Home Country Environment and the Internationalization-Performance Relationship

The international performance of MNEs from emerging versus developed home markets and the

effect of R&D intensity

Master Thesis MSc in Business Administration – International Management Track

University of Amsterdam

Inge Kodden

10871330

Supervisor: Dr. L.E.D. DiVito

Second reader: Dr. M.K. Westermann-Behaylo

San Francisco, 24th of March 2017

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! !

Statement of Originality

This document is written by Inge Kodden, 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

Although many scholars studied the existence of the Internationalization and Performance (I-

P) relationship, the influence of a multinational enterprise’s (MNE) Home Country Environment is

understudied. R&D Intensity was previously found to moderate the I-P relationship, but its potential

moderating role via the MNE’s Home Country Environment moderation effect is unclear. Prior

research suggests Emerging Market (EM) MNEs benefit more from internationalization and a focus

on R&D than Developed Market (DM) MNEs because of 1) their potential to learn from established

actors in the global market; 2) their higher flexibility resulting from more risky home country

institutional environments. A quantitative database study is performed to research the moderation-

moderation effect of Home Country Environment (EM vs. DM) and R&D intensity on the I-P

Relationship. Results show Home Country Environment moderates the I-P relationship. The

moderation effect for R&D intensity was not significant, although interaction effects indicate low-

medium R&D intensity minimizes the differences in performance between EM and DM MNEs. The

results contribute to International Business literature by mapping predictors of MNE success.

Furthermore, the results contribute to institutional theory by showing isomorphism in informal

institutional values between both markets, indicating home country formal institutional risk is a

better predictor for MNE international performance.

Key words: Internationalization, Performance, Home Country Environment, R&D Intensity,

Institutional Theory, Formal Institutions, Informal Institutions

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Table of Contents

Abstract ..................................................................................................................................... 2"

List of tables and figures .......................................................................................................... 5"

1. Introduction .......................................................................................................................... 6"

2. Literature review ................................................................................................................ 10"

2.1 Internationalization drivers, costs and benefits ............................................................. 10"

2.2 The Internationalization and Performance relationship ................................................ 15"

2.2.1 The moderating effect of R&D intensity ................................................................ 17"

2.2.2 Integrating perspectives .......................................................................................... 18"

2.3 Home country environment and the I-P relationship ..................................................... 19"

2.3.1 Institutional context ................................................................................................. 19"

2.3.1.1 Formal institutions ........................................................................................... 20"

2.3.1.2 Informal institutions ......................................................................................... 23"

2.4 Market types ................................................................................................................... 25"

2.4.1.1 Developed market MNEs ................................................................................. 25"

2.4.1.2 Emerging market MNEs .................................................................................. 26"

2.4.1.3 Internationalization-Performance assumptions for EM versus DM MNEs ..... 26"

2.5 Conceptual Framework and Hypotheses ....................................................................... 28"

3. Methodology ....................................................................................................................... 31"

3.1 Research design ............................................................................................................. 31"

3.1.1 Validity and reliability ............................................................................................ 31"

3.1.2 Sample ..................................................................................................................... 32"

3.1.3 Variables and measures ........................................................................................... 33"

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3.1.3 Data analysis ........................................................................................................... 36"

4. Results ................................................................................................................................. 41"

5. Discussion ............................................................................................................................ 47"

6. Conclusion ........................................................................................................................... 51"

References ............................................................................................................................... 53"

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List of tables and figures

Figure 1 Multinationality and Performance: a Three-Phase Model 17

Figure 2 Conceptual Framework 30

Table 1 Average firm size in net sales 32

Table 2 Variable definitions 35

Table 3 Means, Standard Deviations, Correlations 38

Table 4 DM MNE home countries and institutional values 39

Table 5 EM MNE home countries and institutional values 40

Table 6 Hierarchical Regression Analysis I 41

Table 7 Hierarchical Regression Analysis II 42

Table 8 Moderation-Moderation Analysis 44

Figure 3 Moderation effect of Market Type 45

Figure 4 Institutional differences between DM and EM MNE HQ locations 45

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1. Introduction

Multinational enterprises (MNEs) compete in the global market through their

international network of subsidiaries and partnerships. The decision to internationalize into a

foreign market is one of their most significant strategic decisions (Arregle, Miller, Hitt &

Beamish, 2013; Hitt, Hoskisson & Kim, 1997). As a result, the relationship between an

MNE’s level of internationalization and performance (I-P) has received ample academic

attention (i.a. Bausch & Kist, 2007; Rugman & Oh, 2010; Arregle, Miller, Hitt & Beamish,

2013; Musteen, Datta & Francis, 2014). There is consensus in International Business

literature on the existence of a relationship between Internationalization and Performance.

Results on the direction and strength of the relationship are inconclusive, however, with

different studies finding support for completely contradicting relationships based on different

theoretical perspectives (Ruigrok & Wagner, 2003; Capar & Kotabe, 2003; Contractor,

Kundu & Hsu, 2003).

One of these perspectives stresses the importance of institutional differences. Scholars

solely studying the firm level of analysis neglect home country level institutional influences

that have been found to significantly influence a firm’s international performance (Peng,

2002; 2009). Markets are not completely integrated or completely isolated, a result of

different institutional rules and regulations (Ghemawat, 2003). Studies that do consider

location specific institutional factors focus either on firms from developed markets or on

firms from emerging markets (Douglas & Eden, 2004; Kumar & Singh, 2008; Luo & Tung,

2007). Surprisingly little attention has been given to the distinctive differences between firms

from these market types in relation to internationalization and firm performance, and thus the

potential role of the home country institutional environment in influencing successful

internationalization. Even if a sample consists of firms from different market types, the

difference between firms from emerging versus developed markets is not addressed (e.g.

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Palich, Carini & Searman, 2000; Elango & Sethi, 2007). The importance of research on the

home country environment effect was confirmed by the meta analytical studies conducted by

Bausch and Kist (2007) and Marano et al. (2016), that found a more modest positive I-P

relationship for EM MNEs compared to DM MNEs.

Furthermore, firm level assumptions of international business are designed to explain

DM MNE activity but do not always apply to EM MNE behavior (Luo & Tung, 2007;

Marano et al., 2016). Take for example the moderation effect of R&D Intensity on the I-P

relationship: high R&D Intensity was found to moderate the I-P relationship (Lu & Beamish,

2004; Kotabe, Srinivasan & Aulakh, 2002; Musteen, Datta & Francis, 2014). Studies on the

EM MNE’s internationalization process indicate successful internationalization is even highly

dependent on a focus on technological innovation (Luo & Tung, 2007; Musteen et al., 2014

Purkayastha, Manolova & Edelman, 2016; Hsu, Lien & Chen, 2015). EM MNEs can learn

from established market firms, creating the opportunity of using the DM MNEs’ experience

as a springboard to successful rapid internationalization (Luo & Tung, 2007).

More research is required specifically to map the moderating effect of home country

environment and R&D intensity on MNE performance at different levels of

internationalization (Lu & Beamish, 2004; Marano et al., 2016; Bausch & Kist, 2007). The

study’s main contribution thus will not be proving the existence of the I-P relationship itself,

nor is it to add to the debate on its shape and direction. This thesis’ primary goal is to fill the

gap in IB research by examining and comparing the effects of firm level and country level

influences on the I-P relationship for firms from developed versus emerging markets (as

categorized by the United Nations Trade and Development Report). The research question is:

“What is the effect of home country environment and R&D intensity on the

internationalization and performance relationship for firms from developed versus

emerging countries?”

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The sample consists of 600 MNEs from developed and emerging markets collected

from the UNCTAD Trade and Development Reports over a three-year period to account for

temporal influences (2010-2012). After accounting for missing data and inactive firms, the

sample consists of 422 data entries in total. The assumed relationship between variables is a

moderation-moderation effect of the moderator R&D intensity on the moderator home

country environment for the I-P relationship. The three-way interaction is tested by multiple

regression analysis, more specifically by using Hayes’ (2012) PROCESS tool for SPSS.

The overall I-P relationship was negative. The home country environment was found to

moderate the Internationalization and Performance relationship, with EM MNEs generally

benefitting more from internationalization than DM MNEs. R&D intensity did not appear as a

statistically significantly moderator in this three-way interaction model. Inspection of the

Johnson-Neyman scores indicated low to medium R&D intensity minimizes the differences

between EM and DM MNE performance. This study’s main contribution to literature is that it

proofs the moderating effect of Home Country Environment on the I-P relationship, showing

the considerably higher performance potential of internationalization for EM MNEs compared

to DM MNEs. Additionally, the study finds that informal institutional values are almost the

same for EM versus DM countries while formal institutional values differ greatly. This

indicates that home country formal institutional risk is a better predictor of international

performance.

First, the literature review lays the foundation for this thesis by offering the detailed

theoretical background for the empirical study. Core concepts and their relation as studied in

previous research are reviewed, resulting in the theoretical framework on which the research

question hypotheses are based. The quantitative data and research methodology are described

in chapter three. In chapter four, the results of the statistical analysis are provided and the

applied models are specified. Also, the result discussion includes a short discussion on the

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limitations of the data and the performed analyses. In the following chapter the significance of

the findings is discussed and the answer to the research question is provided, as well as the

study’s implications to the academic debate. Finally, chapter six concludes this thesis by

summarizing the highlights and the key research contributions.

