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Degree: BSc Business Studies 

Cass Business School 


Title: How can firm characteristics affect investments volatility in startups ? 

Name:  Hamza EL annabi 


Supervisor's name:  Simone  

Submission date: 11th April 2018 



"I certify that I have complied with the guidelines on plagiarism 

outlined in the Course Handbook in the production of this dissertation and 

that it is my own, unaided work". 





 Table of content

 Table of content

Introduction  3

 Research questions   3

1.Literature review   4

1.1 Startups   4

1.2 Startup characteristics   4

2. funding  8

 2.1 Venture capital  investors and alternatives 

2.2 Stages of funding   9

   3.investment  11

  3.1 Contextual determinants of funding   11

3.2 Firm determinants of funding   12

3.3 Conceptual model   18

4 Empirical research   18

4.1 Methodology   19

4.2 Sample creation   19

4.3 Regression analyses   21

4.3.1 Binary logistic regression   21

4.3.2 Linear logistic regression   23

5. Conclusion   29

5.1 Research outcomes   29

   6 reference   32   


Startups have definitely changed the world we live in. Starting from the devices we use daily and the services that made our life easier like ( phones, UBER and airbnb), looking at these big startups nowadays make it hard to believe that few years back it was just an idea with no planning nor organisation . Every year 100 million startup is created which accounts for 3 startups per second and 80% to 90% of startups fail in the following few years. this reflects how complex is to build and manage a company.the most challenging task for creating a new business is raising money from investors to develop the idea and grow. investors are usually looking for companies that will become profitable in the future and increase in value. 

To be able to understand the volatility of investments from a company  to another first we are required to understand the insights of a company as well as the dynamics of investments. 

There are many types of startups and investments, some startups are able to significantly raise more money than others. On the other hand investors are willing to invest in a particular types of startups that match their criteria. 


 Research questions  

In order to face every aspect of this dilemma we are willing to answer the following questions in this research  

What type of startups generates more investments? 

What are startups? 

What are startups and how they operate and what are the different types of startups  

What are the different  types of investments available? 

Where we are going to talk about the different types of investments and the funding rounds and what each round denote. 

- What it is the most common investment generated by startups in ?  

From where most investments are generated  

- how can investors decide whether to invest in a company or not?  

-how can investors determine the amount that should be invested in a company?  

1.Literature review  

1.1 Startups  

This paragraph explores literature on startups. The aim is to clarify the phenomenon and its selected features. The first paragraph covers a broad list of features of startups, while the second paragraph focusses solely on internationalization.  


1.2 Startup characteristics  

There is a huge number of articles that have covered the topic of startups, this topic was discussed under numerous point of views and different names. An example of the differences between interpretations is the choice to use the term “start-up” or ”startup” (Collins, 2014). The literature of this topic started from the late eighties (Stuart & Abetti, 1987).As Steve blank and Eric Ries stated in “startup  preachers” startups are characterised by having a lifespan, huge relationship with technology and also posses innovative business models. The aim for startups is to achieve growth in the future and expand to the international market. However, startups face a big risk of uncertainty. 




In the past the term “startup” was only used to address new companies (Cooper, 1971; Audretsch & Acs, 1994; Davidsson & Henrekson, 2002), but now it is more associated with companies of special kind. Even though the interpretations have changed the lifespan of a company still define startups. As for some it only refers to companies with no more than 2 years of life (Cassar, 2004; Koski & Pajarinen, 2012).but for Koski and Pajarinen (2012) a company lifespan does not exceed five years (Koski & Pajarinen, 2012). Other studies claim that startups age should not exceed ten years since foundation (Hellmann & Puri, 2002; Van Dijk et al, 2015; GSA, 2015).  



On the other hand Marmer et al (2012) suggest that startups go through a certain lifecycle during its existence. They claim that startups lifecycle is composed of four major stages that the company go through and stops being a company afterward. The four stages of the startup lifecycle are based on Blank work “the Four stages to epiphany” Blank (2011) which also describes some acts that could be useful for startups that are willing to become successful in the future. In addition to that the writer evoke the idea that there are four types of startups and each type has different lifespan (Marmer et al, 2012b). 





There is a huge relationship between startups and ITC, there are other terms used to describe this relationship such as “internet startups” (Zook, 2002; Chang, 2004; Spiegel et al, 2015), high-technology startups (Manigart & Struyf, 1997; Deeds, 2001; Bruton & Rubanik, 2002) or software startups (Mann & Sager, 2007; Bosch et al, 2013). 


