The Effect of Institutional Distance and Host Country Institutional Quality on Location Choice of the MNEs in Growing Industry: Case of Renewable Energy Firms

The Effect of Institutional Distance and Host Country

Institutional Quality on Location Choice of the MNEs

in Growing Industry: Case of Renewable Energy Firms

MASTER THESIS

MSc International Business & Management

The Effect of Institutional Distance and Host Country

Institutional Quality on Location Choice of the MNEs

in Growing Industry: Case of Renewable Energy Firms

Faculty of Economics & Business Department of International Business

Acknowledgement

Firstly, I would like to express my sincere gratitude to my supervisor Dr. Laetitia Em, for her constructive feedbacks and remarks throughout the whole process of writing my thesis as well as her continuous support during this challenging time of pandemic.

Moreover, I would like to thank you my family for their support and for providing me this opportunity to continue my studies at university of Groningen at which, while I learnt so many interesting subjects, I really enjoyed the atmosphere.

Table of Contents

ABSTRACT ... 5

1. INTRODUCTION ... 6

2. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT ... 8

2.1. LOCATION CHOICE IN INTERNATIONALIZATION: ... 8

2.1.1. Behavioral Theory: ... 9

2.1.2. Economics Theory: ... 10

2.2. LOCATION CHOICE AND MNES IN GROWING INDUSTRIES: ... 11

2.3. INSTITUTIONAL THEORY,INSTITUTIONAL DISTANCE AND LOCATION CHOICE: ... 12

2.4. THE NORMATIVE, COGNITIVE, REGULATIVE INSTITUTIONAL DISTANCE, HOST COUNTRY INSTITUTIONAL QUALITY AND LOCATION CHOICE: ... 14

2.4.1. Normative and Cognitive distance and location choice of the MNEs in a growing industry: ... 15

2.4.2. Regulative distance and location choice of the MNEs in a growing industry: .... 16

2.4.3. Host country Institutional quality and location choice of the MNEs in a growing industry: ... 18

2.5. CONCEPTUAL MODEL: ... 20

3. DATA AND METHODOLOGY ... 20

3.1. RESEARCH PHILOSOPHY STATEMENT ... 20

3.2. SAMPLE DEVELOPMENT: ... 21 3.3. DEPENDENT VARIABLE: ... 22 3.4. INDEPENDENT VARIABLES: ... 22 3.5. CONTROL VARIABLES: ... 24 3.6. DESCRIPTIVE STATISTICS: ... 25 3.7. ANALYSIS APPROACH ... 26 4. RESULTS: ... 28 4.1. CORRELATION MATRIX: ... 28 4.2. REGRESSION RESULTS: ... 28 5. CONCLUSION ... 33 5.1.DISCUSSION: ... 33 5.2.CONTRIBUTIONS: ... 36

5.3.LIMITATIONS AND AVENUES FOR FURTHER RESEARCH: ... 38

REFERENCES ... 41

Abstract

By applying the institutional lens, the aim of this paper is to explore the extent to which the institutional distances (namely cognitive, normative and regulative distances, according to Scott’s (2005) classification) and host country institutional quality affect the location choice strategies of the MNEs in a growing industry. In order to test the hypotheses, an OLS regression analysis is conducted on the basis of data from 1287 subsidiaries, obtained from 100 MNEs which are active in the renewable energy industry. The effect of cognitive, normative and regulative distances is examined separately and according to the findings of the paper cognitive distance has a negative effect and normative as well as regulative distances show a positive effect on the internationalization of the renewable energy industry MNEs. Moreover, the host country institutional quality also demonstrate a positive effect on the location choice of the MNEs in growing industry. The current paper is one of the first to study the institutional distance effect on internationalization of the firms in a growing industry.

Keywords:

1. Introduction

Internationalization is defined as going beyond national geographic borders (Ruzzier & Hisrich, 2006) and it consists of different stages (i.e. location choice, entry mode, global integration and subsidiary-MNE performance in due course) (Beugelsdijk, Kostova, Kunst, Spadafora, & van Essen, 2018).

Compared to some decades ago, recent changes in global economy like economic liberalization and revolution of market structures has led to more complications in location choice decisions for the firms which want to internationalize (Pogrebnyakov & Maitland, 2011). This also raises the importance of the need for more comprehensive studies regarding the location choice in internationalization concepts. In fact, the location choice refers to the countries in which the MNEs intend to invest (Parietti, 2017).

The determinants that explain the location choice decisions of the firms can be viewed from different theoretical perspectives, containing differences between home and host country, based on the behavioral theory as well as host country specific characteristics, based on the economic theory (Romero-Martínez, García-Muiña, Chidlow, & Larimo, 2019).

Differences between home and host country or in other words their distance, develop additional costs of doing business for the firms and this additional cost of doing business abroad refered to as the liability of foreignness (Zaheer, 1995; Ghemawat, 2001). Therefore, the notion of distance is not separable from international business and it is almost included in all the international business subfields (Parietti, 2017)

Over the past few decades the effect of various types of distances such as geographical, political, economic, administrative and cultural (Ghemawat, 2001) on different stages of the internationalization has been increasingly investigated, however, institutional distance has been the subject of fewer investigations (Hutzschenreuter, Kleindienst, & Lange, 2016). The term institutional distance was first developed by Kostova (1996), which refers to the degree of differences between home and host country institutions. According to North (1990) institutions of a country determines the framework for the activities of the market players in that country. Consequently, substantial distances between home and host country of the firm will lead to a higher liability of foreignness, in the sense that, this distance limits the effective interaction of the firm with the market players in that host country (Romero-Martínez et al., 2019).

to economic, political or regulative conditions in a country (Romero-Martinez, Garcia, Muina, Chidlow, & Larimo, 2019) which will make a specific location more or less appealing for firms to invest. These factors can be studies in a broader concept that is the quality of the institutions in a host country. Weak institutions in a host country build serious entry barriers to that country by providing additional cost of doing business and consequently higher liability of foreignness (Nielsen, Asmussen, & Weatherall, 2017).

There are limited studies with regard to the extent to which different institutions can affect the location choice of the firms during their internationalization (Pogrebnyakov & Maitland, 2011). Moreover, according to Beugelsdijk, Kostova, et al., (2018) review, the existing studies do not illustrate a clear answer for the effect of the home and host country institutional distance on location choice decisions, since most of the studies demonstrated mixed results. However, as it is stated earlier, nowadays, due to the global market changes, more options for location choice are available for the MNEs. This implies that they should pursue their international activities in a more diverse institutional system. This also raise the importance of enhancing the literature on the effect of institution on location choice.

