Analysis of FDI patterns into Central and Eastern European countries : the case of Fortune Global 500

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Analysis of FDI Patterns into Central and

Eastern European Countries: The Case of

Fortune Global 500

Master Thesis - Final Version

Track: MSc Business Administration – International Management

Name: Kristina Kinkova

Student number: 11374802

Thesis supervisor: Dr. Niccolò Pisani

Second reader: Dr. Mashiho Mihalache

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2 Statement of Originality

This document is written by Student Kristina Kinkova who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

While most of the current research analysed the host-country determinants behind the location-choices of foreign direct investment in Central and Eastern European countries, little attention has been given to the extent to which firm-level factors influence the decision to enter these transition economies. Analysis of entry by Fortune Global 500 firms shows that both firm size and the level of multinationality are positively and significantly related to the likelihood of entering CEE-countries. Said this, neither home country economic subsidies, nor the level of home country corruption moderate the likelihood of entering at least one of the four CEE-countries. Interestingly, the findings revealed that the direct effect of home country economic subsidies on the likelihood of entering CEE-countries is significantly negative.

Keywords: foreign direct investment, location choice, firm size, level of multinationality, economic subsidies, level of corruption, Central and Eastern European countries

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Abbreviations

MNE Multinational enterprise FDI Foreign direct investment CEE Central and Eastern Europe FG500 Fortune Global 500 companies R&D Research and Development

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Table of

List of Figures & Tables

Figure 1: Conceptual Framework ... 28

Table 1: Host Country Determinants of FDI (Source: UNCTAD, 1998) ... 16

Table 2: Distribution of Home Countries of Fortune Global 500 ... 29

Table 3: Correlation Matrix ... 38

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1. Introduction

In the early 1990s, Central and Eastern European countries opened their markets to foreign investors. Since then, the so-called CEE countries have attracted an increased amounts of foreign direct investment (FDI) and international trade (Gelbudaa, Meyerb, & Deliosc, 2008). The countries of Central and Eastern European region, previously under influence and control of communist regimes, underwent significant political and economic changes in the 1990s and 2000s, establishing democratic systems and adjusting their markets towards a free market economy. These countries are similar in their political, economic, and social issues and demonstrate similar challenges, potential for development, and patterns of foreign investment (Vladescu, 2013). The CEE-economies are considered transition economies (Popescu, 2014) and show higher uncertainty levels compared to traditional market economies (Sušjan & Redek, 2008).

Authors studying the CEE-region often include Bulgaria, Czech Republic, Slovakia, Hungary, Poland, Slovenia, Estonia, Lithuania, Latvia, Romania and Bulgaria in their analysis (Dikova & van Witteloostuijn, 2007; Janton-Drozdowska & Majewska, 2016; Popescu, 2014). Yet, Central and Eastern European countries are far from being homogeneous, both at the volume, and growth of FDI. Differences among countries in this region are evident. While the countries in the Central Europe (Czech Republic, Hungary, Poland, Slovak Republic) have been highly attractive to foreign investors, the South Eastern European countries are falling behind (Carstensen & Toubal, 2004). Throughout the last years, most of the foreign direct investment (FDI) went to the Czech Republic, Hungary, and Poland. These are three of the largest transition economies in the Central and Eastern European region. Hence, they were the first to begin liberalisation (Holland and Pain, 1998). Together with Slovakia, they represent the Central and Eastern European countries in this study.

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8 According to a recent study, the majority of Central and Eastern European countries are becoming less successful in attracting FDI, as they do not provide an environment in which foreign companies wish to conduct their business (Janton-Drozdowska & Majewska, 2016). The question arises, what essentially drives multinational enterprises to invest in Central and Eastern European countries in transition. The initial academic research on these transition economies either attempted to analyse the traits of transition economy environment, or tried to apply mainstream theories to the transition context. Later, scholars progressed to align the existing theories with the rare context of transition economies. New theories were established to explain international business activities within the constraints of this unique environment (Meyer, 2001a; Gelbudaa et al., 2008). The majority of the studies on CEE-countries investigate the traditional host country determinants of FDI (Bellak, Leibrecht, & Riedl, 2008; Bevan & Estrin, 2004; Dauti, 2015). Existing empirical literature suggests that factors such as low labour costs and market size are usually perceived as drivers behind the location choices of firms into markets in transition (Lansbury, Pain, & Smidkova, 1996; Bevan & Estrin, 2004).

While only a restricted number of studies have analysed the impact of firm factors, firm’s international expansion can be an outcome of firm-level characteristics (Childs & Jin, 2015). However, the extent to which firm-level determinants influence location choice of multinational companies in transition economies has not been accordingly explored. Therefore, the purpose of this study is to fill the research gap in determining which firm-level variables play important role in entering transition economies. This study demonstrates the impact of firm size and level of multinationality on the market entry decision of multinational enterprises using the data of Fortune Global 500, the world's largest companies. To further contribute to the current research, this study examines the moderating role of home country economic subsidies on the relationship between firm size and likelihood of entering an CEE-economy in transition. Economic incentives effect foreign direct investments (Villaverde & Maza, 2015),

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9 however, only few authors study the effect of home country economic subsidies (Banno & Piscitello, 2010). Although high corruption levels have a negative influence on FDI, corrupt transition economies still attract investors (Cuervo-Cazurra, 2008). Studies mostly focus on the host country corruption (corruption in the location choice of FDI) and the effect of home country corruption (corruption in the country of origin) is rather neglected (Ferreira, Carreira, Li, & Serra, 2016). Therefore, the home country level of corruption is introduced to analyse its moderating influence on the relationship between the level of multinationality of a firm and CEE-market entry.

The study is structured as follows. The next chapter reviews the existing literature on foreign direct entry modes and FDI determinants, both in global context and transition economies context. Subsequently, hypotheses are formulated and theoretical framework is developed. In the methodology section, hypotheses are tested with variables and moderators using the data of Fortune Global 500 firms with foreign direct investment in CEE countries. Results and conclusion summarize the findings and define the implications for further research.

2. Literature Review

2.1. Foreign Market Entry Modes

In developing internationalisation strategies, firms should consider the foreign market entry mode (Meyer, Estrin, Bhaumik, & Peng, 2009), as well as the timing of entry (Isobe, Makino, & Montgomery, 2000), or their motives for entering specific foreign markets (Demirbag, Tatoglu, & Glaister, 2008). Entry mode research relates to the structure of operations companies use to explore foreign markets (Brouthers & Hennart, 2007). The choice of entry mode is one of the most researched aspects of foreign market entry decisions (Surdu & Mellahi, 2016), as the topic has received extensive attention over the years (Brouthers, 2002; Hennart & Slangen, 2014; Morschett, Schramm-Klein & Swoboda, 2010; Pan & Tse, 2000).

