Faculty of Business and Economics
Corporate Venture Capital investment and syndicate
behaviour: a closer look at the regulatory environment
Name: Rodier Hussainali
Student number: 11236345
Date: 27th of January
Master thesis: Final
Qualification: MSc Business Administration – International Management Institution: University of Amsterdam
Statement of originality
This document is written by Rodier Hussainali 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 content.
Table of contents
Abstract ... 5 1. Introduction ... 6 2. Literature review ... 8 2.1 CVC activity ... 8 2.2 CVC value ... 9 2.3 Syndication ... 10 2.3.1 Cross-border syndication ... 122.3.2 Costs of cross-border syndication ... 13
2.3.2 Benefits of cross-border syndication ... 14
2.4.Regulatory environment host country ... 14
2.5 Research gap ... 15
2.6 Research question ... 16
3. Hypotheses ... 16
3.1 Rule of law and syndication behaviour ... 17
3.2 Experience as a moderator ... 18
3.3 Non-local CVC firms as a moderator ... 19
4. Methodology ... 19 4.1 Data collection ... 19 4.2 Research sample ... 20 4.3 Variables ... 21 4.3.1 Dependent variable ... 22 4.3.2 Independent variable ... 22 4.3.3 Moderating variables ... 22 4.3.4 Control variables ... 23 5. Results ... 24 5.1 Empirical strategy ... 24 5.2 Correlation ... 24 5.3 Regression ... 26 5.4 Moderation ... 28 6. Discussion ... 29 6.1 Rule of Law ... 29
6.2 Experience ... 30
6.3 Non-local CVC firms ... 30
7. Conclusion ... 31
Academic contribution ... 31
Managerial and policy implications ... 32
Limitations / Future research ... 33
Acknowledgement ... 33
References ... 33
Appendix ... 37
Table of figures and tables
Figure 1: United States CVC investment growth in billions by year ... 6Figure 2: Hypotheses being tested in relation to syndication behaviour ... 17
Table 1: Syndication Behaviour ... 21
Table 2: Correlations and descriptive statistics ... 25
Table 3: Binary Logistic Regression Models ... 26
Table 4: Moderation - Experience ... 28
Abstract
In this paper, I examine the influence of the host country regulatory environment, which constitutes the overall regulatory quality of a country, on the syndication behaviour of venture capitalists. The main aim is to study whether the rule of law in a host country influences the syndication behaviour of corporate venture capital (CVC) firms that participate in cross-border investments. In addition, I investigate whether having previous investment experience has a moderating effect on the relationship between rule of law and syndication behaviour of CVC firms. Finally, I also examine whether the presence of experienced non-local CVC firms has a moderating effect on the relationship between rule of law and syndication behaviour. To study the syndication behaviour, CVC investment data from between 2005 and 2015 are gathered via Thomson One; a final research sample of 5,117 portfolio company investments is used. The findings show support for the prediction that rule of law influences the syndication behaviour of CVC firms that invest across borders. However, the two other predictors do not seem to have statistical support.
1. Introduction
‘Microsoft buying Nokia’s phone business in a $7.2 billion bid for its mobile future’ (Pierce, 2013). Who would have thought fifteen years ago that Nokia would stop making phones by the end 2013? Innovation is the key to preserving a competitive advantage. This is necessary, even for a big pioneer in the industry, like Nokia, because neglecting the market can cause
Figure 1: United States CVC investment growth in billions by year
companies to go out of business. The Nokia example illustrates a prime reason why CVC investment has gained popularity over the last few years (PwC/NVCA MoneyTree, 2016) (see Fig. 1.). CVC investments are primarily equity investments in young, privately held companies, where the investor is a financial intermediary who is typically active as a director, an advisor, or a manager of the firm (Gompers & Lerner, 1998). Companies seek practices that allow them to gain, or preserve, a competitive advantage, and a CVC investment can be considered as a possible option to reach this gain. A CVC investment allows making an equity investment in a company, instead of building up a new one. There is always the risk of making the ‘wrong’ investment. These are investments that do not yield to the expected return. However, it is also possible to try to reduce the risk. One possible way of achieving that is by syndication. This is when two or more venture capitalists come together to take an equity stake in an investment (Lockett & Wright, 2001). By syndicating, the risk is shared with other (large) firms. Yet, this also means that the potential benefit of the investment will be shared as well (De Clercq & Dimov, 2004). Therefore, the decision to syndicate must be a well-thought-out process by the investing firm. The firm must analyse the potential risk(s) and benefit(s) by looking at specific factors, such as country size, institutions, and politics. By considering such factors, firms try to predict whether they are making the right decision by
investing. This leads to an interesting aspect of CVC investments: how is a syndicate decision eventually made, and what are the conditions/factors that are taken into account in this process? A previous study by De Clercq and Dimov (2004) showed that knowledge-, and finance-sharing may be considered as the main reason to syndicate.
The decision to syndicate most likely hinges upon two arguments, as described above. Previous studies have looked at several conditions that can affect syndication behaviour of well-established firms. An interesting factor to consider when confronted with overseas CVC investment is that of institution. ‘Institutions are the humanly devised constraints that structure political, economic, and social interaction’ (North, 1991). The informal side of these constraints resembles the culture of a country. The cultural environment can play a role in the decision to either syndicate or not. More precisely, the distance in culture between the home and host countries affects this decision (Dai & Nahata, 2016). However, the term institutions is broad.
Another environmental factor that has received less attention regarding the decsion to syndicate is regulation. The regulatory environment of a country structures the way in which business is conducted and perceived in a certain country (OECD, 2011). It can thus also affect the formation of a syndicate. There can be a risk with regard to the quality of the law, for instance. A number of studies have tried to address the link between the regulatory environment and syndication behaviour (E.g. Bruton et al., 2005; Hain et al., 2014). However, only a few of these studies have succeeded in capturing this in detail. This leaves room for further research on this topic.
At the end of the previous paragraph, I already gave an idea of the potential research that I am going to conduct. I will study how CVC investments are affected by the regulatory environment of the host country. Specifically, I want to research whether the regulatory environment of the host country influences the firms’ decision to syndicate or not. This has lead to the following research question: How does the host country regulatory environment
influence CVC firms’ syndication behaviour?
By studying the phenomenon of CVC investments, from a different perspective, I expect to extend the current literature. So far, previous studies have neglected certain factors of the regulatory environment (e.g. rule of law, taxes) with regards to syndication behaviour. By studying this phenomenon it will, hopefully, be possible to see to what degree specific regulatory environmental factors influence syndication behaviour. Future CVC firms can use the results to better analyse a potential investment in a foreign country and anticipate, instead of react, to the possible difficulties of the regulatory environment of the given country.
