---
Key connections in high-growth startup ecosystems
Evidence from Israel’s entrepreneurial technology ecosystem
Tel Aviv / Amsterdam, December 2017 Author: Jorik Hofland Student number: 10668071 Date of first draft thesis proposal: 26/01/15 Date of final version thesis: 27/11/2017 MSc. In Business Administration | Entrepreneurship & Innovation track University of Amsterdam | Business School 1st supervisor: Dr. T.G. Vinig| Associate professor entrepreneurship
STATEMENT OF ORIGINALITY _____________________________________________________________________________________________________ This document is written by Jorik Hofland who declares to take full responsibility for the content of this document. I declare that the text and the work presented in this document is original and that no source other than those mentioned in the text and its references have been used in creating it. The faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents. © 2017 Jorik Hofland
TABLE OF CONTENTS _____________________________________________________________________________________________________ TABLE OF CONTENTS………..……….………...……...3 LIST OF TABLES AND FIGURES……..………...……….…...……...5 LIST OF ABBREVIATIONS………..………...…………....………...6 ACKNOWLEDGEMENT….………...…………...………...7 ABSTRACT... ………...8 1 INTRODUCTION …...9 1.1 PROBLEM STATEMENT AND RESEARCH QUESTION ...9 1.2 THE OBJECTIVE ...13 1.3 THE METHODOLOGY ...14 2 LITERATURE REVIEW …...16 2.1 REVIEW OF ANTECEDENT LITERATURE AND CONCEPTS ...16 2.2 ANALYSIS OF ENTREPRENEURIAL ECOSYSTEM RESEARCH…….. ...19 2.3 SYNTHESIZING LITERATURE………... ...23 3 SITUATING THE CASE …...25 3.1 SITUATING THE CASE...25 3.2 ABOUT THE ISRAELI REGION...28 4 DATA AND METHODS …...31 4.1 RESEARCH STRATEGY AND DESIGN……...31 4.2 RESEARCH SAMPLE………...32 4.3 DATA COLLECTION PROCESS………..……...33 4.4 DATA ANALYSIS………...…..………..……...35 4.5 RESEARCH REFLECTION………..……..……...35 5 DATA ANALYSIS AND DISCUSSION …...37 5.1 DATA ANALYSIS……….……...37 5.2 RESEARCH AREA: KEY ACTORS IN HIGH-GROWTH EE’S………....38 5.3 RESEARCH AREA: EFFECT OF EE ELEMENTS ON INTERACTION OF ACTORS ...41 5.4 RESEARCH AREA: IMPACT OF PEER-BASED LEARNING & SUPPORT...…...44 5.5 SYNTHESIZING FINDINGS AND INTERRELATED THEMES………...…...47
6 CONCLUSIONS, LIMITATIONS & FUTURE RESEARCH …...48 6.1 CONCLUSION………..……...48 6.2 LIMITATIONS…..………...…..………..……...50 6.3 FUTURE RESEARCH……...………..……..……...50 7 REFERENCES…… …...52 8 APPENDIX…….… …...56 8.1 INTRODUCTION LETTER TO KEY ACTORS IN TEL AVIV...57 8.2 INTERVIEW PROTOCOL...…..………..……...58 8.3 CODED NAMES AND DESCRIPTION OF HIGH-GROWTH STARTUPS……….59 8.4 INTERVIEW QUESTIONS….……..……..……...60 8.5 KEY CONNECTION ASSESSMENT OF 20 RESPONDENTS…...61
LIST OF TABLES AND FIGURES _____________________________________________________________________________________________________ TABLE 1.1: TOP 5 TECHNOLOGY FAST 500 EMEA RANKING 2014…………...……...……….13 FIGURE 1.2: ISRAELI IPO’S BY MARKET IN 2014………...…...13 TABLE 1.3: MOST SUCCESSFUL ISRAELI M&A DEALS IN 2011 - 2014……..………...…...14 FIGURE 1.4: ISRAEL ACCORDING TO THE GREEN LINE………...…...16 TABLE 2.1: RESEARCH SCOPE AND METHODOLOGY OF EE LITERATURE……….………...19 TABLE 2.2: AN ANALYSIS OF THE CURRENT EE GAPS, FINDINGS & RESEARCH SUGGESTIONS...21 FIGURE 3.1: CONCEPTUAL FRAMEWORK…..…………...28 TABLE 3.2: ENTREPRENEURIAL ECOSYSTEM RANKING 2012...31 TABLE 3.3: ENTREPRENEURIAL ECOSYSTEM RANKING 2015...31 FIGURE 4.1: PARTICIPANT AND METHODOLOGY STATISTICS………34 TABLE 5.1: THEORY-BASED CATEGORIES IN DATA ANALYSIS...38 TABLE 5.2: DATA ANALYSIS OF ENTREPRENEURIAL ACTORS...39 TABLE 5.3: DATA ANALYSIS OF RESOURCE PROVIDERS………...40 TABLE 5.4: DATA ANALYSIS OF CONNECTORS...41 TABLE 5.5: DATA ANALYSIS OF EE ELEMENTS CULTURE AND HUMAN CAPITAL...43 TABLE 5.6: DATA ANALYSIS OF PEER-BASED LEARNING AND SUPPPORT...46