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2. Literature review

The following literature review forms the foundation of this study by reviewing how

core concepts have previously been found to be related. In the next section (2.1) a review of

existing theories on the drivers, costs and benefits of internationalization follows. The basic

considerations for internationalization decisions are defined here, setting the stage for a more

critical review of the current status of the literature on the I-P relationship specifically in

Section 2.2. In this section, the way the advantages and risks of internationalization have been

found to impact MNE performance are addressed and compared, and the moderating effect of

R&D Intensity is specified. In section 2.3 the current status in academic literature regarding

the moderating influence of home country environment on the I-P relationship will be

discussed. In the same section, R&D intensity will be defined in relation to the home country

environment – specifically its potential moderating effect on EM versus DM MNE

performance. In 2.4, finally, the review ends with the conceptual framework of the thesis and

hypotheses.

2.1 Internationalization drivers, costs and benefits

Firms internationalize by entering foreign markets and conducting parts of their

business across borders (Hitt, Hoskissen & Kim, 1997). The general motive is to exploit

market imperfections and to generate economies of scope and scale. To exploit market

imperfections and be successful internationally, firms have to be able to deploy their

capabilities across different contexts. Firms base their entry decision on coordination costs of

the entire network and costs of operating in the foreign market versus the benefits that

accessing the new market bring, for example the opportunity to access resources (Dunning,

2000; 2001).

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Classic IB theory holds that internationalization impacts performance positively when

MNEs are able to recombine their Firm Specific Advantages (FSAs) with foreign Country

Specific Advantages (CSAs) (i.a. Rugman & Verbeke, 1992; Birkinshaw, Hood & Jonsson,

1998; Rugman, Verbeke & Nguyen, 2011). FSAs are defined as specific capabilities of a firm,

for example proprietary know-how and optimal coordination and control mechanisms.

Consider, for example, a firm that has the specific technological capabilities to offer a good or

service with improved durability vis-à-vis competitors: it has a competitive advantage

compared to other firms in the same market. CSAs, on the other hand, are not tied to a firm

but to the MNE’s home country or host country. Different locations bring different

advantages and risks - from knowledge spillovers due to proximity to other firms, to

differences in government regulation (Rugman & Verbeke, 1992). Firms therefore aim for a

fit between their own capabilities and the potential risks and advantages of a host country

when considering internationalization to drive performance and minimize costs of

internationalization. In other words, firms aim to exploit market imperfections by redeploying

and recombining FSAs in multiple countries (Rugman & Verbeke, 1992). IB scholars

generally agree on the basic drivers of internationalization. The considerations for operating

internationally, however, can be divided into two main perspectives: the internalization theory

(Dunning, 2000; 2001) and the Uppsala model (Johansson & Vahlne, 1990; 2013).

2.1.1 Internationalization: OLI advantages and experiential learning

An MNE can in theory chose to expand in any market it seems fit. Foreign market entry

enables a firm to gain access to resources outside of the home market environment, creating

the opportunity of improving its competitive advantage. Dunning’s (2000; 2013) eclectic

paradigm specifically points out three motives for internationalization, also referred to as OLI

advantages: 1) Ownership advantages; 2) Location advantages, and; 3) Internalization

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advantages (Rugman et al., 2011) Ownership advantages include tangible and intangible

assets, but also transactional variables that come from benefiting from operating and

geographically dispersed network. Location advantages, or CSAs, influence the location

decision of MNEs. Specific countries have CSAs that are a better fit with the firm’s FSAs or

goals than others, making some countries more attractive than others. Internalization

advantages relate to the advantages of recombining FSAs internally as compared to dealing

with external parties via contractual arrangements (Dunning, 2000; 2001; Rugman et al.,

2011). Dunning’s (2000; 2001) theory falls in the wider stream of theory called

‘internalization theory’, which focuses on the costs and advantages related to internalizing

business processes through FDI compared to other entry modes in international markets. Four

accepted FDI motives based on Dunning’s (2000; 2001) eclectic paradigm are:

1. Market seeking: to satisfy specific foreign markets;

2. Resource seeking: to gain access to natural resources;

3. Efficiency seeking: to more efficiently organize the division of labor or

specialization of the existing portfolio of foreign and domestic assets;

4. Strategic asset seeking: to make optimal use of, and protect, the O-specific

advantages and to reduce the advantages of competitors (Dunning, 2000).

These four motives imply internationalization decisions are made step-by-step and

assessed per host country environment. Other authors like Johansson and Vahlne (1990;

2013) take on a process view on internationalization and argue decisions are interrelated.

Johansson and Vahlne (1990; 2013) agree with internalization theory that firms will

internationalize into markets that are relatively familiar to the home market, since risk and

thus costs will be lower. Over time, however, firms will invest in more foreign environments

in terms of geographic, cultural and institutional distance. Instead of the driving force being

related to one or more of the OLI advantages, the driving force for internationalization

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decisions is considered to be ‘experiential market knowledge’ in their Uppsala model

(Johansson & Vahlne, 1990; 2013). The strategic assets seeking driver of Dunning (2000;

2001) is strikingly similar to the experiential market knowledge driver: both of these drivers

revolve around learning and improving the MNEs position by partnering with parties in the

new business environment. The difference is, again, that the strategic asset seeking driver

assumes it as an advantage of a specific internalization decision whereas the experiential

market knowledge drives assumes it is the basis of all internationalization decisions of an

MNE.

As MNEs learn from their environment, new growth opportunities open up and thus

their potential next step in the internationalization process. Whether the costs outweigh the

benefits of entering a market through FDI cannot be determined solely up front according to

this process view on internationalization. The potential benefits of the learning experience

should be considered as well. MNEs operate as part of a network and are dependent on their

environment. Not only are products and goods exchanged in (international) business,

knowledge and information also flow between the parties of the entire business network

(Johansson & Vahlne, 1990; 2013). The MNE has to learn to operate in the new environment,

however, and build relationships to tap into the existing body of knowledge. If a market is

more foreign, Dunning (2000; 2001) would argue FDI is less likely as it becomes more

complex for an MNE to leverage its FSAs effectively to reach OLI advantages. Johansson and

Vahlne (1990; 2013) look beyond CSAs and FSAs, emphasizing the importance of the

process of internationalization and the network a firm can gain access to. After a firm is

familiar with the foreign business network and has established relationships, it can leverage

that experience and use it in new environments. Knowledge spillovers and information

externalities explain the spatial agglomeration of MNEs (Mariotti, Pscitello & Elia, 2010).

The potential knowledge inflow is balanced with the potential knowledge outflow, resulting

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in the decision to either join the agglomeration or not. Firms operating in similar

environments tend to have access to similar knowledge and information, which explains

isomorphism in international business activity.

Internalization theorists argue the decision to internationalize through FDI should

depend on the OLI advantages outweighing the benefits of other entry modes (e.g exports or

joint ventures) (Dunning, 2000; 2011; Rugman et al., 2011). Other authors argue the decision

depends on the market knowledge, which influence the costs of internationalization into a

specific market (Zaheer, 1995; Lu & Beamish, 2004; Rugman & Verbeke, 2012). Costs of

internationalization are argued to come from a lack of knowledge and information on how to

operate in the foreign environment compared to operating in known environments. Three core

concepts of internationalization costs are Liability of Foreigness (LoF), Liability of Newness

(LoN) and coordination costs (Zaheer, 1995; Lu & Beamish, 2004; Contractor, Kumar &

Kundu, 2007; Rugman & Verbeke, 2012; Joardar, Kostova & Wu, 2014).

Liability of Foreigness (LoF) stems from differences in conducting business in the

foreign environment, specifically political, economic and cultural differences (Zaheer, 1995;

Rugman & Verbeke, 2012). From an institutional perspective, LoF comes from the MNE’s

“lack of isomorphism with the host-country’s environment” (Sethi & Judge, 2009). This lack

of isomorphism makes the firm vulnerable to institutional pressures, incurring additional costs

compared to home country MNEs. Section 2.3.1 offers a more elaborate review on

institutional context. Liability of Newness (LoN) comes from the initial costs an MNE incurs

by entering the foreign market and setting up its organization in the new environment. The

start-up costs from LoN are completely mitigated over time, whereas LoF merely decreases

over time as an MNE learns the rules of the game and gets more experience in the context

(Vermeulen & Barkema, 2002; Rabiosi & Santangelo, 2013). Finally, coordination costs are

those costs a firm incurs to manage its network of foreign assets. The larger the international

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network, the harder it will be to know what is going on in different units of the company and

for the different units to be on the same page. The increase of international units increases

coordination costs, which can exceed the benefits of internationalization (Hitt, Hoskissen &

Kim; 1997). At the same time, internationalization enables firms to spread risks over different

countries and thus reduce fluctuations in revenue (Lu & Beamish, 2004). Operating in

multiple contexts also enables an MNE to learn from operating in different contexts, and

different organizational units can contribute its knowledge base by sharing best practices from

all over the globe (Zahra, Ireland & Hitt, 2000; Lu & Beamish, 2004).