The current literature has analysed this concept from the perspective of different institutions, such as the cultural and regulatory environment. However, the regulatory environment leaves some room open for further study (Lockett & Wright, 2001), especially with regards to specific factors that have been neglected in those earlier studies. Investigating how certain regulatory environmental factors of the host country affect CVC firms’ investment behaviour will contribute to the literature. It will allow CVC investors to anticipate instead of react in situations where there is risk involved. For example, they could learn that it might be better to syndicate in a country with a low level of rule of law. This research will grant firms insights regarding when it might be better to syndicate or not to syndicate, considering the regulatory environment of the host country. Furthermore, it will show which composition is better: local firm(s) or well established firm(s)?
This paper is structured as follows. First, I will start with a literature review, in which I will discuss the current literature on CVC investments and syndication behaviour. Second, I will identify the research gap that I have found in the literature. This will lead to my research question. Third, the research design of the study will be discussed. Which variables will be tested, and how? Finally, I will propose a work plan for my thesis process for the upcoming months.
2. Literature review
As with the start of many studies it is useful to examine what previous researchers have found regarding the topic of interest. What are the contributions to this topic from a research perspective?
2.1 CVC activity
Before venture capitalists even consider the decision to syndicate, they think about the decision to make an investment. They consider whether it is necessary to make this kind of investment. For a great part, this depends on the industry in which the firm participates. Basu et al. (2011) show that firms in industries with rapid technological change, a high competitive industry, and weak appropriability engage in greater CVC activity. This suggests that the threat and pressure of competitors in an industry contribute to the decision to engage in investing. Firms in these industries feel that their position is not secured if they do not invest. Basu et al. (2011) approach this study from the resource-based view, which means that firms use their unique access to tangible or intangible resources to gain a competitive advantage
(Peng, 2001). The opportunity to engage in CVC investments depends on the way in which firms can exploit their resources (Basu et al., 2011).
The rate of innovation and competitiveness in an industry determines the degree of investment. CVC investments are therefore primarily made when there is the need to innovate in order to survive in the industry. However, Dushnitsky and Lenox (2005) also found that firms with a great absorptive capacity and a large cash flow, the more likely they are to invest. A great example, of the pressure to innovate, can be seen in the telecommunication sector. This is an industry pressured to have devices that get faster, lighter, and more capable of doing things by the year. If you as a firm are not able to cope with the rapid change in innovation then you will not survive in this industry (see Nokia example). With CVC investments you are able to place yourself on top of the newest technology of the industry that might be integrated in a later model. This also contributes to the findings of Dushnitsky and Lenox (2005). They found evidence that industries with a lot of technological potential will have a greater chance of CVC investments.
Most researchers try to capture innovation by looking at Research & Development expenditure, or alternatively by considering the amount of patent applications (Chemmanur et al., 2013). Earlier studies show that the more patents a company has, the greater its level of innovation is. Furthermore, the technological fit between the CVC and the start-up is also an important contribution to innovativeness.
Choosing the right investment seems to be a specialisation in its own right. Shikhar Gosh illustrates this in his study on the success rate of CVC. ‘If failure is defined as failing to see the projected return on investment – say a specific revenue growth rate or date to break even on cash flow – then more than 95% of start-ups fail’ (Gage, 2012). Prior experience can help with the selection of the appropriate investment and thus reduce the rate of failure (Yang et al., 2009). This makes sense, because a firm can learn from the pitfalls that it has experienced in past investments.
2.2 CVC value
In order to gain experience, firms have two options: either invest frequently and learn from their mistakes, or attract specialists who have prior experience with CVC investments. Considering that CVC firms want to reduce the rate of failure, hiring or collabarating with experienced specialists is likely the option to pursue (Lerner, 1994). The rate of failure can be seen as a risk factor for an investment. Other possible risk factors include the skills of the employees (internal) and currency changes (external), for example. A popular measurement
used to weigh the costs against the possible benefits is the return on investment. This measurement allows firms to predict whether the investment will eventually result in performance improvement. But does a CVC investment automatically result into improved value for the firm?
A previous study by Dushnitsky and Lenox (2006) provides useful information about the relationship between an investment and performance improvement. By using a special measure, Tobin’s q (See also Dushnitsky & Lenox, 2006), the authors find evidence that CVC is indeed associated with performance improvement. ‘The contribution of corporate venture capital investment is strongest when it is focused on attaining a window on technology rather than a purely narrow return on investment’ (Dushnitsky & Lenox, 2006). This shows that performance improvement hinges on the motivation to pursue the investment.
Whereas Basu et al. (2011) showed that certain industry conditions lead to greater CVC activity, it could also be stated that this activity can be transformed into greater value whenever there is a strong focus on the attainment of technology. However, the ability to realise a benefit from a CVC investment hinges on the strength of the internal knowledge base. An CVC investment will create an improved value when the internal knowledge base of the firm recognizes how to use the acquired information to its maximum (Benson & Ziedonis, 2009).
So a CVC investment can contribute to an improved value of the firm. But why do firms choose to form a partnership, and how does this create value? A partnership can lead to an increased deal flow (Lockett & Wright, 2001). This means that you have more options to invest in companies. A partner creates a that bigger network, which both partners will profit from, as it leads to newer and bigger selections of investments. Having these options creates a stronger position in the investment market for the firm. It allows the CVC firm to make a top selection of the possible investments. Therefore, increased deal flow, by partnering, can lead to value improvement. Though, even top selection investments are not guaranteed successes.
2.3 Syndication
Sometimes it is difficult to retrieve knowledge about the foreign market, culture, or environment for instance, within the existing network in order to make a CVC investment. This knowledge can be highly tacit. Therefore, firms have to look for solutions to overcome this difficulty. Syndication is a possible solution to this problem. Syndication is a common form of partnership where the investor engages in a partnership with one or more firm(s) in order to reduce the potential risks involved in the investment (Lerner, 1994). The forming of
syndication usually happens in rounds. In each round, there is the possibility to invest. The firm that brings in the most resources usually acts as the lead firm in the syndicate formation (Wright & Lockett, 2003). Reasons to syndicate vary mostly over three aspects: finance sharing, knowledge access, or increased deal flow.
Partnership with other firms can be a successful move to access resources or retrieve new information. This is confirmed by multiple studies that investigate the motivation behind syndicate formation. There are multiple reasons for firms to syndicate. Knowledge sharing and finance sharing are the most important motivations (Lockett & Wright, 2001; De Clercq & Dimov, 2004). Finance sharing is mostly a means to constrain possible loss by syndicating with other firms.