LIST OF ABBREVIATIONS _____________________________________________________________________________________________________ AIM Alternative investment market (sub-market of the London Stock Exchange) EE Entrepreneurial ecosystem EMEA Europe, Middle East and Africa FDI Foreign direct investment HGF High-growth firm IPO Initial public offering M&A Mergers & Acquisitions Nasdaq National Association of Securities Dealers Automated Quotations NYSE New York Stock Exchange ROE Return on equity ROI Return on investment RQ Research question SV Silicon Valley VoIP Voice over Internet Protocol VC Venture capital WEF World Economic Forum
ACKNOWLEDGEMENTS
_____________________________________________________________________________________________________
Through this acknowledgement I intend to thank my supervisor, sparring partners, informants and others who have supported me during the writing process of my thesis.
First of all, I would like to express my appreciation to Dr. Vinig. In general, for the freedom we have been given as students to choose our own research topic, focus and scope. And personally, for coping with my challenging situating in terms finalizing my thesis while building my own company.
Secondly, my gratitude goes out to my Israeli family and particularly to Omer and Merom, without you it would have been much harder to complete the data collection process. Moreover, the opportunity to spend time and investigate a piece of Israel’s prodigious technology environment is one of the most interesting and instructive events I experienced during my study.
Thirdly, I want to thank two of my sparring partners. Karren Watkins from Washington University for discussing the dissimilarities among the entrepreneurial ecosystems of St.Louise and Tel Aviv and reflecting on the potential effects to the research design.
Fourthly, I would like to convey my recognition to all interviewees. Acknowledgements for your time, effort and openness of sharing your experiences and knowledge about key connections, relations and motivations with me. This was critical for the formation of my research. Finally, I deeply value the relationship with my family and friends. More individually, my acknowledgements go to Roos for supporting me throughout the entire process. And to my parents for their patience. Furthermore, I would like to thank the rest of my family and friends for the cognitive support and pleasant distractions. Thank you all, for the time and effort you have allocated to help me, it’s genuinely valued. With grateful regards, Jorik Hofland
ABSTRACT
_____________________________________________________________________________________________________ Scope & research target - a small number of entrepreneurial
ecosystems are accountable for a significant share of the global output of new HGF’s. The need to understand the dynamics around entrepreneurial ecosystems has led to many new approaches. Previous studies mainly approached the functioning of entrepreneurial ecosystem from a static perspective, neglecting motives, connections and processes, necessary to understand and establish sustainable technology hotbeds. Therefore, this paper analyses, integrates and further develops the concept of EE’s by taking a holistic perspective but focusing towards key actors and connections within the high-growth startup ecosystem. Methodology - this qualitative study applies inductive case study as a strategy to answer the research question. The cases are selected via both purposive homogeneous sampling and referral sampling methods. Subsequently, the data collection occurred within a short period of time and can be described as a cross-sectional study. Finally, several data analysis strategies approach phenomena from different angles to identify relationships and deepen the current body of knowledge. Findings, contributions & suggestions - key connections in fast-growing entrepreneurial ecosystems are individuals who simultaneous take an active role as entrepreneurial actor, resource provider and connector. They have a least a transferable level of skills, experience, resources and network and share this proactively with peers in the EE. In many ways this is similar to the description of a dealmaker, but unlike dealmakers, key connections are present in all layers of EE’s and not only limited to the top of the hierarchy.