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10 Until now, existing literature has not yet recognized a unified categorization of foreign entry modes (Brouthers & Hennart, 2007; Hennart & Slangen, 2014; Hill, Hwang, & Kim, 1990). One aspect of the literature determines the entry modes along a continuum, starting with arranged contracts, joint ventures, and wholly owned subsidiaries. Along this continuum, the control, commitment, and risk increase. Wholly owned subsidiary is chosen as entry mode of maximum control, given that firms are willing to make maximum commitment and take on maximum risk (Brouthers & Hennart, 2007; Hill et al., 1990). However, most of the scholars agree that the entry modes fall into two distinctive categories: non-equity based modes and equity based modes (Hennart & Slangen, 2014). Export and contractual agreements are considered non-equity modes, while wholly-owned operations and equity joint ventures create the category of equity-based modes (Pan & Tse, 2000).

Compared to other international transactions, the equity-based market entries follow at a significantly higher speed as they allow firms to gain access to new technologies, markets, and managerial knowledge. As such they have significant impact on performance (Surdu & Mellahi, 2016). However, scholars disagree whether a subsidiary’s ownership mode (joint venture or wholly owned subsidiary) and its establishment mode (greenfield or acquisition) should be treated as different entry mode dimensions (Hennart & Slangen, 2014). Brouthers and Hennart (2007), as well as Dikova and Van Witteloostuijn (2007), distinguish four equity-based modes: greenfield joint ventures, wholly owned greenfield investments, partial acquisitions, and full acquisitions. In contrast, Chang and Rosenzweig (2001) differentiate between full acquisitions, joint ventures (including both greenfield joint ventures and partial acquisitions), and wholly owned greenfield investments.

To overcome challenges associated with a weaker institutional environment, the choice of entering via a joint venture grants firms access to many resources (Meyer et al., 2009). Although it is possible to acquire valuable resources and to minimize investment risk, when

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11 sharing ownership with a local partner, combining partner’s capabilities, interests, and goals with MNE’s own can be challenging (Dikova & van Witteloostuijn, 2007). Acquisitions ensure the access to intangible and organizationally embedded resources. Preferably, companies choose acquisitions, when they enter countries with a stronger institutional framework (Meyer et al., 2009). Aside from quickly establishing local presence in the foreign market, firms may experience post-acquisition integration failures, which are often determined by cross-cultural and technological differences (Dikova & van Witteloostuijn, 2007).

Entering a foreign market via greenfield investment gives firms the possibility to leverage their own strong intangible capabilities (Brouthers & Brouthers, 2000). The protection of managerial autonomy and full control over local operations are further advantages of wholly owned subsidiaries. However, without the assistance of a local partner, overcoming the liability of foreignness may be difficult (Dikova & van Witteloostuijn, 2007). Although greenfield entry mode ensures the preservation of corporate culture in the foreign market, the establishing period is longer, as the companies need more time to set up local business networks (Dikova & van Witteloostuijn, 2007). When firms wish to acquire certain capabilities from local expertise and experience a lack of location-specific resources, this can lead to market failure and acquisition and joint venture strategies are then favoured. In industries, in which firm-specific advantages compensate for the missing location-firm-specific advantages, greenfield entries are preferred (Anand & Delios, 1997).

A portion of empirical studies analyses the choice between greenfield and acquisition entry mode into the foreign market (Barkema & Vermeulen, 1998; Hennart & Park, 1993; Larimo, 2003). Hennart & Park (1993) examine Japanese firms and their entry modes into the U.S. market. Firms with weak competitive advantages choose to enter via acquisitions, while investors with strong advantages favour greenfield investments as a more efficient way to transfer these advantages. Reviewing the entry mode forms of Nordic firms into global markets,

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12 acquisitions seem to be overall the dominant form of entry mode for Nordic manufacturing firms. This is in contrast to the internationalisation behaviour of Japanese firms (Hennart & Park, 1993; Larimo, 2003). A study of Dutch companies shows that multinational diversity prompts firms towards greenfield investments in foreign markets instead of acquisitions (Barkema & Vermeulen, 1998).

Furthermore, the decision between wholly owned subsidiary and subsidiary with shared ownership has inspired several empirical studies (Brouthers, 2002; Hebous & Weichenrieder, 2010; Mihir, Desai, Foley, & Hines, 2004; Pan & Chi, 1999; Yiu & Mankino, 2002). Multinational firms favouring wholly foreign-owned subsidiaries achieve lower profits than MNEs entering China via equity joint ventures (Pan & Chi, 1999). An empirical study, using data on U.S. firms’ foreign branches, suggests that whole ownership mode prevails when firms organise their integrated production activities across different locations, transfer technology and are able to benefit from worldwide tax planning (Mihir et al., 2004). In periods of crisis, partially-owned affiliates achieve comparatively worse results in term of sales growth than wholly-owned subsidiaries (Hebous & Weichenrieder, 2010). The greater the corruption distance between host and home country, the more likely MNEs are to choose wholly owned subsidiary over a joint venture. On the contrary, the entry mode decision of MNEs from equally corrupt or more corrupt home countries is not affected by the corruption distance (Duanmu, 2011). Hence, distance, especially cultural distance, is one of the most frequently investigated aspects effecting the choice of entry modes (Hennart & Larimo, 1998; Morschett et al., 2010; Slangen & van Tulder, 2009; Tihanyi, Griffith, & Russell, 2005).

Studies find that a positive relationship exists between cultural traits and entry mode decisions (Morchett et al., 2010). Empirical results demonstrate that cultural characteristics of the home country do not influence entry mode decisions (Hennart & Larimo, 1998). While Tihanyi et al. (2005) fail to provide statistical evidence about the relationships between cultural

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13 distance and entry mode choice, Morschett et al. (2010) find a strong positive relationship between power distance as a cultural trait of the firm's home country and the tendency of MNEs to establish a wholly owned subsidiary. Complementing the research that demonstrates no relationship between culture and entry modes, Slangen and van Tulder (2009)’s findings support the evidence of the insignificant impact of cultural distance. However, they do demonstrate the weak influence of political risk on entry mode choice. Depending on the extent to which MNEs face expropriation, the effect of political hazards on the choice of market entry mode differs (Henisz, 2000).

Nevertheless, Yiu and Makino (2002) show that institutional variables, such as state influences, have stronger impact on entry modes decisions than cultural distance. Legal restrictions and weak intellectual property rights significantly determine the ownership level, while host country risk plays a less important role (Delios & Beamish, 1999). Furthermore, government corruption is an important and complex external issue reflecting on entry decisions (Rodriguez, Uhlenbruck, & Eden, 2005.