Knowledge sharing, however, is a way to fill up the current lack of expertise. Other well-established firms might be more knowledgeable on certain aspects and vice versa. By participating in a syndicate the firm can reduce the uncertainties due to the new knowledge the other firm has. This can help the firm in gaining knowledge and experience for future CVC investments. However, it is important that you do not give away all your expertise. The firms in the syndicate could use that knowledge to outcompete you in the future.
Besides sharing knowledge or finance, syndication can also function as a way to access new markets as discussed earlier. An increased deal flow can widen the firms network and give it a stronger position in the investment market to choose the top picks. Sometimes CVC firms make their investment in the last round of a syndicate (Lerner, 1994). Even though the financial return might be less, their name is still attached to the promising firm and is seen as investors in the firm.
The reasons to syndicate are quite clear (knowledge flow, deal flow, reduce uncertainties), but what about composition? Do venture capitalists tend to look for partners that are well established or have a certain reputation? The partner choice has an effect on the further process of syndication. A potential partner should hold information or resources that are not known by or available to the other venture capitalist in order to be attractive. This is necessary, because otherwise there is probably no benefit in syndicating. In a study by Lerner (1994), although primarily focused on biotechnology, it is shown that syndication in the first round is usually done with other well-established firms. The distinction between well established firms and smaller firms is based on fund size and firm age (Lerner, 1994). In the first round, the experience and willingness of the potential partner plays a huge role. Venture capitalists like to form partnerships with other experienced firms because they are perceived to be on the same level. This is done in order to reduce the uncertainties that are involved with
the potential investment. Only in later rounds are inexperienced firms brought into the syndicate formation (Lerner, 1994).
2.3.1 Cross-border syndication
Cross-border syndication differs from normal syndication, because in this process country differences may affect the partner choice. The type of partner they choose differs. It is most common that CVC firms choose for other well-established firms in the first round of investment. The experience and expertise of a well-established firm feels more secure than a firm that has relatively little experience with CVC investments in the given country (Lerner, 1994).
Entering a foreign country does not go without any difficulties. Currency, language, laws, culture, and many more factors can be considered as possible difficulties to overcome. Ghemawat (2001) claims that these kinds of country factors may impact the business of a firm. Institutional difference(s) between the home and the host country can be considered as a problem for cross-border investment. The way property is protected for instance can differ between countries. In a weak institutional environment there is little to no protection for (intellectual) property. This can be a substantial risk for a CVC investment.
Syndication can be seen as a mean to overcome risk in the host country. With syndication you can overcome the institutional differences. Possible reasons to syndicate with a local investor are: access to knowledge, or avoid foreign discrimination. The latter has to do with receiving less protection due to be being foreign in the host country. Knowledge in the host country can be highly tacit. A local investor can be the key to receiving this knowledge (De Clercq & Dimov, 2004). In this situation the CVC firm is almost forced to capture this knowledge in the country of investment. Just as with (normal) CVC investment, syndication again becomes a possible solution. As described earlier, with syndication you receive access to certain expertise from the other firm. In this case the knowledge of the local investor can be useful to overcome institutional difference(s).
Why, however, would foreign firms consider a syndicate with a foreign firm? Start-ups seem to face a dilemma when it comes to forming a syndicate with well-established firms. A ‘sharks dilemma’ is the term that is often used to describe this situation (Katila et al., 2008). Start-ups have the potential risk of losing their unique resources to the investor. On the one hand, they are faced with the dilemma of either taking the risk of forming a syndicate and potentially losing their competitive advantage; but on the other hand, not taking the risk means a lost opportunity to potentially grow as a firm. Eventually the start-up firm’s level of
resource needs influences the decision of whether to syndicate with the investor (Katila et al., 2008). The level of information asymmetry also influences this decision. Start-ups sometimes opt not to disclose certain specific information due to the threat of imitation (Dushnitsky & Shaver, 2009).
2.3.2 Costs of cross-border syndication
Venture capitalists who engage in cross-border investments are likely to be confronted with differences between the home and host countries. The most common difference between countries is cultural distance. This can be defined as ‘the extent to which the shared norms and values in one country differ from those in another’ (Kogut & Singh, 1988): for example, differences in the acceptance of power distance in firms between Japan and the Netherlands. In Dutch firms, there is only little power distance between managers and employees, whereas in Japanese firms there is a higher level of power distance. This means that employees in Japanese firms have less to say to their superiors compared to employees in Dutch firms (Geert Hofstede, 2016). Distance in culture affects the likelihood of forming a partnership (Dai & Nahata, 2016). However, it is not in the way one might expect: a large cultural distance between countries reduces the likelihood of syndication. One might expect this relation to be the other way around, because it would make more sense to co-operate to overcome differences. The reduction of syndication between firms from culturally distant countries can be explained by the extra costs that are associated with the complexity of coordinating the investment due to the large difference in culture (Drogendijk & Slangen, 2006). Due to this complexity, a CVC firm that wants to invest in culturally distant countries pursue different strategies. A possible strategy is to start a new greenfield project, which allows the investor to lead the firm with employees who understand the investor’s way of thinking.
Besides cultural distance, there is also the cost of losing a higher return by syndicating. Syndication means that the equity investment is shared with two or more firms. Thus, the potential return on investment will be lower than would normally be the case if there were no partners. Firms may therefore choose to make the investments by themselves. However, the CVC firm must have enough equity in order to pursue such a strategy. The firm also needs to have prior experience with the host country. A lack of experience can eventually lead to more costs, due to the challenges that need to be overcome in the host country.
2.3.2 Benefits of cross-border syndication
Beside the costs of cross-border syndication there are also benefits. These benefits, namely knowledge and finance, which have already been cited in this paper, can also be accounted for with cross-border investments. With regard to knowledge, syndication represents a way to access knowledge or share risk in the host country (Lockett & Wright, 2001). Without syndicating, the knowledge would not be accessible. Another motivation might be to obtain a second opinion about an investment (Lerner, 1994). If more investors share the same opinion about the investment, then this can take away the fear of making the wrong decision. On the other hand, the finance incentive relates to sharing the costs of the investment. Due to the unknown outcome of the investment, venture capitalists would like to share the financial risk with others. In case an investment fails, then at least the financial loss has been constrained by making use of the syndication form.
Clearly, the overarching benefit of cross-border syndication regards sharing the risk of the investment in an unfamiliar environment. A lack of experience or equity will most likely lead to syndication. The CVC firm can benefit from the syndicate, because it allows him to cope with the absence of certain characteristics.
