Do corporate venture capital investments enhance fund performance compared to independent venture capital investments? : a cultural-based view

Master Thesis

Do Corporate Venture Capital investments enhance fund

performance compared to Independent Venture Capital

investments?

A cultural-based view

University of Amsterdam MSc Business Administration

Faculty of Economics and Business Track: International Management

Author: C.R.M. Wolkenfelt Student number: 11235543

STATEMENT OF ORIGINALITY

This document is written by student Claudia Wolkenfelt 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.

ABSTRACT

With a growing number of Corporate Venture Capital (CVC) investments and an increase in interest in the literature around CVC investments, knowledge about which constructs influences the fund performance of a CVC investment becomes more and more vital. A broadly studied effect in the IM literature, which influences the performance of international investments, is the influence of cultural distance. Extensive research has been conducted about the effects of cultural distance on the fund performance of Independent Venture Capital (IVC) investments. However the effect of cultural distance on the fund performance of CVC investments is relatively unexplored. Therefore, this research focuses on the differences between IVC and CVC investments and the effect of cultural distance on the fund performance of both investment types. Because IVC investors focus on financial outcomes and CVC investors are most likely to invest for strategic reasons, it is suggested that these different goals will result in differing effects of the cultural distance on the fund performance of IVC and CVC investments. As cultural distance may trigger the investors to pay more attention to the effects of cultural distance, IVC investors are more likely to focus on the financial performance of the company and therefore this effect may even be enhanced. The study shows that cultural distance positively affects the fund performance of an IVC investment and that there is no significant effect on the fund performance of the CVC investment. Furthermore, the moderating effect of the presence of a local partner in the syndicate is examined. Results show that the presence of a local partner in the syndicate has a greater positive influence on the fund performance of an IVC investment compared to CVC investments.

Keywords: Corporate Venture Capital investments, Independent Venture Capital

TABLE OF CONTENTS

1. INTRODUCTION

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2. LITERATURE REVIEW

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2.1 Corporate Venture Capital

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2.2 Corporate Venture Capital vs. Independent Venture Capital investments

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2.3 Institutional effects

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2.4 Informal institutional or cultural effects

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3. HYPOTHESES DEVELOPMENT

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3.1 Cultural distance and fund performance of IVC

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3.2 Cultural distance and fund performance of CVC

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3.3 Cultural effect on fund performance CVC and IVC

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3.4 Effect of presence local partner on fund performance CVC and IVC

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4. DATA AND METHOD

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4.1 Sample

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4.2 Variables

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4.2.1 Dependent Variables: Fund performance CVC and IVC

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4.2.4 Control variables

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5. RESULTS

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6. DISCUSSION

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7. CONCLUSION

47

1. INTRODUCTION

‘How to create a sustainable competitive advantage?’ remains an important question among both managers and researchers. Creating and obtaining knowledge plays a significant role in containing this sustainable competitive advantage. Driven by the emergence of new technologies, CVC investments might offer the investing firms a way to contain their sustainable competitive advantage, as these investments allow them to get easy access to external knowledge. Corporate Venture Capital investments, seen as a source to enclose external knowledge of firms, therefore witnessed an increased share within the scholarly interest (Dushnitsky and Lenox, 2006).

A Corporate Venture Capital investment is defined as an equity investment by incumbent firms in independent entrepreneurial ventures, i.e. relatively new, not-publicly-traded companies that are seeking capital to continue their operations (Gompers and Lerner, 1998). These independent entrepreneurial ventures will be called the Portfolio Company

(PC). An important characteristic of a CVC investment is the embeddedness of the

investment in the investing firm, as the partners who are providing the fund and the managing partners who are investing these funds are in the same firm (LiPuma, 2006).

With the increase in interest in the literature around CVC investments and the growing number of CVC investments (Schildt et al. 2005), especially in the high-tech sector (Lantz et el., 2011), any possible positive or negative effects that influence the fund performance of a CVC investment become more and more considerable.

As most CVC investments are cross-border investments, the impact of cultural distance could be of main importance on the fund performance of a CVC investment. In the International Management literature many thoughts has been given to the effect of cultural distance on the cross-border investment.

However, previous research mainly focused on the effects of cultural distances on the Independent Venture Capital (IVC) investments in general (Lantz et al., 2011). Both IVC and CVC investors strive to invest in high-growth companies that derive value for the firm. But, the way they derive value for the firm differs. CVC investments strive most of the time to achieve strategic goals and IVC investments are purely focused on financial returns (Lantz et al., 2011). Along with these different goals, CVC investing firms are more likely to collaborate on a different level with a different time-focus compared to IVC investors. More detailed differences will be extensively discussed in the Literature Review, but the main difference between these investments lies in their objective.

These distances may be important for CVC investments, as most CVC investments strive beyond a pure financial goal (Rind 1981, Dushnitsky et al., 2006 and Lanz et al., 2011) and pursue a strategic goal. The sought strategic gains, such as an early window on important technological developments or the creation of new potential suppliers and complementary technology (LiPuma, 2006) require a deep understanding of the market and a different collaboration with the PC. Furthermore, investors of CVC investments are likely to select PC’s and evaluate the effectiveness and return on the investment in a different way compared to IVC investments due to their distinctive objectives.

Because of the substantial differences between an IVC and a CVC investment, the cultural distances may affect the CVC performance in a different way. As previous research mainly focused on the effects of cultural and informal institutional distances on the IVC investments (Chakrabarti et al., 2009; Nahata et al., 2014; Lantz et al., 2011; Siddiqui et al., 2014), further thought should be given to the effects of cultural distance on CVC investments and their fund performance. Especially, because the way cultural distances effect the fund performance is not apparent either (Li et al., 2014; Nahata et al., 2014).

In order to overcome this research gap, this study will therefore analyse the effect of cultural distance on the fund performance of a CVC investor. Furthermore, this study will also compare the effects of cultural distance on the fund performance of both CVC as IVC investments. In this research the fund performance will be successful if the CVC investor exits the investment via an IPO or an acquisition, which is compatible with previous research on Venture Capital success (Hochberg et al., 2007, Nahata et al., 2014). Furthermore, this study focuses on a way to enhance possible positive effects of cultural distance and to downplay any difficulties that come along when investing abroad by elaborating on the liability of foreignness theory (Zaheer, 1995). Costs originating from doing business abroad are for example costs due to the ‘unfamiliarity of the environment’ (Zaheer, 1995, p. 4). Therefore, a contingency factor, which could mitigate the unfamiliarity of the environment, will be tested. This will be done by analysing the impact of a local partner in the syndicate on the previously described relationships.

