attention. EM-MNEs are defined as “international companies that originated from emerging markets and that are engaged in FDI. They exercise effective control and undertake value-adding activities in one or more foreign countries” (Luo & Tung, 2007). According to Luo & Tung (2007), emerging markets are low income and high growth economies that are using market liberalization as their main means of growth. There are various essential differences between the MNEs and the EM-MNEs. A first important difference between AM-MNEs and AM-MNEs is their relation with the government (Gammeltoft et al., 2010). In general, EM-MNEs have stronger relations with the government in their home country. Strong relations with the government can be valuable to EM-MNEs to acquire critical resources or support. Strong relationships offer also opportunities for governments in emerging markets.
9
The government can ask MNEs to fulfill certain objectives or wishes, and they can use MNEs for their own internationalization objectives and for increasing the country’s competitiveness in the international market. In some cases MNEs are owned by the state, this is called a fully state-owned enterprise. A second key difference between AM-MNEs and EM-MNEs is their institutional environment. Institutions are defined as formal and informal rules of the game, that shape relationships and behavior of people and organizations in a given region (North, 1991). Institutional environments in emerging economies are in general less developed, since ambiguous or absent rules can lead to uncertainty among companies. EM-MNEs can reduce the level of uncertainty by working together in business groups (Khanna & Yafeh, 2005). Within these business groups, MNEs share managerial skills and economic and technological resources. In this research the BRIC countries are considered and used as emerging economies. The BRIC countries, consisting of Brazil, Russia, India and China, are often seen as frontrunners of the emerging markets, seeing that their FDI outflows are strikingly growing. The FDI outflows from developing countries grew from 10% up to 35% from 2010 till 2014 (UNCTAD, 2015). China’s outward FDI flows for example, cover almost one third of the total global outward flowing FDIs in 2017 (UNCTAD, 2017). Hence, it is important to understand and to consider the importance of emerging economies and the growing presence of EM-MNEs within the international market.
2.2 Internationalization motives
The independent variable in this research are the internationalization motives of AM-MNEs as well as EM-MNEs. Building on Dunning (2000) and Luo & Tung (2007), several motives for FDIs are considered for AM-MNEs as well as for EM-MNEs.
Dunning (2000) introduced a framework to analyze determinants for a successful FDI by AM-MNEs. He argues that the geographical and industrial composition of the foreign productions facilities are affected by three components that determine the success of a foreign FDI investment. The first component refers to ownership advantages. Ownership advantages are firm specific advantages that can create a competitive advantage. Ownership advantages can be divided in assets and transactional advantages. Asset advantages can be intangible and tangible assets, and transactional advantages refer to the strengths of a company to coordinate a network of geographically dispersed subsidiaries.
10
The second component refers to location advantages in a certain host country, such as natural resources, demand conditions, institutional and cultural factors. Within the location advantages, Dunning made a distinction between four different reasons to do an FDI: market seeking, resource seeking, efficiency seeking and strategic asset seeking. In this research strategic asset seeking is considered as the main motivation for doing a FDI. The importance of strategic asset seeking can be justified by the rapid growth of intellectual capital as the key wealth-creating asset in most industrial industries. Moreover, the globalization of economic activities and the use of new communication and transport technologies gives more priority for creating and exploiting strategic assets (Dunning, 2009). The factual growth of strategic asset seeking FDIs is best demonstrated by the increasing role of M&As as modalities for FDIs. In 2015, the cross-border M&As increased from $432 billion in 2014 up to $721 billion.
Dunning’s framework is especially focused on AM-MNEs. However, we also see new theories that focus on the rapid growth and transformation of emerging economies. In contrast to AM-MNEs, EM-MNEs have been forced to not rely on the typical traditional advantages for internationalization, such as firm specific advantages. EM-MNEs exploit home-country specific advantages such as low-cost labor and natural resources in order to successfully internationalize. An important consequence of this contrast is the tendency of EM-MNEs to seek for technological knowhow in their home country and in host countries. This is also defined as a springboard effect: EM-MNEs use spillovers gained by cooperation with AM-MNEs in their home country for their own international expansion. By acquiring critical strategic resources, such as technological knowhow and managerial skills, EM-MNEs can overcome latecomer disadvantages and competitive disadvantages in the global economy (Luo & Tung, 2007).
Luo and Tung (2007) have introduced two different internationalization motives for EM-MNEs. The first motive is that EM-MNEs use international expansion to compensate for their competitive disadvantage. This competitive disadvantage is formally formed through the evidence that EM-MNEs usually have more tangible than intangible resources: EM-MNEs have a lack of technological knowhow.
One of the causes of the lack of technological knowhow is that emerging economies have a relatively weak National Innovation System (NIS) (Elia & Santagelo, 2017). A NIS represents a country’s ability to produce new knowledge (Freeman, 1987).
11
According to theories of the NIS, emerging economies have a weaker NIS, because the number of R&D facilities is relatively low and there is a lack of capabilities to create skills by education. In addition, the information systems in emerging economies are slower and less ramified because of a less developed IT infrastructure (Chaminade et al., 2009). In order to overcome these institutional disadvantages, EM-MNEs can create access to (technological) knowhow and brand names from AM-EM-MNEs in doing an FDI (Child & Rodriques, 2005).