According to what discussed, the aim of this paper is to study the location choice decisions of the firms from economic and behavioral perspectives and through the lenses of different institutions. For doing so, the focus of the study will be specifically on the growing industries, since I believe institutions can affect each industry in a different way. Moreover, the growing industry encompasses a wide range of industries and taking into account the rapid change in technology and IT developments which introduces new products and services to the world, growing industries have an important contribution to the global economy.

As such the research question I address in this paper is:

“to what extent do the institutional distance as well as the host country institutional quality affect the location choice of the MNEs in growing industry?”

For doing so, the classification of Scott (1995) for the study of the institutions is accepted in this paper, the classification includes normative, cognitive and regulative institutions, which I believe study the effect of each of them separately will provide a broader view on the concept. For the purpose of the study, cross sectional data is going to be collected from 1287 subsidiaries of 100 MNEs in the renewable energy industry, as one of the growing industries. A quantitative approach with different measurements for independent variables of the study will be conducted to test the hypotheses. The data is going to be collected from different data bases including Boardex, Orbis, Human development Indicators as well as Hofstede’s cultural dimensions scores and World Governance Indicators.

Using a sample of multiple home and host countries, the results demonstrate a significant positive effect of normative distance, regulative distance as well as host country institutional quality and a significant negative effect of cognitive distance on the location choice of the MNEs in renewable energy industry.

The remainder of this paper is organized as follows. In section 2, the theories of location choice in international process, institutional theory and institutional distance theory are reviewed and the literature on the impact of institutional distance and host country institutional quality on location choice of the MNEs in a growing industry is discussed. Section 3 describes databases used in this study and variable construction. Moreover, a descriptive statistics and methodology is also provided. The results of the analyses are in section 4. Finally in section 5, the discussion, theoretical and managerial implications of the findings of this study are discussed. Subsequently limitations of this study and several avenues for further research are highlighted.

2. Literature Review and Hypothesis Development

markets, lack of legitimacy of the MNE in the new market and the restrictions that the MNEs’ home country may impose on them for their internationalization (Zaheer, 1995). The liability of foreignness affects the whole process of the MNEs’ internationalization.

The internationalization of the MNEs includes several stages, within each of those stages, MNEs should take a strategic decision in order to make an efficient internationalization. Among the internationalization stages, location choice, as a first step which will affect the effectiveness of the following stages as well, receives considerable attention from multiple international business scholars such as Ahsan and Musteen (2011), Brouthers and Hennart (2007), Casillas and Acedo (2013) and Deng (2012). This is also due to the evolution of global context such as recent changes in political, economic and social environments all over the world as well as global economy integration which identified more location choices for investment of the MNEs specifically outside the boundary of developed economies (Kim & Aguilera, 2016).

Two distinct views exist with regard to the factors motivating or discouraging MNEs to invest in a particular location. One of them is related to the behavioral theory and the other one is linked to the economics theory (Kim & Aguilera, 2016). The difference between these two perspectives is that in the former the notion of distance is the central point and it mostly refers to the differences between home and host countries while the latter connected to the characteristic of the host country and the purpose of the internationalization.

2.1.1. Behavioral Theory:

As Johanson & Vahlne (1977) argued, those differences make the MNEs internationalize to the more geographically and culturally close countries. While geographical distance increases the cost of transportation and coordination between home and host countries (Zaheer, 1995), the cultural distance affects the cost of doing business abroad in a different manner. Considering that the culture is an important factor in shaping the organizational as well as individual behavior, studying the cultural differences is one of the most common used subjects within the concept of distance in international business (Beugelsdijk et al., 2018). Gathering the information regarding culture and the way of thinking of the people in the host country requires a deep integration with that country (Scott, 2008). Moreover, this information gathering is a time-consuming process which will also impose considerable costs on MNEs. Thus, when there is a large cultural distance between home and host country, these costs overweight the benefits of internationalization to that host country (Parietti, 2017).

One of the recent concepts with regard to the study of distance in international business refers to as institutional distance which receives more attention from scholars in international business studies (North, 1990; Kostova, 1997; Scott, 2008; Peng, 2009). The importance of institutional distance for MNEs is associated to the fact that MNEs are present in multiple markets and correspondingly in different institutional environments which, while providing them with more opportunities, it also leads to more challenges as well. One of those challenges is gaining legitimacy (Van Hoorn & Maseland, 2016). Additionally, given that the MNEs develop their firm routines in a specific institutional environment, it makes it difficult to transfer their firm routines and practices to the distant institutional environments. As such, the institutional distance acts as a hamper for transfer of knowledge and information between home and host country which as earlier discussed this will lead to the complications for MNEs to work effectively in those host countries by increasing cost of doing business and the liability of foreignness respectively (Xu & Shenkar, 2002).

2.1.2. Economics Theory:

the location choice decision is the result of the interaction among ownership advantage and location advantage. The ownership advantage refers to the assets, capabilities, firm-routines and product innovations which are specific to one MNE (Han et al., 2016) and the location advantage refers to for example holding natural resources, encouraging economic and political environments and institutions (Ruzzier & Hisrich, 2006). These special locational advantages of a country can attract the MNEs investments. Furthermore, within the economic concept of location choice, Dunning (1998) introduced different types of drives for MNEs to select a specific location for investment, the ones which are seeking for assets in overseas markets and the ones looking for opportunity. In such a way, the motivation for internationalization for the MNEs which are seeking assets is to have access to natural resources, human capital as well as different institutional environment. Furthermore, the purpose of opportunity seeking MNEs is to enhance their trademark and introduce their products to the new markets (Luo & Tung, 2019).

2.2. Location choice and the MNEs in growing industries:

I believe that the interpretation of the location choice of the MNEs from the behavioral and economic theories perspective is also dependent on the characteristics of the industry within which the MNE is located. In the current study the focus is on the location choice of the MNEs in growing industries. The growing phase is one out of four phases of industry life cycles1_{. The} growing industries are oligopolistic which entails that there are few players in their market, furthermore, they have a high growth rate which means that the demand for the products offered by them is rapidly increasing since they usually introduce new products and technologies to the market (Klepper, 1997). According to the mentioned characteristics, the MNEs in these industries are looking for market growth, therefore, the locations with adequate market demand are going to be their priority choices for internationalization. Moreover, for the MNEs in growing industry to be able to develop their products in those markets, they should have access to the corresponding resources in those locations, for instance natural resources or knowledgeable workforce. These locational advantages will decrease the liability of foreignness associated with the internationalization of the MNEs in growing industries which in turn will lessen the uncertainty and cost of doing business in the new markets respectively (Rhee & Cheng, 2002). Moreover, taking into account the characteristics of these MNEs the

concept of distance or differences between home and host countries according to behavioral theory will affect their location choice in different ways, the details of which will be more discussed in the following sections.