2.4.Regulatory environment host country
Williamson’s ‘New Institutional Economics’ theory suggest that when a company enters a foreign country, it has to deal with level two of this theory. Level two involves dealing with the rules of the game. It includes the ‘executive, legislative, judicial, and bureaucratic functions of government as well as the distribution of powers across different levels of government’ (Williamson, 2000). The regulatory environment can harm the CVC firms’ investment. For example, the level of legal protection is an important dimension on which investors rely (Bruton et al., 2005). The host country might give the CVC firm less protection of his property than in the home country, simply because it is a foreign investor. Some countries do this to protect their own industry. However, this adds additional risk to one’s investment.
Syndication is a common strategy used by CVC firms in this situation. By syndicating with local investors, for instance, one can overcome certain barriers of the local regulatory environment (Hain et al., 2014). The local partner does have the legal protection on property rights that the venture capitalist does not have. ‘Local partners provide a means to access resources such as networks held by local firms, that may help to counteract idiosyncrasies of a weak institutional environment’ (Bruton et al., 2005). For example in America, foreign
defenders will most likely lose cases against American firms (Tabuchi & Wingfield, 2012). This has to do with the protection of the own industry in a country and different rule-setting.
On the other hand, the regulatory environment may also lead to no syndicate formation. Institutional trust, termed as the overall trust in the structure and honest behaviour, affects the decision to make an investment in a country (Hain et al., 2014). A lack of institutional trust can even lead to the decision to not make an investment in a country. High corruption is a good example of a lack of trust. Brazil is a country where a high degree of corruption exists. Corruption can affect the investment, because there is the possibility that the the government officials will constrain the venture capitalist from pursueing business. Perhaps you have to bribe them in order to get things done, which are additional costs to the venture capitalist. But also results into an unpleasant situation.
2.5 Research gap
The regulatory environment is important due to its influence on the way business is done in a country and CVC firms need to deal with this environment when they make an investment. Although there is a lot of literature available, I still see some room for new insights.
First of all, Katila et al. (2008) indicated that firms consider the level of resource needs by start-ups as a main incentive to syndicate or not. The threat of imitation plays a role in this decision, which leads to the paradox of disclosure. Especially if the firms act in the same industry then there is a decresae of chance to syndicate (Dushnitsky & Shaver, 2009). However, these authors are mainly focused on the resource needs whereby they lose sight off other important factors such as institutional distance.
A study that does consider the influence of institutions on CVC investments is the research performed by Dai and Nahata (2016). They particularly have a focus on the syndicate behaviour, influenced by the distance in culture, and find that a large distance actually increases the likelihood to not pursue a syndicate. Yet, they pay little attention to the regulatory environment in their study. The regulatory environment plays an important role in the way that a country is structured (OECD, 2011). A high level of corruption could perhaps have a great impact on the syndication behaviour CVC investments, but this is not studied by Dai and Nahata (2016).
A number of studies did do research on the regulatory environment. Hain et al. (2014) have studied how institutional trust affects cross-border syndication behaviour, using China as a model. They tested whether institutional simalarities and differences in legal systems likely influence cross-border CVC investment. The results show that the negative effects of
institutional distance is reduced by syndicating, for instance, with local investors in China. But this paper is more focused on trust instead of the quality and effectiveness of laws.
Bruton et al. (2005) developed working propositions with regard to how the legal environment influenced the behaviour of cross-border CVC investments. The main focus is on the legal protection of foreign firms in the host country. They argument that local partners provide a means to adapt to counteract idiosyncrasies of a weak institutional environment, which is confirmed by Tykvová and Schertler (2011).
Finally, Lerner (1994) has also done research but more on the composition side of syndication. He finds that, especially in the first round, venture capitalists tend to syndicate with similar experience. However, he neglects the regulatory environment in his study.
Overall the studies neglect factors such as the rule of law, or taxes. This is important because differences in taxes with the host country, for instance, can possibly lead to syndication. By syndicating with local investors they get computed by a lower tax perhaps. This could be interesting to test. Therefore I see the opportunity to create more insight in the way these factors influence cross-border syndication behaviour.
2.6 Research question
Several studies have tried to address how certain conditions influence the decision to syndicate. However, not a lot research has been done with regard to the possible link in the decision to syndicate and the regulatory environment with cross-border investments. Factors that can be studied are the rule of law, regulatory quality, and government effectiveness.
This study will add to the literature by showing that there are more factors, besides cultural distance, that influences the behaviour of CVC investments. I would like to generate new insights in the regulatory environment of the host country and how this influences CVC investment syndication behaviour. Combining the literature and the research gap leads to the following research question: How does the host country regulatory environment influence
CVC firms’ syndication behaviour?
3. Hypotheses
As stated before, there is not a lot of prior research that studies the linkage between the host country regulatory environment and cross-border investments. In order to capture this in more detail, the following hypothesis structure has been set up (see figure 2).
Figure 2: Hypotheses being tested in relation to syndication behaviour
3.1 Rule of law and syndication behaviour
As previously stated, a cross-border investment is not an easy decision to make for a CVC firm. There are some difficulties to overcome with regard to the difference between the home and the host country. Such difficulties can be distance in culture (Dai & Nahata, 2016), or in the regulatory controls. The former represents differences mainly in norms and behaviours. The latter concerns differences in regulatory controls, such as the protection of intellectual property, which could influence the volume of cross-border investment in a specific country and thus influence syndication behaviour. Firms should therefore always consider these regulatory differences. For example, a weak intellectual protection has a negative effect on cross-border investment volume (Lee & Mansfield, 1996). Having a local partner could be a possible solution to the liability of foreignness, such as foreign discrimination, as these partners sometimes have more rights than foreign firms do (Dai & Nahata, 2016).
The World Databank has created an index to capture the regulatory quality of a country: the World Government Index (WGI) (World Data bank, 2016). The rule of law indicator of this index can be used to measure the distance of regulatory quality between countries. For example, if a CVC firm invests in a country with a lower regulatory quality than its home country, it can expect to face some difficulties with regard to doing business in the country abroad. A local partner could be useful in this situation.
An example of foreign discrimination can be seen in the difference between tax for a domestic firm and for a foreign firm investing in that country: it could be higher for the foreign firm. A reason for this could be that the country favours domestic producers over foreign producers (Warren, 2001). To benefit from or by-pass the foreign policy, syndication with a local partner could be the answer to the problem (Dai et al., 2012). A local partner can
provide the CVC firm with the knowledge that it needs, and at the same protect it from any foreign restriction policy set up by the government.