This study conducted an empirical analysis on data that is extracted from the ThomsonOne Database by analysing a sample that covers the registered Private Equity (PE) investments made between 2005 and 2011. The degree of cultural difference is measured by using a dataset that covers the cultural dimensions of 71 countries. A binary regression analysis is performed to analyse the ability of cultural distance to predict the fund performance of an IVC or CVC investment and to examine whether a local partner in the syndicate influences this relationship for IVC and CVC investments.

As the CVC investments continue to grow in the high-tech sectors (Lantz et al., 2011) despite the crisis, this paper contributes to the growing interest in CVC investments (LiPuma, 2006) and the impressive literature on cultural distances. The research presented in this paper contributes to the existing CVC literature in several ways. First, the effect of cultural distance, or informal institutional distance, on the success of CVC and IVC investments remains

ambiguous (Li et al., 2014; Nahata et al., 2014) as 1) the differences between these investment types and 2) the different ways they are affected by cultural distances are relatively unexplored. Furthermore, this study will provide more clarity whether the fund performance of an IVC or a CVC will be affected more in case of a higher degree of cultural distance. As results show, IVC investors are most affected by cultural distances. Besides that, this study contributes to the literature by analysing whether and how the presence of a local partner in the syndicate affects the relationship between the cultural distance and the fund performance of an IVC and CVC investment. We find that the positive effect of cultural distance on the fund performance of IVC investments is even stronger when there is a local partner in the syndicate and that the presence of a local partner has a greater effect on IVC investments rather than CVC investments. Lastly, this study contributes to the international business (IB) literature because the empirical results are based on an extensive dataset.

This study contributes on a managerial level by explaining why IVC investors should pay close attention to cultural distance when making international investment decisions and thereby why the degree of cultural distance is a decisive factor which is affecting the fund performance of an investment. Furthermore, a firm can respond to the possibility of enhancing positive effects by investing in a PC with a local partner in the syndicate. Which type of investor is (more) dependent on the presence of a local partner in the syndicate and should therefore focus on their presence when pursuing a financial outcome? This study contributes by elaborating on that question by showing results that indicate that IVC investors are more dependent on the presence of a local partner in the syndicate.

The remainder of this paper is organized as follows. The next section presents this study’s theoretical background and discusses the related literature about the CVC and IVC investments and the affects of cultural distance. Based on this, the subsequent section presents the framework and hypotheses. The following section will give an overview of the data,

methods and the empirical results. Finally, the implications of the key findings are discussed and concluding remarks with regard to further research are provided.

2. LITERATURE REVIEW

CVC investments are equity investments by established corporations in entrepreneurial ventures (Dushnitsky and Lenox, 2006). CVC units are part of a parent corporation (named a firm) and invest for this parent corporation in new companies for several reasons (Phanke et al., 2015). According to Rind (1981), most firms make CVC investments in ventures for strategic reasons and although firms strive to accomplish strategic objectives, it is impossible to not make substantial financial gains, since CVC investments that have been run by professionals, generally perform as well as other venture capital firms. Dushnitsky et al. (2006) compare the underlying CVC objectives. In their research they analyse 171 U.S. firms, which invested in CVC investments during the period 1990-1999, and find that 64% of the firms stated a strategic motivation for starting the investment and 36% used a singular desire to gain financial returns. Lantz et al. (2011) analyse the objectives of CVC investments as well. Their results focus on the dual objectives, just as Rind (1981) noted, and find that 15% only strive a strategic objective, 16% invest only for a financial return and almost 70% show a combination of strategic and financial objectives. They argue that when aiming for strategic value, the financial return remains a requirement for the investment. In the opposite way, those CVC investments that are made primarily to invest for financial returns look for synergies with the target.

According to Rind (1981), firms expect each investment to provide one or more of the following benefits; a mechanism for identifying/engaging with companies whose products or

technologies might play important future roles in their businesses; a method for better understanding the management strengths or weaknesses of possible acquisitions; a technique for getting certain products designed and built at lower cost and faster than could be done inside; an early window on important technology, market, government and business developments; an assurance of continued supply of needed materials or components. Lantz et al. (2011) enhances this list of benefits by giving an overview of the main strategic reasons cited by managers of CVC funds. Their main objectives are: provide window on new markets, develop new products, gain window on emerging technologies, explore new directions, support existing businesses and/or improve manufacturing processes. With these benefits Rind (1981) and Lantz et al. (2011) both emphasize the strategic benefits. In this research the CVC unit will be seen as a strategic unit, which seek with a lesser extend financial returns.

CVC investments could also be defined as ‘an input of capital equity and technical or strategic expertise to start-up entrepreneurs’ (Lantz et al., 2011 p. 369). With this definition the focus lies on the possible benefits for the investee, as a CVC investment does not only bring strategic advantages for the investing firm, but it could bring strategic advantages for the investee as well. The most significant benefits are an increased credibility, the help with short-term problems and access to organizational management know-how (Lantz et al., 2011).

2.2 Corporate Venture Capital vs. Independent Venture Capital investments

Venture Capital investments gained a higher scholarly interest compared to CVC investments over the last four decades (Lantz et al., 2011). While CVC investments have a few elements with Venture Capital investments in common, there is a significant difference between these investment forms. What are the differences between a CVC and an independent IVC investment and why are new insights needed?

As discussed in the previous paragraph, CVC investments are primarily made in a highly strategic way to maintain a control of innovation by acquiring innovations when they start developing and IVC investments focus primarily on the financial return: CVC is another form of Venture Capital (Lantz et al., 2011).

Besides its preferred outcome and the underlying goals, the structure within these investment funds form the foundation of the differences between IVC and CVC investment funds. The IVC and CVC investments differ in their organizational structure, as most CVC investment funds are structured as corporate subsidiaries (Gompers and Lerner, 2000). For example, the firm, such as Google, has their own venture capital fund: Google Ventures. As a result in the equity structure, only the parent corporation/firm makes the financial investment. This parent corporation (or the investing firm) buys a minority equity stake in the PC and because of this, the investing firm may exert influence on its corporate decisions (Dushnitsky, 2012). As CVC funds are part of a parent corporation, the CVC executives often worked for the parent company in a business unit in the past and report nowadays to the Chief Technology Officer (Phanke et al., 2015).

Besides the underlying structure, the incentives seem to differ as well. CVC investors have a lower incentive-based compensation model (Gompers and Lerner, 2000), as they focus on strategic outcomes such as accelerating the process of training or to increase the effectiveness of technological watch (Lantz et al., 2011). As IVC investors are pure financially driven and are used to a financial incentive-based compensation system.