2.3. Institutional theory, Institutional Distance and Location choice:

By providing guidelines for political, economic and social exchanges, the institutions reduce the uncertainty within the community (North, 1990). These guidelines or rules impose restraints on conventions and norms in the community which in turn frame the expected behavior as well as establish legitimacy in different markets (Keig, Brouthers, & Marshall, 2019). Considering the fact that each community signifies a specific combination of institutions, for MNEs, the differences between home and host country institutions are crucial to be able to operate efficiently across countries (Kogut, 1991; Xu; & Shenkar, 2002).

The classification of Scott (1995, 2008) with regard to different types of institutions among nations is adapted for further analyzing the institutional distance in internationalization of the MNEs. Three distinctive institutional pillars are developed by Scott (1995): cognitive normative and regulatory.

The cognitive pillar relates to social psychology (Scott, 2014). For the MNE to be legitimated in the host country it is important to follow the cognitive structure of the host countries (Suchman, 1995). Cognitive institutions refers to “shared beliefs, logics of action and mental modes” (Chao & Kumar, 2010:p.2; Scott, 2011). As such, differences in thinking manner in different countries lead to cognitive institutional distance which affects MNEs strategies if they are not in line with the countries’ “national symbols” (Xu & Shenkar, 2002). The cognitive institutional distance also results in high mimetic isomorphism pressure in the internationalization of the MNEs. According to March (1981), mimetic isomorphism exists when “enough social actors” in a community act in a certain way, so this course of action becomes institutionalized in that environment and the newcomers will feel the pressure to act in the same way to be accepted in that environment and gain legitimacy. As such, these circumstances will discourage the MNE to choose the host countries with significant cognitive distance as their location choice for internationalization.

host country is essential. In other words, receiving legitimacy depends on how much cultural support the MNE could get in the host country (Meyer & Scott, 1983; Kostova & Zaheer, 1999). Countries can be very dissimilar with respect to their normative institutions, which mostly refer to the values of the society, on the basis of which certain behavior can be expected from members of that society. According to what discussed, the normative distance restricts the MNE’s location choice by providing barriers in transferring firm routines to the host countries with different social values and expectations, this is also argued by Xu; & Shenkar (2002).

The regulatory pillar refers to the rules and regulations for stabilization of the societies (North, 1990). MNEs have to comply with the regulatory system of different host countries in order to gain legitimacy in those host countries. Thus, when specific regulations are stricter or looser in one country comparing to the other country the MNE faces regulative distance which makes it critical for them to operate in different countries. As an example, the regulations regarding property rights are among laws which have diverse practices in different countries. Formal regulations which support extensively the intellectual property are more advanced in developed markets comparing to developing markets (Chao & Kumar, 2010). Developed regulative institutions are considered as high-quality institutions: the countries with high quality institutions make incentives for MNEs to invest in those countries. This can refer to the locational advantage in Dunning’s (1981) OLI framework. In this way, the institutional theory can explain the incentives behind internationalization of MNEs to a specific host country by analyzing the host country institutional quality (Parietti, 2017).

While the regulatory pillar is more explicit and consequently the foreigners can better understand and interpret it, normative and cognitive institutions are more implicit and since they are rooted in the social values of the community, for foreigners it is more difficult to understand them (Parietti, 2017).

Pursuing from the previous section, the central focus of the current study is to find out to what extent institutional distances (cognitive, normative and regulative distances) and host country institutional quality drive the location choice of the MNE in growing industry within their internationalization.

institutional environments. In the following section, I discuss whether this can hamper the process of their internationalization to distant markets or not.

2.4. The normative, cognitive, regulative institutional distance, host country institutional quality and location choice:

Norms and cognitions are rooted in the culture of each country which makes them hard to understand since comprehension of the other cultures in many cases is tacit (Estrin, Ionascu, & Meyer, 2005). Consequently, the normative and cognitive institutional distances can increase the cost of doing business in a specific host country and make a negative impact on internationalization to that host country.

Following from behavioral theory in location choice for internationalization and Uppsala model which are discussed earlier, the MNEs will choose the host countries which have similar normative and cognitive institutional environments either to their home country or to the other countries that they have already internationalize to and gained sufficient experience regarding their normative and cognitive institutional setup.

Contrary to the above discussion, there are factors which repress the negative effects of normative and cognitive distance and this opens a new perspective on studying these effects on the internationalization (Beugelsdijk, Kostova, et al., 2018; Luo & Tung, 2019). According to Andersson (2004), the suitability of the internationalization theories depends on the industrial context they are applied to. Subsequently, the concept of gradual expansion in the Uppsala model also depends on the characteristics of the industry. In a growing industry, the industry is volatile, which means changes are so quick that learning from previous internationalizations is almost impossible. Moreover, as discussed in the previous section, the MNEs in a growing industry need to internationalize rapidly since their products are in increasing demand and there are limited players in the industry, so that they do not have enough time to invest in collecting information about their host countries.

2.4.1. Normative and Cognitive distance and location choice of the MNEs in a growing industry:

Normative institutional distance has a greater effect on the MNEs that their competitive advantage is attached to their firm routines, because it makes it hard for them to transfer their competitive advantage to the countries with distant norms and behaviors.

However, the MNEs in a growing industry are willing to transfer their new products and/or technology (Andersson, 2004) rather than their firm routines. Therefore, I argue that they are more flexible to internationalize to normatively distant institutions and more open to adapt new norms and behaviors in order to access to the new markets (market growth). In fact, MNEs in a growing industry combine ownership and location advantages in order to exploit the resources and opportunities of the host country in their internationalization. This argument in

relation to normative distance is also supported by Xu and Shenkar (2002), who claimed that when MNEs are searching for competitive advantage in the host country, “host country-based competitive advantage” and they do not own “routine-based competitive advantage”, more likely they enter countries with greater normative distance (Xu, Shenkar, 2002, p.611).