The definition of Marmer et al (2012b: 10) of startups is inspired from Ries (2011) and Blank (2011) work as they see startups as designed organisations aiming to expend into larger companies. Another definition that derived from Ries (2011) and Blank (2011) by Lalic et al (2012) is that the ability for a company to scale to a large company depends on the possession of technology based service or product that can satisfy consumers needs worldwide. 


Globalisation had a huge impact on consumers as as their preferences became alike (Knight & Cavusgil, 2004) and this was in favour for technology-based products and services as it gave startups a larger potential market to operate in. However, the number of competition also increased worldwide (Knight & Cavusgil, 2004; Tanev, 2012), which required startups to be innovative in order to differentiate from other competitors. 


Innovative business models  



innovation is perceived as implementing new concepts in business. Startups tend to implement leading technologies, products and services (Tanev, 2012; GSA, 2015).others claim that startups also use innovative business models in order to differentiate themselves (Freeman & Engel, 2007; Van Dijk et al, 2015). Marmer et al (2012b) divided startups to four different types this classification is based on the degree to which startups rely on sales or marketing as a main source for revenue. 

The first two types, social transformer and automator they operate under users continuity which means the focus of these two types is mainly marketing. Their revenue come from data monetisation in many ways such as advertising like Instagram and Google.for the remaining types, the Integrator and the Challenger, they focus on sales. The integrator offers subscription services or product meanwhile the challenger rely on large transactions that takes place in complex markets Marmer et al, 2012b).  




Marmer et al (2012b) believe that the classification of startups of whether they target businesses or individuals is not a valid option anymore. in addition to that the majority of startups claim to be more of a business to business according the analysis ran by the European Startup Monitor (GSA, 2015) . Moreover the business to business startups tend to be more successful and have more revenue than other startups Van Dijk et al (2015). 

Its complex to breakdown and identify the components of an innovative business model as its not restricted in methods of revenue creation or the targeted groups (Morris et al, 2005; Osterwalder & Pigneur, 2009).on the other hand Morris et al (2005) argue that rapid growth is the most interesting feature in a business model of a company as it will be discussed in this paragraph .the innovation in startups business models arise from implementing existing concepts in a unique and creative way and this is exactly how Schumpeter defines innovation (Schumpeter, 2000). 


Ries described startups as organisations that operate under high uncertainty (Ries, 2011: 24). Uncertainty had been brought to attention in the liability of adolescence concept by (Bruderl & Schussler, 1990) where they argue that company mortality depends on how long the firm have been operating meaning that firms that have been operating for a short period of time face greater risk of failure. 

Garnsey (1998) expressed his thoughts on the early years of a firm by stating in his growth model that the firm always start with a phase called prospecting phase (Garnsey, 1998) where the most important thing for the firm is to acquire the necessary knowledge about the market where it is competing in order to build an effective business plan. The following phase named resource mobilisation which represents the testing phase for the firm where decisions are made based on business plans (Rea, 1985). The fact that a firm is validated by the market is an important factor for the development and growth of the company as at the start the company is unsure about the future position of the firm or about the growth trajectory(Garnsey, 1998). 


Authors Blank and Ries indicate the challenging test for startups to acquire customers.the Marmer stages (figure1) give a better understanding for the authors ideas.there is a resemblance between the discovery stage and the early prospecting phase in the growth stage model of Garnsey (1998).according to Blank 2011 the company need to design a problem-solution fit. The main purpose for the product or service offered should be to solve a problem for consumers world-wide (Lalic et al, 2013). When the company succeed to solve consumers problem the solution could be implemented in a small business as a prototype in order to be tested in the validation phase (Marmer et al, 2012b). Blank and Ries claim that it is hard for a company to deviate from the initial path after it has invested time effort and money in a different direction. Thus the firm need to control its size in the early stages and when the product/service is validated by the market and the level of uncertainty becomes low the company should focus in expanding the business Blank 2011. 

Figure 1: Marmer stages by the average worked months and average raised funding (Marmer et al, 2012b).