The findings enhance in-depth knowledge of key connections in EE’s which are relevant for researchers, policymakers and entrepreneurs. There are a number of preconditions that must be marked when reading the conclusions of this study. The sample is delineated to 20 Israeli high-growth startup entrepreneurs with technology intensive products or services. These conditions limit the general transferability. It is therefore important that future studies increase sample size and investigate other ecosystems and industries.
Keywords: High-growth Entrepreneurship, Entrepreneurial ecosystems,
“A SMALL NUMBER OF TECHNOLOGY HOTBEDS ARE RESPONSIBLE FOR A SIGNIFICANT SHARE OF THE GLOBAL OUTPUT OF NEW HIGH-GROWTH VENTURES”.
1 INTRODUCTION
_____________________________________________________________________________________________________ Technological revolutions are disrupting the economic landscape and transforming competition. In the past two decades, the system of developed economies has changed from managed economy towards entrepreneurial economy (Thurik, et. al. 2013). Many scholars see entrepreneurship and technological development as the main growth engines of innovation capacity and economic and social progress (Vinig, 2002; Isenberg, 2010; Vogel, 2013a; WEF, 2013). The influence of entrepreneurial activity and technology is evident when looking at high-growth firm’s (HGF’s) that have been listed on some of the world’s most prominent stock exchanges over the past years (Nasdaq, NYSE & AIM). HGF’s are fast growing ventures that are responsible for a disproportional large stake of total new jobs and their impact in terms of innovation, internationalization and overall economic progress is tremendous (WEF, 2013; Mason & Brown, 2014).
1.1 Problem statement and research question
Remarkable is that a small number of technology hotbeds are accountable for a significant share of the global output of new HGF’s (Startup Genome, 2012; EY, 2014). Accordingly, these hotbeds or entrepreneurial ecosystems (EE’s) capture most of the value creation that is affiliated with rapid enterprise growth. A technology hotbed, such as Silicon Valley (SV), is a possible embodiment of an EE. An EE is a system of separate actors and components orchestrated in such a manner that it progresses entrepreneurial activity and the net revenue of an economy (Stam, 2015). Positive effects related to successful entrepreneurial activity, as the attraction of talent, resources and funding, and the presence of role models and expertise, enhances the local ecosystem’s competitiveness and conditions for entrepreneurial activity (Isenberg, 2010; Feld, 2012). Entrepreneurial activity can exhibit various forms, as corporate entrepreneurs or innovative ventures, but literature on EE’s increasingly aims the attention at new HGF’s (WEF, 2013; Stam, 2014). Vice versa, EE’s have the
potential to supply significant leverage in the progress of startups; therefore, many policymakers have tried to imitate prosperous hotbeds like SV (Isenberg, 2010). Despite the efforts and high-prioritization of policymakers, most attempts failed and did not achieve the intended results due to lack of thorough understanding (De Haan, 2008; Isenberg, 2010; Feld, 2012; Vogel 2013b).
Previous studies have shown that entrepreneurship is principally a local phenomenon (Feld, 2012; WEF 2013; Mason & Brown, 2014; Motoyama et. al, 2014). Understanding EE’s from a local perspective is a difficult due to local dependencies and path-dependent developments (Vinig, 2002). Consequently, scholars are not able to find consensus on how to theoretically examine EE’s (Vogel, 2013b). While the theory is relatively new, the theme is not, classical studies such as cluster formation1 and regional innovation systems2 already investigated the relation between geographic areas and entrepreneurship (Motoyama & Watkins, 2014). However, earlier studies treated the local system of entrepreneurship as a secondary factor and certainly not as a driver of regional development.
The increased need to understand the local dynamics around entrepreneurship has led to many new approaches, but most approaches can’t thoroughly explain local dissimilarities (Motoyama & Watkins, 2014). Initially, multiple papers studied the formation of entrepreneurial hotbeds from policy perspective and assumed a leading role for governments along the entire development process. In addition, most examinations were static and tended to identify, list and frame components of technology hotbeds and often neglected the interconnected nature of the EE elements (Motoyama & Watkins, 2014). According to Stam (2014) the concept suffers from several shortcoming and he concludes that the theory is in absence of causal depth. So, although the correlation between factors and successful entrepreneurial ecosystem has been studied before, multiple researchers report deficiencies in the concept of entrepreneurial ecosystems (Thurik, et. al. 2013; ANDE, 2013; Vogel, 2013; 1 Cluster formation: tendency of similar firms to locate in the same geographical area, but does not mean presence of interdependencies (Malecki, 1997) 2 Regional innovation systems: systemic, goal-oriented activity by regional alliances with the purpose
WEF, 2013; Stam, 2014; Motoyama & Watkins, 2014). Yet, contemporary research provides new insights and directions to overcome prior shortcomings.