The second internationalization motive stated by Luo & Tung (2007) is that EM-MNEs can use internationalization as a springboard to overcome their latecomer disadvantage. While AM-MNEs have an evolutionary path of internationalization, EM-MNEs do not have this path. An evolutionary path of internationalization refers to the incremental process of learning. Most AM-MNEs start with selling products and services in their home country followed by exporting, establishing a foreign sales subsidiary and the last step is a foreign production facility (Vahlne, 2013). Meanwhile, EM-MNEs use internationalizations as a springboard, which means that EM-MNEs use outward investments as a springboard to acquire strategic assets that are necessary to compete more effectively against global rivals, and to avoid institutional market constraints that they face in their home country (Luo & Tung, 2007, pp. 482). The internationalization of AM-MNEs is formally stimulated by push factors in their home country such as high operating costs or labor shortage, whereas EM-MNE’s internationalization is stimulated by pull factors, such as a desire to secure critical resources and to obtain managerial expertise abroad. As mentioned before: Dunning’s OLI paradigm is an important framework to assess internationalization success of AM-MNEs. AM-MNEs can overcome their cost disadvantages and inherent disadvantages in a given host country by using their own firm specific advantages. They perform an FDI because they are convinced that they can exploit their firm specific advantages, and that they can create a competitive advantage outside their home country. This is also known as asset-exploitation (Kedia et al., 2012). The primary reason for an EM-MNE on the other hand, is not exploiting firm specific advantages, but creating a firm specific advantage, which is called asset-augmentation. According to Kedia et al. (2012), EM-MNEs use aggressive, proactive and risk-taking acquisitions to overcome their latecomer disadvantage.
12
They argue that the key difference between AM-MNEs and EM-MNEs is the accelerated pace of internationalization. EM-MNEs need to be aggressive to be a global player.
2.3 Ownership intensity
The dependent variable in this research is the level of ownership intensity. AM-MNEs and EM-MNEs have different ownership choices to fulfill their strategic asset seeking motives. Ownership choices can be divided in acquisitions, greenfield investments, alliances or the use of a sales agent. In this research the ownership choice is measured in terms of ownership intensity. The focus is on the acquired share in a given target company performed by an AM-MNE or an EM-MNE. The acquired share is measured in percent on a scale from 1% up to 100%.
Choosing an appropriate ownership level is important for a foreign (successful) market entry, because it determines the control of the venture, the impact on the transfer of goods and services and it determines commitment of resources and risk. Acquiring an existing company by a foreign firm is the most frequent type of FDIs (Contractor et al., 2014). Contractor et al. (2014) make a distinction between full and partial acquisitions, and they argue that the differences between these two are underexposed in the literature. They consider an acquisition as partial when it is less than 99.99%. Chen (2008) describes pros and cons of partial and full acquisitions. He states that MNEs might prefer full equity investments in order to avoid possible management problems that could evolve in co-ownership structures. However, partial ownership can minimize capital commitments, the risks of investments and it offers learning opportunities. A consequence of doing a partial acquisition is that it might result in a greater organizational flexibility compared to a full-commitment in a full acquisition. In addition, in some cases the ability to increase ownership in the future is defined in a contract between the seller and the buyer: MNEs might have a possibility to acquire the full company after a certain period. In doing so, these contracts offer opportunities for MNEs to first learn about the local market before acquiring a company as a whole. Furthermore, these contracts enable MNEs to acquire a part of the shares of a company and to leave some shares to the former owners, which will insure some continuing support and guidance. Contracts are especially relevant in emerging markets, since in emerging markets family concerns dominate and control the market (Chen, 2008).
13
According to the recourse-based view, a full acquisition can generate synergy-based rents by integrating and accessing valuable assets and capabilities. Through a full acquisition, an MNE can compete more effectively in a foreign country (Lopez-Duarte & Garcia-Canal, 2004).
The institutional theory offers another vision on ownership intensity. Central is this theory is that MNEs from both developed and emerging economies need to respond to their institutional environment (Contractor et al., 2014). Institutions in a host-country consist of formal and informal rules which can be difficult for MNEs when they enter the host market. Berrry et al. (2010) state that a greater institutional distance between two countries results in a greater risk, that could have ramifications for FDIs undertaken by foreign MNEs. High institutional distance could create uncertainty in how resources, routines, procedures and knowhow are efficiently transported between the host and home country. The transportation of these resources is vital in case of strategic asset seeking FDI, since knowhow and procedures are the main driver for a strategic asset seeking FDI. Additionally, institutional distance increases obstacles for successfully establishing, monitoring and sustaining relationships with business partners, agents, suppliers, institutions and distributors. Different studies have specifically examined how differences in institutions can influence the ownership intensity of MNEs. Xu, Pan and Beamisch (2004) for example, found that a greater institutional distance (regulative and normative) is correlated with a lower level of ownership intensity. Moreover, a greater institutional distances could make the creation of legitimacy in a host country a quite complex and a time-consuming process (Dikova et al., 2010). Demirbag (2007) found that high corruption and/or transparency differences between home and host countries increase the likelihood of a partial acquisition.
2.4 Cultural distance
The first moderator in this research is cultural distance. Building on Hofstede (1980), Contractor et al. (2014) and Barkema and Vermeulen (1997), different visions on the effect of cultural distance on the ownership intensity will be considered.
14
In the last few decades, international business theories are focused on the concept of cross-cultural distance (Hofstede, 1980). Cross-cultural distance refers to the extent to which shared norms and values in one country differ from those in another country. Central in cross-cultural theories is the expansion behavior of MNEs and the successes of cross-border affiliates in combination with the differences in cultures between the home and host country (Hofstede, 2001).
Hofstede introduced one of the most famous frameworks to measure cultural distance: he states that there are four dimensions of cultural distance: power distance, uncertainty avoidance, individualism and masculinity. Power distance refers to the extent to which people believe and accept that power and status are distributed unequally within the society. Uncertainty avoidance refers to the extent to which people can handle uncertain, unknown or unstructured situations. Individualism refers to the degree to which a society emphasizes the role of the individual as opposed to that of the society. Masculinity at last, refers to the traditional masculine values such as competitiveness, assertiveness, achievement, ambition and high earnings that are present in a given society.