Classic (OLI) motivations for an MNE to identify the right market might play a crucial

role in determining the host country, but liabilities change over time due to experience in

international markets (Johansson & Vahlne, 1990; 2013; Dunning, 2000; 2001; Rugman,

2011; Lu & Beamish, 2004). This suggests there is an optimal point of the number of foreign

compared to total operations (the level of internationalization) - after liabilities diminish and

before internationalization costs outweigh the benefits. This is the focus of the next section: a

review of the literature on the I-P relationship.

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2.2 The Internationalization and Performance relationship

Studies on the internationalization and performance (I-P) relationship found support

for different shapes. Support has been found for a positive linear relationship (Bausch & Kist,

2007; Marano et al., 2016), an (inverted) U-curved relationship (Lu & Beamish, 2001;

Ruigrok & Wagner, 2003; Capar & Kotabe, 2003), and for an S-curved relationship

(Contractor, Kundu & Hsu, 2003; Lu & Beamish, 2004). Studies finding a positive linear

relationship all focused on the benefits of internationalization, e.g. the access to new markets,

resources, knowledge opportunities et cetera. Critics of this approach argue it simplifies

international business activity, since it ignores its complexity and therefore part of the costs of

internationalization (Cardinal, Miller & Palich, 2011). The U-shaped relationship studies do

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include a balance between both the costs and benefits of internationalization and how their

impact differs over time. Time is the key word in these studies, where the benefits and costs

of internationalization impacting performance are researched over a longer period. The

benefits of internationalization are more likely to outweigh the costs in the long term

(Douglas, 2004). As MNEs learn to navigate new contexts, their costs of internationalization

lower and performance is impacted positively. International market experience has thus been

found to impact performance, in line with Johansson and Vahlne’s process view (1990; 2013).

Still, studies found support for both an U-shaped as well as an inverted U-shaped relationship:

complete opposites. Proponents of the inverted U-shaped relationship argue that the costs of

internationalization can exceed its benefits when the international network becomes too large.

The costs of coordinating the international network exceed the benefits, implying only

moderate levels of internationalization result in positive performance (Lu & Beamish, 2001).

The argument makes sense, but does not explain why a polar opposite relationship has been

found as well.

An important reason for the different results lies in the period in which firms are

studied. Studying a longer period of time allows for capturing different stages of

internationalization and showing how different levels of internationalization impact

performance differently over time. Lu and Beamish (2004) were able to integrate the U-

shaped and inverted U-shaped relationships into one S-curved relationship. Their large sample

of Japanese firms was studied over a ten-year period, ensuring it captured firms in all stages

of internationalization. The S-curved relationship essentially combines the U-curved and

inverted U-curved relationships into one three-stage model (figure 1), making a convincing

argument for its existence. In the first phase of internationalization, firms experience more

costs than benefits. LoF, LoN and coordination costs outweigh the returns. In phase 2,

however, the benefits of internationalization outweigh the costs. LoN lowers as a firm

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establishes its operation in the new environment, just as LoF lowers due to learning to operate

in the new environment. When a firm over-internationalizes, phase 3, the coordination costs

become too high for a firm to effectively manage its international network. In that phase, the

performance goes down and the relationship becomes negative (Lu & Beamish, 2004).

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2.2.1 The moderating effect of R&D intensity

In this model, R&D intensity had a positive moderating influence on the I-P relationship

(Lu & Beamish, 2004). R&D intensity is defined as a firm’s focus on technological

innovation (Kotabe, Srinivasan & Aulakh, 2002; Musteen, Datta & Francis, 2014).

International business scholars found high R&D intensity drives performance for MNEs in

general, since it enables a firm to benefit from the latest technological advancements that

generally relate to higher efficiency and thus higher returns over time. Firms investing heavily

in R&D capabilities can for example generate efficient procedures in managing the

international network. Although initial investment is required, the procedure can in time be

Figure 1. Multinationality and Performance: A Three-Phase Model.

From: Lu & Beamish (2004; 600)

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implemented throughout the network. Technological assets can generally be deployed across

markets without significant value depreciation, therefore becoming an important source of

potential significant competitive advantage (Luo & Tung, 2007; Kotabe et al., 2002; Musteen

et al., 2014). Moreover, high R&D intensity is positively related to internationalization itself

(Purkayastha, Manolova & Edelman, 2016; Hsu, Lien & Chen, 2015). It means that R&D

intensity does not only influence the I-P relationship, but that firms with high R&D Intensity

tend to be more internationalized. This is not surprising considering high R&D investment

pays off the most for firms being able to implement their technological innovations

throughout their international network.

2.2.2 Integrating perspectives

The inconclusive results on the shape and direction of the I-P relationship are addressed

by Lu and Beamish (2004) study that integrated different views by taking a process view on

internationalization. The different stages of internationalization create a picture that is

consistent with classic IB literature regarding LoF, LoN and coordination costs. The

moderating effect of R&D intensity was supported in Lu and Beamish’ (2004) study. Still,

their sample brings up some concerns and with that, opportunities for further research. The

study was based on a large sample, but studied firms from one country only (Japan). As Lu

and Beamish (2004) point out in their article, this brings up the concern that the findings

might be country specific. The assumptions underlying their study are clearly focused on

developed markets and might not apply to emerging market environments. Moreover, the

study does not consider the influence of the institutional environment at all. A comparative

study looking into international firms from different type of home markets and considering

the impact of their home country environment is thus a relevant addition to academic research

on the I-P relationship.

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2.3 Home country environment and the I-P relationship

The advantages and risks of internationalization outlined above apply to developed

markets, studied heavily over the past decades. Recent studies suggest there are significant

differences in the drivers, costs and risks of internationalization for MNEs from developed

versus emerging markets (Johansson & Vahlne, 2013; Musteen, Datta & Francis, 2014; De

Clerq, Zhou & Wu, 2014). The home country environment, also referred to as country of

origin, has been found to influence the MNE’s international strategy and its international

performance. Just like a host country’s CSAs, the home country’s CSAs enable a firm to

access certain resources. The next section reviews the impact of home country environment in

relation to internationalization and performance. First, the potential impact of the institutional

context is discussed in 2.3.1. Then, contemporary academic theories on formal and informal

institutions are reviewed in sections 2.3.1.1 and 2.3.1.2. Finally, the characteristics of

developed markets (2.3.1.1) and emerging markets (2.3.1.2) and their implications for

international business activity are reviewed.

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2.3.1 Institutional context

The Institution Based View (IBV) in international business holds that institutions

influence the differences in performance of firms, besides industry differences and differences

in resources (Peng, 2002). Home country environments have been found to shape firm’s

strategies, specifically as access to home country CSAs can be linked to an MNE’s FSAs

(Peng, 2002; Marano et al., 2016). The institutional environment shapes interaction in a

certain context, defined by Peng as “the set of fundamental political, social and legal ground

rules that establish the basis for production, exchange and distribution” (2002; 252; North,

1990). The political and legal ground rules can be categorized as the formal institutional

context, whereas the social ground rules fall under the informal context (see sections 2.3.1.1

& 2.3.1.2). Home country institutions can reduce uncertainty and enable efficiency,

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effectively influencing the costs of doing business abroad and therefore directly influencing a

firm’s performance. Different institutional environments have clear implications for MNEs:

firms have to adjust to differences in government regulations, political structures and social

norms to be able to operate internationally.

The influence of home country environments has not been studied in depth in relation to

the I-P relationship, besides Marano et al.’s recent study on home country effects. A modest

positive I-P relationship was found when taking country of origin effects into account, defined

as differences in institutional context. Section 2.3.1.1 and 2.3.1.2 zoom in on the formal

institutions and informal institutions that shape the rules of the game of a certain environment.

Marano et al. (2016) did not, however, make a specific distinction between market type in

their study.

2.3.1.1 Formal institutions

The formal institutional environment is made explicit through codified rules, laws and

regulations, and through the political structure of a society (North, 1990; Peng, 2002). It can

provide firms with a stable foundation via rules that make it easier to start and operate a

business, and with political structures that make it easier for firms to make long term

decisions.

In contexts with underdeveloped formal institutions, rules are not codified or change

frequently (Peng, 2009). Developed formal institutions indicate a stable business environment

and thus minimize risk of operating in that environment, whereas underdeveloped formal

institutions imply higher uncertainty and risk. This view is quite biased, however.

Underdeveloped formal institutions might imply higher uncertainty and risk for firms from

contexts with developed formal institutions, while firms that are from these contexts

experience the ‘stable’ environments to be more risky. Where some authors relate weak home

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country formal institutions to lower competitiveness (Porter, 1990), others indicate firms from

these contexts are simply used to more politically risky environments (Chacar, Newburry, &

Vissa, 2010). It does not mean they are less competitive, but rather that firms from contexts

with weak formal institutions will have developed capabilities to navigate it successfully.