 Growth design  

In order to understand the rapid growth of a company we look at the growth stage model presented by Garnsey (figure 2; 1998).Garnsey illustrate that startups experience a turnover in the third stage where the firms start making profit. Most of the companies in this stage aim to stabilise as shown in the horizontal growth trajectory, startups need to achieve a continued growth trajectory as shown in figure 2 (Garnsey, 1998) by shifting their product range or extending it. But in other to achieve this a big amount of funding Is required. Moreover Garnsey (1998) interpret the cases where startups reached the third stage in growth model quickly. These companies proved to investors that they are worth the funding and generated the required capital for expansion (Garnsey, 1998). 

  Figure 2: The growth stages model of Garnsey (1998).  


The scaling stage which is the last stage in Marmer growth model where startups aim to reach the final form of the company by scaling the business (Marmer et al, 2012b).Many studies argue that venture capital has an important impact on the company's growth (Davila, 2003; Puri & Zarutskie, 2012; Rosenbusch, 2013). On the other hand Davila (2003) and Garnsey (1998) claim that the lack of funding can jeopardise the growth of the company .capital injection can help the company in different ways such as employment growth and increase sales (Helmann & Puri, 2000; Puri & Zarutskie, 2012). A single round of funding from different investors can enhance international growth Smolarski and Kut (2009).also Tanev (2012) claim that firms are forced the scaling of technology to expand into international markets. 




2. funding 

There are many funding options available for startups. Angel investors and venture capital firms can help startups to start operating, in exchange of equity in the company or seed money. angel investors and venture capital firms provide capital for a range of startups that construct a portfolio for the investor expecting to make profits from the startups that will become profitable in the future. However, lot of startups tend to be founded by “bootstraping” meaning that the founders collect loans from family and friends plus savings in order to fund their company. There is also the crowdfunding where startups get funding from a large number of people by using internet to market their idea. 


 2.1 Venture capital  investors and alternatives 

Venture capital investments are different from bank loans because the money is invested to the other party in exchange of private equity of the startup. Private equity represent a share from the company In order to have a return on investment in the future (Wright & Robbie, 1990; Gompers & Lerner, 2001).On the other hand bank loans require the receiving company to have a collateral. Venture capital  firms are composed of professional investors that work full time to invest their funds.they aim for investment that generate huge profit for the firm and in order to achieve that they invest in startups that are expected to grow rapidly and change the market. Asymmetry of information can be an inconvenience for Venture capital  firms because they need to value the company given that the information provided is limited (Wright & Robbie, 1990). In addition in order for a Venture capital  firm to determine the value of an investment or to weight the companies potential for constructing a portfolio, they need to be fully aware of the market development and the last technology(Hellman & Puri, 2000). 


After investing, Venture capital  firms get involved in the firms in different positions (Jeng & Wells, 2000). The Venture capital  firms are known to be more experienced and when they invest in a company they also try to help the company to be more successful by managing different department of the company and hiring the right people for the job(Kaplan & Strömberg, 2000; Hellman & Puri, 2002). Moreover, Venture capital  firms help fast growing companies to secure a subsequent funding (Dean & Giglierano, 1990). Finally, Venture capital  firms can also influence the company's decision of going public. 


Alternative investors  


Authors like jenny and wells (2000:247) argue that Venture capital  firms are responsible for the company success because they posses the experience to manage a company and provide the involvement needed by the startup which makes other investors like banks and insurance companies less vulnerable to be involved in startups.investment banks happen to invest in startups indirectly by using a subsidiary (Hellman & Puri, 2000). It is very rare when an investment bank get involved in startup management in order to achieve an IPO.big companies also can invest in startups trough Venture capital  firms. There are other funding sources like self-funding where the founder ask for loans from family and friends or angel investors who represent wealthy individuals that invest their own money in exchange for a share of the company (Rosenbusch et al, 2013), angel investor rely on their entourage to invest and they tend to invest in companies as a group of individuals and they tend to be entrepreneurs that have managing positions (Hellman & Puri, 2000; Rosenbusch et al, 2013). Usually companies in the first development stages and less profit driven are targeted by investors. Another type of investors are private equity firms and leverage buyout firms (Rosenbusch et al, 2013), they usually ask for private equity as insurance which means they take lower risk than venture capitalists and they invest in later stages of the startup. However, they are less involved than Venture capital  in the companies they invest in.The vast majority of the writing on the previously mentioned funding types is from the earliest starting point of the 21st century, as those sorts have not altogether changed after some time. However another method for generating capital for startups has risen as of late. Crowdfunding as explained by Schweinbacher and Larralde (2010: 3) is a way of raising capital from the internet either by donations or exchange of equity for money . However there are many regulations that hamper the crowdfunding(Mollick, 2014). Even though it can help companies to find a good substitute to generate funding (Schweinbacher & Larralde, 2010; Ley & Weaven, 2011).