According to Contractor et al. (2014), the dimension uncertainty avoidance is specifically related to FDI since capital expenditures in foreign settings can be risk-assuming and could be more complicated by subsequent uncertainties after an FDI. This makes the transfer of firm routines, procedures and management practices more difficult. In addition, uncertainty avoidance brings complications for monitoring and creating stable relationships with stakeholders. Authors such as Rothaermel, Kotha & Steensma (2006) advocate that a high uncertainty avoidance level in a target country reduces the probability of market entry by an MNE. Whereas, Barkema and Vermeulen (1997) found that relatively high uncertainty avoidance scores will increase the likelihood of a wholly owned subsidiary (100% ownership intensity). Contrasting to Barkema and Vermeulen, Contractor et al. (2014) state that bigger differences in the levels of uncertainty avoidance between the host and home country will increase the likelihood of a minority acquisition. According to Pan (2003), MNEs originated from a country with a high uncertainty avoidance level are less focused on FDIs. Tse et al. (1997) state that countries with lower uncertainty avoidance scores are willing to take more risks, with the consequence of a higher ownership intensity which is line with the theory of Contractor et al. (2014)
15
In sum: we can conclude that there is no clear consensus on the influence of cultural distance on FDI investments. Nevertheless, most authors subscribe the statement that bigger differences in levels of uncertainty avoidance will increase the likelihood of a minority acquisitions which is a lower level of ownership intensity.
2.5 Global cities
The second moderator in this research is global cities. Goerzen, Asmussen and Nielsen (2013) introduced this concept, referring to cities that have interesting pull factors for AM-MNEs and EM-MNEs as location choice for an FDI. They state that global cities have three characteristics that distinguish them from other cities in the world, which make them especially attractive for MNEs. The first characteristic is international connectedness, referring to the presence of major financial centers, headquarters and transportation nodes. The second characteristic is the presence of advanced producer’s services, such as finance, law, accounting and advertising. The third characteristic is a cosmopolitan environment, bringing a need for good education, strong politics and communications. One of the main causes underlying the upcoming global cities, is the so-called Liability Of Foreignness (LOF), because the characteristics in a global city could diminish the LOF. This concept, introduced by Hymer (1976) and Kindleberger (1996) years ago, refers to the fact that MNEs have to deal with more costs in a given host country compared to their incumbent competitors. Several studies showed empirical evidence of these costs (Zaheer, 1995).
When combining the theory of Goerzen et al. (2013) with Zaheer’s theory (1995), an explanation can be given about how global cities can diminish the LOF, and why global cities are attractive to MNEs.
Zaheer (1995) introduces three components that could describe the causes of LOF. The first component that influences the LOF is complexity. MNEs suffer from the geographic separation between headquarters and subsidiaries, and this geographic separation can lead to significant problems, such as information asymmetry and the principal-agent problems (Luo, 2001). One possible solution for such problems is the interconnectedness of global cities to the global economy.
16
Interconnectedness makes it easier to transfer capital, goods, people and information between headquarters and their foreign subsidiaries. In addition, the agglomeration of advanced producer services in global cities, reduces the need for transportation of information between headquarters and subsidiaries. To conclude: the interconnectedness of and within global cities diminishes complexity, since complexity is better manageable (Edstrom & Galbraith, 1977). The second factor that influences the LOF is uncertainty (Zaheer, 1995). Uncertainty arises from the MNE’s unfamiliarity with a host country, such as unfamiliarity with legal and cultural norms. Uncertainty can lead to additional search costs and extra costs for flawed product launches. An MNE’s presence in a global city can diminish the negative effects of uncertainty, since the availability of extended IT infrastructures and availability of global media in global cities reduces the extra costs that are associated with uncertainty. The presence of extensive IT infrastructure guarantee that data about the local environment is widely available and highly codified. Furthermore, the agglomeration of advanced producers within the global cities stimulates learning, which reduces the level of uncertainty. The third factor that influences the LOF is discrimination. Discrimination occurs when MNEs are forced to use different rules and regulations instead of their domestic rivals (Kostova & Zaheer, 1999). Discrimination can be the result of the MNE’s lack of legitimacy in the local environment. Local stakeholders in global cities tend to be more cosmopolitan because these stakeholders are more familiar with foreign companies (Siguaw, 2012). An appreciation of diversity by local stakeholders, and a preference for international consumption and open-mindedness to other countries, will make foreign firms more legitimate in the eyes of customers, suppliers and prospective employees in the global cities.
17
3. Theoretical framework
In this section an overview will be given of the key concepts in this research and their mutual relations. First, the relationship between internationalization motives and ownership intensity will be discussed. In addition, the moderating influence of global cities and cultural distance on internationalization motives will be discussed, after which hypotheses will be formed in order to analyze relationships with statistical analyses.
3.1 Internationalization motives and the ownership intensity
Different authors discuss the influence of knowledge on ownership intensity, since strategic asset seeking is considered as a critical motive to internationalize for AM-MNEs as well as for EM-MNEs. Knowledge, knowhow, and other intangible resources are considered as vital components of strategic assets (Kedia et al., 2012).
Intangible resources play an important role in internationalization processes of AM-MNEs as well as for EM-MNEs since knowledge has become one of the preeminent resources of MNEs (Dunning, 2009). Although strategic asset seeking is important for both MNEs, the drive to seek strategic assets as part of an internationalization process arises from different points for MNEs and EM-MNEs. For an AM-MNE, a strategic asset seeking motive arises from a need to invest in brands, distributing networks or to gain knowledge about their host environment. In contrast, for EM-MNEs strategic asset seeking motives are mostly caused by the need to acquire technological knowhow to create firm specific advantages in order to overcome latecomer disadvantages and competitive disadvantages (Kedia et al., 2012).
In his OLI paradigm, Dunning (2000), focuses on the internationalization of mainly AM-MNEs. Dunning states that an AM-MNE can overcome its cost and inherent disadvantages in a certain host country by using its own firm specific advantages.