Furthermore, the governance differs. With CVC investments, ‘the parent company manages the CVC via a dedicated IVC arm or a corporate business development unit’ (Dushnitsky, 2012). A CVC investing fund’s goal is to create a useful relationship between the parent company and the PC. Whereas with an IVC investment, the relationship between the independent IVC firm and the investee is governed by a partnership agreement. Although,

as the main objective of an IVC investor is to achieve a greater return, investors often require a board seat as an effort to help the firms grow and achieve a higher financial return.

Another distinction can be found in the competitive advantage. Whereas CVC investors have a competitive advantage in identifying investment opportunities at a earlier stage, because CVC investors are more likely to have specific knowledge and more relevant industry experience (Siddiqui et al., 2016). As IVC investors ‘usually fall short of industry specialization with little competitive knowledge in early stage ventures’ (page 85, Siddiqui et al., 2016), they are as affiliates of financial institutes able to manage a larger fund size.

The differences between IVC investments and CVC investments may affect the fund performance of the CVC investment as well. Lantz et al. (2011) imply that these differences between CVC and traditional IVC investments may induce implications for the CVC performance, as CVC’s are able to provide their start-ups with a rapid access to markets, technical help and an inside knowledge of the product, given their collaboration with trade industries. Gompers and Lerner (1998) argue that the performance of a CVC investment is more volatile compared to the general IVC market, as the CVC life span is shorter and the investors are prepared to pay a premium price to secure the equity stakes in the ventures. A few years later, they find support that the performance of a CVC investment is similar to that of an IVC investment, assuming an equal level of risk and activities in the same industries (Gompers and Lerner, 2000). Dushnitsky and Lenox (2006) come up with similar results as they state that the financial performance to the CVC investor have been found to vary widely across CVC programs (p. 755), but they find that firms, which pursue CVC, experience more value creation. Dushnitsky and Lenox (2006) measure firm value by calculating the Tobin’s

q, which is the market valuation of a firm over the value of tangible assets. As the evidence

investment types not on financial performance, but on the overall benefits. They argue that because of the tight commitment to start-ups, CVC investments will gain higher benefits.

Assessing the previous literature, the differences between CVC and IVC investments become clear. The main differences between the CVC and IVC investments are shown in Table 1.

CVC investments IVC investments

Strategic objectives Financial objectives Dushnitsky et al. (2006), LiPuma (2006), Lantz et al. (2011), Siddiqui et al. (2016)

Corporate subsidiary Independent venture Gompers and Lerner (2000), LiPuma (2006), Lantz et al. (2011), Dushnitsky (2012), Phanke et al. (2015)

Short investment period Longer investment period Gompers and Lerner (1998)

Strategic incentive-based model Financial incentive-based model Gompers and Lerner (2000)

Early stage venture investments Later stage venture investments Sapienza (1992), Siddiqui et al. (2016)

Competitive advantage: industry knowledge

Competitive advantage: financial resources

Siddiqui et al. (2016)

Table 1: Differences CVC and IVC investments. Since, the fund performance of a CVC investment may differ from an IVC investment, further attention should be given to the effects of cultural distance on CVC investors’ fund performance.

2.3 Institutional effects

CVC investments may create unique growth opportunities in foreign markets for both the investing firm and the PC. But, as the economic activities are embedded in an institutional setting (North, 1990), the CVC investors’ financial performance will be influenced by the

environment of the foreign CVC investment. The institutional environment consists of formal and informal institutions (Peng, 2000). The formal rules shape human interaction and regulate the individual behaviour (North, 1990) and they are manifested in political rules, legal decisions and economic issues (Peng, 2000). The informal rules consist of norms and codes of conduct and are part of a country’s cultural heritage (North, 1990). They include the socially sanctioned codes of conduct and the norms of behaviour, which are embedded in the culture (Peng, 2000). In previous research, the informal institutional distance is often measured as the cultural distance between two countries (Estrin et al., 2009; Nahata et al., 2014). Li and Zahra (2012) state that the informal rules are ‘conventions, codes of conduct, and norms of behaviour that come from socially transmitted information and as such are part of a country’s cultural heritage’. Previous research mainly focused on the effects of cultural differences between the companies on the IVC investments. The cultural dimension is a widely studied dimension in order to analyse the national distance (Li et al., 2014) and therefore, this study will focus on the effect of cultural difference between the PC and the investing firm.

2.4 Informal institutional or cultural effects

Estrin et al. (2009) and Nahata et al. (2014) argue that the informal institutions can be explained by using the cultural dimensions of Hofstede (1990), as the informal institutions encompasses culture as operationalized by Hofstede (1990) and Schwartz (1994).

As previous research focused on the cultural distance and its role in international diversification (Dai et al., 2012) on CVC investments, this literature review will analyse the cultural effect on the IVC investment as a way to understand the possible effect of cultural differences on the CVC investors’ fund performance. For example, Dai et al. (2012) examine the impacts of IVC on the performance and innovation of China’s small- and medium sized

enterprises. They analyse the effect of cultural distance on IVC’s cross-border investment behaviour and the specific performance in Asia. When the cultural distance increases, countries display higher mutual distrust (Guiso et al., 2008). For example, a Dutch IVC will have less difficulty in cooperating and understanding the culture with a German local IVC, compared to a Chinese IVC. These cultural differences may cause several frictions between foreign IVC and local entrepreneurs, such as misunderstanding due to ineffective communications (Dai et al., 2012). Dai et al. (2012) find that the greater the cultural distance between the country of the IVC investor and the country of the investee, the less likely the foreign and local firm will form partnerships and that this distance is associated with ventures’ exit performance. As Dai et al. (2012) show a negative effect of cultural distance on the fund performance of an investment, other studies show positive effects of an increase in the cultural distance on the performance of international investments. For example, Morosini et al., (1998) find a positive association between national cultural distance and the cross-border acquisition performance. They argue that the cultural distance enhances the performance by providing access to ‘to the target's and/or the acquirer's diverse set of routines and repertoires embedded in national culture’. Furthermore, Nahata et al. (2009) and Chakrabarti et al. (2009) show similar results. They argue that the cultural distance does create difficulties, such as a higher degree of distrust, and that these investments in more distant cultures further multiply the uncertainty for non-local firms. However, these uncertainties may trigger the investors to be more cautious and pay more attention to the effects of these cultural distances.

Most IVC related research analysing the cultural effects on the fund performance, identify the cultural distance by using the four cultural distances defined by Hofstede: power distance, uncertainty avoidance, masculinity and individualism (Hofstede, 1983; Nahata et al., 2014; Li et al., 2014; Nahata et al., 2014). As these cultural dimensions were created with the

use of data from a large corporation (IBM), these dimensions clarify the cultural differences between companies.