 Parallel to the development stages are the investments stages. They can help to better understand the types of funding startups attract throughout their existence and will thus be treated in the following subparagraph.  

2.2 Stages of funding  

Other than development stages there are also funding stages that happen simultaneously with the startup development (Cassar, 2004; Ley & Weaven, 2011). Funding stages are classified differently by authors (see figure 5). In the following  paragraph three stage models are going to be discussed and proved to be same. Startups funding was recognised to be important in the nineties by Dean and Giglierano (1990). As the markets of startups are very volatile, receiving funding to develop a product is very helpful for the company.

The authors drew a stage model in order to demonstrate how Venture capital  firms help the companies in their portfolio to receive funding. To be sure that firms stay in operation and grow more (Dean & Giglierano, 1990). Another phenomenon called syndication by Venture capital  firms. Venture capital  firms tend to increase investment in tandem to lower the risk, but also to guarantee more reliable decisions in investment (Sorenson & Stuart, 2001). Back to the sequence stage, Dean and Giglierano (1990) determine five rounds. The first one is the ‘founders round', according to the first stage of Garnsey (1998) founders finance the beginning operations of their company. This round is not very attractive for Venture capital  firms, as big uncertainties are facing the firms concerned. The sample of Dean and Giglierano (1990) with Silicon Valley Venture Capitalistes demonstrate that Venture capital  firms are interested in the seed round and the ‘second stage'. In these stages, the firm become more reliable for investment and it can enter the market and axpand. In the penultimate round, the aim for investments is to make the company go public.  

Figure 5: Stages of funding classified by different authors.  

Shachmurove (2001) illustrate different rounds of funding. He emphasise on the main reason for funding for the firm (see figure 5). He also define three types of early stage funding. First one is "seed funding”, the first step of validation in the firms trajectory . The company ca. Use a program to accelerate the seed. Accelerators manage programmes where a group of firms is chosen, the startups are funded with (equity-based) capital and expertise, to finally push the firm to the following  phase of development and funding (Cohen & Hochberg, 2014). A similar phenomenon is an incubator, which provides working space and the occasional mentoring. However, incubators generally do not work in strict programmes (Cohen & Hochberg, 2014). The funding that follows seed is ‘start-up funding', used to launch a product on the market. ‘First stage funding' is utilized to ramp up the sales of the product (Shachmurove, 2001). Subsequent stages are for expansion, going public and acquisition of other companies. The framework is useful because it distinguishes particular types of funding and at the same time provides useful overarching categories.  

Gabrielsson et al (2004) also use three overarching categories, which are in line with development stages of a rapidly internationalizing company. The company progresses from the establishment phase to the international and global phase. Figure 5 also shows that authors use the same terms for different phenomena, which leads to confusion. Gabrielsson et al (2004) for example talk about start- up capital when addressing founders' capital, angels and seed money, while Shachmurove (2001) has a different, narrow definition for start-up funding. The framework of Gabrielsson et al (2004) implies that companies utilize international investors to enter international markets and the same with global investors and markets. Their study however shows that the latter is rare, which comes down to the geography of venture capital (Stuart & Sorenson, 2001; Gabrielsson et al, 2004). The following  paragraph discusses the influence of geography and other contextual factors  


  3.1 Contextual determinants of funding  


The supply of venture capital is unevenly distributed across regions (Stam, 2009). Contextual characteristics determine the supply of venture capital within a region, specifically government policy and regulations and the initial public offering (IPO) market. In addition, funding stays within certain geographical boundaries.  