Business regulations can still make it easier for firms to start up and operate a business,

for example through antitrust regulations and contract enforcement (Chacar et al., 2010). In

environments with weak business regulations, it is more complex to start up a business and it

will be less clear how to navigate the system. Marano et al. (2016) point to two perspectives

regarding the impact of business regulations, similar to the discussion above on the impact of

strong and weak formal institutions. The first perspective holds that strong business

regulations positively moderate the I-P relationship, while the second perspective expects

strong business regulations to negatively moderate the I-P relationship (Marano et al., 2016).

Scholars arguing for the first perspective assume strong business regulations reduce

uncertainty and create a stable business environment (Chacar et al, 2010; Wan & Hoskisson,

2003). Opportunistic behavior is minimized, and a stronger national economy offers firms

better access to resources (Marano et al., 2016). Studies following the second perspective

argue that firms develop coping mechanisms when faced with weak business regulations,

enabling them to deploy these skills across markets. This skill itself can become an FSA,

creating a potential competitive advantage compared to firms from countries with strong

formal institutions (Luo & Tung, 2007; Marano et al., 2016).

Besides business regulation, research indicates the political structure of a country can

influence the I-P relationship (Wan & Hoskisson, 2003; Stevens, Xie & Peng, 2015). Similar

to the effect of business regulation, more transparent political systems offer a stable home

environment for MNEs to build their international network from (Wan & Hoskisson, 2003).

Others add that the political structure is the way governments establish the rules and standards

22"

that shape the nature of the political process, especially concerning how power is distributed

and which stakeholders are allowed to participate in the system (Holmes, Miller, Hitt & Paz

Salmador, 2012). Autocratic regimes create an uncertain environment and involve less

stakeholders, resulting in higher uncertainty and thus a more risky business environment.

Two approaches are dominant in research into political risk according to Stevens et al.

(2015): 1) the bargaining power approach (BPA); and 2) the political institutions approach

(PIA). The bargaining power approach focuses on the balance between the bargaining power

of the firm and the government. Political risk associated with BPA stems from the erosion of

the bargaining power of the firm over time, as its investment into the country pave the way for

other actors (Boddewyn, 2016). The MNEs power to stop the initial bargain from changing

goes down, resulting in an increase of political risk (Stevens et al., 2015). In other words,

political risk increases from the moment resources are committed and the MNE has set up its

organization in the country. The PIA focuses on “the degree of checks and balances in a

country’s political institutions” (Stevens et al., 2015; 1). This approach takes on a more

structural perspective on political risk. Instead of focusing on a specific MNEs bargaining

power, it looks at the reliability of a specific country’s political structure over time. Henisz

(2000) argues that governments are inherently tempted to change policies to their advantage.

A higher degree of checks and balances in a country’s political structure decreases political

risk, since it constrains the governments’ ability to alter existing policies (Stevens et al., 2015;

Henisz, 2000).

Wan and Hoskisson (2003) found that firms with headquarters in strong political

environments were found to profit more from internationalization than their counterparts from

less strong institutional environments. Their argument is that firms from strong political

environments have developed the capabilities to participate in the political structure, since

they were offered a chair at the table. Firms from countries with weaker political structures

23"

have developed capabilities to navigate the complex environment and were likely able to

generate competitive advantage through leveraging them. These are location-bound

capabilities, however, specific to that political structure (Wann & Hoskisson, 2003; Marano et

al., 2016). Other authors argue unpredictable political systems force firms to develop coping

mechanisms to navigate complex institutional contexts. These skills enable firms to manage

the challenges they face in foreign operations as well (Elango & Sethi, 2007). This

perspective focuses on the positive impact of weak home country institutions on MNE

internationalization, and thus expects home country political risk to positively moderate the I-

P relationship.

2.3.1.2 Informal institutions

The informal institutional environment is formed by the shared norms that guide

accepted behaviors in a certain context. Where formal constraints fail, the informal constraints

will take over to establish ‘a way of doing things around here’ (North, 1990). The values and

norms in a country are embedded in its culture (Hofstede, 1994; Caprar, Devinney, Kirkman

& Caligiuri, 2015). Culture provides a long-term measure of informal institutions and is the

basis for the development of formal institutions (Holmes et al., 2013). Culture informs the

way managers set up their organization and thus operate both on a national and international

level (Marano et al., 2016). Previous research identified specific dimensions of culture that

influence MNE performance and thus help explain the differences between MNEs from

different home country environments (Holmes et al., 2013; Marano et al., 2016; Elango &

Sethi, 2007). Various authors found that some cultural gaps are more disruptive than others in

international business (Hofstede, 1991; Barkema & Vermeulen, 1998; Shenkar, 2001). Future

Orientation and Uncertainty Avoidance are expected to be the most important for

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international business, since they translate into different tolerances for risk and formal

structures (Shenkar, 2001; Marano et al., 2016)

Future orientation can be related to a focus on either long –term versus short-term

outcomes. Higher degrees of future orientation suggest more planning and investing activities

that consider long-term outcomes. When a country’s future orientation is low, short-term

results will be more important (Hofstede, 1994). When relating future orientation to

international business and institutional environment, high degrees of future orientation may

encourage firm investments in the country and thus benefit its position in the international

market. Furthermore, Marano et al. (2016) argue high degrees of future orientation can impact

supply and demand if the country’s investment options are framed as long-term growth

opportunities. That way, the country’s long-term perspective turns into a CSA the firm can tap

in to.

The degree of uncertainty avoidance has also been found to impact the I-P

relationship, since it reflects how well individuals in a country deal with uncertain situations

(Hofstede, 1994). Organizations from countries with low degrees of uncertainty avoidance are

assumed to be used to dealing with vague situations and thus used to being very flexible: they

are open to uncertain outcomes (Venaik & Brewer, 2010). High uncertainty avoidant societies

tend to avoid ambiguous situations, on the other hand, which exist more in international

cooperation than in domestic cooperation (Venaik & Brewer, 2010; Shenkar, 2001). Thus,

firms from high uncertainty avoidant countries prefer rules and regulations that guide their

actions, but limit their flexibility. Since international business consists of dealing with

unknown environments and adapting to foreign contexts, low flexibility can harm an

organization to learn to operate in foreign contexts successfully. Relating this to the

experiential market knowledge concept of Johansson and Vahlne (1990; 2013) suggests that

low flexibility reduces a firm’s ability to learn from new business behavior in local contexts,

25"

thus negatively impacting performance. Following these authors’ line of argumentation, it can

be expected that low uncertainty avoidance in the home country positively moderates

international performance.

2.4 Market types

Home country environment was defined in the previous section as a country level

concept, but this thesis looks to identify the moderation effect of market types specifically in

relation to internationalization and performance. Home country environment is related to

market type, as it expected that specific home country environment scores correspond to

either developed or emerging markets. The next two sections clarify the assumed

characteristics of developed markets (2.4.1.1) and emerging markets in relation to MNE

behavior (2.4.1.2), building on Marano et al.’s (2016) work.

2.4.1.1 Developed market MNEs

Developed markets (DM) are characterized by relative economic and social stability,

promoting the acceptance of the rules of trade and investment. Additionally, developed

market MNEs can usually benefit from more established partnership activity. The structures

for business activity are well established and transparent. Moreover, these DM MNEs tend to

have better access to resources and are generally better equipped to generate higher financial

assets as compared to other market MNEs (Hitt, Dacin, Levitas, Arregle & Borza, 2000).

Institutional environments in developed countries are generally more stable, resulting in more

predictable business environments. Reduced complexity and uncertainty reduce costs of doing

business, offering firms from developed countries a safe platform to build their international

network and translate it into higher performance. The general assumptions of international

business literature apply to developed markets. Emerging market MNEs, however, might

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follow slightly different paths due their institutional differences and opportunity to tap into

existing market knowledge.

"

2.4.1.2 Emerging market MNEs

Emerging markets (EM) went through significant structural transformation relatively

recently. Their national economies have grown rapidly and are showing promise despite

weaker legal systems and volatility compared to developed markets. EM MNEs are defined as

“international companies that originated from emerging markets and are engaged in outward

FDI, where they exercise effective control and undertake value-adding activities in one or

more foreign countries” (Luo & Tung, 2007). Emerging markets are usually smaller

compared to developed markets, with a deficit in resources and at considerable distance from

major European and North American markets. The generally young nature of the emerging

market’s structure in terms of institutions and legal systems means that management

capabilities and decision-making processes are not as developed as compared to firms in

advanced markets (Hitt et al., 2000; Luo & Tung, 2007, Contractor et al., 2007). Additional

EM challenges stem from the rapid changes in economic, political and social institutions,

according to Wu (2013). CSAs that firms from the more established developed markets have

access to (Wan & Hoskisson, 2003).