These previously discussed studies show a significant impact of cultural distance on the IVC fund performance and the authors emphasize the importance of considering the effects of cultural differences on the IVC investments. But does the same effect relate to CVC investments?

Why is it important to understand the effects of cultural distance on the fund performance of a CVC? The structure and the goals of a CVC fund differs compared to an IVC fund, as the CVC fund could have internally conflicting goals (both strategic and in a certain matter financial), focus purely on corporate strategic goals instead of just financial goals, have a more complex and slow decision making process and maintain a higher distance from PC as they often do not take seats in the board and are afraid to scare of future PC with the threats of corporate dominance (Pahnke et al., 2015). Because of this increased distance between the CVC and the PC, the effect of the cultural distance, which flows through the companies, might be reduced compared to the same effect on IVC investments. Therefore the cultural distances may affect the fund performance of a CVC in a different way than IVC investments do and thus should the effects on the CVC investments not be overlooked.

The existing literature about the factors affecting the CVC fund performance is still limited. Most of the CVC performance related research focus on the American market. The research of Rindermann (2003) and Khalfallah et al. (2014) form an exception, as they focus on the changes in profitability of companies financed by CVC investments on the French market. Since most of the research focus on American CVC investments, the effect of cultural distance is not properly analysed.

Although it is clear that the cultural distances affect the IVC financial performance, there are as discussed some contradicting outcomes in the literature. Li et al. (2014) show that

both cultural and institutional distances negatively affect the likelihood of international venture capital exit success. However, Morosini et al., (1998), Chakrabarti et al. (2009) and Nahata et al. (2014), argue that cultural distance positively affects the IVC success. They explain this outcome by arguing that cultural differences create incentives for rigorous ex ante screening and giving extra attention to this new market. With this contradiction, it remains unclear if cultural distance effects the CVC fund performance, and whether this is in a positive or negative way. This leads to the following research question:

How does cultural distance affect the fund performance of the CVC investor compared to that of an IVC investor?

An important contingency factor, the access to local information, will be analysed as an effect on the main relationship. As Lerner (1994) state, IVC syndication can provide several benefits, which will downplay the possible negative effects of the information asymmetry on the fund performance of the IVC investor. Li et al. (2014) state that IVC syndication will help IVC’s to select deals and enhance monitoring and advising capabilities. Furthermore, a local communication point, such as a local office, will create a better access to information about the local environment. Nahata et al. (2014) enhance the study of Li et al. (2014) by not only analysing the cultural and institutional effects on the IVC success, but by comparing the effects on developing and emerging countries. Furthermore, they analyse the effect of local IVC participation and find that this mitigates the foreign IVCs’ liability of foreignness: the presence of local investors in IVC syndicates has a positive impact on the company’s success in developed countries (Nahata et al., 2014). As the presence of a local partner reduces the liability of foreignness for the IVC investor and create a better access to local information, this variable might affect the main relationship between the cultural distance and the fund

performance of the CVC investor as well. The local partner in the syndicate could for example inform the CVC investor about a changing institutional environment and might be able to better understand the cultural distances. Furthermore, there might be some differences between the effect of the presence of a local partner in the syndicate for IVC and CVC investments. One investment type might for example rely more on this provision of information. Therefore, this study will also analyse the effect of the presence of a local partner in the syndicate as a contingency factor and analyse possible variances among the investor types.

3. HYPOTHESES DEVELOPMENT

3.1 Cultural distance and fund performance of IVC

Previous research analysed the effects of cultural distances on different types of investments. Most of the outcomes of these analyses come to the same conclusion: cultural distance does influence the fund performance of an IVC investment (Nahata et al., 2014; Li et al., 2014). However, the way in which the cultural distance influences the fund performance of an investment remains ambiguous.

First, when the cultural distance between two countries increases, people are more likely to have miscommunications and the change of a higher mutual distrust increases (Guiso et al., 2008). Besides the fact that cultural distance can lead to a decrease in the level of trust, it can also affect the nature of financial contracting and the portfolio company performance (Nahata et al., 2014). A company has to invest time to understand these differences: the cultural and social norms. Furthermore, Dai et al. (2012) discuss that IVC investors differ in the way they monitor their investments, which could influence the fund performance.

Different cultures are known for a certain type of monitoring. For example, American firms tend to put more emphasis on monitoring compared to Indian IVC’s (Dai et al., 2012). Dai et al. (2012) underline the importance of these different ways of monitoring the investment, as some American IVC monitoring activities are regarded as intrusive in China. These underlying reasons may even create a negative spiral. For example, when the cultural differences cause a miscommunication, the distrust is likely to increase, which may lead to the withholding of information. This may mitigate the effectiveness of the monitoring and creating a negative effect on the exit performance of an investment (Dai et al., 2012).

However, several other studies argue that when the level of cultural distance increases, this will lead to a positive effect on the fund performance of an investment. Morosini et al. (1998) explains this effect by using the resource-based view (RBV) as an underlying framework: sustainable competitive advantage results from valuable, rare and inimitable resources. When investing and gaining access to a valuable pool of critical routines and repertoires, these cross-border investments could increase the fund performance. And because ‘a greater national cultural distance makes it more likely that the target will provide a set of routines and repertoires that are significantly different from the bidding firm's own set, and which cannot be easily replicated in the acquirer's country of origin - or vice versa’ (Barney, 1991; Morosini et al., 1998), this could lead to an improved fund performance.

Nahata et al. (2014) elaborate on this by stating that the cultural distance could positively affect the fund performance of an IVC investment as these clear differences make investors realise the importance to screen that investment. This effect appears because of the extensive way of screening and therefore investments only materialize when they have a substantial economic potential (Nahata et al., 2014).

As researchers (Barney, 1991; Morosini et al., 1998; Li et al., 2014; Nahata et al., 2014) find that the cultural distance has a negative effect on the fund performance of the IVC investment, the following H0 is set as a theoretical baseline:

H0: Cultural distance positively affects the fund performance of an IVC investment.

3.2 Cultural distance and fund performance of CVC

Previous research mainly focused on the effects of cultural distance on IVC investments, instead of CVC investments (Barney, 1991; Morosini et al., 1998; Li et al., 2014; Nahata et al., 2014). These research findings conclude that the cultural distance has a positive effect on the fund performance of the IVC investment. As discussed above, cultural distance has a positive effect on the fund performance of an IVC investment due to several reasons. The main reason for this is the extensive way of screening an investment and therefore investments are only likely to materialize when they have a substantial economic potential (Nahata et al., 2014). But how does cultural distance affects the fund performance of a CVC investment?