Thus, if the rule of law is lower in the host country than in the home country, it can be expected that the CVC firm will syndicate with a local partner in order to overcome the differences in regulatory controls.
Hypothesis 1: Syndication with a local partner is weakened when the rule of law in the host
country is high.
3.2 Experience as a moderator
As discussed above, the regulatory control of a country might have an effect on a CVC firm’s syndication behaviour. However, how does this effect stand when the investing CVC firm already has a certain amount of past investment experience?
One might expect that having previous experience in a foreign country should help to reduce the uncertainty that CVC firms face when entering a foreign country. However, in his study, Hopp (2010) states that industry experience does not mitigate the risks faced by a CVC firm when investing in a foreign country; instead, experience acts as a certified argument for new potential partners. This could mean that experience is not necessarily a decisive factor with regard to syndicating with a local partner.
Schertler and Tykvová (2011) show results in line with Hopps’s view. A CVC firm that has made many investments gains knowledge with every investment. The accumulation of knowledge makes it more familiar with the regulatory environment of the host country. Due to this increased familiarity, it may also have more privileges because it has linkages in the network of the host country. This takes away the uncertainties for the CVC firm, which reduces the necessity to syndicate with a local partner.
As described by the aforementioned studies on experience, it is expected that the need for syndication with a local partner will be weakened with increased experience (Schertler & Tykvová, 2011; Hopp, 2010). For instance, the knowledge of the local partner becomes less desirable because the CVC firm has already gathered knowledge through past investments. The information asymmetry between the CVC firm and the local firm is thus resolved. Furthermore, the CVC firm’s familiarity with the regulatory environment can also lessen the need to form a syndicate with a local partner.
Hypothesis 2: The need for syndication with a local partner is weakened when the CVC firm
3.3 Non-local CVC firms as a moderator
There are usually several parties interested in investing in a particular company. Most of the time, this leads to a syndicate due to the possible benefits that this has for the investing firms, such as financial sharing or knowledge exploration (Lockett & Wright, 2001). Lerner was one of the first researchers to try to study the reasons behind syndication. In his study (1994), Lerner showed that venture capitalists tend to syndicate with other well-established firms in the first round of syndication, and that later on smaller firms are considered. His results show that receiving a second opinion plays a role in this situation: the venture capitalists would prefer to receive this from an experienced company than from a new or small firm.
Besides ensuring a second opinion from other firms, syndication can also expand the choices for a CVC firm in the future. Syndication enables the firm to have access to the partner’s network. The partner can introduce the firm to this network, which can ultimately lead to new opportunities and more investment choices (Lerner, 1994).
The previous reasonings show signs of why syndication is or could be beneficial for the CVC firm. However, most of these reasonings do not take into account the possible effect of foreign partners on syndication behaviour. Instead, they focus more on the relative size of a firm. A local partner can be beneficial with regard to overcoming the differences in the regulatory environment, but an experienced non-local partner can be beneficial in terms of gaining access to a new network with new possibilities. Moreover, the experienced non-local partner could also help to overcome the differences in regulatory environment, for example, if it has already built a relationship with the government in the host country from which the orignial CVC firm can benefit (Shaver et al., 1997). It could thus be expected that experienced non-local CVC firms could affect the likelihood of syndication with only a local partner. Hypothesis 3: The likelihood of syndication with only a local partner is weakened when other
(non-local) experienced CVC firms are also investing in the host country.
4. Methodology
4.1 Data collection
To collect the required data for this study, I have made use of mainly secondary data provided by two databases: Thomson One and the World Databank. The Thomson One database, provided by Thomson Reuters, has allowed me to gather data about CVC investments. Previous studies have also made use of this database. In older studies, it is still referred to as
VentureXpert. It contains information about CVC investments by size, location, industry, and many more variables. There are multiple levels on which data can be gathered, such as the
firm-, fund-, and portfolio company levels. I will focus on the firm level and the portfolio
company level.
At the firm level, I have collected standardized data with regard to the firm. For instance, firm nation will help me distinguish cross-border investments from domestic investments. The amount of deals made will be the grounds on which the amount of experience will be based. Finally, to control for the size of a firm, I have also selected the variable total funds managed by firm. Other variables are found year and firm type.
At the portfolio company level, I have gathered information about the companies that are being invested in by the firms. In the research sample 5,117 portfolio companies are being invested in. The most important variable is company nation, to distinguish the host country. Furthermore, information regarding company status has also been gathered. This variable shows whether the portfolio company is a public company or a private company, etc.
Appendix 1 provides a full overview and description per level of the collected variables that are included in the database of my research. To combine all of the information from the different levels, I have constructed unique identifiers. These unique identifiers are present on every level, such as company ID, firm ID, and investment date. Together, they form a unique code. This is necessary in order to combine the information from the different levels into one dataset.
In addition to Thomson One, I have also made use of the World Databank. This database contains country-specific information, including regulatory factors. The World Government Index contains specific information regarding the regulatory environment of a country.
Finally, the level of analysis focuses on the portfolio company level. This means that I am interested in determining how the portfolio companies are syndicated, for instance, and which country the partners are from. Thomson One makes it possible to gather this information. In the dataset, looking at the first investment date filters the information. This step ensures that there is no double counting with regard to the amount of partners involved in the syndicate.
4.2 Research sample
Much information is available about CVC investments in the Thomson One database, it is therefore important to have a specific sample. Few studies focus on the recent number of
CVC investments. A sample from 2005 to 2015 therefore differentiates the present study from most studies. Furthermore, the sample also makes this study more up-to-date, thereby further differentiating my research from other studies on the same subject.
To construct the final sample, I have filtered the dataset because it initially showed roughly 290,000 investment transactions. These were dispersed over 48,026 unique syndications. In this study, a syndicate is recognised as the collaboration between two or more venture capitalists to take an equity stake in an investment (Lockett & Wright, 2001). The first step I have taken is to determine which syndicates are also cross-border, as this study is particularly focused on cross-border syndicates. In this study, cross-border investments are investments made by CVC firms outside of their domestic country. Out of the 48,026 syndications, 27,005 are cross-border investments. I have also removed bias in the form of firms whose countries are unknown.
Furthermore, since I am only interested in CVC, I have also filtered the database for firm type: Corporate PE/Venture. Filtering for this result in a sample of 12,017 investment transactions dispersed over 5,317 portfolio companies. After deleting cases due to missing values in SPSS, the final amount of portfolio companies is 5,117.