The first major pivot in comprehending EE dynamics comes from Feld (2012). He focuses on startup communities, a core part of EE’s, and unlike conventional thoughts he states that entrepreneurs lead the community and other stakeholders have a facilitating role, which he describes as feeders. Additionally, the emergence of the entrepreneurial ecosystem approach unfolds as a second key advancement (WEF, 2013; Mason & Brown, 2014; Stam, 2015). The approach offers an innovative perspective on local clustering of economic activities and is a synthesizes of multiple key perspectives including Isenberg’s (2010), Feld’s (2012) and Napier & Hansen’s (2012). One of the differentiating traits of the entrepreneurial ecosystem approach is its acknowledgement that entrepreneurial activity can flourish in unique forms of supportive environments (Mason & Brown, 2014; Stam, 2015). The findings are in line with the local and path-dependent features earlier mentioned and can assumable explain local EE disparities. Although both perspectives significantly advanced the theory of EE’s, there are still obscurities and discussions.
In terms of research perspective, Thurik, et. al. (2013) affirm that the attention should not be on the policy of entrepreneurship, but should focus on stimulating the holistic perspective (Isenberg, 2010; Vogel, 2013). On the contrary, Motoyama & Watkins (2014) claim that the tendency towards a holistic perspective frequently leads to encompassing all elements, something that does not benefit detailed implications about the functioning of local entrepreneurial ecosystems. Mason & Brow (2014) recognize this and explain that previous studies mainly analyzed entrepreneurial ecosystems from a static perspective, disregarding important determinants and processes critical for understanding entrepreneurial ecosystems. Therefore, their study indicates future research should take a holistic perspective, but aim attention towards key actors and connections within the high-growth startup ecosystem. A connection is an activity among actors as individuals or organizations (Motoyama & Watkins, 2014). Multiple scholars agree with this perspective (Feld, 2012; Vogel, 2013) and also underline the necessity for more detailed research into the ecosystems’
In conclusion, research of EE’s need a holistic but aimed approach, target key actors and generate in-depth knowledge. Therefore, this paper analyzes, integrates and further develops the concept of EE’s by focusing on the startup ecosystem and key connections to achieve high-growth entrepreneurial activity. The following research question (RQ) guides this thesis: What are the key connections in high-growth startup ecosystems?
Table 1.1: Top 5 Technology Fast 500 EMEA Ranking 2014
The abiding progress of the Israeli entrepreneurial ecosystem constructs a good business case to understand the connections and dynamics around fast-growing startups. To elaborate, Israel is one of the most thriving startup ecosystems in the world in terms of talent, technological output and innovation (Startup Genome, 2012). A brief examination of the top 5 fastest growing technology companies in Europe, Middle East and Africa (EMEA) exhibits that 60% of the ventures originates from Israel (figure 1.1) (Deloitte, 2014). Local Israeli entrepreneurs funnel vast amounts of technology and innovation into the global scene and arouse interest from international investors and tech giants (EY, 2014). To illustrate in 2014 18 Israeli ventures were listed in New York and London (figure 1.2) (PWC, 2014). From financial perspective, there are about a hundred liquidation events3 a year (IVC, 2014) and between 2011 - 2014 Israel has generated serious exits (M&A & IPO’s) with a combined value of $33.14 billion (PWC, 2014) (figure 1.3).