Although, there are some significant differences between a CVC investment and an IVC investment, the underlying reasons why cultural distance is likely to positively influence the fund performance of an investment, are not likely to differ. Cultural distances are as likely to increase the impact when addressing the resource-based view (RBV). The effect caused due to the extensive way of screening and monitoring an investment isn’t likely to differ as well. Therefore, the first hypotheses will be as follows:

3.3 Cultural effect on fund performance CVC and IVC

As discussed, the IVC and CVC investments differ on a few important aspects. The main differences are summarized in table 1. Besides the studies of Gomper and Lerner (2000), Dushnitsky and Lenox (2006) and Siddique et al. (2016), Phanke et al. (2015) compared the two investment types as well. Phanke et al. (2015) sum up several differences. First, the process to gain resources as a PC from CVC investors is complex as many large corporations use a matrix structure with units that have their own aims. This is likely to result in a slow organizational process. Second, CVC executives are embedded in a corporate hierarchy and may have a more limited authority compared to IVC investors. Third, CVC investors are more likely to keep their PC’s at arms length and therefore they are less able to influence venture’s decision making. For example, CVC investors often do not take seat in boards. As the distance and the contact between the CVC investor and de PC decreases, it may be possible that the cultural distance between the two has a smaller leverage compared to IVC investors.

Taken these differences together, IVC investments are more likely to be influenced by cultural distances as; CVC investors tend to stay at an arms length, IVC investors are more likely to take seat in boards and because IVC investors are less likely to be embedded in a strong hierarchical corporate structure which could debase their impact.

As proposed, the IVC is more likely to be effected by cultural differences between the PC country and the firm country. This leads to the following hypothesis:

H2: The influence of the cultural distances is more important for the fund performance of an

IVC investment, rather than the influence of the cultural distance on the fund performance of a CVC investment.

3.4 Effect of presence local partner on fund performance CVC and IVC

In what way can these positive effects of the cultural distance be enhanced? Local knowledge about the market could offer a way. The knowledge about the market, the buyers, the trends, the access to information networks (Nahata et al., 2014), information about local market conditions and investment opportunities (Chemmanur et al., 2011), may create a competitive advantage for a local investor. With this local knowledge and a smaller geographical distance, the investor can more easily monitor the PC and may be able to add value to this PC and thus it’s investment (Chemmanur et al., 2011). As the Liability of Foreignness (Zaheer, 1995) may create a substantial disadvantage for foreign investors, a local partner in the syndicate may create an opportunity to overcome this. As a local partner in the syndicate could indicate that with the local knowledge a firm would invest in this PC. Chemmanur et al. (2011) find that syndicates that consist of both international and local partners have a higher probability of an IPO exit. Furthermore they state that ‘the negative association between the geographical distance of the international venture capitalist and the probability of a successful outcome of an IVC investment is mitigated by syndication between the international venture capitalist and local venture capitalists’ (page 19).

As previous research point out, the presence of a local partner in the syndicate will mitigate the negative effect of the information asymmetry (Nahata et al., 2014; Siddiqui et al., 2016). However, research about the effects on the fund performance of a CVC is still lacking. Would the presence of a local partner in the syndicate have a similar effect on the relationship between the cultural distance and the fund performance for both IVC and CVC investments? Due to the differences between IVC and CVC investments, which discussed before, one could argue that the IVC investors more highly depend on the presence of a local partner in the syndicate. When considering the main differences between the two investments, IVC

investors focus solely on the financial outcome. Furthermore, they possess less inside-industry knowledge compared to CVC investors (Siddiqui et al., 2016), as they focus on different markets that show market opportunities. An IVC investor is more likely to seek industry specific expertise and therefore more highly depend on the local knowledge of a local partner in the syndicate compared to a CVC investment. This leads to the last hypothesis:

H3: The positive moderating effect of a local partner in the syndicate is stronger for IVC

investors compared to CVC investors.

The next section will provide a data description, a description of the various variables and the statistical methodology.

4. DATA AND METHOD

4.1 Sample

For this research an empirical analysis is the most suitable option, as this will provide the most extensive quantitative information. Previous research (Dushnitsky and Lenox, 2006; Mohamed and Schwienbacher, 2016) uses the Compustat database of Standard and Poor and the Venture Economic’s database as a tool to measure the firm value and the financial performance. The data concerning information about the PE investment of a CVC and IVC is extracted from the ThomsonOne Database. The following variables were subtracted from the ThomsonOne Database: the company ID, Name of the Portfolio Company, Country of the Portfolio Company, Firm ID, Name of the Firm, Country of the Firm, Exit type, Investment

date and the Investor type. In this way the fund performance, as the exit type, could be analysed for both the IVC and CVC investments.

The data is subtracted within a time period between 2005 and 2015 and consisted of 292.136 PE investments. As the methodology proposes a minimum of four years in order to measure whether an exit via an IPO or acquisition was successful (Gompers and Lerner, 2000), the first investment date ranges between 2005 and the end of 2011. The data about these investments made between 2005 and 2011 are then linked with the exit type, which is subtracted from the end of 2015. After removing duplicates and only using first investments made until 2011, the total number of PE investments went down to 172.994. When looking at only CVC investments made between 2005 and 2011, the total number of investments is 10.200. The total number of IVC investments between 2005 and 2011 is 108.617. These numbers rise above the number of investments analysed in previous research (LiPuma, 2006; Nahata et al., 2014).

Besides this comprehensive time scheme, the data covers a comprehensive geographical area as well. In order to compare the cultural differences, a worldwide analysis is needed. Therefore, the sample covers all registered private equity investments in ThomsonOne, whether these investments are made by a local or a foreign investor (Nahata et al., 2014). In order to match this data, the complete Hofstede database is used. The dataset covers the cultural dimensions of 71 countries. When comparing the home and host country, the level of analysis used is both the company level (the investee) and the firm level (the investor). In order to understand the fund performance of a CVC or IVC investment, data from the fund level is used: how did the firm exit the investment? By using the ThomsonOne Database and Hofstede’s cultural dimensions, the data aligns with the research question by comparing the cultural differences and including the registered private equity investments.

4.2 Variables

4.2.1 Dependent Variables: Fund performance CVC and IVC

Previous research concerning IVC investments and the fund performance of these investments used the type of exit to measure the fund performance (Hochberg et al., 2007; Nahata, 2008; Noyes et al., 2014). Hochberg et al. (2007) argue that the IVC investments companies earn their capital gains from those investments that exit via an IPO or an acquisition. Therefore, in this research the type of exit, whether this is an IPO (IPO or a Reverse Takeover) or an acquisition (Trade Sales, Secondary Sales), will result in a successful fund performance. When the first investment is made between 2005 and 2011 and the exit type in 2015 states that there is made or an IPO or an acquisition, then a dummy variable is created with 1 = successful investment, otherwise 0 = unsuccessful investment. This data is subtracted from the ThomsonOne Database. As discussed above, it takes a few years for a firm to exit the investment after the primary investment is made and therefore the database consists of all first private equity investments made between 2005 and 2011 and is linked to the information available about these investments’ exit type between 2005 and 2015. In this way, the data about the exit types covers at least four years after the primary investments were made. Because the CVC or IVC investors often invest in a syndicate, an investor type could not be excluded. Therefore the dataset covers both IVC and CVC investments. The CVC investments are obtained by firm type as Corporate PE/Venture and the IVC investments as Private Equity firm.