Finally, I am also interested in the syndication behaviour with regard to the portfolio companies. Table 1 provides an overview of this distribution. This data shows that, at first sight, most CVC firms engage a syndicate with only a local instead of other syndication forms. The analysis of this behaviour will be central in the following sections.
Table 1: Syndication Behaviour
Syndication Behaviour (5117)
# Portfolio Companies
Local Partner Other
4507 610
4.3 Variables
Due to the explanatory character of this study, it is important to distinguish the different dependent and independent variable(s). This will provide a clear overview of the research and the desired outcome. Figure 2 also offers an overview of the linkages between the dependent variable, independent variable, and moderating variables.
4.3.1 Dependent variable
The main part of the research question focuses on syndication behaviour. Syndication behaviour is the dependent variable of this study. Syndication behaviour has to do with the extent to which CVC firms choose to syndicate, and on which grounds they base their decision. However, syndication behaviour is not a loose variable that can be measured. Behaviour can be seen as a set of criteria that, together, form the behaviour. In this study, the dependent variable measures whether the syndication involves only a local partner. In order to capture this behaviour, a simple dummy variable will indicate whether a local partner is involved in the syndicate. If this is the case, the variable will result in a 1. Anything else will be presented as 0.
A different form of syndication behaviour could be the syndication with only (a) foreign partner(s), or with both a local partner and foreign partner. This behaviour is captured in the moderator variable non-local, which is explained further in section 4.3.3.
4.3.2 Independent variable
To research syndication behaviour, I selected a few independent variables that represent a country’s regulatory environment. However, a Pearson correlation test showed that the variables rule of law, regulatory quality, and government effectiveness are highly correlated with each other. This suggests that the variables may be measuring the same thing, which could have an effect on the statistical result of the study. To prevent this situation, I have selected a compromised variable named rule of law. This variable is an aspect of the World
Governance Index. The index consists of five aspects, but rule of law is the only part that
directly measures the regulatory environment of the country. It measures government effectiveness, regulatory quality, corruption, and body of laws. These measures are in line with the original independent variables, but the latter are now combined into a single indicator. The outcomes of this variable range from 0 to 1. The higher the score, the better the quality of the regulatory environment of that country.
4.3.3 Moderating variables
As discussed in the hypothesis section, I will be testing whether experience has a moderating effect on syndication behaviour with a local partner. Experience is based on the amount of deals made by the venture firm. Furthermore, I chose to mean-centre the independent variable
rule of law and the moderator experience, because they are both numerical. This choice is
the degree to which centering in fact affects the statistical tests for moderating effects is questionable (Kromrey & Foster-Johnson, 2016)
The process of mean centring created two new variables: RolCent and ExpCent. The moderator variable is the multiple of the two variables, which creates the new variable
ExpRol. Due to this process, the outcome of the variable ranges from -1,245 to 1,084. If the
outcome is precisely 0, this means that the CVC firm is local. I will test the moderator variable by using the add-on macro called ‘Process’ in SPSS (Hayes, 2016). This add-on automatically takes into account the binary context of the dependent variable.
Besides experience, I will also test whether the presence of experienced non-local CVC firms influences syndication behaviour. For the creation of this moderator, I also used the centred variable RolCent. The non-local variable was then combined with the variable experience. Next, the variable was mean-centred, which led to the new variable NLCent. To create the moderator, NLCent was then multiplied by RolCent, which resulted in the final moderator variable NLRol. The outcome of this variable ranges from -2,660 to 1,261. If the outcome is precisely 0, this means that the CVC firm is local.
4.3.4 Control variables
Several control variables are included in the database. The control variables ensure that the variables that are being measured yield the right results. A variable that needs to be controlled, for instance, is the total number of deals. By using the control variable Firm age, I will control for the amount of deals made. For example, it could be that a firm has made a low amount of deals. However, this could be because it has only existed for two years. This variable is measured using the formula of founded year minus the current year of the firm. For example, 1947 – 2017 yields a firm age of 70.
Market capitalisation % of GDP is also included as a control variable (World Data
bank, 2016). A stock market that is vivid can influence the choice of market (as cited in Hain et al., 2014). When the stock market is vivid, it will be viewed as an attractive market for an exit strategy, and is thus said to have a positive effect on venture capital activity. Market capitalisation is measured by calculating the average of the country’s market over the period of 2005 to 2015. This results in a range of outcomes between 0 and 3.0.
GDP growth is also a control variable to be included in the study (World Data bank,
2016). The growth rate of the destination country’s GDP reflects the tendency to invest in countries with high economic growth and the differential between the growth of the destination and the source of country (Hain et al., 2014). The variable is measured using a
calculation of the GDP growth per country over the period of 2005 to 2015; this is given in a percentage. The outcome of this variable ranges from 0 to 2.0.
The variable total funds managed by firm will control for the size of a firm (World Data bank, 2016). Larger firms have access to a more diverse range of resources and might therefore be less inclined to syndicate deals (as cited in Meuleman & Wright, 2011). The variable is measured by counting the amount of funds that are managed by the firm. The amount of funds managed by firms ranges from 1 to 143.
5. Results
5.1 Empirical strategy
The dependent variable in this study is binary, which means that it has two outcomes. The outcome can either be 1, a local partner, or 0, anything else. A linear regression would not be able to keep both outcomes apart, and therefore a different type of analysis is suggested: Binary Logistic Regression (BLR). The BLR deals with studies that have one or more independent variables being tested on a dichotomous dependent variable (Bonney, 1987), as the present study does. Therefore, this type of regression is a more appropriate method to test and analyse the proposed hypotheses. The coefficients of the BLR have the same interpretations as in a normal regression: they reflect the marginal effect of the independent variable on the dependent variable (Powers & Xie, 1999).
5.2 Correlation
Table 2 shows the descriptive statistics of the dataset. After removing missing values, the observations are based on 5,117 investments. The table also shows the range of the variables. For example, the maximum index grade for rule of law is 0.891. Besides the descriptive statistics, correlation between the variables is also an important aspect to examine. The correlated variables could be measuring the same thing. Furthermore, most variables have values of ±0.80 as a rule of thumb, and they are statistically significant. This implies that the variables are not highly correlated with each other, which is a positive sign for the further analysis of the data. Venture firm managed fund is the only variable that is not significant. This result suggests that there is no direct correlation between syndication behaviour with a local partner and the amount of funds managed by a firm. Two highly correlated variables are visible with a correlation score of 1 and -1; however, these variables will not be included in
the regression or moderation model. Therefore, I do not expect that they will affect the results of the research.