2.2. FDI Location Choices

Following the review of the literature on both non-equity and equity based entry modes, this study concentrates particularly on equity based foreign market entry decisions, i.e. entering a foreign market through foreign direct investment (Mudambi & Mudambi, 2002; Surdu & Mellahi, 2016) and the determinants of this decision. OECD (2015-2016: 76) defines foreign direct investment as “a category of investment that reflects the objective of establishing a lasting interest by a resident enterprise in one economy in an enterprise that is resident in an economy other than that of the direct investor. The direct or indirect ownership of 10% or more of the voting power is evidence of such a relationship.” While the literature on the potential motives of foreign direct investment is extensive, authors have not yet agreed on a general theory (Villaverde & Maza, 2015).

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14 The location choice of an MNE is a crucial decision, as the determinants which attract foreign firms to certain locations ultimately influence the firm’s competitiveness (Porter, 1994). Neoclassical trade theory attempts to explain FDI determinants first (Faeth, 2009). Since FDI demands market imperfections, the assumption of perfect competition is criticized by Hymer (1976). Foreign companies must possess ownership advantages such as product differentiation, managerial expertise, new technologies, patents, the existence of internal or external economies of scale, or government interference in order to be able to compete with local companies. Moreover, these ownership advantages also prevent the disadvantages of operating in foreign markets such as less information, higher risk, more uncertainty, physical and cultural distance, business ethics, the legal system, and further governmental regulations (Faeth, 2009; Hymer, 1976).

Additionally, Faeth (2009) identifies the dominant FDI determinants of earlier studies, such as marketing factors, trade barriers, cost factors and investment climate. Marketing factors, particularly market size, market growth, maintaining market share, and dissatisfaction with existing market arrangements qualify as the main determinants of location choice. Furthermore, cost factors, specifically the availability of labour and raw materials, lower production costs and financial inducements by the government are recognized as equally important. In addition, political stability, foreign exchange stability and a positive attitude to foreign investment are identified as motives of foreign direct investment in the earlier studies.

Vernon (1966) introduces four stages of product life cycle and considers the possibility of production at lower-cost as a driver for deciding on location. Aspects of multinational operations such as technology transfer or international trade in semi-processed products can be explained using a model of internalization of imperfect markets (Buckley & Casson, 1976; Buckley & Casson, 2009). Buckely and Casson (1976) base their analysis on the principle that “the boundaries of a firm are set at the margin where the benefits of further internalisation of

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15 markets are just offset by the cost” (Buckely & Casson, 2009: 1564). One of the fundamental theories that shapes the literature on determinants of FDI is the OLI paradigm (Bellak et al., 2008). The elective paradigm of Dunning (1980) argues that there are three main determinants of foreign direct investment, namely of three variables – Ownership-specific advantages (O), location-specific advantages (L) and internalization-specific advantages (I). Ownership-advantages are Ownership-advantages on the firm-level, which can be both tangible and intangible assets. Internalization-advantages appear when a firm can leverage and benefit from exploiting the ownership-advantages abroad to produce internally, rather than though the market. Finally, location-advantages are bound to the location, where the firm decides to produce (Bevan & Estrin, 2004; Dunning, 1980).

The institutional perspective for location choices of MNEs attracts growing attention. The focus of the institutional perspective lies on the embeddedness of the firms into local institutional environments (Kostova & Zaheer, 1999). Some of the literature, using institutional approach, recognizes that factors such as financial incentives, fiscal incentives, and other economic incentives influence foreign direct investments (Villaverde & Maza, 2015). The overall macroeconomic, financial, and institutional condition of the host country is a significant driver of FDI inflows (Popescu, 2014). Firms considering investment to a particular location base their decisions on the institutional factors of the given location. At a certain degree, firms entering foreign markets must adapt themselves to the local institutional framework to gain legitimacy and integration within the regional economic system (Kang & Jiang, 2012).

Dunning (2000) identifies four main motivations behind location choices for FDI - market seeking, resource seeking, efficiency seeking and strategic asset seeking. The World Investment Report (UNCTAD) from 1998 provides a good summary of host country determinants of FDI (Table 1). Market seeking investors are attracted by the host country’s market size, its income per capita, market growth and country-specific consumer preferences.

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16 Resource seeking investors strive for the availability raw materials, low-cost and skilled labour or physical infrastructure. Foreign direct investment, motivated by efficiency, is usually a consequence of reduced entry barriers and decreased transport costs (UNCTAD, 1998).

Following some empirical studies conducted globally across regions, various -determinants are affecting MNE’s decisions in different locations. For instance, market size, trade openness, preferential trade agreements and financial development play an important role for FDI inflows to Arab economies. Hence, the motives behind FDI in Arab economies appear to be resource seeking, considering the significance of oil supply variable (Aziz & Mishra, 2016). In African region, several significant determinants of FDI, namely government consumption, inflation rate, investment, governance (political stability, accountability, regulatory burden, rule of law) and initial literacy are recognized. However, market-seeking motives do no play a dominant role (Naude & Krugell, 2007).

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17 2.3. FDI Location Choices in Transition Economies

Following the review of the literature on FDI determinants in country specific economies (Aziz & Mishra, 2016; Naude & Krugell, 2007), several empirical studies examine FDI location choices precisely across transition economies (Bevan & Estrin, 2004; Dikova & van Witteloostuijn, 2007; Meyer, 2001b), and in particular across Central and Eastern European countries (Chidlow, Salciuviene, & Young., 2009; Sakali, 2015). Host institutions in transition economies impact the choice of entry modes, as underdeveloped institutions are responsible for higher costs of establishing wholly-owned affiliates (Meyer, 2001b). The degree of the host country's institutional advancement effects the establishment and entry mode choice of MNEs in transition economies (Dikova & van Witteloostuijn, 2007).

While the Central European countries attract noticeable amount of foreign capital, the South Eastern European countries, namely Romania and Bulgaria, do no draw the same amount of FDI inflows (Carstensen & Toubal, 2004). The different location choice of MNEs between Central Eastern and South-Eastern countries should be, as Carstensen and Toubal (2004) suggest, investigated with the help of transition-specific FDI determinants rather than exanimating traditional FDI determinants.

However, traditional economic variables such as labour costs and availability of skilled labour are generally reflected in discussion of foreign direct investment determinants across transition economies (Bevan & Estrin, 2004; Lansbury et al., 1996). Some investors are intrigued by the combination of relatively low labour costs and the availability of skilled labour in particular sectors and countries (Chidlow et al., 2009; Landsbury et al., 1996). The analysis of Gauselmann, Knell and Stephan (2011) supports the evidence that investors in CEE-countries are mainly interested in low (unit) labour costs affiliated with a well-trained and educated workforce. Furthermore, expanding market with high growth rates drives foreign direct investment in these countries (Gauselmann et al., 2011). In addition to labour

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18 availability, traditional drivers of firm’s internationalisation, namely natural resources such as oil and gas, and proximity to the land and sea, are ranked high by foreign investors coming to Russia, Azerbaijan, Kazakhstan and Ukraine (Kudina & Jakubiak, 2008).