4.2.2 Independent Variable: Cultural distance

Informal institutional distance: the informal rules as described by North (1990), are embedded in the shared norms, values and beliefs of a society. As discussed by Estrin et al.

(2009, pag. 1175), ‘the notion of informal institutions encompasses culture as operationalized by Hofstede (2001), Schwartz (1994) and others (Hofstede et al., 2002; Peng, 2003)’. The cultural analysis of Hofstede (1983) consists of four different dimensions. The first dimension is power distance, which is the degree to which the less powerful people accept and expect that power is distributed unequally. The second dimension covers the uncertainty avoidance. This dimension expresses the degree to which the members of a society feel uncomfortable with uncertainty and ambiguity. The third dimension is individualism; this is the degree of which individuals are expected to take care of only themselves and their immediate families. The last dimension covers the level of masculinity. This dimension shows whether there is a preference in society for achievement, heroism, assertiveness and material rewards for success. More recently, Hofstede added a fifth dimension: term orientation. The long-term orientation stands for ‘the fostering of virtues oriented toward future rewards’ (page 359, Hofstede, 2001).

Even though the Hofstede dimensions are a widely used tool, Shenkar (2001) discusses seven points of critique: the illusion of symmetry, the illusion of stability, the illusion of linearity, the illusion of causality, the illusion of discordance, the assumption of corporate homogeneity and the assumption of spatial homogeneity. Even though, Shenkar (2001) mentioned these shortcomings, Hofstede’s national cultural dimension is still used extensively in the scholarly as most of the previous empirical studies use the index by Kogut and Singh (1988) to analyse the impact of cultural distance between the FDI’s home and host country on the investment (Estrin et al., 2009; Chemmanur et al., 2011). This index and formula make it possible to measure and compare the overall cultural distance between the firm country and the PC country. Furthermore, the Kogut and Singh approach coincide with the comparison of cultural differences between IVC and CVC investments on a company level, because this dataset is generated by looking at the cultural differences within companies (IBM), which.

Third, as most other studies concerning cultural differences in the international business context use the Kogut and Singh (1988) index (Li et al., 2014), this study will build upon Hofstede’s dimensions by using the Kogut and Singh (1988) formula to measure and compare the cultural differences. Kogut and Singh (1988) created the following formula based on the dimensions of Hofstede (1983):

𝐾𝑆

=

∑

Where KSij is the cultural distance between countries i and j, 𝐼_𝑥𝑑 is the index of a country

x in the dimension d, Vd _{is the variance of the index for the dimension d, and n is the number}

of cultural dimensions.

In order to measure the cultural differences between the firm country and the PC country, first the cultural dimensions are indexed between 0 and 100 and these index numbers are matched with the firm nation and the PC nation. The firm nation and the PC nation are subtracted from ThomsonOne database, together with the information about the fund performance, as described above. The fifth dimension of Hofstede is omitted due to the lack of measurement of this dimension for many countries and therefore only the four primary dimensions of Hofstede (power distance, uncertainty avoidance, individualism and masculinity) are taken into account (Kandogan, 2012). After matching these countries and their corresponding indexes the country scores were equated following the formula.

4.2.3 Moderator: Local partner in the syndicate

The presence of a local partner in the syndicate is measured by using data from the ThomsonOne database. The private equity investments between 2005 and 2015 are used

together with the firm nation and the company nation. A local partner in the syndicate is part of a cross-border investment and there has to be one investor within this syndicate that has the same country of origin as the PC nation (Nahata et al., 2014).

The presence of a local partner was subtracted from the data by creating a new variable that stated the investment number. With this number the different investments are shown and several funds that invested in the PC can be compiled. Then the investments were coded, 1 = cross-border investment and a 0 = not cross-border investment. Then the investments are sorted by investment number and whether they were cross-border or not. After this, the first conditional was created; ‘if it is a border investment’. Besides the fact that it is a cross-border investment, the investment should include a local partner as well. Therefore a new dummy variable is created: whether there is a local partner. Finally, the variable ‘local partner in the syndicate’ is computed why combining the two conditionals: it should be a cross-border investment and there should be a local partner in this syndicate. When there is a local partner in the syndicate, this dummy variable equals 1 and 0 if there is no local partner in the syndicate.

4.2.4 Control variables

The fund performance of a CVC investor is likely to be influenced by several other factors. The first control variable is the economic growth of the PC country, as it might influence the performance of the PC. A growing economy in the host country can influence the level of risk and therefore investors might fund riskier businesses (Li and Zahra, 2010). Furthermore, in a growing economy there may be more appealing opportunities for firms. The

GDP growth rate will be used to measure this control variable. The GDP data is subtracted

from the World Bank Database, the International Comparison Program Database and gives access to all the GDP rates from 1990 until 2015 for more than 250 countries. The data is

linked with the PC country, as this country is more likely to influence the fund performance. The GDP growth rate of the PC country is calculated by looking at the average GDP growth rate between 2005 and 2015, as a growing GDP growth rate may create new investment opportunities for firms.

The second control variable is a venture-related characteristic. Because ventures which are less developed and in an early stage of doing business are, according to Li et al. (2013), less likely to achieve significant returns and might have a greater chance of failure. The age of the venture firm may indicate whether a firm is more experienced or more established. These restrained results are likely to affect the fund performance of an IVC and CVC investor. The data about the Age of the Venture Firm is collected from ThomsonOne (Li et al., 2014). By collecting the data about the year in which the venture firm is founded, the age of the venture firm could be calculated by subtracting that year from 2016. The age of the Venture Firm is given in round numbers.

The third control variable is coherent with the previous variable as it gives some information about the experience and establishment of the investor. The Total Number of

Companies Invested in by the Venture Firm will indicate in how much other PC’s the firm has

invested in. When a firm has made large amounts of other deals, it is more likely that this firm really emphasize on investing. It might be their core business or it contains an important part of their activities. Therefore, these firms are more likely to know in which companies to invest. The previous number of investments will therefore create a higher degree of investment experience and might affect the fund performance of the CVC or IVC investor (Li et al., 2014). The number of companies invested in by the venture firm (both IVC and CVC investments) ranges between 1 and 9.183 companies. This data is subtracted from the ThomsonOne database by looking at the total number of companies invested in by the firm.