Furthermore, the MNEs in a growing industry have this independency to choose locations for internationalization with high cognitive distance. One of the reasons for this is less mimetic isomorphism pressure (DiMaggio & Powell, 1983) that these MNEs will encounter in their host countries. As already stated, the growing industries are oligopolistic markets, so the limited number of players in the market provides this opportunity for the MNEs that the community of the host country are not able to compare them with many other firms in that community. As such, their mental modes toward that industry are not well-built and it is less likely that their activities in the host country are deemed to be in contradiction with the social values or national symbols. This is supported by Li and Ding (2013) who showed that mimetic pressure positively affected the firm internationalization when there is a considerable number of competitors in the market.

Hypothesis 1) Cognitive institutional distance does not have a significant effect on location choice of the MNE in growing industry.

Hypothesis 2) Normative institutional distance does not have a significant effect on location choice of the MNE in growing industry.

2.4.2. Regulative distance and location choice of the MNEs in a growing industry:

According to the institutional economics school of thought (Kostova et al., 2019), regulative institutions define the rules that are the bases for the economic activities in a community and consequently reduce risk and uncertainty with regard to those economic activities. As such, regulative distance refers to the difference between the rules and regulations which support the market transactions in the home versus the host country (Kostova et al., 2019). According to Parietti (2017), this regulative distance leads to the liability of foreignness which in turn will cause higher uncertainty and cost of doing business in the host country. Accordingly, he hypothesized that the MNEs will have a lower amount of investment within the countries with a higher formal institutional distance from their home country, which is also supported by his findings (Parietti, 2017). In this regard, whether MNEs are from a high or low regulative institution, they will encounter some constraints in order to gain legitimacy, when they internationalization to the regulatory distant countries. One of the sources that cause those constraints, is institutional duality, since, MNEs are exposed to both home and host country regulative institutions (Kostova & Roth, 2002). In other words, while MNEs feel the pressure to gain legitimacy in the host country by adapting their regulative practices, those practices should not be in violence with home country’s regulative practices. An example for the institutional duality is with regard to the corruption, when an MNE face the pressure from the host country to engage in corruption in order to be able to run the business in that host country, while corruption has been prohibited by the home country (Spencer & Gomez, 2011). According to DiMaggio and Powell (1983) this refers to as coercive pressure which originates from governmental and authority control and legitimacy issue. High coercive pressure will impose higher cost of doing business on the MNEs in their internationalization.

In my opinion, this aspect mostly affects the MNEs from higher level regulative environments when they want to internationalize to lower level regulative environments. It is because, in a less developed regulation systems, the rules are implicit and vague which make them hard to understand before having a direct experience in those countries. Contrarily, the rules and regulations in a highly developed regulation systems are more explicit and well defined, which makes it easier to learn and understand for foreigners.

As such, MNEs from high regulative system will encounter greater liability of foreignness and uncertainty and more conflicts to gain legitimacy when they internationalize to lower regulative system.

Another facet of the MNEs in the growing industries is that they are looking for locations to expand their market and introduce their new products. High regulative institutions are more supportive of financial establishments by providing suitable rules and regulations for their economic transactions. Forceful financial institutions, will provide a better economic condition for the community and higher standards of living for citizens and or more capital available for firms (Romero-Martínez et al., 2019), which makes them a better location for market growth for the MNEs. This is not the case for the countries located in a lower regulative institution. I believe that, this is another constraint for MNEs from highly developed institutions if they want to choose less developed institutional environments as their location for internationalization.

With respect to the MNEs from less developed institutional systems, there exist different challenges to get legitimacy when they move to stricter regulative systems. As I already discussed, it’s easier for these MNEs to learn about the regulative conditions with regard to economic transactions of more developed regulative systems. However, the authority control over these MNEs will be higher in the host countries with high regulative system, which in turn will impose more restrictions on them and leave less options for their strategic decision. As such, in this way, they have a disadvantage comparing to the local firms (Zaheer and Mosakowski, 1997). More specifically with respect to the growing industries, considering that the firms in this industry introduce a new technology or product, the standards with regard to those technology and products can be more advanced in highly developed regulative countries comparing to the less developed regulative countries. This even set more limitations on those MNEs to internationalize their products.

Hypothesis 3) Regulative distance has a negative effect on the location choice of the MNEs in a growing industry.

2.4.3. Host country Institutional quality and location choice of the MNEs in a growing industry:

While regulative institutional distance between the home and the host country decreases the probability that this host country is chosen as the favorable location choice for internationalization of the MNE, the weak institutions of the host country will also discourage investing in that host country (Chao & Kumar, 2010). The weak institutions of a country result in an excessive costs of doing business in that country due to the high level of for example bureaucracy, corruption, political instability or poor legal system (Nielsen et al., 2017). When the host country has a higher quality institutions compared to the home country, it makes it more favorable for the MNE to invest in that host country, even if there is a significant institutional distance between the home and the host country (Peres, Ameer & Xu, 2018). This refers to the location advantage as discussed earlier which plays an important role in location decision of the MNE.

As already mentioned in previous sections, one of the key measures of a high-quality institution is supporting the intellectual property rights. In a country with high-quality institutions, proper rules encourage the intellectual property rights in that country (Kaufmann, Kraay, & Mastruzzi 2011) and in this way the MNEs in that country will feel secure to introduce their products and innovations. In case of MNEs in growing industry since they possess new resources like high technological products or a novel innovation, it is essential for them to be able to protect those capabilities/assets as their competitive advantage when they enter into new markets. Consequently, the better the institutions support intellectual property rights, the more chance that the MNE in a growing industry choose that country as their location for internationalization.

The transparent and well-defined institutions will decrease the liability of foreignness MNEs face in a growing industry as well as the uncertainty in the new market. Transparent institutions can be characterized by low or no corruption. The level of corruption in a country refers to the extent that public power in that country is used for the personal benefit (Kaufmann et al., 2011). Therefore, the lower the level of corruption in a country the more chance that the MNE in growing industry choose that country as their location for internationalization.

Also, I argue that the level of the regulation developments pertaining a specific industry in a host country, has a crucial impact on the location choice of the MNEs that are active in that specific industry. This is also confirmed by the study of Pogrebnyakov & Maitland (2011), as their findings presented a significant effect of industrial level regulative distances on location choice of the MNEs in the communication industry. This implies that rules and regulations at the industry level has an important role in MNEs location choice. Consequently, the host countries that establish better regulations with regard to a specific growing industry in comparison to other host countries will be able to attract more MNEs within that industry.