18
An important difference in the motives for internationalization between AM-MNEs and EM-MNEs, is that an AM-MNE’s primary reason to perform an FDI because they are convinced that they can exploit their firm specific advantages, and that they can create a competitive advantage outside their home country. This is also known as asset-exploitation (Kedia et al., 2012). EM-MNEs on the other hand, perform an FDI to create firm specific advantages in order to overcome latecomer disadvantages and competitive disadvantages, this also known as asset-augmentation. According to Kedia et al. (2012) EM-MNEs use aggressive, proactive and risk-taking acquisitions in order to overcome disadvantages by compensating for their lack of (technological) knowhow. According to Luo and Tung (2007) EM-MNEs use international expansion to compensate for their competitive disadvantage and as a springboard to overcome their latecomer disadvantage. An EM-MNE’s lack of knowhow is firstly influenced by their relatively weak national innovation system (NIS), which have shortages in terms of valuable R&D facilities and good education. One of the consequences of these shortages is that there are less diversified and underqualified workers in emerging markets, which makes it difficult for EM-MNEs to compete with other EM-MNEs (Chaminade et al., 2009). A second reason for the lack of technological knowhow by EM-MNEs is that information systems in emerging economies are slower and less ramified because of less developed IT infrastructures, which makes sharing knowledge more problematic.
Choosing an appropriate ownership level is important for successfully entering a foreign market for AM-MNEs as well for EM-MNEs, since it determines the control of the venture, the impact on the transfer of goods and services and the commitment of resources and risk (Contractor et al., 2014). Ownership intensity is discussed by many authors, by which a greater ownership intensity is recommended for reducing possible management problems and for acquiring full equity in order to create access to critical tangible and intangible assets. According to the resource-based view, a full acquisition can generate synergy-based rents by integrating and accessing valuable assets and capabilities. Through a full acquisition, an MNE can compete more effectively in a foreign country (Lopez-Duarte & Garcia-Canal, 2004).
19
On the other hand, a lower level of ownership intensity can minimize capital commitments, the risks of investments and it offers learning opportunities, which can result in a greater organizational flexibility (Chen, 2008). These contradictory statements give room for investigating to what extent each statement is applicable to EM-MNEs as well as to AM-MNEs.
When taking the strategic asset seeking motives into consideration together with the contractionary statements about the ownership intensity, the level of ownership intensity is expected to be higher for EM-MNEs than for AM-MNEs. The EM-MNEs competitive disadvantages, latecomer disadvantages, their weak NIS, and a lack of firm specific advantages make EM-MNEs more likely to engage in full equity or majority equity investments. Acquiring a bigger share in a target company will provide an EM-MNE with access to critical assets and it could be an appropriate solution to overcome latecomer and competitive disadvantages.
Therefore, the following hypothesis is formulated:
H1: When involved in a strategic asset seeking FDI, an EM-MNE will more likely acquire a bigger
share in a target company compared to an AM-MNE, who will more likely acquire a smaller share.
3.2 Moderating role of cultural distance
Contractor et al. (2014) state that out of the several sorts of cultural distance introduced by Hofstede (1980), uncertainty avoidance is specifically related to strategic asset seeking FDIs. This is because large capital expenditures in foreign settings are risk assuming and can be complicated further by subsequent uncertainties after a first FDI. Contractor et al. (2014) found in their research that when differences in uncertainty avoidance levels between a home and host country are greater, a minority acquisition is more likely to take place. Rothaermel, Kotha, & Steensma (2006) found that when the level of uncertainty avoidance in a target country is relatively high, the probability of market entry by a US firm within the internet industry will reduce.
Furthermore, Tse et al. (1997) found that countries with a lower uncertainty avoidance level are willing to take more risk, which is basically inherent to the definition introduced by Hofstede.
20
Building on the literature written on the influence of uncertainty avoidance on ownership intensity, a negative relationship between greater differences in uncertainty avoidance and ownership intensity is expected. This leads to the following hypothesis:
H2a: There is a negative moderating effect of differences in uncertainty avoidance on the relationship
between strategic asset seeking motives and ownership intensity for both EM-MNEs and AM-MNEs.
As mentioned before: an important difference in motives for internationalization of AM-MNEs and EM-MNEs, is that an AM-MNE’s primary reason to perform an FDI is that they are convinced that they can exploit their firm specific advantages and create a competitive advantage outside their home country, a process that is called asset-exploitation (Kedia et al., 2012). EM-MNEs on the other hand, perform an FDI to create firm specific advantages in order to overcome their latecomer disadvantages and their competitive disadvantage, a process that called asset-augmentation (Kedia et al., 2012).
When taking together the views of internationalization motives of both AM-MNEs and EM-MNEs with the influence of uncertainty avoidance on ownership intensity, expected is that the moderating effect of uncertainty avoidance on ownership intensity is negative for both AM-MNEs and EM-MNEs (see hypothesis H2a). However, based on the theory elaborated by Kedia et al (2012) and Luo and Tung (2007), the moderating effect of uncertainty avoidance on the relation between strategic asset seeking and ownership intensity is expected to be different in case of EM-MNEs than in case of AM-MNEs. This proposition is based on the idea that EM-MNEs operate in a different context, in which they have to cope with competitive disadvantages, latecomer disadvantages, a weak NIS and a lack of firm specific advantages. In order to overcome these drawbacks, EM-MNEs accelerate the pace of internationalization compared to AM-MNEs, and EM-MNEs use aggressive, proactive and risk-taking acquisitions to create firm specific advantages in order to be a global player (Kedia et al., 2012). This aggressive, proactive and risk-taking acquisitions lead to the proposition that EM-MNEs will take more risks in case of a high level of uncertainty avoidance compared to AM-MNEs. These higher risks are expressed in a higher-level ownership intensity.