The fourth control variable is the Market Capitalization: the total dollar market value of all of a company’s outstanding shares. The larger the amount of the market value, the more likely it is that this firm has a relatively large amount of resources. The firm might therefore for example, have more skilled personnel or more contacts that have relevant information. The Market Capitalization in this analysis is calculated as the average market capitalization of domestic companies from 2005 to 2015 (% of GDP).

At last, the model is controlled for the year in which a firm invested in a company. As for example, the economic crisis influenced the investment period after 2008 as the number of CVC investments decreased from 729 investments to 405 investments made in the year after. Therefore, seven control variables are created as a dummy variable for the years 2005 until 2011. The number of investments is equally distributed for both the IVC and CVC investments. The number of CVC investments per year lies between 372 and 747 investments and the number of IVC investments per year lies between 4.716 and 7.985. The control variable is calculated as follows: when the investment was made in 2009, D.2009 denotes 1 and all other years are denoted as 0.

5. RESULTS

In order to compare the IVC and CVC investments, the data is split into two groups. The CVC investments group consists of 10.200 investments and the data group that covers the IVC investments consists of 108.617 investments. After deleting missing values by using a list-wise deletion approach, the dataset of IVC investments contained 44.016 data strings. For the dataset of CVC investments the missing values were deleted using a list-wise deletion approach as well. This resulted in a dataset of 3.936 complete data strings. As with list-wise deletion the entire record is excluded from the analysis if any single value is missing, this

resulted in a substantial decline of the available data strings. However, as the successfulness of an investment is strictly linked to a specific country and the presence of a local partner in the syndicate, the list-wise deletion approach is more suitable compared to the pair-wise deletion approach. Both data sets still include a great amount of investments and the number of observations is in line with the number of analysed investments in other literature studies (Nahata et al., 2014). The number of successful investments within IVC investments is 42.446 (96,4%). The total number of successful investments within CVC investments lies as at 3.926 (95,4%). The descriptive table of both the IVC and CVC investments are shown in respectively table 2 and table 3.

Descriptive Statistics IVC investments

N Minimum Maximum Mean Std. Deviation Cultural Distance 44016 ,000000 7,664000 ,15996474 ,564398949 Local Partner in the Syndicate 44016 0 1 ,14 ,352 Successful Investment 44016 ,00 1,00 ,9643 ,18547 GDP % 44016 ,050136 1,747749 ,19388722 ,295888632 Market Capitalization 44016 0 2 1,15 ,237 Venture Firm Age 44016 2 177 24,63 14,013 Total number of companies

invested in by Venture Firm

44016 1 9183 499,13 1574,504

Valid N (listwise) 44016

Table 2: Descriptive statistics of IVC investments.

Descriptive Statistics CVC investments

N Minimum Maximum Mean Std. Deviation Cultural Distance 3936 ,000000 7,520550 ,34311808 ,850507363 Local Partner in the Syndicate 3936 0 1 ,15 ,355 Successful Investment 3936 0 1 ,96 ,199 GDP % 3936 ,050136 1,747749 ,21508943 ,352172603 Market Capitalization 3936 ,127213 2,379447 1,15715997 ,238823503 Venture Firm Age 3936 1 194 30,52 21,155 Total number of companies

invested in by Venture Firm

3936 1 4996 1402,43 2103,094

Valid N (listwise) 3936

Table 3: Descriptive statistics of CVC investments.

By comparing the means of the cultural distance in terms of successful or not-successful investments in the dataset of IVC investments, the results show that the mean of the cultural

unsuccessful investment is .089. The Levene’s test shows there is a significant difference between these means of .0934 (p =.000). The results are shown in table 4.

The same is analysed for CVC investments. The results show that when comparing the means of the cultural distance for successful and not-successful CVC investments, the equal variances are assumed (F = 1.952, p = .162) and there is no significant difference between the means. This might imply that there is no significant difference (in means) between the degree of cultural distance of successful and not-successful CVC investments. The results are shown in table 5.

Table 4: Levene’s test for equality of variance – IVC investments.

Group Statistics Successful

investment N Mean Std. Deviation Std. Error Mean Cultural Distance 1 - Successful 43585 ,18282786 ,612626505 ,002934454 0 – Not successful 1625 ,08947349 ,415536519 ,010308192

Independent Samples Test Levene’s Test for

Equality of Variances t-test for Equality of Means

95% Confidence Interval of the Difference

F Sig. t df

Sig. (2-taled)

Mean

Differences Std. Error Differences Lower Upper Cultural Distance Equal variances assumed 137,636 ,000 6,091 45208 ,000 ,093354366 ,015327267 ,063312680 ,123396053 Equal variances not assumed 8,710 1897,413 ,000 ,093354366 ,010717735 ,072334583 ,114374150

Table 5: Levene’s test for equality of variance – CVC investments.

Independent Samples Test Levene’s Test for

Equality of Variances t-test for Equality of Means

95% Confidence Interval of the Difference

F Sig. t df

Sig. (2-taled)

Mean

Differences Std. Error Differences Lower Upper Cultural Distance Equal variances assumed 1,952 ,162 0,891 4094 ,373 ,062290167 ,069883842 -,074720153 ,199300487 Equal variances not assumed 0,951 186,262 ,343 ,062290167 ,065492714 -,066912678 ,191463012 Group Statistics Successful

investment N Mean Std. Deviation Std. Error Mean Cultural Distance 1 - Successful 3926 ,36798343 ,894504901 ,014276034 0 – Not successful 170 ,30569326 ,833386691 ,063917841

When analysing the correlation matrix of the IVC data group, all correlations are below .7. This is in line with statistical guidelines (Cohen et al., 2013), as all variables are now most likely to measure a different construct. In Table 6, the correlation matrix of the IVC investments is shown. These results suggests that when the Venture Firm exists for a longer period of time (Venture Firm Age), these firms are more likely to: invest in PC’s with a higher cultural distance, invest when there is a local partner in the syndicate and to engage in successful investments. Furthermore, there is a positive correlation between the successful investments and the cultural distance (ρ = 430, p = .000) and between the presence of a local partner in the syndicate and the cultural distance (ρ = 027, p = .000). However, these results are purely based on correlations and should be further analysed.