Based on the reviewed literature, I suggest the following hypothesis:

2.5. Conceptual model:

Figure 1 - Conceptual Model

3. Data and Methodology

3.2.Sample development:

To create the sample, I looked for the MNEs in the renewable energy industry. In light of the increasing concern about the global and environmental issues which also affects the environmental laws and regulations to reflect those concerns, MNEs feel the urge to find new ways to meet the environmental challenges (Asemokha, Ahi, Torkkeli, & Saarenketo, 2019). Nowadays, renewable energies have a significant role to achieve those goals. While the renewable energy technologies contribute to the reduction of the emissions, they also contribute to the economy by creating new opportunities in the energy market such as capital investments and new jobs (Ellabban, Abu-Rub & Blaabjerg, 2014). Therefore, the increasing investments in renewable energy technologies place this industry among the fast-growing industries (Asemokha et al., 2019).

Due to the newness of the industry there are not many studies with regard to the drivers of its internationalization and more specifically the effect of the different institutional distances. Considering the aforementioned points, for the purpose of this study the data for the sample is derived from the top 100 MNEs in renewable energy industry all over the world ranked by their 2018 year end revenue obtained from BoardEx. The BoardEx database provides an extensive data for around 17,000 public and private companies worldwide (BoardEx, 2020). Moreover, it includes the firm data from a wide range of developed and developing countries, classified in the groups of Europe, North America, UK and Rest of the world.

At the next step the information of the subsidiaries belonging to those 100 MNEs extracted from Orbis. Orbis is also providing considerable amount of the data with regard to different firm-level variables especially financial and ownership data.

3.3. Dependent Variable:

The dependent variable in the current study is location choice of the MNE in the growing industry. The dependent variable is measured by the proportion of the MNEs’ foreign subsidiaries to examine the internationalization scope of the MNEs (Dörrenbächer, 2000). This measurement is presented as a percentage which shows the proportion of the number of subsidiaries of the MNE in one specific house country relative to that MNEs’ total number of subsidiaries. In this way, I take into account the weight of each host country in the whole internationalization portfolio of the MNE. Considering the purpose of the study I found this measurement most suitable, since it shows the tendency of the MNE to invest more in a specific host country.

According to the normal probability plot of the dependent variable, this variable is not normally distributed, Baltagi (2008) discussed that if the variables are not normally distributed, they can be converted by taking their natural logarithm, so the log value of the dependent variable is considered to have stronger results. In appendix B, the normal probability of the dependent variable before and after taking the logarithm is illustrated.

3.4.Independent Variables:

Four independent variables are used in different models in order to survey effect of institutional distance between home and host countries, namely normative, cognitive and regulative distances as well as institutional quality of the host country on dependent variable. Various measurements are developed in order to study the institutional distances.

As discussed in the literature review the normative pillar affect legitimacy of the MNE in the host country by the amount of cultural support that the MNE could get in the host country. Following this discussion, for measuring the normative institutional distance between home and host country of the MNEs, the Hofstede six cultural dimensions scores are used. These scores are retrieved from Hofstede’s website. These dimensions include power distance, uncertainty avoidance, individualism, masculinity (Hofstede, 1980), long-term orientation (Hofstede & Bond, 1988) and indulgence (Hofstede, Hofstede & Minkov, 2010). The Hofstede framework is the most used data source for the study of culture at country level in international business and management literature (Beugelsdijk, Kostova, et al., 2018).

per the following formula. This measurement has become one of the essential variables in international business and management studies during the last decade (Beugelsdijk, Ambos, & Nell, 2018).

possibility of high correlation between these WGI measurements (Mauro 1995) that can lead to multicollinearity and consequently reduce the relevance of each individual indicator, an aggregate component of the these three dimensions is used. Thus, the aggregate component is calculated according to the below formula as the difference between average scores of rules of law, control of corruption and regulatory quality of home and host country.

Regulative Distance = ((IRR, Home+ICC, Home+ IRQ, Home)/3) - ((IRR, Host+ICC, Host+ IRQ, Host)/3)

With respect to the host country institutional quality variable, I used a different set of measurement comparing to the measurements applied for regulative distance, despite the fact that both variables capture somehow the same concept. Following previous literature (Romero-Martinez, Garcia, Muina, Chidlow, & Larimo, 2019), I operationalized the host country institutional quality by using the institutional pillar of the Global Competitiveness Index (2018) by the World Economic Forum. This index evaluates 140 countries on the bases of their competitiveness, more specifically the institutions pillar within this index provides a wide range of estimations such as; security, property rights, transparency, corporate governance and renewable energy regulations, etc. (reports.weforum.org, 2018) the details of which can be found in appendix C. As discussed within the literature review, this variable refers to the effectiveness of the institutions in supporting and promoting economic activities within that country. By using the Global Competitiveness Index while I am preventing the multicollinearity in my analysis (by not using the same measurements of the regulative distance independent variable), I am including a comprehensive estimation of the institutional quality of different countries. More importantly, following my literature review, well-defined industry specific regulations are also incorporated in providing a sound environment for the investment of the MNEs in that specific industry. The institutions pillar dimension within this index also provides the information regarding the level of development of the renewable energy regulations in each country which is in line with the sample I developed for this study.

3.5. Control Variables:

otherwise the closest preceding year, which accounted for less than 15% of the total number of the MNEs employed for the study.

Inter-country control variables : in order to control for economic performance of the home and host country and on the basis of the previous research (Billington, 1999), GDP per capita is used to control for the living standards. This factor shows the economic well-being of a country which can be an incentive for internationalization of the MNEs to that country. Moreover, economic distance is generated by calculating the difference of the home and host country’s GDP per capita.

In this study I also incorporated different control variables that may affect the relationship between institutional distance and internationalization. First geographical distance that refers to the physical distance between two countries. High geographical distance comes along with high transportation and or communication costs between two countries (Ghemawat, 2001). The data for geographical distance is retrieved from Centre d'Études Prospectives et d’Informations Internationales (CEPII) (Mayer & Zignago, 2012) and because of large range of numbers the logarithm of the geographical distance is used in the regression analysis. Common boarder is also used as a dummy variable to account for the fact that two pairs of countries have a common border or not. To control for the normative distance two inter-country variables selected to use in the study including common language and common colony which the data again extracted from The CEPII data set. According to CEPII, both variables provide dummy values in case that two countries have the same colonial history or not and if a specific language is spoken by at least 4% of the population of either country (Melitz & Toubal, 2012).

3.6. Descriptive Statistics:

The descriptive statistics of all variables that are defined above and which used in the regression analysis for the purpose of this study, is illustrated in table 3.1. Since for the binary variables descriptive statistics do not make sense, table 3.2 displays the frequency statistics for binary variables.