Apart from unit labour costs, foreign direct investment from developed economies into countries in transition is influenced by host country size. Country risk proves to be an insignificant factor (Bevan & Estrin, 2004). The announcement regarding the European Union entry has had a significant impact on FDI inflows into Central and Eastern European countries (Clausing & Dorobantu, 2005). Timing and the form of privatisation programmes influence the pattern of foreign direct investment (Landsbury et al., 1996). Holland and Pain (1998) show that the method of privatization plays a key role (Holland & Pain, 1998). Control of corruption and corruption perception index significantly regulate inward FDI stock to the South Eastern European region and new EU member states (Dauti, 2015).

Furthermore, large part of foreign direct investment inflows in transition economies can be explained through gravity factors (Demekas, Horváth, Ribakova, & Wu, 2007). According to Demekas et al. (2007), unit labour costs, the corporate tax burden, infrastructure, foreign exchange regime, and trade regime find the most support in the empirical study. The empirical research of Günther and Kristalova (2016) confirms the influence of gravity factors in CEE-countries as “FDI flows are attracted from relatively large economies to relatively large recipient economies, but the gains from foreign production activities diminish with distance from the source economy” (Günther & Kristalova, 2016: 98). Market size, distance, and other traditional determinants of FDI influence inwards flows into transition economies (Dauti, 2015). Moreover, trade volume, followed by investment climate and density of transportation infrastructure are identified as important determinants (Deichmann, 2001). During the years before and after the 2008 financial crisis, Sakali (2015) attempts to find the impact of the economic and financial crisis on FDI as well as on the changes in patterns. The changes reflect

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19 the short-term viability of investment projects, rather than locational, traditional, and transitional determinants that modify slowly.

To conclude, several studies focus their research on specific countries in transition (Chidlow et al., 2009; Dauti, 2015, Zorska, 2005), while others collect evidence on FDI determinants of the entire regions (Bellak et al., 2008; Carstensen & Toubal, 2004; Deichmann, 2001; Gauselmann et al., 2011; Günther & Kristalova, 2016; Kudina & Jakubiak, 2008; Sakali, 2015). Most of the recent empirical research focuses on host country determinants in examining the choice of MNEs to enter the transition economies and CEE-countries (Bevan & Estrin, 2004; Holland & Pain;1998 Kudina & Jakubiak, 2008; Zorska, 2005). However, the extent to which firm-level determinants influence location choice of multinational companies in transition economies has not been properly examined. The purpose of this study is to fill the research gap in determining which firm-level variables play important role in entering transition economies. We follow the foreign direct patterns of the Fortune Global 500, the world's largest companies and their market entry into the Central Eastern European countries.

3. Theoretical Framework

As discussed in the literature review above, empirical studies on FDI determinants of MNEs location choices in the transition context have essentially centred their analysis around country-level factors, i.e. low labour cost and availability of skilled labour (Gauselmann et al., 2011, Landsbury et al., 1996), or host country market size (Bevan & Estrin, 2004; Dauti, 2015). Therefore, to address this research gap, this study focuses on the firm-level determinants and their role in MNE’s location decision-making. Additionally, literature recognizes economic incentives and their effect on foreign direct investment (Villaverde & Maza, 2015). However, the role of the home country incentives comes short in the majority of the empirical research (Banno & Piscitello, 2010). To contribute, this study examines the moderating role of home

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20 country economic subsidies. Furthermore, transition economies, though demonstrating high levels of corruption, receive relatively large amounts of foreign direct capital (Cuervo-Cazurra, 2008). Previous research identifies a negative effect of host country corruption level on the decision to enter a country, however the effect of home country corruption level remains rather unexplored (Ferreira et al., 2016). Therefore, this study tests the moderating influence of home country level of corruption in this study.

3.1. Firm Size and Market Entry into CEE-Countries

For several years, one of the frequently studied firm-level variables in the internationalisation literature is firm size (Blomström & Lipsey, 1991; Dass, 2000, Pradhan, 2004), as the likelihood of becoming a foreign direct investor is determined mainly by firm size (Blomström & Lipsey, 1991). Firm size has proven to be a crucial factor influencing firm survival and performance (Porter, 1980) that influences firm’s international diversification and enables the organization to achieve economies of size and scope (Dass, 2000). Although, some argued that there are no elemental differences between small and large firms (Casson, 1999), some studies, especially in the context of a firm’s internationalisation (Coviello & Martin, 1999), support the proposition that differences exist between large corporations and small and medium-sized enterprises. Smaller and larger firms vary in their managerial style, independence, ownership, and extent of operations (Coviello & Martin 1999; O'Farrell, & Hitchins, 1988). Johanson & Vahlne (1990) indicate that small firms are expected to take smaller internationalisation steps than large firms.

Larger firms are assumed to be in powerful position on the market and can keep later entrants from getting access to suppliers, markets, customers, and other necessary assets (Gaba, Pan, & Ungson, 2002, Kobrin, 1991). International expansion demands a considerably large resource commitment by the expanding firm. The larger a firm, the greater its ability to deal with the risks associated with internationalisation (Javalgi, Griffith, & White, 2003). Firm size

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21 has been frequently applied as a proxy to seize firm-specific advantages (Kirca, Hult, Deligonul, Perry, & Cavusgil, 2012; Lu & Beamish, 2004). Firm's specific advantages such as brand names, external and internal economies of scale, research and development, product differentiation, proprietary management skills, and government promotion policies normally increase with firm size or are more related to larger firms (Lin, 2010). Being larger in size allows firms to gain more resources to invest in innovation and to follow aggressive internationalisation strategies. This enables them to carry the costs and risks of internationalisation (Cohan, 1996, Kirca et al., 2012).

Furthermore, larger companies might be able to access resources denied to smaller firms and thereby support the organization while handling risks, resisting setbacks, and initiating changes (Dass, 2000; Kimberly & Evanisko, 1981). Larger firms can prevent risk through wider portfolios and benefit from superior bargaining power to attain grants from host country governments (Kirca et al., 2012). Since they have a greater ability to handle the risk and uncertainty associated with operating in foreign markets it is the large firms that usually engage in cross-border investment. As previously mentioned, firm size is connected to several benefits such as large resource base, easy access to market information, knowledge of procurement sources and preferential access to capital markets. These advantages likely favour larger firms to diversify their production overseas (Pradhan, 2004).

Most of the empirical studies on location choices of foreign firms do not distinguish firms by their characteristics, such as their size, and blend together various firm types (Cieślik, 2013). Different firm types may be provided with different opportunity costs of acquiring information about potential locations (Figueiredo, Guimarães, & Woodward, 2002). Large firms can gather more useful information in potential locations in addition to holding information on alternative locations (Arauzo-Carod & Manjón-Antolin, 2004). Following the reasoning in this section, large firms should be capable to combine resources outside their

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22 domestic markets, gather useful information in potential locations and handle perceived risks and uncertainties of transition economies. Thus, this study hypothesizes:

H1: Firm size is positively related to the likelihood of entering a CEE-economy in transition.