21
In case of great differences in the level of uncertainty avoidance between the home and the host country, EM-MNEs are expected to acquire a bigger share in a target company in order to accomplish their strategic asset seeking goals compared to AMNEs. Therefore the following hypothesis is formulated:
H2b: In case of a high differences in the level of uncertainty avoidance in a target country, EM-MNEs
are more likely to acquire a bigger share in a target company compared to AM-MNEs.
3.3 Moderating role of Global cities
Goerzen et al. (2013) introduce the concept of global cities: cities that have interesting pull factors for MNEs as a location choice for an FDI. Goerzen et al. (2013) state that global cities have three characteristics that distinguish them from other cities: international connectedness, the presence of advanced producer’s services, and a cosmopolitan environment. These three characteristics reduce the LOF that MNEs face by doing business abroad. In case an MNE settles in a global city, the international connectedness of global cities can reduce the complexity that an MNE face from the geographic separation between headquarters and subsidiaries. The levels of uncertainty are lower in global cities, since the availability of extended IT infrastructures. Discrimination occurs when MNEs are forced to use different rules and regulations instead of their domestic rivals (Kostova & Zaheer, 1999). Discrimination is lower for MNEs that settle in a global city since the stakeholders in global cities tend to be more cosmopolitan, because these stakeholders are more familiar with foreign companies
Considering the different strategic asset seeking motives for both AM-MNEs and EM-MNE, the motives of EM-MNEs to seek strategic assets are mostly based on creating firm specific advantages in order to overcome latecomer disadvantages and competitive disadvantages. The strategic asset seeking motives for AM-MNEs on the other hand, are more based on exploiting firm specific advantages. Next to exploiting firm specific advantages, AM-MNEs motives are also influenced by push factors which make them eager to overcome labor shortages, to create access to (cheap) intangible resources, to invest in brands, and to focus on new distributing networks. As mentioned before, AM-MNEs perform an FDI mainly because they are convinced that they can exploit their firm specific advantages in order to attain a sustainable competitive advantages outside their home country (Kedia et al., 2012).
22
The primary reason to do an FDI for EM-MNEs on the other hand, is to create firm specific advantages, which called asset-augmentation.
Considering the presence of knowledge in global cities, the potential positive knowledge spillovers to MNEs and the number of other MNEs situated in the global city, global cities are expected to be more attractive and urgent to EM-MNEs for supporting the creation of firm specific advantages, for boosting their social and economic development, and eventually for compensating for their latecomer disadvantages and their competitive disadvantages. EM-MNEs are expected to acquire a bigger share and so have a higher ownership intensity in global cities compared to AM-MNEs. Expected is that the power of global cities as location choice is weaker for AM-MNEs. This expectation is based on theory that AM-MNEs perform a strategic asset seeking FDI to invest in brands, distributing networks or gaining knowledge about the host country and so the characteristics of a global city are less crucial for AM-MNEs. As mentioned in the literature review: AM-MNEs are more familiar with internationalizations and expected is that the LOF will be lower for AM-MNEs compared to EM-MNEs, since AM-MNEs have a more incremental process of internationalizations (Vahlne, 2013).
Hypotheses 3a and 3b are formulated as follows:
H3a: There is a positive moderating effect of global cities on the relationship between strategic asset
seeking motives and ownership intensity for both EM-MNEs and AM-MNE.
H3b: In case of being settled in a global city, the moderating effect of H3a will be stronger for
23
3.4 Conceptual model
Figure 1. Conceptual model
The discussed hypotheses are showed in the conceptual model as presented in figure 1.
As showed in the figure, the double plus means that when involved in a strategic asset seeking FDI, an EM-MNE will more likely acquire a bigger share in the target company compared to AM-MNEs who will more likely acquire a smaller share. The min in the figure means that there is a negative moderating effect expected of differences in uncertainty avoidance scores on the relation between strategic asset seeking and ownership intensity for both EM-MNEs and AM-MNEs. Although expected is in case of greater differences in uncertainty avoidance an EM-MNE will more likely acquire a bigger share in a target company instead of an AM-MNE who will acquire a smaller share, as showed with the min/ plus for EM-MNEs.
24
The plus in the figure shows that the presence of global cities will have a positive moderating effect on the relation between strategic asset seeking motives and ownership intensity, the double plus shows that this effect will be stronger for EM-MNEs and expected is that they will more likely acquire a bigger share in a target company in a global city instead of an AM-MNEs who will acquire a smaller share.
4. Methodology
In this research a quantitative approach is used for answering the research question. The output from Zephyr, World Bank and the Hofstede dataset generated the required data for the identification of the (potential) influence of strategic asset seeking motives on ownership intensity. Additionally, it showed how the two moderators, global cities and uncertainty avoidance contributed in this (possible) relationship. The dataset that is used for creating an overview of the cross-border activities of AM-MNEs and EM-AM-MNEs is collected from Zephyr and is specially created for this research.
4.1 Sample
The sample that is used for running the statistical analyses in SPSS, is a sample of acquisitions, mergers, joint ventures and minority stakes of AM-MNEs and EM-MNEs. The time period was focused on deals between 1/1/2010 up till 1/1/2017, whereby the claim was that the deal needed to be complete before 1/1/2017. The industry that is used in the sample is the manufacture of basis pharmaceutical products and pharmaceutical preparations; this industry is known as highly knowledge intensive. The most important shift in this industry is towards the strategic asset seeking FDI and the cause of this shift is the rapid growth in emergence of intellectual capital as the key wealth creating asset in most industrial modalities industries (Dunning, 2009).