Table 3.1– Descriptive Statistics

Obs. Mean Median SD Skewness Kurtosi Min. Max Ln subs 1287 -4.5411 -4.158 2.500 -0.498 2.602 -10,633 0 Cognitive Distance 1287 1.1444 0.422 1.666 2.547 11.862 -0.6 12.789 Normative Distance 1287 1.229 1.097 1.136 0.899 3.470 0 6.008 Regulative Distance 1283 -0.459 -0.365 1.253 0.074 2.515 -3.984 2.387 Host Inst. Quality 1287 3.981 4.1 1.576 -1.310 4.362 0 6.1 Economic Distance 1287 -15150.3 -15191.5 37366.8 0.340 3.729 -113544.7 175970.4 Ln geo Distance 1168 8.476 8.856 0.955 -0.855 2.714 5.1525 9.896 Ln Firm Total Asset 1287 15.570 16.375 1.807 -0.820 5.368 8.356 21.470

Table 3.2 –Binary Variables

Freq. Percent Cum.

CommonBorder (0) 1.177 91.45 91.45 CommonBorder (1) 110 8.55 100 CommonLang (0) 1.060 82.36 82.36 CommonLang (1) 227 17.64 100 CommonColony (0) 1.193 92.7 92.7 CommonColony (1) 94 7.3 100 3.7.Analysis Approach

Table 3.3- Description of Variables included in the models

Variable Description/Measurement

Ln subs Log value of the proportion of the number of subsidiaries in a

specific host country in relation to the total number of subsidiaries of each MNE

Cognitive Distance Cognitive distance measured by the difference between average _{years of schooling (age 25+) of home and host country} Normative Distance Normative distance measured by Hofstede cultural dimensions Regulative Distance Regulative distance measured by WGI indicators including rule of

law control of corruption and regulative quality

Host Inst. Quality Institutional quality of the host country measured by the institutional _{pillar scores of the world competitiveness index.} Economic Distance Economic distance measured by the difference between GDP per _{capita of home and host countries} Ln geo Distance Log value of the geographical distance between home and host _country Ln Firm Total Asset Firm size measured by log value of the firm total asset

Common Border Common border measures whether the home and the host country have come on border together which takes the map view of 1 and if they do not have a common border it takes the value of 0

Common Lang

Common language, measures whether a language is spoken by at least 9% of the population in both countries, takes on the value of 1 if this is the case, and 0 if this is not the case.

Common Colony

4.

Results:

4.1. Correlation matrix:

The correlation matrix of all variables included in the study is shown within the tables 4.1. Overall, all independent variables show a significant relation with the dependent variable. While, cognitive distance showed a negative correlation, normative distance, regulative distance and host country institutional quality show a positive correlation with dependent variable.

According to table 4.1., there is a correlation of 0.765 between two independent variables of the study namely regulative distance and host country institutional quality which can be an alert of multicollinearity issue (Luger, Raisch & Schimmer, 2018). Since, multicollinearity would cause serious problems with regard to the reliability of the regression results (Alin, 2010), I conducted the Variance Inflation Factor (VIF) test to investigate the extent of the multicollinearity issue (Appendix D) The results demonstrate values below 2 for all independent and dependent variables, which are not exceeding the threshold of 10 (Dormann et al., 2013). Moreover, I run two regression models one with presence of both of aforementioned independent variable and one by eliminating one of them and the results of the regression models do not show a change in coefficient’s sign or value of the R-square. Consequently, I concluded that the correlation of these two independent variables will not affect the reliability of the results.

Furthermore, there is also a high correlation of 0.836 between regulative distance as one of the independent variables and economic distance as one of the control variables. Again, I run two regression models to compare the results, and the results show a considerable difference. As such to deal with this issue I did not include economic distance as control variable in the regression models related to regulative distance as independent variable.

4.2. Regression Results:

with the control variables. Model 4 is showing the estimated coefficients for hypothesis 4 which is related to the host country institutional quality. Finally, Model 5 includes all independent variables as well as control variables to compare the results with previous constructed models. The regression results of these 5 models are reported in Table 4.2, and will be further discussed below.

Results Model 1: this model shows the effect of cognitive distance as one of the institutional pillars on location choice of the MNEs in growing industry and in their process of internationalization. The model has an R² of 0.372, which means that around 37% of changes in the dependent variable can be explained by the changes in cognitive distance and a significant F statistic of 98.4 (p<0.01). Results show a coefficient of -0.090 with respect to cognitive distance which is significant at the p<0.05. While the magnitude of the coefficient is not so high (around -9%), this indicates that the higher the cognitive distance between home and host country the less likely that an MNE in growing industry chooses those host countries as their location choice. Since the results are significant, it shows that cognitive distance has a significant effect on location choice which is in contrast with hypothesis 1 (Cognitive distance does not have a significant effect on location choice of the MNE in growing industry). Therefore, hypothesis 1 is not supported based on this model.

Table 4.1- Correlation between the variables included in the models (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (1) Ln subs 1.000 (2) Cognitive Distance -0.192* 1.000 (3) Normative Distance 0.083* 0.186* 1.000 (4) Regulative Distance 0.366* -0.242* 0.034 1.000

(5) Host Inst. Quality 0.464* -0.270* 0.098* 0.765* 1.000

(6) Ln geo Distance -0.165* 0.190* 0.221* -0.040 -0.197* 1.000

(7) Ln Firm Total Asset -0.419* 0.026 -0.001 -0.151* -0.164* -0.023 1.000

(8) Economic Distance 0.313* -0.199* 0.012 0.836* 0.571* -0.044 -0.183* 1.000

(9) Common Colony 0.071* -0.096* -0.069* -0.059* -0.0579* 0.101 0.014 -0.006 1.000

(10) Common Lang 0.280* -0.079* -0.120* 0.080* 0.131* 0.019 -0.170* 0.083* 0.528* 1.000

Robust standard errors in parentheses reported under the coefficients *** p<0.01, ** p<0.05, * p

Table 4.4- OLS Regression Results on dependent Variable “Ln Subs”

Model (1) Model (2) Model (3) Model (4) Model (5) Cognitive Distance -0.090** (0.013) -0.104** (0.002) Normative Distance 0.419*** (0.000) 0.280*** (0.000) Regulative Distance 0.573*** (0.000) 0.250*** (0.000)