3.2. The Level of Multinationality and Market Entry into CEE-Countries

Another key dimension that extends to all theoretical frameworks, levels of empirical analysis and domains of investigation in international business literature is the degree of firm-level multinationality. Apart from being large in size, MNEs are regarded to be international in their operations, vision and strategies. Multinationality creates firm value due to the potential of multiple host countries to provide operational flexibility (Aggarwal, Berrill, Hutson, & Kearney, 2011). Firms are increasingly involved in broadening the geographic scale and scope of their international operations (Qian & Li, 2002). Large companies, such as IBM, Colgate-Palmolive, Xerox, and Hewlett-Packard obtain 50 per cent or more of their revenues and profits from foreign markets rather than earning these revenues in their home market (Shapiro, 1996; Qian & Li, 2002).

Qian and Li (2002) define foreign involvement or multinationality in terms of geographic scale. Degree of internationalisation, international geographic diversification, international expansion, geographic scale or scope of foreign operations, and multinationality are just several terms that have been used interchangeably (Kirca, et al., 2012). Following Kirca et al. (2012), the term multinationality refers to the degree to which a firm’s expansion stretches out beyond the borders of its home market into new host country markets and geographic regions to engage in value-adding activities. Multinationality indicates the firm’s current state of internationalisation rather than the process of internationalisation. The arguments, to which extent the degree of multinationality contributes to firm’s value, are not conclusive. Scholars have initially searched for evidence of a positive linear relation, however the mixed results

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23 have led to the investigation of various possible nonlinear relations, such as quadratic, U-shaped, and horizontal S-shaped (Aggarwal et al., 2011). Grant (1987) in his research among a sample 304 British firms confirms that higher level of multinationality leads to increased profitability.

Firms with a higher percentage of overseas operations diversify their risks as they serve multiple markets, which show distinctive political instability and exchange rate fluctuations (Annavarjula and Beldona, 2000; Geleilate, Magnusson, Parente, & Alvarado-Vargas, 2016). Important outcomes of multinationality are technological and organizational learning, which eventually lead to improved financial performance. Furthermore, contributing positively to a firm’s financial performance, international diversification ensures greater operational efficiency (Hitt, Tihanyi, Miller, & Connelly, 2006). A higher level of multinationality will allow firms to exploit market imperfections and firm-specific assets (Buckley, 1988; Caves, 1971; Lu and Beamish, 2004).

International diversification allows MNEs to tap into different resources and allows firms to provide better and more flexible production, to scan markets for profit opportunities, and to gain greater learning and international experience (Contractor, 2007). Firms operating in foreign countries gather knowledge that can be used for later expansion to host countries (Shaver, Mitchell, & Yeung, 1997). Foreign markets offer unique resource endowments and assets bound to the home country location, which firms might not be able to find in their domestic markets. To explore these advantages, firms might be encouraged to establish operations in the host countries, to gain access to these specific advantages (Kogut & Chang, 1991; Lu and Beamish, 2004). Although there is no guarantee that a firm might be able to successfully transfer the experience gained from one market to another (Gaba et al. 2002), this study hypothesizes that the higher the level of multinationality, the more likely is a firm to leverage its international experience entering transition economies. This could allow MNEs to

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24 distribute risks and, concludingly, leverage operational flexibility and gain location-specific assets and knowledge. Thus, we summarize:

H2: Level of multinationality is positively related to the likelihood of entering a CEE-economy in transition.

3.3. The Moderating Effect of Home Country Economic Subsidies

Over the last couple of decades, the approach towards inward foreign direct investment has alternated considerably, as most countries have liberalized their policies to attract investments from foreign multinational corporations. Despite the mixed evidence on the advantages of FDI, increasing number of nations are offering services and incentives to attract investment by multinational firms, as the area of foreign investment promotion has become an active area for policy changes (Charlton & Davis, 2007). Moreover, recent econometric studies of the effects of FDI incentives, in particular fiscal preferences, suggest that they have become significant determinants of international direct investment flows (Taylor, 2000). The competition between governments aiming to attract FDI has also been subject to numerous studies (Barros and Cabral 2000; Haaparanta 1996). As previously mentioned, FDI incentives, such as financial and fiscal incentives, can be anticipated to significantly influence patterns of international investment (Blomström & Lipsey, 1991; Villaverde & Maza, 2015). Yet, only little attention has been given to the role of home country financial subsidies to support outward FDI of companies (Banno & Piscitello, 2010). Subsidies are defined as “a transfer of money from the government to an entity “(Economic Times, n.d.). The term subsidy is often used interchangeably with the term incentive (e.g. Banno & Sgobbi, 2010).

The home government’s policy requirements and preferences can influence firms’ capabilities to take these risks in the context of uncertainty and information asymmetries concerning foreign markets (Lu, Liu, Wright, & Filatotchev, 2014). Firms following these

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25 requirements benefit from financial support, favourable exchange rates and taxation (Luo, Xue, & Han, 2010). Since internationalisation involves risks and demands significant proportion of firm’s resources (Javalgi et al., 2003), firms utilize public incentives in order to amplify the risk of challenging circumstances of cross-border operations, in which they experience difficulties (Torres, Clegg, & Varum, 2016). Today’s governments are facing a challenge to develop appropriate measures aimed at reducing market failures, uncertainty, risks, while simultaneously encouraging firms to obtain or develop the resources needed for internationalisation (Bannò, Piscitello, & Varum, 2014).

The boost of outward international expansion through incentives attempts to lower economic and political risks, to help overcome uncertainties and close the information gap, and to relieve any lack of resources and capabilities of a company that begins to internationalise or seeks to invest in geographically culturally and institutionally distant environments (Banno & Sgobbi, 2010; Te Velde, 2007). Banno and Piscitello (2010)’s results support the positive effects of the financial incentives on firm’s growth.

The mechanism behind subsidies is mainly associated with firm’s lack of resources and capabilities. However, the costs of information gathering and screening, as well as a lack of international experience and fewer capabilities might lead to reduced awareness of these public subsidies. Therefore, certain firms might be neglected from the process of participation due to the lack of their knowledge about these incentives (Torres, Clegg, & Varum, 2016). Larger firms that are usually in possession of the necessary resources can carry the costs of information and screening. The gathered international experience leads to increased awareness of incentives. Furthermore, economic subsidies can relieve any deficiency in resources and capabilities of MNEs and help them to overcome uncertainties associated with internalization into unknown transition markets. Thus, we hypothesize:

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26

H3: The level of economic subsidies provided to the firms by the home country government positively moderates the relationship hypothesized in H1.