25
4.2 Data collection
The data for the statistical analysis is downloaded from the Bureau van Dijk’s Zephyr database. The selection criteria that are used to find the correct data were: deal type, date of completion of the deal, target name, target country code, target city, target BvD ID number, acquirer name, acquirer country code, acquirer city, acquirer BvD ID number, acquirer number of subsidiaries and the data of incorporation. The raw data had to be cleared and after cleaning the outliers, 159 cross-border deals remained.
4.3 Variables
In this section an overview will be presented about how the different variables in this research are measured. First, the dependent variable, the ownership intensity will be described. Followed by the independent variable, namely the internalization motives of AM-MNEs and EM-MNEs. At the end the two different moderators, uncertainty avoidance and global cities will be described. Finally, the control variables will be explained.
Dependent variable: ownership intensity
The dependent variable in this research is ownership intensity, which is the acquired share in a certain target company, acquired by AM-MNEs or EM-MNEs. Different authors used different ways to measure the ownership intensity, such as Contractor et al. (2014) who have made a distinction between three categories – full, majority and minority and Chari and Chang (2009) who have made a distinction between full and partial acquisitions. For doing a more precious research, the acquired share in this research will be measured as an acquired share in percent on a scale from 1 up till 100 percent. The reason for this specific way of measurement is when the data will be arranged in classes it will lose their actual value, for example 99.9% will be a partial acquisition. Since we want to expose the actual differences between AM-MNE and EM-MNEs, it is quite important to use exact numbers.
26
Independent variable: strategic asset seeking motives by AM-MNEs and EM-MNEs
The strategic asset seeking motives of MNEs and EM-MNEs are measured with FDIs from AM-MNEs and EM-AM-MNEs. As introduced by Dunning (2009), the growth of strategic asset seeking FDIs in recent years is best demonstrated by the increasing role of mergers and acquisitions as modalities for FDIs: the merger and acquisitions are extended with joint ventures and minority stakes. By using the country codes from Zephyr an overview is created with FDIs originated from AM-MNEs and FDIs originated from EM-MNEs. By creating a dummy variable, the FDIs from AM-MNEs are labeled with a 1 in the dataset and the FDIs from EM-MNEs are labeled with a 0.
The BRIC countries are used for analyzing the FDIs of EM-MNEs. Most studies that are focused on EM-MNEs use India as research object (Nicholson & Salaber, 2013), as well is China often used in the literature (Deng, 2004). For the FDIs of AM-MNE’s, the United States are used (Contractor et al., 2014) complemented with FDIs of MNEs originated from Germany and the Netherlands. In 2017, the biggest amount of outflowing FDIs came from the United States, a highly developed economy. They had an FDI outflow of 299 billion dollars, followed by the Netherlands with an FDI outflow of 174 billion dollars (UNCTAD, 2017). The time period is focused on deals between 1/1/2010 up till 1/1/2017, whereby the claim was that the deal needed to be complete before 1/1/2017.
Moderator’s uncertainty avoidance and global cities
In the following section an overview will be given on how the two moderator variables, uncertainty avoidance and global cities are measured.
Uncertainty avoidance
The first moderator in this research is uncertainty avoidance. According to Contractor et al. (2014) uncertainty avoidance is specifically related to FDIs. The data for analyzing the uncertainty avoidance scores is collected from the database of Hofstede (Hofstede, 2018).
27
The uncertainty avoidance scores for the BRIC countries, the United States, the Netherlands and Germany are collected from the Hofstede database. By selecting the uncertainty avoidance scores of the home and host countries, an overview about the differences is included in the dataset. Important to notice is the fact that we are talking about the uncertainty avoidance scores in the target countries. As an illustration: a negative relation is expected when an AM-MNE from the Netherlands, with an uncertainty level of 53, enters the Russian market with an uncertainty level of 95. These negative differences will be showed in the dataset with a minus.
Global cities
The second moderator in this research are the global target cities. Through the obtained data about the cross-border deals and the locations, the influence of global target cities on the relation between strategic asset seeking motives and ownership intensity is examined. Goerzen et al. (2013) obtained a list of global cities in their article: these global cities are as mentioned before in the literature review selected on three characteristics. The first characteristic is the international connectedness of the city, the second characteristic is the presence of advanced producer’s services in the city and the third characteristic is the cosmopolitan environment. For the creation of a clear overview of the global cities, the first three given world cities as showed in table 1, will be handled as global cities: these are the alpha, beta and gamma cities. The last 67 given world cities are showing strong evidence of world city formation but are not real world cities (Beaverstok et al., 1999). The boundaries of the world cities are widely discussed in the literature. Gordon and McCann (2000) found that unlike the surrounding metropolitan of London, only the inner City of London was characterized by a high concentration of finance industries. Friedmann (1986) states that the territorial basis of the world city is not only the central city but also the economic space of the surrounding. For the sake of this research, the location name (city) given in Zephyr will be used as location choice. For the measurement of the global cities, a dummy variable is created, whereby 1 is indicating a global city and 0 is indicating a non-global city. In the table below, the list with global cities is presented.
28
The (global) city of origin is as well obtained in the dataset as a control variable. It could be possible that when an MNEs city of origin is a global city, that this will reduce the chance that an MNE will settle in a global city again since they already took profit from the advantages that a global city has to offer.