2.4.1.3 Internationalization-Performance assumptions for EM versus DM MNEs

Previous studies on EM MNE activity showed that these firms can benefit greatly from

international expansion, as the importance of spreading risk over multiple countries enables

them to deal with uncertainty of their home country’s CSAs. Luo and Tung (2007) developed

the springboard perspective. EM MNEs internationalize to benefit from more developed

countries and their firm network and infrastructure. Firms can overcome latecomer

advantages and institutional home country constraints when internationalizing into developed

27"

markets (Luo & Tung, 2007). At the same time, it can be argued that the costs of international

expansion might be higher due to the lack of access to similar home country. Successful early

internationalization from emerging market firms implies gaps in traditional assumptions of

experiential learning and internalization theory that both advocate an incremental

internationalization process. These firms instead rapidly internationalize successfully, while

tradition theory would predict negative performance consequences. Firms from transitioning

economies that internationalize into developed economies have the opportunity to tap into the

same existing market knowledge as developed firms, which is in line with Dunning’s (2000;

2001) strategic asset seeking and Johansson and Vahlne’s (1990; 2013) experiential market

knowledge drivers. In this theory, experiential market knowledge of other firms can be an

advantage to new MNEs entering the network. Luo and Tung (2007) found that early

internationalization from MNEs from emerging economies is facilitated by a reliance on

international networks. The relationship, however, is contingent on technological innovation

and a firm’s perceived environmental hostility (Musteen et al., 2014; Luo & Tung, 2007).

This contingency is quite logical when considering that EM MNEs offering technologically

advanced services or goods will be more in line demand in the global market. Furthermore,

consider that EM MNEs tapping in to the international networks need to match their

technological know-how with that of DM MNEs to have it be mutually beneficial.

De Clerq et al., (2014) found that internationalization of emerging market MNEs can

positively impact their performance. Especially in more turbulent markets, international

learning efforts are proven to be essential early on. Turbulent markets and less well-

established institutional environments bring unpredictability and uncertainty - thus effectively

increasing risk and making it harder for firms to operate in the environment. These theories

imply internationalization does not become a driver after a firm has established a network in a

few countries, but as soon as possible to spread institutional risk.

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The new insights of international business studies pointing out differences between the

internationalization of EM and DM MNEs are the foundation of this study. Previous studies

of the I-P relationship have assumed relatively similar motivations for internationalization,

reflected in the research design. This study expects the home country environment of

successfully internationalized MNEs to moderate the I-P relationship,

2.5 Conceptual Framework and Hypotheses

The meta-analytical studies of Marano et al. (2016) and Bausch & Kist (2007) both

resulted in significant statistical support for at least a modest positive I-P relationship for both

EM and DM MNEs. Therefore, the first hypothesis of this study assumes a positive linear I-P

relationship for MNEs from both market types.

Hypothesis 1: The relationship between internationalization and firm performance is

positive.

Current academic literature has studied the I-P relationship, but reviewing the literature

made clear that the potential country of origin effect was not taken into account. Often a

sample consisted of firms from one country or, when more firms from more countries are

included, only focusing on firms from developed markets. The limited amount of studies that

did examine the I-P relationship in emerging market economies have been found to in turn

only focus on those markets, equally not applying the same methods to MNE activity from

other type of markets. Therefore, effectively comparing results is difficult. Different studies

have used slightly different measures of the main variables, resulting in unreliable cross-study

comparison. Marano et al. (2016) found that the strength of the relationship was moderated by

the country of origin, resulting in a more modest positive I-P relationship for EM MNEs

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compared to DM MNEs. At the same time, the springboard perspective of Luo and Tung

(2007) suggests the I-P relationship to be stronger for EM MNEs than traditional IB literature

implies as it enables them to tap into the existing network and more stable institutional

environment Therefore, this study reviews the potential moderating effect of the Home

Country Environment by assuming a more positive I-P relationship for EM MNEs compared

to DM MNEs. Hypothesis 2 is formulated as follows:

Hypothesis 2: The relationship between internationalization and firm performance is

moderated by the home country environment, displaying a stronger positive effect for

EM MNEs compared to DM MNEs.

Following the literature review, a focus on technological assets is related to high

performance for both market types. Studies have, again, been inconclusive on the moderating

effect of R&D intensity on firm performance. It is usually studied as a separate moderator for

the I-P relationship. The literature review suggests, however, that the effect might be different

for EM MNEs and DM MNEs. Therefore, R&D intensity is studied as a moderator on the

moderation effect of Home Country Environment, resulting in the following two hypotheses:

Hypothesis 3a: The firm’s level of R&D intensity moderates the effect of the home

country environment in such a way that high R&D intensity increases MNE

performance

Hypothesis 3b: Firms from emerging market environments benefit more from a focus

on technological assets, i.e. the moderation effect of R&D intensity is stronger for EM

MNEs compared to developed market MNEs.

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Figure 2. Conceptual Framework

H3a +

H3b +/++

H2 +/++

H1 +

Performance

! ROA as Net Sales/Total Assets

Level of Internationalization

! Foreign Assets/Total Assets

! Foreign Sales/Total Sales

! Foreign Employees/Total

Employees

Home Country Environment

! Emerging Markets vs. Developed Markets

R&D intensity

! R&D Expenditures/Total Sales

31#

3. Methodology

The following chapter outlines the research methodology and design in order to answer the

research question. Section 3.1 details the research design in terms of validity and reliability

(3.1.1), Sample (3.1.2), Variables and measures (3.1.3) and finally, Data analysis in section

3.1.4

3.1 Research design

The research question will be examined by testing the hypotheses through a quantitative

databased research design. This study’s main objective is to test existing theories, thus

following deductive reasoning. The total dataset is the result of combining several public

databases. The first part consists of the UNCTAD top 100 MNEs for developed country plus

the UNCTAD top 100 MNEs for emerging countries annex tables to the Trade and

Development Reports of 2010, 2011 and 2012. Company information from the

COMPUSTAT WRDS database was added, as well as country level information from the

GLOBE project, the Economic Freedom Index of the Heritage Foundation, and the Witold

Henisz Political Constraint Index. The specific measures included in the dataset are addressed

in relation to the variables in section 3.1.2. A quantitative approach is the preferred way to

answer the research question, because it concerns a relationship and impact of variables on

that relationship. The results are generalizable, because of the large amount of observations

in the sample (n = 419).

3.1.1 Validity and reliability

Validity is the extent to which the measurement method or instrument measures what it

is intended to measure (Field, 2013). In the case of this study, validity was increased by

several factors. It was based on the research design of previous studies. Two key studies that

32#

form the foundation of this research design are the studies of Lu and Beamish (2004) study

and Marano et al. (2016). Building on the findings of these studies means the design was

tested and the measurements were proven to be fit for the study’s objective. Furthermore, data

checks were performed and appropriate models were chosen based on that, increasing the

trustworthiness of the results.

Reliability can be defined as the extent to which a measurement method or instrument

leads to the same results when the study is repeated (Field, 2013). The reliability was

increased because it is exactly documented which variables, data and methods were used. A

repeat study can thus be performed based on the documented results.

3.1.2 Sample

The sample consists of the world’s top 100 non-financial MNEs from developed and

emerging countries (UNCTAD 2011; 2012; 2013). Data was collected from the reports over a

three-year period from 2010 to 2012 to improve reliability of results. The company

information per year was supplemented with financial company information from

COMPUSTAT (Wharton Research Data Services) needed to measure performance. The total

sample consisted of 600 firms. After correcting for missing values and inactive firms, the

sample consists of 422 data points: 197 for developed markets and 225 for emerging markets.

The dataset consists of firm and country level measures (see variables section 3.1.2). Table 1

offers an overview of the range in terms of size in net sales of the MNEs in the sample.

Table 1

Average firm size in net sales

Developed Market MNEs Emerging Market MNEs

Small $36.450,85 $13.271,34

Medium $68.013,68 $50.150,84

Large $2.043.687,54 $9.274.895,24

33#

Previous studies have established there is at least some relationship between

Internationalization and Performance. The main objective of this study is to identify potential

moderator effects of the home country environment and R&D intensity on the I-P

relationship. The sample therefore does not consist non-MNEs versus MNEs as in other

studies on the I-P relationship, but only of MNEs to allow for a more detailed inspection of

the moderation effect. The companies in the sample are all industrial companies, based on the

industry indicator of the COMPUSTAT database. Table 1 offers an overview of the HQ

locations of the companies in the sample.

3.1.3 Variables and measures

Internationalization (IV) The independent variable, Internationalizatio, was first

measured in three separate ratios: foreign sales to total sales (INTSA), foreign assets to total

assets (INTAS), and foreign employees to total employees (INTEMP). A composite measure

for internationalization was computed following the method used by Sanders and Carpenter

(1998). The sum of the three ratios forms the Internationalization variable, taking a value

between 0 and 3. The three measures demonstrated high reliability (α = .827) and the

corrected item-total correlations display good correlation with the total score of the scale (all

>.30). Furthermore, none of the items would substantially be affected if they were deleted.

Performance (DV) The dependent variable is performance, for which the commonly

used measure Return on Assets is computed. ROA was calculated as the ratio of net sales and

total assets, following Bertrand and Schoar’s method (2003).