3.4. The Moderating Effect of Home Country Corruption Level

Governmental corruption, in this context meant as both home and host country corruption, is a significant player in international business activities (Cuervo-Cazurra, 2006). A corrupt economy does not support open and equal market opportunities to all competitors. Corrupt practices such as payments to the governmental representatives do not add to market value and even increase the cost of goods when compared to a competitive market (Habib & Zurawicki, 2002). Corruption reduces the economic growth of a country (Mauro, 1995) due to high costs, involved risks, uncertainty of doing business, and ineffective distributing of resources (Stoain & Mohr, 2016). Moreover, corruption is recognized as a policy variable influencing almost all aspects of social and economic life, especially in developing countries (Freckleton, Wright, & Craigwell, 2012). Corruption is defined as “the abuse of public power by government officials for private gain” (Cuervo-Cazurra, 2006: 807). Government officials gather “bribes for providing permits and licenses, for giving passage through customs, or for prohibiting the entry of competitors” (Shleifer & Vishny, 1993: 599).

Presence of corruption in a country represents a lack of compliance with rules and regulations that regulate interactions in societies. It indicates the need to make extra irregular payments to accomplish operations (Cuervo-Cazurra, 2006). In general, corruption, both in a host and a home country, can have a direct effect on foreign direct investment, as corrupt practices raise the costs of doing business by including bribes and other questionable expenses (Robertson & Watson, 2004). Furthermore, weak or missing property rights legislation and poor enforcement are often identified in corrupt environments, creating uncertainty and additional costs for firms and hinder both domestic strategy and home market growth (Shleifer & Vishny, 1993; Stoian & Mohr, 2016). Participating in corrupt practices, both in the host and

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27 home country, is often risky as it can lead to reputational damage and influence firm performance (Luo, 2005; Rose & Thomsen, 2004; Stoian & Mohr, 2016).

High home country corruption prevents MNEs in acquiring firm-specific competitive assets such as technology, brand name, organizational skills (Cuervo-Cuzarra and Genc, 2008). MNEs comply with their home country conditions while designing their international expansion strategies (Luo & Wang, 2012). Hence, the advantages that arise from international expansion seem to be formed by constraints of the home country environment. (Geleilate et al., 2016). MNEs with lower levels of corruption at home are more committed in cross -borders activates than those coming from highly corrupt countries with low quality of governance (Geleilate et al., 2016; He and Cui, 2012). Multinational firms are more accustomed to function in transparent environments, as they find it difficult to overcome the administrative burdens in corrupt environments (Wu, 2006). In that sense, home country corruption can determine the location choice of MNEs. Firms from a home country with relatively low levels of corruption are not accustomed to deal with the formal and informal institutions related to corruption (Godinez & Liu, 2015). Corruption distance does not seriously hinder outward direct investment from more-corrupt countries as much as it prevents firm from less-corrupt countries to invest abroad (Wu, 2006).

Higher home country corruption increases the costs of doing business in the domestic market and hence limits the scale of multinational activities of companies. On the other hand, multinationals from a country with lower levels of corruption will avoid risk and uncertainty of more corrupt markets, such as those of transition economies (Cuervo-Cazurra, 2008). Furthermore, multinational companies operate in business networks, in which multiple agents are interconnected and embedded. While companies operate a portfolio of direct business relationships, they are also confronted with the existence of many indirect business relationship and mediocre connections that mediate the direct relationships (Thornton, Henneberg, &

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28 Naudé, 2013). Home country level of corruption can influence the indirect business relationships of MNEs with the actors such as governments or trade organizations. Corrupt partners in company’s business network can prevent multinational companies from leveraging their international experience and knowledge, as they raise the costs of doing business and thus negatively moderate the likelihood of entering CEE-transition economies:

H4: The level of corruption of the home country negatively moderates the relationship hypothesized in H2.

The relationships as hypothesized in this chapter result in the following conceptual framework:

Figure 1: Conceptual Framework

4. Methods

4.1. Sample and Data Collection

The sampling frame of this study includes the world’s 500 largest companies, ranked annually in accordance to their total revenue in American dollars for the fiscal year 2015 by the Fortune magazine. Together for the fiscal year 2015, Fortune Global 500 companies generated $27.6 trillion in revenues, employed 67 million people worldwide and were present in 33 countries (Fortune, n.d.). Fortune Global 500 firms are typically multinational enterprises in that “they produce and/or distribute products and/or services across national borders”

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29 (Rugman & Verebke, 2004: 6). Examining the firm-level determinants and the likelihood of entering Central and Eastern European countries, the sample frame of Fortune Global 500 companies is chosen for its substantial size in revenues and number of employees as well as its dispersed geographical presence. The sample consists of a total of 500 companies with home base in 35 different countries across 21 different industries. The secondary data for this study is retrieved from two different sources: ORBIS database and annual reports of the companies. ORBIS database provides detailed accounting and financial information for the largest firms across the world. The data is collected and made available by Bureau van Dijk, a large international consultancy firm. Additionally, annual reports of companies are collected to support the final dataset. Due to missing information of some companies, the hypotheses can be tested on a final sample of 465companies from the Fortune Global 500 list. Most Fortune Global 500 companies are home-based in United States (26.88%), followed by Chinese companies (19.57%). The third most represented country of origin among FG500 is Japan (10.11%). European countries Germany, France and United Kingdom are almost equally represented in the sample (Table 2).

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30 4.2. Variables and Measures

Dependent Variable

This study tests for one dependent variable, CEE-market entry, to measure whether a company enters the four Central and Eastern European transition economies, namely Czech Republic, Hungary, Poland, Slovak Republic, via foreign direct investment. For the purposes of this study, the CEE-market entry is coded with a dummy variable. A MNE with a subsidiary in at least one of the four countries is coded as ‘1’, which means ‘CEE-market entry’ and a MNE with no subsidiary in these transition economies is coded as ‘0’, meaning ‘no CEE-market entry’.

Independent Variables

The independent variable, firm size, will be measured estimating total number of employees. Empirical studies either test for firm size using the amount of total sales (Huang & Song, 2006) or number of employees (Brouthers, 2002). Despite most research includes only one single indicator for firm size (Camiso´n-Zornoza, Segarra-Cipre´s, & Boronat-Navarro, 2004), recent empirical work gravitates towards involving both, the number of employees and total sales, as indicators to assess the size dimension more accurately (Beker-Blease, Kaen, Etebari, & Baumann, 2010). Using the provided data for the purposes of this study, rescaled size variable measured by number of employees is included to test the independent variable (number of employees/100,000).

To calculate the level of multinationality of a company, this study measures international sales in relation to total sales of MNEs. Researchers have employed a variety of measures to examine global focus of a company. Most of the studies use aggregate measures to calculate a firm’s multinationality level. A common multinationality measurement is the ratio of the number of overseas subsidiaries in relation to all subsidiaries (Yang, Martins, &

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31 Driffield, 2013) and perhaps the most frequently used measure of international diversification is the proportion of a firm's sales derived from operations outside the home country to total sales. (Rugman & Verebke, 2004). Thus, the second independent variable in this study is measured as international sales divided by total sales.