The role of the government is two-sided. Governments are responsible for regulations which can hamper entrepreneurial activities (Davidsson & Henrekson, 2002). On the other hand they can implement policies which stimulate entrepreneurial and financial activities (Jeng & Wells, 2000). Davidsson and Henrekson (2002) illustrate that negligence of Swedish policy-makers led to a declining rate of starting companies. Together with limited employment contribution of the fastest growing cohort of firms. Jeng and Wells (2000) draw a distinction between determinants of early stage and later stage investment activity. They find that labour market regulations negatively affect early stage investments. Initial public offerings mainly effect later stage investments (Jeng & Wells, 2000). Late stage investors often aim for the invested-in company to go public, when there is no (stock) market demand these investments get discouraged (Gompers & Lerner, 2001). IPOs initiate upward trends in cycles of investment, during these periods venture backed ‘former startups' reach higher valuations when going public (Jeng & Wells, 2000; Nanda & Rhodes-Kropf, 2013).  

One could argue that with the modern day communication methods and ease of transportation companies can tap into worldwide financial resources. However, venture capitalists also monitor and stay involved in the young companies in which they invest. This requires face-to-face contact between both parties, which cannot be entirely substituted by digital (tele)communications (Stam, 2009). “Inherent boundaries around the flow of timely, reliable, and high-quality information produce localised patterns of exchange” (Stuart & Sorenson, 2001: 1584). If there is no bridge between these bounded networks young companies will not have access to venture capitalists and vice versa. Jeng and Wells (2000) simply state that the cost and effort involved with monitoring and even selling of distant companies discourages venture capitalists.  

Stuart and Sorenson (2001) studied the effects of distance on an investment decision of a Venture capital  firm. The authors found that the likelihood of a Venture capital  firm to invest in a company decreases when the distance between them increases. Investments are however more likely to occur when the receiver is a later stage company, rather than one in seed or startup stage. In addition, venture capitalists that are more experienced are more inclined to make a distant investment (Stuart & Sorenson, 2001). A venture capitalist is also more likely to invest in a distant company when another Venture capital  investor in their network (syndicate) has already invested in it. The effects of syndication are even that a Venture capital  firm would be more likely to invest in a distant company when it is close to a syndicate partner (Stuart & Sorenson, 2001). This suggests that accessing networks of investors is beneficial for startups. The following  paragraph will focus on factors at the firm level that influence attracting funding.  

3.2 Firm determinants of funding  

In this study, the goal is to find which startups manage to attract (more) funding and why. There is much literature that focusses on Venture capital  investors, most of the information on factors that influence startup funding also originate from such studies (Hellmann & Puri, 2000; Kaplan & Strömberg, 2000; Cassar, 2004). However, there have been studies that illustrate different factors per stage (Rea, 1985; Haar et al, 1998) and more recent studies that illustrate differences between investors (Madill et al, 2005; Nofsinger & Wang, 2011). This paragraph will treat several main factors; market, product, business model, management and proven record. During the examination of the factors, differences according to stage and investor are mentioned.  


A company generally has an uncertain future, which is a risk for investors. However, the investor can assess the startup according to the market they (aim to) operate in. An often reported requirement of a Venture capital  investor is that the market of the startup allows for rapid growth (Rea, 1985; Kaplan & Strömberg, 2000; Vinig & De Haan, 2003). The investors require the growth of the firm to get a better return on investment. Investors are also, but less explicitly, attracted to startups that potentially create new markets or change existing ones (Kaplan & Strömberg, 2000; Vinig & De Haan, 2003). The market opportunities influence all types of investments. However, they are more determining in early stage investments because startups not yet have a proven record in that stage. Vinig and De Haan (2003) illustrate that investors in the Netherlands illustrate special interest in startup in markets in which they are familiarized. In other words, investors target companies in specific industries.  

Multiple studies illustrate different chances of attracting funding in different industries. Hellman and Puri (2000) discover that companies in the telecom and medical industry have more chance to attract funding, while this is less likely for companies in the computer industry. Chang (2004) recognized two categories of internet startups; e-commerce companies and internet platforms. The market for e- commerce companies proved to be more mature than the investment market for internet platforms. The study of Puri and Zarutskie (2012) showed that mainly companies in capital intensive industries, like electronics and biotech, are more likely to attract venture capital. Capital is indeed more abundant in the biotech industry; the companies in the sector are mainly targeted for their technology and product (Baum & Silverman, 2004; Haüssler, 2009).  


The product of a company is important for investors, the emphasis however differs per investment stage. In the early stage, the product is still in development, so investors assess it on grounds of its innovativeness, market potential and proprietary character (Kaplan & Strömberg, 2000; Vinig & De Haan, 2003).  