Host Inst. quality 0.835***

(0.000) 0.484*** (0.000) Economic Distance 0.000*** (0.000) 0.000*** (0.000) -- 0.000*** (0.002) -- Ln geo Distance -0.311* (0.073) -0.426* (0.071) -0.343* (0.072) -0.168** (0.017) -0.260*** (0.000) Ln Firm Total Asset -0.501**

Results Model 3: in this model the effect of the last institutional pillar, regulative distance, on location choice of the MNEs in growing industry is tested. As already discussed, I do not include economic distance as control variable in this model. The model demonstrates an R² of 0.374, which means that around 37% of changes in dependent variable can be explained by the changes in regulative distance and a significant F statistic of 100.5 (p<0.01). Results indicate a coefficient of 0.573 with respect to regulative distance which is significant at the p<0.01. This indicates that the higher the regulative distance between home and host country the more likely that and MNE in growing industry choose those host countries as their location choice. Again, the results of the model are significant, which confirms that regulative distance has a significant effect on location choice. However, this effect is positive which is not in line with hypothesis 3 (Regulative distance has a negative effect on location choice of the MNE in growing industry). Consequently, hypothesis three is not supported by the results of the regression analysis of this model.

Results Model 4: the model presents the impact of the host country institutional quality on location choice of the MNEs in growing industry. The model demonstrates an R² of 0.430, which means that around 43% of changes in dependent variable can be explained by the changes in host country institutional quality and a significant F statistic of 125.33 (p<0.01). Results indicate a coefficient of 0.835 with respect to host country institutional quality which is significant at the p<0.01. Therefore, the independent variable in this study shows a positive and significant effect on dependent variable. Correspondingly, hypothesis 4 (Host country institutional quality has a positive effect on location choice of the MNE in growing industry), is supported by the results of this regression analysis.

Results Model 5: this model includes all the independent variables together with the control variables (except economic distance). In this model, I can observe the extent to which the results of the other 4 models are reliable. As can be seen Model 5 has an R² of 0.455, which means that around 46% of changes in the dependent variable can be explained by the changes in cognitive, normative and regulative distance as well as host country institutional quality and it shows a significant F statistic of 107.71 (p<0.01). Results of model 5 are completely consistent with the results of models 1,2,3 and 4.

which included in models 1,2 and 4 has a low positive effect which is significant at p<0.01. Log value of geographical distance has a negative significant effect ranging from 0.168 to -0.426 that are significant at p<0.1. Log value of firm total asset has a negative significant effect ranging from -0.461 to -0.504 that are significant at p<0.05. Common border has a positive significant effect ranging from 0.574 to 0.819 that are significant at p<0.1 in Models 1 and 3 and at p<0.05 in Models and at p<0.01in models 4 and 5. Common language has a positive significant effect ranging from 0.989 to 1.430 that are significant at p<0.01. Common colony has a mixed result but all of them are insignificant: in Model 1 it has a negative effect with a coefficient of -0.083 and in the other three models the effect is positive ranging from 0.082 to 0.331.

5. Conclusion

The current study incorporates different theories including location choice theories, institutional theory an institutional distance theory to improve the literature with regard to the effect of institutions on location choice of the MNEs. The research question aimed to be addressed in the study is “to what extent do the institutional distance as well as the host country institutional quality affect the location choice of the MNEs in growing industry?”

For the purpose of addressing this research question a data set of 1287 subsidiaries related to 100 MNEs in renewable energy industry for the year 2018 was created and analyzed by the use of OLS regression in order to investigate the hypotheses developed in the paper.

As presented in the previous section, except for hypothesis 4, the other hypotheses (1, 2 and 3) are not supported by the results obtained from the regression models. Possible explanations with respect to the results of the hypotheses is discussed as follows.

suppliers and governors in a community, so for a foreign firm it would be very critical to gain legitimacy in a community that their economic players have completely different mental modes comparing to them. As I argued in the literature review, MNEs will face a high mimetic pressure when they enter cognitively distant markets if specifically a considerable number of competitors already exists in that market. Because, presence of the other firms which are active in the same industry as the MNE, affect the understanding of the economic players about that specific industry. Nevertheless, this is not the case for growing industries since as discussed, they are few players in these industries. But as the findings of the this study show, there should be other factors affecting how the economic players in a country think toward a specific industry. One possible explanation is that considering renewable energy industry as one of the growing industries, in order to develop or improve consumption of renewable energies in a certain community, the public acceptance of the renewable energies is required and this public acceptance stems from the information and knowledge that the people in that community have about renewable energy industry (Karytsas & Theodoropoulou, 2014). 74% of the sample created for this study consists of MNEs with developed home countries (according to World Economic Situation and Prospects (2018) classification), which also demonstrate higher levels of education, and this confirms the discussion that renewable energy consumption is more common in highly educated societies. Lower levels of education also contribute to the lack of qualified workforce for implementation of the renewable energy systems in the host countries that is one of the barriers for diffusion of the renewable energy (Economics, 2013). As a consequence, I interpret the findings of the analysis with respect to negative effect of cognitive distance as follows. On the one hand, the MNEs from countries with high levels of education choose the host countries with the same or higher level of education. Since these host countries have higher knowledge about environmental issues and renewable energies so they are more ready to adjust their lifestyle by changing their energy resources from conventional to renewable energies, also, more skilled employees can engage in the activities of the MNE in those host countries. In this way, they are entering countries with smaller cognitive distance and closer mindset toward the industry. On the other hand, with regard to the MNEs from countries with lower levels of education, since they consist only 26% of the whole sample (according to World Economic Situation and Prospects (2018) classification), it is difficult to make a definite conclusion according to the results of the regression model.

positive effect. This entails that high normative distance increases investment of the MNE in growing industry in those host countries. The normative pillar describes the social norms and beliefs of the communities (Xu & Shenkar, 2002). As such, the normative pillar is rooted in the culture of the communities and for the MNEs to acquire legitimacy in that community they could be able to make a balance between their organizational culture and the host country’s culture. However, making this balance will be more critical for the MNEs with their competitive advantage embedded in their firm routines and for MNEs in growing industry that their competitive advantage is attached to their new technology or product that they introduce to the market, the effect is not significant. By combining this perspective with the two other perspectives of Xu and Shenkar (2010) as well as Chao and Kumar (2009), I interpret the results of the regression analysis as follows: because normative distance does not have a negative impact on the internationalization of the MNEs in growing industry, these MNEs can turn it into a competitive advantage over other MNEs to be able to go to a more normatively distant countries. Thus, they will utilize this competitive advantage to expand their market and achieve their target of market growth. Moreover, more normatively distant countries have the potential to provide more opportunities such as access to diverse knowledge, technology or ideas for the MNE. As an example, within the sample created for the purpose of this study, one of the Spanish MNEs with subsidiaries in 159 countries has more than 20% of its subsidiaries located in the US, while the Spain has a score of 68 on uncertainty avoidance and the US 49. It shows that even though there is a considerable difference between this cultural dimension among these two countries, the MNE chose the US as one of its main host countries with the relatively low uncertainty avoidance. In countries with high uncertainty avoidance, the society resists against new technologies and or products because they usually have low tolerance for change which is usually attached to the new products and technologies (Zakour, 2004). One can conclude that low uncertainty avoidance countries are more accepting of innovations and are experts in new technologies.

formal institutional distance on location choice. The MNEs face different challenges when they go from more to less developed institutional setting and vice-versa (Trapczynski & Banalieva, 2016).