Moderating Variables

This study analyses the moderation effect of home country economic subsidies and home country corruption level on the relationship between firm-level determinants and market entry. For the purposes of this study, the subcategories of the Fraser Institute Index that since 1996 publishes annual reports examining the impact of economic freedom on investment, economic growth, income levels, and poverty rates, will be used. The EFW index now ranks 159 countries and territories and is divided in several subcategories. The EFW index will be used for the first moderator in this study – home country economic subsidies. Following the definition of subsidy as “a transfer of money from the government to an entity “(Economic times, n. d.), the subcategory, “transfers and subsidies” is used. The index measures general government transfers and subsidies as a share of GDP. The formula, this score is based on, generates lower ratings for countries with larger transfer sectors (Gwartney, Lawson, & Hall, 2016). Thus, the lower the country scores on the scale from 0 to 10, the more likely is for MNE to get economic subsidies.

Furthermore, under the category “Business regulation”, the subcategory “Extra payments / bribes / favouritism” will be used as a baseline to test the level of home country

corruption. To score high in this part of the index, countries must allow markets to determine

prices and refrain from regulatory activities that prevent entry into business. The score is based on questions concerning undocumented extra payments, bribes, illegal payments aimed at influencing government policies, or the extent to which government officials show favouritism,

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32 ranged from 1 (always) to 7 (never) (Gwartney et al., 2016). Thus, the lower the country scores on the scale from 0 to 10, the higher is the corruption level in the respective country.

Control Variables

Control variables include additional variables on firm-level. Firstly, the study controls for firm

age, measured as the year of data collection minus the year of firm foundation. Firm age has

potentially an impact on international operations and how these operations perform (Zahra, Ireland, & Hitt, 2000). Furthermore, the study control for firm’s profitability. Profitability, defined as return on assets (ROA), is included because it is expected to positively affect internationalisation (Herrmann & Datta, 2005). Profitability is reported to influence multinationality, because well-performing firms are likely to have the resources necessary to successfully diversify internationally (Hitt et al., 2006). This study controls for industry type, as there are differences in internationalisation attributed to speciﬁc industries (Westhead, Wright., & Ucbasaran, 2001). Included are dummy variables for 3 most represented industries in the sample of Fortune Global 500 companies. Besides, this study controls for ownership, as different types of ownership impact firms, while influencing their internationalisation (Fernandez & Nieto, 2006). This control variable is a dummy variable, coded ‘1’ for ‘state ownership’ and ‘0’ for ‘other’. Innovative firms are expected to be more capable of conquering international markets and to embrace investment opportunities across borders (Filippetti, Frenz, & Ietto-Gillies, 2011). Innovation results from internal R&D efforts, which in turn are based on firm’s accumulated knowledge (Knight & Cavusgil, 2004). Therefore, this study controls for R&D expenses of FG500 firms (rescaled: R&D expenses/1000).

4.3. Statistical Analysis and Results

After importing the finalized data in SPSS, first steps in the analysis are carried out to control for missing or incorrectly entered data and to test for multicollinearity by assessing the

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33 correlations between all the predictor variables. Furthermore, testing the data for frequencies, several missing cases are identified. SPSS recognizes 38 missing cases for the dependent variable ‘CEE-market entry’ out of the total number of 465 companies provided in the sample. Additionally, no outliers are recognized among dummy coded variables, as the indicators for minimum and maximum of the variables lay between 0.00 and 1.00. To eliminate any possibility of multicollinearity, a listwise correlation is run to verify that none of the variables correlate too highly (>.7). Multicollinearity can occur when there are high levels of correlation (Field, 2009). None of the independent, dependent and control variables correlate very highly (about 0.7), concluding that multicollinearity is not a potential issue.

Several significant correlations are found. Firm size positively correlates with CEE-market entry (r =.285, p < 0.01) and both independent variables positively correlate with each other (r =.245, p < 0.01). Furthermore, the second independent variable - the level of multinationality - is positively significantly correlated with the dependent variable CEE-market entry (r =.412, p < 0.01) and with several control variables. Positive correlation is observed between multinationality and age, indicating that older firms are more multinational (r =.342, p < 0.01) and corruption (r =.467, p < 0.01). Negative correlation is observed between multinationality and ownership (r =-.327, p < 0.01) and subsidies (r =-.392, p < 0.01). Age positively correlates with the dependent variable (r =.267, p<0.01). Ownership negatively correlates with multiple variables: market entry (r =-.349, p<0.01), age (r =-.265, p<0.01) and profitability (r =-.190, p<0.05). An average firm in the sample of Global Fortune 500 list has 131, 070 employees and is approximately 59 years old. 17 per cent of the companies are from the financial industries, 16 per cent operate in the wholesale and retail business and 25 per cent are manufacturers. 21.1 per cent of the Global Fortune 500 companies are state owned. The average corruption level in the countries of origin of the FG 500 companies is 6.49, which is considerably higher than the average score of the CEE countries (4.76). Subsequently, the

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34 average score on economic subsidies is approximately 5.78 (for comparison, CEE = 4.31). The level of multinationality is measured as international sales to total sales. 285 companies provide information on distribution of their sales and report for an average level of multinationality of 44.87 per cent. This indicates that on average, 44.8 per cent of sales is retrieved from outside the home market. Finally, out of the 427 firms, which grant information about their subsidiaries, 191 have entered at least one of the Central and Eastern European countries.

In this study, the dependent variable market entry is coded ‘1’ for entry and ‘0’ for no entry in the CEE-countries. Considering that the dependent variable is a dichotomous variable, i.e. binary variable, a binary logistic regression is appropriate to test the relations proposed in the hypotheses (Fields, 2009). For the purposes of multiple hypotheses in this study, all the relevant relationships need to be tested. Thus, several logistic regressions will be run in the statistical program SPSS. The Beta (b) coefficient describes the change in the logit of the outcome variable associated with a one-unit change in the predictor variable and the significance reflects whether the variable has a significant impact on predicting the dependent variable (Fields, 2009).

Model 1 in the analysis includes only the control variables so that their effect on the dependent variable (CEE-market entry) can be identified. Model 2 introduces the independent variable, firm size, measured in rescaled number of employees, to the analysis and allows for testing of hypothesis 1. Model 3 presents the second independent variable and level of multinationality is introduced to test hypothesis 2. Furthermore, to examine the effect of the moderator variables (home country economic subsidies and level of home country corruption), interaction terms are created. The interaction term is a product of the respectable independent variable and a moderator variable. Model 4 includes the independent variable firm size, moderator variable home country economic subsidies, and their interaction term, which allows for testing of hypothesis 3. Model 5 includes the independent variable level of multinationality,

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35 moderator variable level of home country corruption, and their interaction term, which allows for testing of hypothesis 4.