Home country environment moderator Home country environment is measured first of

all by market type, measured as a dichotomous, binary variable (EM = 0, DM = 1). The

classification is based on the UNCTAD classification of MNEs from developed versus

emerging economies. To test whether the market type corresponds to the assumption of

34#

institutional environment of the literature review, measures for formal and informal

institutions are included. Formal institutions are measured in two separate variables: Political

Constraints and Business Freedom. Political Constraints is defined as “the degree to which

the country’s political structures create political risks for firms and investors” (Marano et al.,

2016; 1089). The Witold Henisz Political Constraint Index data set (POLCON V) ranges from

0 (most risky) to 1 (most stable) and is time variant. The index was reverse coded (POLCON)

so the high values represent more politically risky home country environments. The second

measure of formal institutions is Business Freedom, defined as “the extent to which

regulatory and infrastructure environments constrain the efficient operation of businesses”

(Heritage Foundation, 2017). The data is obtained from the Index of Economic Freedom from

the Heritage Foundation. It captures the ease of starting, operating and closing a business

within a specific country.The measure is a number between 0 and 1, with 1 indicating the

freest business environment and is time variant. This variable is recoded (RBFREE) to have

lower valuables represent a more transparent and thus less risky business environment.

Informal institutions are captured by two variables: Future Orientation (FUTOR) and

Uncertainty Avoidance (UNAVOI). Both measures are obtained via the GLOBE project and

are widely used in IB studies. Future Orientation is a time invariant variable and can be

defined as “the extent to which individuals engage (and should engage) in future-oriented

behaviors such as planning, investing in the future, and delaying gratification” (GLOBE,

2016). Uncertainty Avoidance is also a time invariant variable, defined as “the extent to which

a society, organization, or group relies (and should rely) on social norms, rules, and

procedures to alleviate unpredictability of future events.” (Globe, 2016). Higher values for

both of these measures indicate strong informal institutions, originally measured on a 7 point

scale. The scales were divided by 7 to allow for comparison with the formal institutional

35#

measures. The scores take on values between 0 and 1. An overview of the EM and DM MNEs

home country institutional values is given in table 4 and 5.

R&D Intensity moderator R&D intensity is calculated by the total R&D expenditures

per year divided by the total sales in one year, following Bertran & Schoar’s method (2003).

Table 2

Variable Definitions

Variable

Definition

DATA_YEAR Reporting year for the company’s financial data (2010, 2011, 2012)

INTEMP A ratio calculated by dividing foreign employees by total employees (0 to 1)

INTAS A ratio calculated by dividing foreign assets by total assets (0 to 1)

INTSA A ratio calculated by dividing foreign sales by total sales (0 to 1)

INTTOTAL A composite measure of the combined ratios of INTEMP, INTAS and INTSA.

(0 to 3)

ROA Return on Assets, a ratio calculated by dividing net sales by total assets

POLCON Political Constraints measure on a 0 to 1 scale as defined by the Witold Henisz

Political Constraint Index data set. Recoded so high values represent high

political risk

RBFREE Recoded Business Freedom measure on a 0 to 1 scale. Based on the Index of

Economic Freedom from the Heritage Foundation. High values represent higher

business risk

FUTOR Future Orientation measure on a 0 to 1 scale as defined by the GLOBE project.

High values indicate strong informal institutions

UNAVOI Uncertainty Avoidance measure on a 0 to 1 scale as defined by the GLOBE

project. High values indicate strong informal institutions

ECON Market type indicator taking on a 0 for Emerging Markets and 1 for Developed

Markets

RDINT R&D Intensity measure, calculated by dividing the R&D expenditures by the

total sales

FSIZE Firm size measure as the logarithm of Net Sales

TRADE_HOME The home country's Trade in Goods, a control variable obtained from the World

Bank

GDP_HOME The home country GDP, a control variable obtained from the World Bank

36#

Control variables The logarithm of Net Sales was included to control for Firm Size.

Also, logarithms of MNEs home country’s GDP per capita as well as Trade in Goods were

included as control variables to measure the effect on performance by factors outside of the

firm’s control (obtained from the World Bank).

3.1.4 Data analysis

SPSS was used to empirically test and analyze the data. First, the descriptive statistics

were computed (table 3). These statistics include the means and standard deviations for all

non-dummy variables in the dataset. Then, a closer inspection of the distribution of the data

was conducted. First, skewness and kurtosis tests were performed to test for normality. The

variables are not normally distributed, which is not surprising considering the dataset used for

this study (e.g. RDINT is positively skewed, platykurtic; INTTOTAL slightly negatively

skewed, normal kurtosis). Histograms were created to test whether the distribution was bell

shaped, another indicator of normality. Non-normality was further confirmed by these tests.

Non-normality is not a big issue considering the tests used and the sample size (n = 422).

Therefore, non-normality is accepted. The Firm Size variable, which showed substantial

positive skewness, was normalized by transforming it into a logarithm value (Field, 2013).

R&D intensity values are missing for a large amount of firms (147). Only when R&D

intensity is added to a model (models 2 and 3), the missing data points are excluded.

Finally, a correlation analysis was performed to test for the direction of the relation

between the main variables. Table 3 also includes the correlation values in the diagonal. The

correlation matrix shows that variables are significantly correlated, allowing for further

analysis (Field, X).

The first tested model, to test Hypothesis 1, was a hierarchical regression to test whether

Internationalization predicts performance, when controlling for firm size, home country GDP

37#

and home country Trade in Goods. Model 2 was a similar hierarchical regression model, this

time controlling for GDP_HOME, TRADE_HOME, POLCON, BFREE, FUTOR and

UNAVOI. This test was done to test the individual effect of a focus on R&D Intensity to

explain ROA in general, without the effect of internationalization. Then, the numerical

Independent Variable (INTTOTAL) and Moderator (RDINT) were standardized to allow for

the main moderation-moderation analysis, required since the ECON moderator is categorical

(Field, 2013). The statistical equation of Hayes’ (2012) third PROCESS model was modified

to apply to this study’s third model:

Conditional effect of INTTOTAL on ROA = b1 + b4ECON + b5RDINT + b7ECON*RDINT

38#

Table 3

Means, Standard Deviations, Correlations

Variables M SD 1 2 3 4 5 6 7 8

1. Internationalization 1.741 .653 (.827)

2. ROA .777 .483 -.097* -

3. Firm Size a 4.817 1.001 -.109* .283**

4. Political Constraints .384 .295 -.295** .081 -.192**

5. Business Freedom 78.916 17.731 .354** -.056 .107* -.024

6. Future Orientation 5.255 .361 -.185** -.171 -.012 -.271** -.328**

7. Uncertainty Avoidance 4.536 .602 -.469** .139** .035 .474** -.351** .228**

8. R&D Intensity .027 .041 .119* -.150* -.007 -.083 .086 -.309** .228**

9. Market type .47 .499 .504** -.120* .024 -.576** .342** -.300** -.768** .198**

*. Correlation is significant at the 0.05 level (2-tailed)

**. Correlation is significant at the 0.01 level (2-tailed)

a. Logarithm

39#

Table 4 ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !DM MNE home countries and institutional values ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