Table 2: Correlations and descriptive statistics
1 2 3 4 5 6 7 8 9 10 11 1. S yndi ca ti on B eha vi our 1 2. R ul e of L aw -.0 80 ** 1 3. P or tf ol io C om pa ny -.0 60 ** -.0 27 * 1 4. L oc al C om pa ny -.0 58 ** .3 68 ** -.0 15 1 5. C ros s-B or de r .0 58 ** -.3 68 ** .0 15 -1 ** 1 6. L oc al P ar tne r -.1 73 ** .3 69 ** .0 16 .3 72 ** -.3 72 ** 1 7. B ot h F or ei gn and L oc al -.1 73 ** .3 69 ** .0 16 .3 72 ** -.3 72 ** 1 ** 1 8. V ent ur e Fi rm A ge -.0 87 ** .1 04 ** .0 12 .0 26 -.0 26 .0 38 ** .0 38 ** 1 9. M ar ke t C api ta li sa ti on -.0 80 ** .3 46 ** -.0 23 .2 34 ** -.2 34 ** .2 77 ** .2 77 ** .1 10 ** 1 10 . G D P G row th R at io .0 74 ** -.6 77 ** .0 65 ** -.2 19 ** .2 19 ** -.2 92 ** -.2 92 ** -.1 24 ** -.5 58 ** 1 11. V ent ur e Fi rm M ana ge d Funds -.0 25 -.0 07 .0 54 ** -.0 16 .0 16 -.0 06 -.0 06 .0 25 -.0 25 .0 43 ** 1 O bs . 5117 5117 5117 5117 5117 5117 5117 5117 5117 5117 5117 Me an .88 .65 2. 09 .59 .41 .82 .82 30. 25 1. 08 .311 10. 09 S td. D ev. .32 .15 .29 .49 .49 .39 .39 22. 04 .32 .46 13. 98 Mi n 0 0 2 0 0 0 0 0 .08 .05 1 Ma x 1 .09 6 1 1 1 1 194 2. 38 1. 75 143 **. C or re la ti on is s ign if ic ant a t t he 0. 01 le ve l ( 2-ta il ed ).
5.3 Regression
Table 3: Binary Logistic Regression Models
ar ia bl es M ode l 1 M ode l 2 M ode l 3 M ode l 4 M ode l 5 β S. E β S. E β S. E β S. E β S. E ons ta nt 2. 82 ** .22 3. 86 ** .42 3. 84 ** .42 3. 87 ** .42 3. 76 ** .43 ar ke t C api ta li sa ti on -. 52 ** .16 -. 58 ** .17 -. 56 ** .17 -. 57 ** .19 -. 57 ** .17 D P G row th R at io .42 ** .15 .08 .19 .12 .19 .09 .19 .13 .19 ent ur e Fi rm M ana ge d F unds -. 01 * .00 -. 01 * .00 -. 01 .00 -. 01 .00 -. 01 * .00 ent ur e Fi rm A ge -. 01 ** .00 -. 01 ** .00 -. 01 ** .00 -. 01 ** .00 -. 01 ** .00 ul e of L aw ( H 1) -1. 33 ** .45 -1. 37 ** .45 -1. 37 ** .46 -1. 22 ** .46 xpe ri enc e (H 2) .00 .00 -. 00 * .00 on -l oc al e xpe ri enc ed H 3 .00 .00 .00 .00 age lke rke R 2 0. 028 0. 031 0. 032 0. 031 0. 033 2 74 84 87 84 89 og li ke li hood 3665 3655 3652 3655 3650 5117 5117 5117 5117 5117 Si gn if ic an t a t t he 0 .0 1 le ve l Si gn if ic an t a t t he 0. 05 le ve l
As discussed in the section on the empirical strategy, a BLR is the most appropriate statistical analysis for this study. To test the effects of the independent variable and moderators, I have made different models, to which I have added one variable at a time (see table 3). The Nagelkerke R2 represents, the explanatory power of the models (Statistics Solutions, 2016). As can be seen, this is not high for any of the models. However, adding variables does increase the R2 in most cases. For example, model 1 only has the control variables and has an R2 of 0.028. Yet, adding variables eventually leads to an R2 of 0.033 (see model 5).
Model 1 (X2=74, P<.01) in table 3 shows only the control variables. The control variables seem to be significant (P<.01). Only venture firm age is not significant at the 0.01 level, but it is significant at the 0.05 level. Furthermore, the β shows the effect of change on a variable per unit of increase or decrease. A BLR model is predicted by the formula: Log(p/1-p)= b0 + b1*x1. This formula estimates the relationship between the independent variable and the dependent variable. ‘These estimates tell the amount of increase (or decrease, if the sign of the coefficient is negative) in the predicted log odds of syndication behaviour = 1 that would be predicted by a 1 unit increase (or decrease) in the predictor, holding all other predictors constant’ (UCLA: Statistical Consulting Group, 2016). For this study, the BLR model is estimated as follows:
Logit ρ syndication behaviour = log(ρ syndication behaviour/ 1- ρ syndication behaviour) = β0 – β1 M_CAP + β2 GDP – β3 VF_FUNDS – β4 VF_AGE – β5 ROL – β6 ExpRol + β7 NLRol
The variable market capitalisation is helpful to explain the formula. In model 1, the variable has the strongest (negative) β (β=-.52). Based on the previous β description, this indicates that for every unit increase in market capitalisation, we expect to see a -.52 decrease in the dependent variable syndication behaviour while holding other independent variables constant. Thus, a negative relation exists between market capitalisation and syndication behaviour.
In table 3, model 2 (X2=84, P<.01), the independent variable rule of law (β=-1.33, P<.01) is added. The model indicates that there is a significant effect with regard to the direct relationship between rule of law and syndication behaviour. The way to interpret the result is that the stronger, as in higher quality, the regulatory environment is, the lower the chances are of syndication behaviour with only a local partner. In model 5 (X2=89, P<.01), the full model,
rule of law (β=-1.22, P<.01) still has a significant relationship with regard to syndication
5.4 Moderation
In table 3, model 3 (X2=87, P<.01) the moderator experience is added. However, in the regression model, the variable does not seem to have a significant effect on the relationship between rule of law and syndication behaviour. Yet, it is still necessary to test the moderation effect. To test this effect, I have created the moderator experience (see 4.3.3. moderating
variables). With the use of Hayes’s (2016) Process macro for SPSS, I am able to test the
moderation. The macro recognises the binary character of the dependent variable and automatically adjusts the type of regression to this variable. I have also added the control variables to the model; however, these are not shown in table 4.