3 Liquidation events: An exit-strategy event which allows founders and investors of a company to
Rank Country Company Name % Growth
1 France Weezevent 43202%
2 Israel Taboola 42048%
3 Israel Superfish 37102%
4 Israel Valens 33244%
5 Germany Goodgame Studio / Altigi GmbH 28327%
Nasdaq NYSE AIM
Table 1.3: Most successful Israeli M&A deals in 2011- 2014
To put this in perspective, Israel is a small isolated country with a limited population and a small domestic market, but has raised most venture capital (VC) investments per capita and has the largest startup density per capita in the world (Startup Genome, 2012). Not to mention, in 2014, the number of startups went up, the amount of investments grew, the acquisition time4 shortened and the return on equity (ROE5) improved. Furthermore, VC confidence in the country's’ technology sector is at an all-time high and foreign direct investments (FDI) hit a new record (EY, 2014; KPMG, 2014; No Camel, 2014a). So, the success of the Israeli EE forms an instructive business case to investigate how Israeli actors are able to create such a huge global impact in terms of high-growth startups. 1.2 The objective Before the literature review, it is necessary to discuss the current state of literature to briefly elaborate on the time frame and answerability of the research question. The study project is undertaken and executed by a single postgraduate investigator within a limited time frame. It is therefore unattainable to strive for the development of core knowledge via foundational research, but more realistic is the aim to conduct an exploratory research. Consequently, this research targets to gain more in-depth knowledge by exploring the ambiguous domain of high-growth startup ecosystems and by providing richness of information. The purpose of this thesis is to identify, integrate and further develop the concept of entrepreneurial ecosystems by constructing a business case around the high-growth startup ecosystem (Feld, 2012; Motoyama & Watkins, 2014). In this analysis, specific emphasis is put on the correlation between early high-growth entrepreneurs and key 4 Acquisition time: Time from starting a business to transferring part or all of the ownership stakes Venture name Acquiring company Year Deal size in $
NDS Cisco Systems 2012 $ 5 billion
Waze Google 2013 $ 966 million
Viber Rakuten 2014 $ 900 million
Given Imaging Covidien 2013 $ 860 million
connections. A comprehensive exploration of what happened and how and why certain behavior and connections induced early expansion will generate a rich information portrait, which serves as the basis for answering the research question and a potential valuable in-depth explanation. The expected outcomes of this paper is an all-inclusive exploration on key connections in Israel’s high-growth startup ecosystem.
Deepening the detailed understanding about key connections, interactions in high-growth startup ecosystems and the effect of the ecosystem on those relations contributes to the concept of EE’s and the body of knowledge in the areas of high-growth entrepreneurship, network communities and innovation. Moreover, it benefits both the public and private sector because better comprehending the dynamics, interactions and key actors in high-growth startup ecosystems is essential for both venture- as well as regional success. 1.3 The Methodology This qualitative research uses inductive case study as a strategy to answer the research question. As recommended by the ANDE (2014), multiple data collection methods are implemented in the research design to generate reliable and transferable data that fit the exploratory and descriptive nature of this paper. Two types of data are gathered in this study, primary qualitative data and secondary qualitative data. The primary data are obtained via semi-structured interviews with Israeli high-growth startup entrepreneurs and are supplemented with some additional observations. While secondary qualitative data are retrieved via archival research, data are therefore derived from industry reports, Internet sources, institutional information, videos and newspapers.
The specific characteristics of the target population, the limited time-span of the research and geographic distance between the researcher and the target population (most of the time) mean that the cases are best selected via both purposive homogeneous sampling and referral sampling methods. Purposive homogeneous sampling is a non-probability sampling technique applied to focus on the specific needs to the cases (Laerd, 2012). And referral sampling is also a non-probability
sampling technique but is used when traits of participants are rare and consequently cases are hard to find/approach (Dudoviskiy, 2011). Data collections takes place within a short period of time and can be described as a cross-sectional study. This implies that each participant is once subject of study at the same time as the rest of the case partakers (Laerd, 2012). The data entail occurrences and knowledge experienced by Israeli high-growth entrepreneurs over a longer period of time, especially in the case of (older) serial entrepreneurs.
More specifically, the geographic unit of analysis is defined as the entrepreneurial ecosystem within the boundaries of the state of Israel according to the green line (Figure 3) (Newman, 1995). This study excludes Israeli occupied territories as West Bank, Gaza Strip, Golan Heights and Sinai Peninsula since no significant EE is present, however it includes East Jerusalem because the city as a whole is emerging as a high-tech hotbed (Cutler, 2015).