2010 2011 2012

POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI

Developed Markets .196 .127 .731 .573 .201 .130 .731 .573 .200 .134 .731 .573

Australia .153 .097 .735 .569 .160 .099 .735 .569 .160 .081 .735 .569

Austria .260 .264 .731 .522 .260 .272 .731 .522 .260 .297 .731 .522

Belgium .107 .071 .724 .464 .107 .074 .724 .464 .107 .077 .724 .464

Switzerland .146 .188 .684 .451 .146 .198 .684 .451 .147 .221 .684 .451

Germany .150 .104 .747 .563 .150 .104 .747 .563 .150 .095 .747 .563

Denmark .225 .021 .619 .545 .225 .003 .619 .545 .227 .009 .619 .545

Spain .164 .242 .804 .680 .164 .228 .804 .680 .152 .187 .804 .680

Finland .225 .050 .724 .550 .225 .050 .724 .550 .223 .051 .724 .550

France .135 .137 .709 .609 .135 .144 .709 .609 .132 .163 .709 .609

Great Britain .255 .051 .723 .588 .251 .054 .723 .588 .251 .053 .723 .588

Israel .219 .336 .749 .626 .219 .339 .749 .626 .219 .356 .749 .626

Italy .243 .221 .845 .638 .243 .227 .845 .638 .243 .226 .845 .638

Japan .252 .155 .750 .619 .252 .162 .750 .619 .252 .182 .750 .619

Luxembourg .235 .249 .724 .464 .235 .236 .724 .464 .235 .241 .724 .464

Netherlands .222 .174 .724 .464 .310 .181 .724 .464 .313 .181 .724 .464

Norway .232 .112 .698 .515 .232 .117 .698 .515 .232 .116 .698 .515

Sweden .232 .045 .698 .515 .304 .050 .698 .515 .304 .054 .698 .515

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

40#

Table 5

EM MNE home countries and institutional values

2010 2011 2012

POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI

Emerging Markets .550 .283 .766 .709 .568 .280 .766 .709 .484 .265 .766 .709

U. Arab Emirates .333 .326 .829 .765 .333 .327 .829 .765 .333 .320 .829 .765

Brazil .264 .455 .812 .713 .319 .457 .812 .713 .319 .463 .812 .713

China 1.000 .503 .675 .755 1.000 .502 .675 .755 1.000 .536 .675 .755

Egypt .680 .350 .829 .765 1.000 .355 .829 .765 1.000 .362 .829 .765

Hong Kong 1.000 .013 .675 .755 1.000 .013 .675 .755 1.000 .011 .675 .755

India .298 .637 .800 .675 .298 .631 .800 .675 .298 .645 .800 .675

South Korea .245 .081 .814 .667 .245 .084 .814 .667 .245 .064 .814 .667

Kuwait .820 .342 .820 .681 .820 .356 .820 .681 .297 .382 .820 .681

Mexico .289 .170 .837 .751 .289 .127 .837 .751 .289 .180 .837 .751

Malaysia .163 .301 .841 .697 .163 .303 .841 .697 .163 .219 .841 .697

Russia .269 .478 .782 .725 .269 .493 .782 .725 .248 .349 .782 .725

Singapore .967 .018 .787 .602 .967 .018 .787 .602 .316 .028 .787 .602

Turkey .627 .311 .833 .667 .627 .313 .833 .667 .627 .329 .833 .667

Taiwan .276 .170 .743 .758 .276 .153 .743 .758 .276 .115 .743 .758

South Africa .588 .270 .742 .684 .588 .277 .742 .684 .588 .242 .742 .684

41#

4. Results

A hierarchical multiple regression analysis (table 6) was performed to inspect the ability

of the level of internationalization to predict performance, after controlling for firm size,

home country GDP per capita and home country Trade in Goods. In the first step of the

hierarchical multiple regression test, the three control variables were entered as predictors:

GDP per capita and Trade in Goods of the MNE’s home country. The model was highly

statistically significant F (3, 378) = 6.76; p < .001 and explained 5% of the performance.

When entering the Internationalization measure in step 2, the total variance explained by the

model was 7% (F = 4, 377) = 6.936; p < .001. The introduction of the Internationalization

measure into the model explained an additional 1.8% variance in performance, after

controlling for firm size, home country GDP and home country trade in goods. (R2 Change =

.018; F (1, 377); p < 0.01). In the final model, two of the predictor values were statistically

Table 6

Hierarchical Regression Analysis I

R R2 R2

Change B SE β t

Step 1 .226 .051***

Firm size .085 .020 .211

Home country GDPa -.073 .047 -.083

Home country trade in goodsa .009 .070 .007

Step 2 .262 .069** .018**

Firm Size .077 .020 .194 3.788

Home country GDPa -.027 .050 -.030 -.539

Home country trade in goodsa .009 .070 .007 .136

Internationalization -.090 .034 -.144** -2.668

*. Significant at the 0.05 level (2-tailed)

**. Significant at the 0.01 level (2-tailed)

a. Logarithm

42#

significant (Firm Size and Internationalization), with firm size displaying a higher Beta value

(β = .194, p < .001) than internationalization on performance (β = -.144, p < .01). This means

that when the firm size increases with 1, the performance in ROA will increase with 0.194.

When a firm increases its international presence with 1, however, the performance will

decrease with .144. This means the hypothesis 1 is not supported, as the regression analysis

shows that performance is negatively influenced by internationalization.

Table 7

Hierarchical Regression Analysis II

R R2 R2

Change B SE β t

Step 1 .250 .062

Home country GDPa -.180 .049 -.234 -3.655

Home country trade in goodsa .247 .088 .181 2.817

Step 2 .407 .166 .104***

Home country GDPa .009 .108 .012 .083

Home country trade in goodsa .216 .110 .158 1.955

POLCON .203 .163 .228 1.249

RBFREE .464 .245 .228 1.896

FUTOR -.269 .096 -.229 -2.801

UNAVOI .089 .078 .136 1.138

Step 3 .431 .186 .020*

Home country GDPa .037 .107 .048 .345

Home country trade in goodsa .217 .109 .159** 1.990

POLCON .168 .162 .109 1.038

RBFREE .538 .244 .264** 2.204

FUTOR -.329 .098 -.280** -3.348

UNAVOI .092 .077 .140 1.187

RDINT -1.322 .542 -.152** -2.441

*. Significant at the 0.05 level (2-tailed)

**. Significant at the 0.01 level (2-tailed)

***. Significant at the 0.001 level (2-tailed)

a. Logarithm

43#

Another hierarchical multiple regression analysis (table 7) was performed, this time to

inspect the ability of the home country institutional environment and R&D intensity to predict

ROA after controlling for home country GDP per capita and home country Trade in Goods. In

the first step of the test, the two control variables entered as predictors were Trade in Goods

and GDP per capita of the home country. This model was statistically significant F (2, 250) =

8.318; p < .001 explaining 6.2% of ROA. When bringing in the formal (Political Constraints,

Business Freedom) and informal (Uncertainty Avoidance, Future Orientation) institutional

measures in step 2, the model remained statistically significant F (6, 246) = 8.155; p < .001

and explained an additional 10.4% of MNE performance making the total variance explained

by the model 16.6% after controlling for home country Trade in Goods and GDP per capita

(R2 Change = .104; F (4, 246); p < .001). In step 3 the R&D Intensity measure was added.

This model was also statistically significant F (7, 245); p < .001 and explained an additional

2% in performance (ROA) after controlling for the other variables (R2 Change = .020; F (1,

245); p < 0.05). In the final model, four out of six of the predictor values were statistically

significant (Trade in Goods, Business Freedom, Future Orientation and R&D Intensity).

Business Freedom displayed the highest Beta value (β = .280, p < .05) on Performance

compared to the other three (Trade in Goods: β = .159, p < .05; Future Orientation β = -.280,

p < .05; R&D Intensity β = -.152; p < .05). Thus, when a country is more regulated in terms

opening and closing businesses, the performance of a firm is positively impacted. On the

other hand, high R&D intensity negatively impacts performance in general.

It is clear that these measures do predict part of firm performance separately. The next

step was to check whether the actual hypothesized moderation-moderation effect, or three-

way interaction, is present. The SPSS macro tool by Hayes, model 3, is used for the

regression analysis. The outcomes are documented in table 8. The first model (1) is used to

check for three-way interaction of the type of economy (Emerging or Developed Market). To

44#

be able to test for the interaction, the internationalization and R&D intensity variables were

transformed into standardized scores. The regression coefficient for XM is c3 = -.231 and is

statistically different from zero, t(267)=-2.422, p <.05. The effect of home market type on

ROA depends on the home market type. Furthermore, this model accounts for 9.5% of the

variance in ROA.

The I-P Relationship is moderated by market type, with EM MNEs benefitting more

from internationalization than DM MNEs (See Figure 3). Performance improves for EM

MNEs as their international presence grows, while DM MNE performance slightly declines

with higher levels of internationalization. Hypothesis 2 is supported. The variation between

EM MNE performance at different level of internationalization is large, however, especially

compared to the minimal variation in results for DM MNEs. The opportunity for high ROA at

medium to high levels of internationalization thus exists. Medium to high levels of

internationalization, however, do not automatically translate into higher ROA.

Table 8

Moderation – Moderation Analysis

Coefficient SE t p

Intercept i1 1.200 .115 10.395 <.001

Internationalization (X) c1 .213 .0896 2.376 <.05

Home Market Type (M) c2 -.491 .119 -4.100 <.001

Home Market Type * Internationalization (XM) c3 -.231 .095 -2.422 <.05

R&D Intensity (W) c4 .297 .202 1.467 .143

Internationalization * R&D Intensity (XW) c5 3.60 .174 2.062 <.05

Home Market Type * R&D Intensity (MW) c6 -.426 .205 -2.075 <.05

Internationalization * Home Market Type * R&D

Intensity (XMW) c7 -.228 .180 -1.263 .207

45#

EM MNEs perform a lot better for all three of the levels of internationalization (figure

3). A closer inspection of the home country environment is done to find an explanation. The

average institutional values for the countries categorized as DM and EM can be found in

figure 4. Here, we see that the difference between values for informal institutional context is

minimal. The value that are considerably different are the political constraint (DM µ =.199;

EM µ =.534 and business freedom (DM µ =.130; EM µ =.276) scores. This suggests the

formal institutional context of an MNE’s home country has the biggest influence on the home

country environment of the four institutional measures used in this study.