Model 1 introduces only the control variables into the regression. Out of the 7 control variables, 3 are highly significant. AGE positively influences the likelihood of entering at least one of the four CEE-countries (b=.008, p=.048). Furthermore, MANUFACTURING (coded: ‘1’ = firm is active in the manufacturing industry, and ‘0’ = firm is operating in a different industry) is also positively and significantly related to CEE-market entry (b=1.243, p=.001). Lastly, OWNERSHIP (coded: ‘1’ = state ownership, and ‘0’= other) is negatively and significantly related to the dependant variable (b=-2.167, p=.000). Model 2 introduces the first independent variable and tests the first hypothesis in this study, which proposes that firm size is positively related to the likelihood of entering at least one of the four Central and Eastern European transition economies. The coefficient of firm size is significant and positive (b =8.661, p =.000). The hypothesis 1 shows that firm size is positively related to the likelihood of entry into CEE-transition economies and therefore, hypothesis 1 is supported. Model 3 analyses the second hypothesis in this study. Hypothesis 2 assumes that level of multinationality positively relates to the likelihood of entering either of the four Central and Eastern European transition economies. The coefficient of the level of multinationality is significantly and positively related to the likelihood of entering a CEE-transition economy (b = 2.324, p =.001). The results demonstrate support for hypothesis 2. Companies with higher level of multinationality, so higher ratio of foreign sales compared to total sales, are more likely to enter at least one of the four Central and Eastern European transition economies. Hence, the more a company participates in foreign markets, the odds ratio of entering a CEE-transition economy increases by 10.219 times.

Model 4 assesses the first moderation effect and includes the interaction term needed to test hypothesis 3, which states that home economic subsidies positively influence the

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36 relationship hypothesised in hypothesis 1. In order to test the moderation effect, an interaction term is generated by multiplying the mean-centred variable home country economic subsidies with mean-centred independent variable of firm size. The coefficient of the interaction term is negative; however, the relationship is non-significant (b = -.118; p = .270). The hypothesis 3 that suggests that home country economic subsidies positively moderate the relationship between firm size and the likelihood of entering a CEE-transition economy, is rejected. Interestingly, the direct effect of home country economic subsidies is significantly negatively related to CEE-market entry (b = -.396; p = .000). Model 5 tests the moderation effect of home country corruption level on hypothesis 2. To evaluate the influence of this moderation effect, a further interaction term is computed. The interaction term is a multiplication of the mean-centred variable home country corruption level with the mean-mean-centred independent variable of the level of multinationality. Although Model 5 shows negative moderating effect of home country corruption on the relationship between the level of multinationality and CEE market entry, this effect is not significant (b=-.321, p=.532). Therefore, hypothesis 4 is also rejected. Furthermore, home country level of corruption has no significant direct effect on CEE-market entry.

Lastly, Chi-square and the Nagelkerke R2 are included to assess the model fit. The Chi-square measures the difference between the model in its current state and the model when only the constant is included. This way, Chi-square answers the question how much better the model predicts the outcome variable. Nagelkerke R2 visualizes how much of the variance is explained by the model (Fields, 2009). Compared to the baseline control Model 1, R2_{in Model 2 increases} from .330 to .416, suggesting that Model 2 fits the data better. However, in Model 3, R2 decreases to .353. This could be due to a lower number of recognized cases, as larger portion of companies is missing data on the level of multinationality. The R2 keeps improving when home country economic subsides are introduced as moderation variables in the analysis (R2 =

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37 .540), however decreases again when corruption level and its moderation effect on hypothesis 2 are tested (R2 =.357).

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38 Table 3:Correlation Matrix

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39 Table 4: Results of Binary Logistic Regression

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40

5. Discussion

While firms’ cross-border investment could be an outcome of firm-level characteristics, only a limited number of studies have investigated the impact of firm factors on this type of investment (Childs & Jin, 2015). Current research on the chosen locations for foreign direct investment into transition economies is largely based on the host-country level (Bevan & Estrin, 2004; Chidlow et al., 2009; Dikova & van Witteloostuijn, 2007; Sakali, 2015). In contrast, this study has adopted a conceptual framework which integrates firm-level determinants as predictors of market entry into the Central and Eastern European transition economies. The empirical results of this study confirm that firm size and level of multinationality significantly influence the location-decision of MNEs to invest in CEE-transition economies. The first hypothesis assumes that firm size is positively related to the likelihood of entering a CEE-transition economy. The results show a significant positive relationship and therefore, this hypothesis is supported. Furthermore, level of multinationality is also positively and significantly related to the probability of a firm entering CEE-transition economies. However, no evidence is found in support of both moderating effects. Within the constraints of this study, the relationship between firm size and likelihood of entering CEE-transition economies is not moderated by home country economic subsidies. Similarly, the connection between level of multinationality and likelihood of entering a CEE-country is not influenced by home country level of corruption of a MNE. The following sub-chapters will discuss academic relevance, managerial implications and limitations and the implications for future research.

5.1. Academic Relevance

This study contributes to the current research on foreign direct investment determinants and location choices. More precisely, it adds to the literature that examines the location choice of multinational enterprises from the firm-level perspective. Both hypotheses conclude that the

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41 decision behind entering Central and Eastern European countries is not determined solely by host-country level factors, but indeed firm-level factors also play a significant role.

The far-reaching effects following from being large in size are responsible for the decision to enter a market, rather than the firm size itself (Lin, 2010). Commonly, the core of the current research, which supports the influence of firm size on internationalisation, is the hypothesized access of large firms to significant amount of resources. Larger firms could invest their resources in innovations and thus pursue rather aggressive internationalisation strategies. Furthermore, larger firms are able to carry the costs and risks, and manage to perform better (Cohen, 1996, Kirca et al., 2012) and are more likely to enter foreign markets earlier (Gaba et al., 2002). The results of this study contribute to the previous research, as the findings support the positive influence of firm size on MNEs internationalisation into CEE-countries. Larger firms could be more resilient and have enough resources to deal with the risks associated with entering Central and Eastern European economies.

Furthermore, the findings prove that the level of multinationality is significantly and positively related to the likelihood of entering CEE-countries. The higher the scale of a firm’s international operation, the more likely the firm is to enter transition economies. Hence, this could be based on the hypothesised mechanism that geographically diversified firms are more likely to leverage their international experience entering transition economies. Internationally diversified firms manage to gain greater learning and international experience (Contractor, 2007) and apply the gathered knowledge in later expansion to host countries (Shaver et al., 1997). MNEs could than distribute their risks and, concludingly, leverage their operational flexibility and gain location-specific assets and knowledge in the CEE-region.

Although the moderation effect of home country economic subsidies on the relationship between firm size and the likelihood of entering a transition economy has not proven significant, economic subsidies show a negative and significant direct effect in the relationship

Analysis of FDI patterns into Central and Eastern European countries : the case of Fortune Global 500