This paper proceeds according to the following structure. Chapter 2 evaluates, synthesizes and critically discusses key articles. Chapter 3 introduces the research approach by situating the case. Chapter 4 describes the methodological framework and data collection. Chapter 5 observes key-interrelated themes, discusses the significance of the findings and answers the sub-questions. Chapter 6 answers the main question and contributions and proposes recommendations for future studies. Finally, chapter 7 and 8 respectively contain the references and appendix. Figure 1.4: Israel according to the Green line
2 LITERATURE REVIEW
_____________________________________________________________________________________________________
This chapter will examine significant issues surrounding the research proposition by providing reflection on findings, discussion about contrasting literature and clarification for potential conclusions. The intention of this section is to synthesize relevant entrepreneurial ecosystem literature and highlight research gaps to vindicate the execution of this thesis.
2.1 Review of antecedent literature and concepts
The concept of entrepreneurial ecosystems evolved from entrepreneurship. According to Schumpeter’s thought from 1934, entrepreneurs are innovators who disrupt the status quo by introducing new combinations. Isenberg (2014b) stresses that the word “disrupt” receives a lot of attention, since people associate it with entrepreneurial success stories. The scholar underlines successful entrepreneurial activity manifests different forms and in essence is about creating value, however it can cause temporary disruption. Ireland, Hitt & Sirmon (2003) define entrepreneurial activity as a context dependent social process in which actors combine resources to exploit opportunities and generate wealth. In this study we use Stam’s (2015) entrepreneurial ecosystem approach to describe the layers of the ecosystem. The ecosystem consists of several building blocks that make up the entrepreneurial ecosystem elements. Within these elements, a distinction is made between the framework conditions and systemic conditions (Stam, 2015). Framework conditions include formal institutions, culture, physical infrastructure and market demand. Systemic conditions comprise of the elements, network, leadership, finance, talent, knowledge and support services (Stam, 2015). All these elements together affect entrepreneurial activity and -output. Subsequently, output results in aggregated value for the entire ecosystem (Stam, 2015). Multiple researchers claim this aggregated value is re-invested back into the ecosystem in the form of knowledge, resources, and money and thereby improving systemic conditions (Napier & Hansen, 2011; Feld, 2012). Importantly to mention is that the composition
of framework- and systemic conditions can vary in local ecosystems and thus can have a different impact on stimulating entrepreneurial activity (Isenberg, 2010).
Today there is still much discussion about the definition of entrepreneurial ecosystems. Stam (2014) states “an entrepreneurial ecosystem is an independent set of actors that is governed in such a way that is enables entrepreneurial action”. Isenberg (2014a) describes an ecosystem as “a dynamic, self-regulating network of many different actors”. Both definitions direct attention towards the inclusion of elements, actors and output, however it is hard to agree upon terminology while in-depth insights are still relatively limit (Motoyama & Watkins, 2014).
Feld (2012) is the first to speak of startup communities. The researcher emphasizes that not the government is the main facilitator of EE success, but rather the entrepreneurs and other stakeholders in the community. To elaborate, the startup community is the part of the EE in which entrepreneurship occurs between interdependent actors (Stam, 2015; Motoyama & Watkinson, 2014). In relation to entrepreneurial output, EE literature increasingly focuses on high-growth startups and HGF’s (Napier & Hansen, 2011; WEF, 2013; Mason & Brown, 2014). High-growth startups or -firms are initiated by entrepreneurs who pursue high-impact innovation and growth (Stam, 2014). This study demarcates the difference between a high-growth startup and a HGF on the ventures life-cycle stage. Companies younger than 5 years are startups.
Table 2.1: Research scope and methodology of EE literature.
___________________________________________________________________________________ Author(s), Research direction of Methodology
Year, Title the study
___________________________________________________________________________________ Isenberg (2010). “To investigate how governments can Qualitative case study built How to start an ignite venture creation and growth from best practices from all Entrepreneurial to create an ecosystem that sustains over the world.
Revolution. entrepreneurs and really works”.
Napier & Hansen “To examine what motivate and drive “Qualitative and quantitative (2011). Ecosystems successful ecosystems for young growth analysis, quantitative data for young scalable firms. And discuss the possibilities to based on 16 sample regions. firms. quantify and benchmark ecosystems on Qualitative data consisted of both new and existing regional data”. Interviews with key actors” Feld (2012). “To investigate what it takes to create “Qualitative study bases on Startup a startup community in any city, Feld’s +20 years of experience Communities. at any time”. as well as other contributors
of startup communities”.