Table 1. World Cities
Alpha World Cities Bèta World Cities Gamma World Cities Evidence of World City Formation
Chicago Brussels Amsterdam Johannesburg Athens Detroit Mumbai Frankfurt Madrid Atlanta Kuala Lumpur Abu Dhabi Dresden New Delhi Hong Kong Mexico-City Bangkok Manila Adelaide Dubai Oslo London Moscow Barcelona Melbourne Almaty Dublin Philadelphia Los Angeles San Francisco Beijing Miami Antwerp Edinburg Richmond Milan Sao Paulo Berlin Minneapolis Arhus Genoa Rio de Janeiro New York Seoul Boston Montreal Auckland Glasgow Riyadh Paris Sydney Budapest Munich Baltimore Gothenburg Rotterdam
Singapore Toronto
Buenos
Aires Osaka Bangalore Guangzhou Seattle Tokyo Zurich Caracas Prague Birmingham Hanoi St Petersburg
Copenhagen Rome Bogota Helsinki Stuttgart
Dallas Santiago Bologna
Ho Chi Minh
City Tashkent Düsseldorf Shanghai Brasilia Kansas City Tehran Geneva Stockholm Bratislava Kiev Tel Aviv Hamburg Taipei Brisbane Leeds The Hague Houston Warsaw Bucharest Lille Tijuana Istanbul Washington Cairo Lima Turin Jakarta Calgary Lisbon Utrecht
Cape Town Luxembourg Vancouver Cleveland Lyon Vienna Cologne Manchester Wellington Colombo Marseille
Columbus Montevideo
Source: Beaverstock, Smith & Taylor (1999)
29
Control variables
In this section an overview will be given about the different control variables, why these variables are obtained in this research and how they are measured.
For the firm specific control variables, the following variables are selected: the years of experience in the business and the number of subsidiaries an acquirer owns. Bigger MNEs can typically more easily cover the costs of larger investments (Drogedijk & Slangen, 2006), which could result in more risky investments. The years of experience of an MNE, which is measured from the year of incorporation up till 2017 is generated from Zephyr. The experience of an MNE can have influence on the ownership intensity. More mature MNEs have more knowledge about foreign markets entries, since they are more experienced (Gaba et al., 2002). The number of subsidiaries the acquirer owns is generated from Zephyr as well and obtained in the dataset.
The country specific control variables that are used in this research are GDP per capita and common language. The reason that GDP per capita is used is because GDP per capita can be an important variable that could have influence on the choice of both AM-MNEs and AM-MNEs for the settlement in a certain country: a higher GDP per capita could reinforce a higher ownership intensity since it creates certainty (Brouthers et al., 2008). The different GDPs per capita are generated from the World Bank database. Through analyzing the dates when the deals were completed, an overview could be given about the different GDPs per capita in those specific years. As an illustration: when a deal was completed in 2011 between Russia and China, the GDP per capita in the target countries of those years are obtained in the dataset. The second country specific control variable is common language, since a non-common language can increase the transaction costs through uncertainties which could have an (negative) influence on ownership intensity (Demirbag et al., 2007). The common language will be measured by a dichotomous variable, a common language is labeled with a 1 in the dataset and a non-common language is labeled with a 0.
30
5. Results
In this section an overview will be given of the statistical tests that are performed in this research, after that, the results of the bivariate correlation analysis and the hierarchical linear regression analysis will be discussed.
Since ownership intensity as the dependent variable can be best measured on an interval scale, and since strategic asset seeking motives as independent variable is a dichotomous variable, a hierarchical linear regression analysis is the most suitable test (Brouthers & Dikova, 2009). Since a hierarchical linear regression analysis enables to add different variables in different models, the influence of different variables on ownership intensity can be analyzed. Fields (2009) states in his book that a linear regression analysis is a valid and robust test for measuring the strength and significance of the influence of an independent variable on a dependent variable.
By checking the assumptions for doing a linear regression, the dependent variable is analyzed with a scatterplot, a histogram, and a test for normality with the Kolmogorov Smirnov test. The results of these tests revealed that the dependent variable is distributed normally. After checking the Z-scores, the minimums, the maximums and the standard deviation, a several outliers were removed from the dataset, outliers were MNEs that had their year of incorporation 200 years ago.Afterwards, 159 deals remained for the linear regression. To test the relationship between the two moderators and the independent variable, the application PROCESS is downloaded and integrated in SPSS. The PROCESS application makes it possible to examine the influence of the dichotomous (moderating) variable global cities and interval variable uncertainty avoidance. The variable uncertainty avoidance is standardized for running the moderator analysis.
By running a bivariate correlation analysis, different correlations between the variables are found. The correlations are presented in table 2. However, none of these correlations are too strong to be harmful since none of them is above 0.7. Only when a correlation is above 0.7, it can be considered as harmful for the interpretation of results (Pallant, 2011).
31
The first notable correlation is the correlation between global cities of origin and ownership intensity. This correlation shows that when an AM-MNE or an EM-MNE comes from a global city, the ownership intensity is lower. Another notable correlation is that between the global city of origin and the target global city. As presented in the correlation matrix: when an AM-MNE or EM-MNE comes from a global city it will increase the likelihood that this MNE will settle in a global city again. As expected, the correlation between the years of experience in doing business and the country of origin shows that AM-MNEs are more experienced in doing a strategic asset seeking FDI. Noteworthy is the correlation between the number of subsidiaries an acquirer owns and ownership intensity; an increase in the number of subsidiaries reduces the ownership intensity.