The product of the company should be differentiated and reach wide markets. Both characteristics refer to the nature of startups and the globalized markets in which they operate. Vinig and De Haan (2003) illustrate that Venture capital  investors indeed screen the companies on the basis of the global potential of their product. Other authors emphasize that investors choose companies that employ new technologies and products (Kaplan & Strömbger, 2000; Nofsinger & Wang, 2011). Hellmann and Puri (2000) distinguished ‘innovator startups' that introduced a new or significantly better product and otherwise develop technology that can lead to the aforementioned. The results illustrate that the innovator companies are more likely to receive funding (Hellmann & Puri, 2000).  

Many studies have studies the effect of patents on investments (Mann & Sager, 2007; Häussler, 2009; Feldman, 2014). The findings are divergent, for example investors in the US value patents more than investors in the Netherlands (Vinig & De Haan, 2003). The differences between industries are more apparent. In the biotech industry investors illustrate a lot of interest in patents, while this is much less the case in the software industry (Mann & Sager, 2007). Feldman (2014) in addition shows that patents are more a signal to investors than an actual determinant for investment.  

Business model  

Kaplan and Strömberg (2000) find that Venture capital  investors illustrate special interest in the business models of companies. Kaplan and Sawhney (1999) found that business-to-business startups receive special interest of investors. Kshetri and Dholakia (2002) correspondingly find that in regions with plenty supply of venture capital (see previous paragraph), B2B companies are favoured among investors. Two aspects of the startup business model treated in the previous paragraph were found in the literature on funding as well. Investors showed to value business models that integrate new concepts and ‘lean operations' (Strömberg & Kaplan, 2000). The evidence on the latter is however circumstantial.  

The customer adoption is a more concrete aspect that investors assess. Investors prefer companies that have large costumers, reflected in the studies on B2B startups. In addition, they prefer companies that have recurring group of customers (Strömberg & Kaplan, 2000). It must be noted that investors do not necessarily refrain from B2C startups. Investors do however assess B2C companies on other grounds. Specifically the way it aims to achieve consumer engagement and the ‘proven' popularity among their target group.  


Authors have long studied the role of entrepreneurs in receiving funding (Rea, 1985; Haar et al, 1989; Cassar, 2004; Gartner et al, 2012). Although all studies agree that the entrepreneurs have a role, the empirics are inconclusive in determining what exactly makes the difference.  

Nofsinger and Wang (2011) find that the experience of the entrepreneurs matters. Gartner et al (2012) illustrate a positive influence of high education on funding. Cassar (2004) on the other hand does not find any effect of experience and education on funding. Vinig and De Haan (2003) illustrate that the entrepreneurs are in particular assessed on their leadership qualities. However, replacing the higher management of the invested-in company is wide practice (Hellmann & Puri, 2002; Madill et al, 2005). This suggests that the leadership qualities of the entrepreneur are not decisive. An older study of Rea (1985) showed that is the credibility of (the future projections by) the entrepreneur which is critical. Although the studies disagree on different points, they all to an extent argue that the network of the entrepreneur is determining (for example Kaplan & Strömberg, 2000; Madill et al, 2005).  

Proven record  

The essential difference between early stage and later stage investments is that the investors in the later stage have more information on the prospective investment. The most important criterion for venture capitalists in later stages becomes the actual performance of the company up until that time (Dean & Giglierano, 1990; Kaplan & Strömberg, 2000; Vinig & De Haan, 2003). This also comes back to the first three factors, there could be growing demand in the market, the product could have proven itself, or the engagement of the costumers could have showed to work. The most important aspect that will be treated here is successive funding.  

A company can be validated by the market via the demand for its product or service, but it can also be accredited by investors. The prominent study of Madill et al (2015) found that startups that received investment of an angel are more likely to receive subsequent venture capital. The angel investors leverage their network and expertise to support the business of the startups (Madill et al, 2005). It shows that the involvement is also partly aimed to prepare the startup for follow-up investments. The same applies to accelerators, which programmes often lead into funding rounds (Cohen & Hochberg, 2014). In addition, being part of an accelerator can also been seen as a quality stamp as the startups have been subject to a selection process. Lastly, Venture capital  investments increasingly happen in succession (Dean & Giglierano, 1990; Stuart & Sorenson, 2001; Brander et al, 2002). Firstly, Venture capital  investors try to ensure their return on investment by stimulating follow-up investments (Dean & Giglierano, 1990). In addition, the syndication of Venture capital  investors has become a wide spread phenomenon (Lockett & Wright, 2001; Brander et al, 2002). This phenomenon not only led to multiple investors involved in funding rounds, but also to more successive funding. Looking at geography, syndication has even made international capital more accessible (Stuart & Sorenson, 2001; Liu & Maula, 2015).  