WEF (2013). “To increase the understanding of “Surveyed over 1000 Entre. Ecosys. around how successful entrepreneurial entrepreneurs from around the globe and Company companies accelerate access to new the globe”.
Growth Dynamics markets and become scalable, high-growth businesses”.
Vogel (2013). The “To propose a new conceptual Exploratory study for the G20 Employment framework describing entrepreneurial Youth forum. Formed around Outlook for Youth. ecosystems to understand its youth employment rates by components and assessment indices”. Thomas Reuters Datastream. Motoyama, et. al. “To deepen our understanding on Recorded Twitter handles (2014). Think Locally, local networking activities and other of 74 people, 56% of the Act Locally. patterns of entrepreneurs”. originally surveyed people. Mason & Brown “To create an approach that helps Systemic literature review (2014). Entre. Ecosy. to develop industry policies for self- which used secondary sources and Growth Oriented sustaining entrepreneurial ecosystems to form policy principles. Entrepreneurship. which increase the number of HGF’s”.
Stam (2014). The To further develop the entrepreneurial Archival research constructed Dutch Entrepreneurial ecosystem approach and provide policy around Dutch entrepreneur- Ecosystem. options for the Dutch government that ship outcomes over the last help boost ambitious entrepreneurship. 20 years.
Motoyama & “To advance the understanding of how “Longitudinal case study Watkins (2014). to establish effective local ecosystems based on observing and Examining the by examining different players in the interviewing 20 Arch Grant Connections within startup ecosystem” recipients”.
2.2 Analysis of entrepreneurial ecosystem research
In recent years there have been lots of developments in the field of EE’s, therefore table 2.1 summarizes the research direction and method of several significant EE studies in order to assess the changes in research direction.
To start, there is a substantial shift in research direction from policy perspective towards entrepreneurial actor approach (Thurik et. al. 2013). Isenberg (2010) and Feld (2012), both renowned researchers with field experience and academic credentials, identify that not the government is the main facilitator of entrepreneurial ecosystems, but rather entrepreneurs and other leading actors. Hence, this results in two new research approaches. There is a transformation from a systemic view towards a more people-oriented perspective (Napier & Hansen, 2011; WEF, 2013). And in relation, there is a change from top-down approach to bottom-up research focus (Motoyama, et. al., 2014). Based on these implications, several researchers adapt methodologies and data collection processes to focus on actors as entrepreneurs and stakeholders to better understand EE’s (Mason & Brown, 2014; Motoyama & Watkins, 2014). Another significant shift in EE literature constitutes the alteration from quantitative to qualitative entrepreneurship. This manifests in an increase in research focusing on HGFs. Napier & Hansen (2011), WEF (2013) as well as Mason & Brown (2014) are all trying to advance in-depth knowledge regarding the concept of EE’s from the perspective of high-growth ventures. Napier & Hansen (2011) focus on the internal motivation of the entrepreneurs and more specifically assess the difference with “normal EE’s”. In addition, the WEF (2013) investigate how fast-growing startups internationalize and scale. Policymakers also adjust their angle in relation with the change towards quality of entrepreneurship. For example, the Netherlands displays a significant increase in the number of entrepreneurs, however it does not result in aggregated value for the Dutch ecosystem. Therefore, Stam (2014) studies how policy can accelerate the quality instead of the quantity of entrepreneurship.