32 Table 2. Means, standard deviations and correlations
Variable Mean S.D. N 1 2 3 4 5 6 7 8 9
1 Acquired share (Ownership intensity)
45,66 29,208 159 1
2 Strategic asset seeking FDIs from AM-MNEs and EM-MNEs
0,53 0.501 159 -0,136 1
3 (Global) target city 0,36 0,480 152 -0,056 0,034 1
4 (Global) city of origin 0,51 0,501 150 -0,282** 0,065 0,328** 1
5 Differences in uncertainty avoidance scores
1,93 15,197 159 0,098 -0,041 0,323 0,153 1
6 Common language 0,65 0,479 159 0,179* -0,626** -0,167* -0,215** -0,137 1
7 GPD per capita in target country 21925 19006 155 0,003 0,701** -0,051 -0,093 -0,059 -0,224** 1
8 Number of subsidiaries an acquirer owns
984 2673 142 -0,324** 0,319** 0,073 0,306** -0,047 -0,286** -0,097 1
9 Years of experience an acquirer has 29 32 142 0,164 0,365** 0,065 -0,078 0,064 -0,363** 0,149 0,061 1
33
The hierarchical linear regression analysis is performed with six models (see table 3 and 4). The first number in each row is the beta coefficient, followed by the standard deviation in the parentheses, and at the bottom of the table, the Nagelkerke Adjusted R square is presented (Chari & Chang, 2009). Model 1 shows the influence of the control variables: the number of subsidiaries an acquirer owns, years of experience an acquirer has, common language, GDP per capita and the global city of origin. Model 2 shows the influence of the moderator variables: global target cities and uncertainty avoidance. Model 3 shows the effect of strategic asset seeking motives of AM-MNEs and EM-MNEs on ownership intensity and is used for testing hypothesis 1. Model 4 and 5 show the effects of the moderating influence of global cities and differences in uncertainty avoidance on strategic asset seeking motives of AM-MNEs and EM-MNEs, and is used for testing hypotheses 2 and 3. Model 6 shows all the measured variables together: the control variables, the moderating variables and the strategic asset seeking motives.
34 Table 3. Results of the linear regression models
Model 1 Model 2 Model 3
Variables
Constant: Acquired share (Ownership intensity) 34,299*** (7,47) 32,953*** (7,634) 31,945*** (8,962) Control variables
Number of subsidiaries an acquirer owns 0,003*** (0,001) -0,003** (0,001) -0,003** (0,001)
Years of experience an acquirer has 0,220** (0,79) 0,197* (0,079) 0,198* (0,082)
Common language 12,609* (5,63) 14,361* (5,709) 14,694 (7.692)
GDP per capita in target country 0 0 0 0
Global target city 1,520 (4,996) 1,692 (5,026)
Global city of origin -6,971 (4,994) -6,600 (5,265) -6,221 (5,307)
Differences in uncertainty avoidance scores 0,246 (0,155) 0,246 (0,158)
Independent variable
Strategic asset seeking FDIs from
AM-MNEs & EM-MNEs 0,896 (10,270)
Moderator variables
AM-MNE/ EM-MNE x global target city AM-MNE/ EM-MNE x uncertainty avoidance
Nagelkerke Adjusted R Square 0,23 0,236 0,235
35 Table 4. Results of the linear regression models
Model 4 Model 5 Model 6
Variables
Constant: Acquired share (Ownership intensity) 31,47*** (8,98) 32,15*** (9,017) 31,68*** (9,06)
Control variables
Number of subsidiaries an acquirer owns -0,0029** (0,0009) -0,003* (0,009) -0,029** (0,001)
Years of experience an acquirer has 0,1973** (0,0808) 0,1977* (0,0820) 0,1972* (0,0824)
Common language 14,82 (7,69) 14,88 (7,74) 14,978 (7,808)
GDP per capita in target country
0 0 0 0,0001
(0,0002)
Global target city 1,6925 5,026 -0,256 (7,76) -0,188 (7,81)
Global city of origin -6,403 (5,0264) -5,76 (5,50) -5,92 (5,67)
Cultural distance uncertainty avoidance 3,37 (9,0352) 0,241 (0,158) 3,37 (3,31)
Independent variable Strategic asset seeking FDIs
from AM-MNEs & EM-MNEs 0,93 (10,31) -0,463 (11,09) -0,302 (11.212)
Moderator variables
AM-MNE/ EM-MNE x global target city 3,364 (10,18) 3,247 (10,26)
AM-MNE/ EM-MNE x uncertainty avoidance 0,76 (4,81) 0,6355 (4,85)
Nagelkerke Adjusted R Square 0,23 0,23 0,23
36
Model 1 shows the direct influence of the control variables on ownership intensity; the model is significant (P<0.001). As presented with the Nagelkerke Adjusted R Square, 23% of the variation in ownership intensity of AM-MNEs and EM-MNEs can be explained by these variables. A closer look to the control variables shows that the number of subsidiaries an acquirer owns (P<0.001), the years of experience an acquirer has (P<0.01) and common language (P<0.05) have significant relationships with ownership intensity.
In model 2, the two moderator variables: global target cities and the differences in uncertainty avoidance scores, are included. Model 2 shows a significant relationship (P<0.001) between the three control variables, the number of subsidiaries an acquirer owns (P<0.01), the years of experience an acquirer has (P<0.05), and common language (P<0.05), with ownership intensity. The Nagelkerke Adjusted R Square of 0,263, shows that 23.6% of the variation in the ownership intensity of AM-MNEs and EM-MNEs can be explained by this model. The two moderating variables: global target cities and differences in uncertainty avoidance scores both show a positive effect on the ownership intensity as presented with the positive β coefficient.
In model 3 the independent variable, strategic asset seeking motives is included. The model is significant (P<0.01), and the Nagelkerke Adjusted R Square of 0,235 shows that 23.5% of the variation in the ownership intensity can be explained by this variables. The control variables in model 3 are significant: the number of subsidiaries an acquirer owns (P<0.01) and the years of experience an acquirer has (P<0.05) have significant relationships with ownership intensity. As presented with a β coefficient of 0,896, the strategic asset seeking FDIs from AM-MNEs and EM-MNEs have a positive effect on ownership intensity. However, this effect is not significant, which means that there is no significant difference between the strategic asset seeking motives of AM-MNEs and EM-MNEs and the influence on ownership intensity. The outcomes of the one-way ANOVA test, show that the means of the acquired shares by AM-MNEs and EM-MNEs are not significantly different. EM-MNEs have a mean of a 50% acquired share while AM-MNEs have a mean of a 42% acquired share. This difference is predicted in hypothesis 1, however, the differences are not significant and therefore hypothesis 1 is rejected.