The correlations of the CVC investments are all below the .7 demarcation (Cohen et al., 2013). This indicates that none of the variables will measure the same construct. However, the correlation between the market capitalization and the GDP growth rate is ρ = -.588, (p = .000). This is relatable as the market capitalization is calculated as a percentage of the GDP growth rate. Furthermore, the results show that the successfulness of a CVC investment correlates with the presence of a local partner in the syndicate (ρ = .042 p = .003) and that the cultural distance correlates with the presence of a local partner in the syndicate (ρ = .281, p = .000) as well. However, there is no significant correlating effect between the cultural distance and the successfulness of CVC investment. These results will be further analysed with the use of a regression analysis. In Table 7, the correlation matrix of the CVC investments is shown.

**. Correlation is significant at the 0.01 level (2-tailed) *. Correlation is significant at the 0.05 level (2-tailed) c. Listwise N = 44016

Table 6: Correlation matrix IVC investments.

Correlations IVC investmentsc

Cultural Distance Local Partner in the Syndicate Successful Investment GDP % Market

Capitalization Venture Firm Age

Total number of companies invested in by Venture Firm Cultural Distance Pearson

Correlation 1 Sig. (2-taled) Local Partner in the Syndicate Pearson Correlation ,430** 1 Sig. (2-taled) ,000 Successful Investment Pearson Correlation ,027** ,000 1 Sig. (2-taled) ,000 ,933 GDP % Pearson Correlation ,290** ,167** ,027** 1 Sig. (2-taled) ,000 ,000 ,000 Market Capitalization Pearson Correlation -,311** -,263** -,039** -,510** 1 Sig. (2-taled) ,000 ,000 ,000 ,000 Venture Firm Age Pearson

Correlation ,050** ,033** ,014** -,094** ,049** 1 Sig. (2-taled) ,000 ,000 ,002 ,000 ,000 Total number of companies invested in by Venture Firm Pearson Correlation -,015** -,011** -,004 -,030** ,052** ,388** 1 Sig. (2-taled) ,002 ,000 ,395 ,000 ,000 ,000

**. Correlation is significant at the 0.01 level (2-tailed) *. Correlation is significant at the 0.05 level (2-tailed) c. Listwise N = 3936

Table 7: Correlation matrix CVC investments.

Correlations CVC investmentsc Cultural Distance Local Partner in the Syndicate Successful Investment GDP % Market

Capitalization Venture Firm Age

Total number of companies invested in by Venture Firm Cultural Distance Pearson

Correlation 1 Sig. (2-taled) Local Partner in the Syndicate Pearson Correlation ,281** 1 Sig. (2-taled) ,000 Successful Investment Pearson Correlation ,010 ,047** 1 Sig. (2-taled) ,523 ,003 GDP % Pearson Correlation ,234** ,239** ,034* 1 Sig. (2-taled) ,000 ,000 ,033 Market Capitalization Pearson Correlation -,189** -,235** -,050** -,588** 1 Sig. (2-taled) ,000 ,000 ,002 ,000 Venture Firm Age Pearson

Correlation -,022 ,000 -,015 -,109** ,135** 1 Sig. (2-taled) ,177 ,987 ,349 ,000 ,000 Total number of companies invested in by Venture Firm Pearson Correlation -,149** -,057** -,002 -,097** ,106** ,414** 1 Sig. (2-taled) ,000 ,000 ,880 ,000 ,000 ,000

A binary regression analysis was performed to analyse the ability of cultural distance to predict the fund performance/success of an IVC or CVC investment and to analyse whether a local partner in the syndicate could influence this relationship for IVC and CVC investments. First the IVC investment data will be analysed.

The first model, Model 1, of the binary regression analysis includes all control variables: GDP %, Market Capitalization, Venture Firm Age, the Total Number of Companies Invested in by Venture Firm and the controls for the investment year. The Omnibus Test of Model Coefficients shows together with the -2 Log Likelihood ratio that Model 1 better explains the variance in the outcome (Chi square = 159,354, p =.000). All control variables show a statistical significance of <0.05, with: GDP % B = .516 (p = .001), Market Capitalization B = ,808 (p = ,000), Venture Firm Age, B = ,010 (p = ,000) and the Total Number of Companies Invested in by Venture Firm B = ,000 (p = ,014). Results of Model 1 and the other upcoming regression models examining the IVC investments (Model 2, 3 and 4) are shown in table 9.

In Model 2 the independent variable, cultural distance, is added. Again, all the control variables show a statistical significant effect with α <0.05: GDP % B = .413 (p = .009), Market Capitalization B = -,753 (p = ,000), Venture Firm Age, B = ,010 (p = ,000) and the Total Number of Companies Invested in by Venture Firm B = ,000 (p = ,021). Furthermore, Cultural Distance shows a positive significant effect (B = .244, p = .000) on the successfulness of an IVC investment. This is in line with previous findings from the correlation analysis and the Levene’s test. This positive effect is in accordance with H0. The

Omnibus Test of Model Coefficients shows that Model 2, with the adjustment of the cultural distance, significantly better explains the variance in the outcome (Chi square = 14,567, p =.000).

After this, Model 3 is analysed. Model 3 consists of the control variables, the independent variable Cultural Distance and the variable Local Partner in Syndicate. Again, all the variables show a statistical significant effect. The effect of Cultural Distance remains significant with B = ,341 (p = ,000). The linear term ‘Local Partner in Syndicate shows a positive significant effect (B = .313, p = .000) on the successfulness of an IVC investments as well. This is in line with the previous discussed literature, as the local partner might have additional and country specific knowledge about a PC. Again, all the control variables show a significant effect: GDP % B = .456 (p = .004), Market Capitalization B = -,756 (p = ,000), Venture Firm Age, B = ,010 (p = ,000) and the Total Number of Companies Invested in by Venture Firm B = ,000 (p = ,020). The Omnibus Test of Model Coefficients shows that the -2 Logit Likelihood decreased significantly and therefore better explains the variance compared to Model 2 (Chi square = 14,883, p =.000).

The Model 4 includes all variables in the model: the control variables, Cultural Distance, Presence of a Local Partner in Syndicate and the interaction term ‘Local Partner in Syndicate x Cultural Distance’. The Omnibus Test of Model Coefficients shows again that Model 4 better explains the variance in the outcome compared to the previous model (Chi square = 10,210, p =.001). The interaction term shows a positive significant effect (B = .470, p = .001) on the successfulness of an IVC investment. However, when adding the interaction term to the model, the direct linear effect of Cultural Distance on the fund performance of an IVC investment is no longer statistical significant (B = .083, p = .391). The linear effect of the presence of a Local Partner in the Syndicate remains significant with B = ,395 (p = ,000). This indicates that there is a moderating effect of the Local Partner in the Syndicate between the Cultural Distance and the fund performance of an IVC investment. Because there is no significant effect of the independent variable anymore in Model 4, this can be explained by the addition of the interaction term. The interaction effect is shown in table 8. The table shows