I believe that one possible explanation from the perspective of the MNEs in a highly developed regulative institutions is as follows. As already mentioned, 74% of the MNEs in the sample of the study are located in the developed countries which implies that they are from well-developed regulative institutions. Because the regulative institutions are contributed to the higher and more productive economic activities in a country (Peres, Ameer & Xu, 2018). Consequently, this means that the competition within the renewable energy industry in the developed countries is already high and this will set limitations on the market growth of those MNEs within developed markets. As the MNEs in the growing industries are looking for higher market shares for their product, developing countries can be a suitable alternative for them since they are providing a considerable market.

On the other hand, from the perspective of the MNEs in a slightly developed regulative institutions, I discuss that they have the motivation to get access to the knowledge and information of the developed countries with regard to the industry, thus they are willing to internationalize to regulatory distant markets, yet it should be taken into consideration that they consist relatively small part of my sample.

The results concerning the fourth hypothesis, which suggests that the host country institutional quality positively impact the location choice decision of the MNEs in growing industry, show support for the hypothesis. Thus, the quality of the institution settings in a host country motivate or hamper economic activity in a country (Kostova et al., 2019). This indicates that the MNEs within the sample will choose countries with highest institutional quality among their host country profile to locate most of their subsidiaries in those ones. This is also consistent with the discussions within the literature review.

5.2. Contributions:

that employed multiple home and host country samples, reported insignificant effects of institutional distance on location choice. This paper with a sample of multiple home and host countries, enhances the literature in this area by demonstrating distinctive and significant results as follows; Significant and positive effect of regulative and normative distances on location choice and a significant and negative effect of cognitive pillar.

Second, whereas among the existing researches about institutional distance and location choice, only a few of them focused on a specific industry (Madsen, 2009; Romero-Martinez, Garcia, Muina, Chidlow, & Larimo, 2019), this paper adds to the literature by concentrating on MNEs within the growing industries. The concept of growing industry includes a wide range of industries which are in the growing phase of their industrial cycle. I do this by analyzing characteristics of the firms within the growing industry with regard to three pillars of institutions separately and their impact on location choice.

Third, most of the previous articles adopted a unidimensional approach in their institutional distance studies, which means that for instance they used a single measure like WGI dimensions to study the effect of all institutions. Even though they recognized and discussed multidimensionality of the institutional distance in their theories (Kostova et al., 2019). This paper tried to overcome this limitation by applying several dimensions in order to measure the normative, cognitive and regulative distances separately in the concept of institutional distance.

Lastly, for the purpose of this study a sample of subsidiaries from a wide range of home and host countries was collected. This will help to control for the level and distance effects separately which was one of the limitations of the previous literature (Brouthers & Brouthers, 2001). Thus, the current study makes an important contribution by including a wide variety of home and host countries from different regions.

The outcomes of this paper also have some implications for managers in international business. First of all, traditionally it is assumed that institutional distances have a negative effect on internationalization by increasing the cost of doing business in foreign countries. But the findings of the current study confirm that institutional distances can be also have a positive effect on the internationalization process of the MNEs. Consequently, I believe that the managers in international business should take this into account throughout their strategic decision-making process toward location choice. As discussed in the concept of normative distance, institutional distances can also provide more opportunities for the MNEs. They can benefit from the variances in cultures, attitudes and regulations between home and host countries during their internationalization.

Finally, the results of the study implies that, for analyzing the effect of institutional distance in practice, managers should consider its impact on the location choice decision-making, in combination with other elements. Those elements consist of firm’s ownership advantage, firm competitive advantage, the industry characteristics including industry phase as well as purpose of the internationalization, whether they are asset and market seeking, or they want to enhance their brand.

5.3. Limitations and Avenues for further research:

Along with the theoretical and managerial implications that this research suggests, there are also some limitations that need to be addressed. Nevertheless, these limitations can lead to an interesting path for future researches.

in this area and that is capturing the effect of the institutional distance on pattern of the internationalization (internationalization process) of the MNEs in growing industry.

Next point refers to the dimensions used for the measurement of the independent variables in the study. To be able to overcome the limitations of some earlier studies in this field, I tried to build a relatively large sample of several home and host countries but obviously, this makes it more challenging to construct a meaningful measurements from the secondary data (Estrin et al., 2005). One of the limitations that this cause for instance with regard to Hofstede dimensions was as follows. According to what I discussed within the literature review and as it can be noticed in my sample, nowadays, the options for location choice of the MNEs is becoming more extensive. However, the country scores of Hofstede dimensions are not extensively available for all countries, specifically some dimensions are even more limited in the number of countries that they include. Moreover, this issue will not allow to study the effect of dimensions individually on location choice since at the end because of the limited size of the sample, strong results cannot be obtained. Consequently, future researches can focus on constructing more comprehensive measurements to overcome these limitations since I believe different aspects of culture can affect the location choice decisions in different ways.

Since the focus of the current study was on the analysis of the effect of institutional distance, within the research only the magnitude of normative, cognitive and regulative distances with regard to location choice were investigated and analyzed. But reflecting the findings of the paper that show a positive effect of normative and regulative distance and negative effect of cognitive distance, studying the direction of the internationalization can also open a new set of discussions and help to better understand the location choice behavior of the MNEs in a growing industry. As such, future research in this area can also investigate on the direction to figure out whether MNEs in growing industris tend to go from high to low regulative or normative institutions or vice-versa.

opportunity to include more MNEs from developing countries. This will enable the researcher to capture better the effect of institutions on location choice of the MNEs in growing industry and from developing countries