3.3 Conceptual model  

The following  chapter will feature all the empirical analyses. Basically there are two main analyses. The logistic regression, which determines the factors that influence whether a company receives any funding. The linear regression, which determines the factors that influence the amount of funding startups receive (extra factors are included in the analysis, see figure 6). It will be analysed whether having been internationalised has an effect on funding. However, it can also be argued that funding makes it possible to internationalize. The relationship is therefore tested two-ways; an extra analysis is focused on finding connections between funding, investors and having an office abroad (see figure 6). The regression models include a variable on the city of the startups. The location alone does not tell much, for that reason additional analyses are made. Firstly, a preliminary analysis of the differences between the cities on the basis of external resources and sample data. Secondly, the regression equations will also be executed over samples split by city.  

4 Empirical research  

This chapter features the empirical analyses that will be used to answer the research questions formulated in the introduction. The chapter starts out with discussing the methodological foundations of the analyses. The Amsterdam and Stockholm context will then be covered more extensively. In the following, the sample of 425 startups and 285 investors will be introduced. How the samples were constructed and subsequently what the samples tell about the cities and their startups. More in-depth analyses will follow that aim to find empirically founded relationships.  

4.1 Methodology  

The study applies a quantitative research strategy because this best suits the aim of the study. The aim is to explain which startups receive funding and which receive more. Quantitative research allows for finding causality and gives opportunity for generalization beyond the studied samples (Bryman, 2012b). The results are representative for the studied environments and possibly also for environments with the same characteristics. The studied environments are the cities Amsterdam and Stockholm, the research design is thus a comparative case study design (Bryman, 2012a). Stockholm was chosen as an exemplifying case (Bryman, 2012a). The city is comparable in size to Amsterdam and in contrast suggests to have plenty supply of startup funding. The units of analysis are startups, based on data that has been subtracted in one point in time. This means the study employs a cross-sectional research design as well, because the data will be used to find patterns of association with different variables (Bryman, 2012a). In this study three different methods of analysis will be used; binary logistic regressions, linear logistic regressions and bivariate analysis.  

Regression analyses use mathematical equations that include different variables to forcast a certain outcome (Field, 2013). The outcome is the value of the dependent variable, in this study ‘having funding' (yes/no) or the amount of funding (in million euro). In order to establish for example which factors affect the height of funding; all context, firm and investor variables (see figure 6) are included in one model. The variable that represents the amount of funding is placed on the opposite side of the equation. Statistical analysis software (for example SPSS) can then be used to calculate the interaction (Field, 2013). The results illustrate to what extent the factors together forcast the height of funding a company receives (measured by the R-square value; Field, 2013). Moreover it shows how variations in separate variables affect the dependent variable.  

4.2 Sample creation  

For the analyses in this study, a sample of 425 startups and additionally 285 investors is used. In the following, the origin and realization of the sample will be described to account for objectivity and replicability (Bryman, 2012b).  

The sample was constructed out of two databases provided by Dealroom. The organisation monitors over half a million technology companies and five thousand investors in Europe and beyond with algorithms and natural language processing. The data is complemented by a community of thousands of industry specialists. Lastly, the data is verified by a rigorous internal manual curation process (Dealroom, 2016a). Despite the latter curation process, the two databases had imperfections, specifically many companies with missing information. The two databases were firstly reduced to the companies that had at least been updated in the last year3, leaving 667 companies in Amsterdam and 166 in Stockholm. Controlling for maximum age in the startup definition, only companies founded between 2011 and 2015 were included (leaving 389 companies in Amsterdam and 122 in Stockholm). These were then subject to an additional refinement. Companies that still had missing information were excluded. Cases that showed anomalies were double checked with external resources to see if the irregular data checked out and if the company was still active4. Lastly, some companies that did not fit the requirements for a company were excluded (for example food producers, co-working spaces and startup service providers). This led to a sample of 327 startups in Amsterdam and 98 startups in in Stockholm.  

  Figure 12: Frequency distribution of the investor sample according to fundie

   6 reference  








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