Table 4: Moderation - Experience
The model summary shows that the model is significant (X2=95, P<.01). The next step is to test the possible moderation of experience. In table 3, model 3, we saw that the moderator experience is not significant. Table 4 supports this view. Although the moderator is significant (β=-.00, P<.01), no significant interaction effect can be found in table 4 (P=.64). Hypothesis 2 expected that experience would have a moderating effect on the relationship between the regulatory environment and syndication behaviour. More specifically, the more experienced a CVC firm was, the less attractive a syndicate with a local partner would be. However, evidence indicates that there is no reason to believe that moderation takes place with regard to experience. Based on this result, hypothesis 2 is not supported.
In table 3, model 4 (X2=84, P<.01), the moderator experienced non-local CVC firm is
added. Just as the previous moderator, this variable does not show any significance in table 3, model 4. However, I still want to see whether there is a moderation effect. To test this, I have created a moderator variable (see 4.3.3. moderating variables). With this variable, I can test the possible interaction. Table 5 shows the results of this test. The control variables are not shown in this table either, but they are included in the statistical model.
Variables β S.E Z P Constant 2.90 .24 12.05 .000 Experience -.00 .00 -2.96 .003 Rule of law -1.19 .45 -2.64 .008 Interaction -.00 .00 -.46 .644
Table 5: Moderation – Non-local
The table shows that an interaction is taking place (β=.0004, P<.01). This indicates that for every unit increase in rule of law, the difference in syndication behaviour between
local and experienced non-local CVC firm increases by .0004 units. Furthermore, because the
interaction is significant, we can probe it (see appendix 2). However, this result shows that the interaction is only significant for the value of 0. This indicates that an experienced non-local CVC firms does not affect syndication behaviour.
The assumption was that the likelihood of syndication with only a local partner would be weakened when other experienced non-local firms were potential partners with which to syndicate. In table 3, model 4, however, we saw that non-local CVC firms has no significant effect on syndication behaviour (P=.88). Even though there is an interaction, we still need to reject the hypothesis because the interaction is only significant for the outcome of precisely 0, which resembles local CVC firms. Based on the results of the regression and table 5, hypothesis 3 is therefore not supported.
6. Discussion
The above analysis led to interesting information. The following section will discuss the results in a more elaborate way.
6.1 Rule of Law
The main thought of this study was to extend the current literature with regard to CVC syndication behaviour. I tried to extend this literature by putting more emphasis on the possible influence of the regulatory environment on this behaviour. Beforehand, it was expected that the relationship between rule of law and syndication behaviour with a local partner would be negative. This study provides support to this prediction. Results indicate that, the stronger the regulatory environment, the less there is the need to syndicate with a local partner and vice versa. Dai and Nahata (2016) indicate that investing in a country with a low regulatory quality increases the chance of foreign discrimination.
Variables β S.E Z P
Constant 2.98 .25 12.06 .000
Non-local -.00 .00 -6.82 .000
Rule of law -1.47 .52 -2.82 .005
In addition to foreign discrimination, risk sharing can also be seen as a reason why we see this behaviour of CVC firms. They are less known with the regulatory environment. This will, most likely, make them more vulnerable to unexpected events. Especially when the regulatory environment can be regarded as weak, because then the interpretation of the body of laws is less clear. However, the CVC firm can reduce this vulnerability by having a local partner that is aware of the ins-and-outs with regard to the regulatory environment (Lockett & Wright, 2001).
6.2 Experience
It was expected that when a CVC firm had previous investment experience, this would lower the likelihood of it syndicating with a local partner. The reasoning behind this was the thought that familiarity with the regulatory environment would reduce the uncertainty and difficulties faced in the host country (Schertler & Tykvová, 2011).
I tested whether having experience moderates the relationship between rule of law and
syndication behaviour. The results of this research indicate that there is no interaction
(P=.64). Hopp (2010) found that, more experience is usually associated with more syndication because this creates a greater network of possibilities for the CVC firm. But looking specifically at the syndication behaviour, there is no statistical support to believe that this is affected by previous experience.
A possible reason for this is that, experience is rather seen as a control than a selection criterion with regard to syndication behaviour. For example, the expertise of an experienced firm feels more secure than a firm that has relatively little investment experience (Lerner, 1994). But, if there is the need to overcome difficulties with the regulatory environment, this study shows that experience does not seem to moderate the relationship between the regulatory environment and syndication behaviour.
6.3 Non-local CVC firms
It was predicted that the presence of experienced non-local CVC firms would weaken the likelihood of syndication with only a local partner. The reasoning was that a non-local CVC firm could help overcome difficulties in the host country due to its previous experience. However, the results suggest that this is not the case. Although interaction was found, (see table 5), further probing showed that this only counts for 0 experience, which indicates a local instead of a non-local CVC firm.
differences: although the non-local CVC firm may have experience, the differences might still be too difficult to overcome for the new entrant, even with this partner. The experience of the non-local may not be enough, for instance, to by-pass the foreign policy of the host country. This may induce the CVC firm to rely on local partners (Meuleman & Wright, 2011).
Second, there could be some difficulties with regard to the equity position. Most CVC firms that invest across borders want to have a lead equity position when they syndicate. Working with another experienced CVC firm could make it more difficult to be aligned regarding which firm has the lead position in the syndicate, as they might both want the same equity position. Sometimes this is resolved by having more arrangements together, wherein the CVC firms swap positions from lead to non-lead and vice versa (Wright & Lockett, 2003).
7. Conclusion
At the beginning of this thesis, I asked the following question: How does the host country
regulatory environment influence CVC firms’ syndication behaviour? Having investigated the
literature and set up and tested my hypotheses, I can now answer this question.
The results suggest that the regulatory environment indeed influences syndication behaviour. A contrasting relationship exists between the regulatory quality of a country and the chosen syndication form. By examining the subject in more depth, it appears that previous investment experience or the presence of experienced non-local CVC firms does not affect this main behaviour.
Academic contribution
This research extends the current literature with regard to CVC firms’ syndication behaviour. As described at the beginning of this study, there was much room for improvement concerning this topic. For instance, Dai and Nahata (2016) have paid little attention to the regulatory environment with cross-border syndication. Furthermore, Lerner (1994) investigated the composition of syndication without taking into account the regulatory environment. Many studies, just as the present one, have one thing in common: they perceive general syndication as a means to overcome difficulties or risks in the host country (Lockett & Wright, 2001; Tykvová & Schertler, 2011).
The main contribution of the present research is that it is shows that CVC firms that participate in cross-border syndication consider the influence of the regulatory environment in doing so. Overall, the results show that the stronger the regulatory quality is, the less need there is to add a local partner to the syndication deal and vice versa.