Figure 3. Moderation effect of Market Type. (EM = 0; DM = 1) Level of Internationalization

Market Type

Ret

urn

on A

sset

s

Figure 4. Institutional differences between DM and EM MNE HQ locations

0

0.2

0.4

0.6

0.8

1

POLCON RBFREE FUTOR UNAVOI

DM

EM

46#

The moderation effect of R&D intensity via the Home Country Environment

moderator is not significant (p = .207), as shown in table 8. The moderator effect of R&D

Intensity itself is significant ( p < .05)., but overall R&D intensity does not predict ROA (p =

.143). The Johnson-Neyman scores were inspected to check for potential regions of

significance of R&D intensity, indicating a small negative effect of R&D intensity on the

moderation by economy type for low R&D intensity to medium R&D intensity. This means

that R&D intensity negatively impacts the moderation effect of market type. In other words,

low to medium R&D intensity makes the difference between EM and DM MNEs’

performance smaller. For MNEs with high R&D intensity, the effect is not significant in this

sample and thus no conclusions can be drawn. Hypothesis 3a and 3b are not supported

47#

5. Discussion

This chapter explains the results and offers alternative explanations for the outcome of

the statistical analysis. Hypothesis 2 was supported, supporting the classification of EM

versus DM Markets as a significant predictor of differences in the I-P relationship. Higher

values of internationalization create greater potential ROA for EM MNEs. For DM MNEs,

performance slightly goes down at higher internationalization levels. The measures used in

this study suggest the main reason for this difference can be found mainly in the formal

institutional environment and associated risks (POLCON and RBFREE). Scholars suggest

institutions are becoming more stable due to (semi-)globalization (Ghemawat, 2003;

Friedman, 2007). In this study the formal institutional values differed considerably between

DM and EM, but was comparable among DM and EM countries. The informal institutional

environment was comparable among and between DM and EM countries, thus making it a

less relevant indicator of differences in institutional risk. Cantwell, Dunning and Lundan

(2010) argue an increase in global interconnectedness is an explanation for isomorphism in

institutional environments. The bargaining power of MNEs in relation to home country

institutions results in more similar institutional environment over time, as international

activity increases.

The rest of the results are not entirely in line with the expectations of the literature

review. Hypotheses 1, 3a and 3b were not supported. The results point to some important

considerations for future research on the I-P relationship regarding 1) Sample; 2) Home

Country Environment assumptions; 3) Classification of EM versus DM markets; and; 4) the

moderating effect of R&D Intensity.

First of all, the sample consisted of well performing MNEs only. Some countries in the

sample were the home country of multiple MNEs, while others corresponded to only one

MNE. A larger sample with the same amount of MNEs per country would improve the

48#

validity of the findings as well as the generalizability. The relationship between

internationalization and performance itself was expected to be positive, as these firms are

classified as the top MNEs of DMs and EMs by UNCTAD reports over three consecutive

years. This was not the case, pointing to firms potentially being in the third phase of

internationalization of Lu and Beamish (2004) model. According to their model, over-

internationalization negatively impacts performance because the international network

becomes too large to coordinate effectively. Another alternative explanation for the negative

effect is the exclusion of non-international firms in this sample. It is highly expected that a

study including non-MNEs will allow for a more relevant analysis of the predictability of

internationalization on performance. It offers the opportunity to inspect the impact of

internationalization on performance specifically, as the contrast will most likely result in a

different picture (e.g. Lu & Beamish, 2004; Contractor, Kundu & Hsu, 2003; Elango & Sethi,

2007). Proving the existence and direction of the I-P relationship in general was not the main

objective of this study, however.

Further mapping the differences between the I-P relationship explained by the Home

Country Environment were this study’s main objective. There is a clear difference between

the performance of DM versus EM MNEs. It is not surprising that the performance of highly

internationalized firms goes down, again considering the three-phase model of Lu and

Beamish (2004). Established DM MNEs are more likely to be in the third stage of

internationalization since they have generally been operating in the global longer compared to

EM MNEs (Lu & Beamish, 2004; Luo & Tung, 2007). The slightly decreasing performance

for higher levels of internationalization for DM MNEs are thus in line with previous findings.

The EM MNEs curve increasing is also in line with the assumptions of the literature review.

They benefit more from internationalization compared to their DM counterparts (H2),

explained by them being earlier stages of internationalization.

49#

The classification of MNEs into market type was based on the UNCTAD report

classification: the top 100 EM MNEs and top 100 DM MNEs as listed in the report. A closer

inspection indicates the countries listed as EMs are defined differently in recent academic

studies. These studies suggest grouping them together in the EM category does not reflect

reality any longer (Kim, Kim & Hoskisson, 2010; Banalieva, Eddleston & Zellweger, 2015).

Countries classified as EM in this study are defined differently by other authors, for example

as transitioning markets or developing markets (e.g Budhwar & Debrah, 2013; Ralston, Egri,

Karam, Naoumova, Srinivasan, Casado, Yongjuan, & Ruth, 2015; Tian, 2016). Classic

classifications of EM imply a bigger difference in institutional environment compared to DM

than the definition of transitioning or developing markets. Transitioning/developing markets

are defined as countries that went through a series of significant institutional transitions from

central planning toward more market competition. They are a subset of EM, but thus with

specifically different institutional characteristics, embedded in a shared history and focus on

market reforms (Meyer & Peng, 2016). Therefore, future research should focus on new

market type categorizations to account for differences in the moderation effect. At the same

time, studies focus on differences between developed and emerging markets but often fail to

account for differences among markets. This is an additional critique on grouping markets

along market type (Meyer & Peng, 2016). Still, the addition of the institutional measures

indicated that the average formal institutional environment does differ substantially in terms

of political risk and risk concerning business freedom. Grouping the countries together based

on these indicators would result in a similar division as the ECON variable, making it a

relevant categorization for the interpretation of results nonetheless.

Finally, the moderating effect of R&D Intensity was significant in other studies as a

separate moderator on the I-P relationship. In this study, R&D Intensity was found to predict

performance. The hypothesized effect of R&D intensity as a moderator via Home Country

50#

Environment, however, was not significant. Low to medium regions were found to minimize

differences between EM and DM, but can only be considered as an indication for future

research. These results can be explained by two alternative reasons: 1) R&D Intensity

moderates the I-P relationship in general and is equally relevant for both EM and DM MNEs;

2) the missing values for R&D intensity in made the sample size too small to find statistical

support for the hypothesis. R&D intensity has previously been found to significantly

moderate the I-P relationship (Lu & Beamish, 2004; Kotabe et al., 2002; Musteen et al.,

2014). Luo and Tung’s (2007) study, among others, suggested a focus technological

innovation mattered more for EM than DM MNEs’ international success. The findings of this

study suggest it could be equally important for both market type MNEs. No real claims can be

made on the basis of this study, however, because of the missing values for R&D Intensity for

a large part of the sample limiting the generalizability of results. Future research should study

the effect with the appropriate sample size.

51#

6. Conclusion

Scholars studying the I-P relationship mainly looked at the direction and shape, while

the moderator effect of Home Country Environment was understudied. Studies by Wan and

Hoskisson (2003) indicated there was a moderation effect of institutional environment,

although their study only included MNEs from Western countries. Marano et al. (2016)

conducted a meta analytical study indicating a different I-P relationship for countries of EM

and DM countries. This study builds on their findings by using similar measures for both EM

and DM markets in a single study. Furthermore, R&D intensity has been found to moderate

the I-P relationship in general. Again, the differences in that effect for MNEs from EM vs DM

home countries were not addressed in prior research. Therefore, the following research

question was formulated to fill this research gap:

“What is the effect of home country environment and R&D intensity on the

internationalization and performance relationship for firms from developed versus

emerging countries?”

A quantitative database study was devised to study the relationship. The final sample

consisted of 422 data points: 66 DM MNEs and 76 EM MNEs yielding 422 firm observations

over a three year period (2011 – 2012). The dependent variable was calculated as ROA. The

Independent Variable Internationalization was a composite measure of the ratios of Foreign

Sales to Total Sales, Foreign Employees to Total Employees and Foreign Assets to Total

Assets. The applied models were two hierarchical regression models leading to the main

model: a three way interaction to test the hypothesized moderation-moderation effect

The study’s main finding is that the Home Country Environment moderates the I-P

relationship. EM MNEs performance is considerably higher for all levels of

52#

internationalization, with considerably high performance potential at high levels of

internationalization. On the other hand, DM MNEs performance slightly goes down for higher

levels of internationalization and potential ROA is within a smaller range. Furthermore, R&D

intensity is a significant predictor for ROA, but does not moderate the relationship between I-

P in this model. Analysis does indicate ranges of influence for RD intensity, but the issue of a

large amount of missing values for (Z-)RDINT creates inconclusive results on Hypotheses 3a

and 3b. Finally, an additional finding of this study is that formal institutions show greater

differences than informal institutions for DM and EM markets, indicating formal institutional

risk of the home country environment in terms of POLCON and BFREE are the best

predictors for performance.

This study has several limitations. First, the sample consists of MNEs only and had a

large number of missing values for R&D Intensity. This limits the generalizability of the

findings. It still is relevant to map the three-way interaction effect of R&D Intensity and

Home Country Environment on the I-P relationship, and it is thus highly recommended as a

topic for future research. Also, a larger sample with the same number of MNEs per country

would improve the validity of the findings and the generalizability of the results. Furthermore,

recent theories suggest classification of EM and DM markets could be an oversimplification

of reality. EM countries can be subdivided into developing markets and transitioning markets,

characterized by different institutional environments. Future research should focus on

addressing the differences among the EM and among DM countries.

#

#

#

#

! !

53#

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