In the next section, a thorough literature review outlines the gaps, findings and future research directions to form the theoretical basis for the identification of the research
AUTHOR(S) (YEAR)
TITLE GAPS FINDINGS SIMILARITIES UNIQUENESS FUTURE RESEARCH
Isenberg (2010) How to start an Entrepreneurial Revolution. Today it is top priority for policy leaders to create thriving entrepreneurial ecosystems (EE’s), however development is often wrongly approached since governments try to imitate conditions of successful ecosystems like Silicon Valley (SV). The entrepreneurial ecosystem consists of multiple components which potentially can boost entrepreneurial activity, innovation and growth. However independently or without balance these elements are unable to sustain a competitive advantage in entrepreneurial ecosystems. Governments should build EE’s around local circumstances. But, there should be close cooperation with the private sector. To elaborate, policy makers have a facilitating role and should manage and optimize bureaucratic, regulatory and legal frameworks and should build in self-liquidation. Isenberg (2010) states that attempts fail since authorities focus on individual EE elements instead of balancing all components around local conditions. Moreover, startups should be exposed to market harshness so politics shouldn’t favor promising startups. There is not one way to create an EE since its development is a path-dependent process. So governments must learn and discover how their ecosystem thrives. Napier & Hansen (2011) Ecosystems for young Scalable firms Napier & Hansen (2011) analyze how EE’s for young scalable firms drive growth and success. Moreover, it explores the motivations and the difference with “normal” EE’s. And finally it examines the opportunity to quantify and compare EE’s dependent on local data. There study describes that successful startup entrepreneurs stay actively involved in local entrepreneurial hotbeds and strengthen the system by reinvesting knowledge, money and experience back into EE and thus reinforcing conditions. The individual presence of entrepreneurial actors doesn’t lead to sustainable value creation, yet a strong network and collaboration between these key actors does. Since actors encourage each other while (or simultaneously) building new scalable global-oriented companies. A ranking Is provided for young high-growth firm ecosystems. The tentative findings suggest that use of dealmaker data can improve the rankings. Framework conditions for growth entrepreneurs should no longer be thought of independently. Policymakers should involve successful entrepreneurial actors in EE’s and activate them, to participate in the growth phase of new scalable firms. Feld (2012) Startup Communities. Feld (2012) states that large numbers of startup communities arise all over the world, however he stresses that there are still many gaps in the knowledge about these communities. According to Feld (2012) startup communities and its stakeholders must be comprehensive, enact a non-zero sum game, focus on advice and be ready to pivot after failing. Furthermore, he claims that startups arise via networks and therefore continuous events and activities are key to involve everyone. Build around local conditions Needs to find right balance to stimulate local growth and success. Limited role for politics, Feld (2012) agrees with Isenberg (2010) that startups should be exposed to market harshness. Setting up a local startup community is a bottom-up development, driven by entrepreneurs themselves, which needs to grow natural. This view is significantly different from most predecessors, which claim governments should top-down build EE. Previous data needs to be re-evaluated since prior results are significantly different from Feld’s claims. Mainly the reticent role of politics and universities.
AUTHOR(S) (YEAR)
TITLE GAPS FINDINGS SIMILARITIES UNIQUENESS FUTURE RESEARCH
WEF (2013) Entrepreneurial Ecosystems around the globe and company growth dynamics. In the new entrepreneurial economy high-growth firms are often seen as a drivers of innovation, productivity and employment. The WEF (2013) investigated which elements of an EE contribute most to the progress of startups and thus economy as a whole. This extensive study showed three primary growth accelerators in the data, even after segmentation per continent, country and sector. The growth accelerators are access to human capital, market opportunities and funding & finance. In addition, WEF (2013) found that entrepreneurs can play multiple key roles, results show (ex-)entrepreneurs in the position of mentor, role model, investor, new founder and employee. Only a minority of people have a pivotal role in central networks since few nodes are necessary to trigger and connect the rest. These feeders aren’t able to create a network on their own, but do contribute to the creation of a high-impact EE by enhancing the effects and outcomes. Significant alignment issues arise amid entrepreneurs and politicians in terms of geographical focus and time horizon. More, often just a small number of local ventures contribute substantially to the early-stage development of a new business sector. According to Entrepreneurs, governments can be both growth accelerators as well as growth preventers. Politicians around the world need to discuss and tune EE policies to maximize societal effects. Vogel (2013b) The Employment Outlook for Youth. A significant amount of uncoordinated startup support programs has been established. In general, their effort doesn’t spur EE success. Therefore, a better understanding of EE elements and assessment indicators is needed to measure and improve the effect of support programs. It is a necessity to comprehend a local community’s strengths and shortcomings before making a substantiated choice about the establishment of an effective EE. One of Vogel’s (2013) key findings is that many aspects of the EE framework must be in place before the other components of the ecosystem can be introduced. Moreover, he stresses that the systemic components must be created simultaneously if possible. Vogel (2013) confirms Feld’s thoughts about the entrepreneur-led startup community and claims that entrepreneurial culture adds to entrepreneurism and inspires novice and upcoming generations. And effectiveness of entire EE’s must be measured in order to develop progress of existing programs. According to his model together three divisions constitute the EE, e.g. externalities, entrepreneurship related environment and finally entrepreneurial actors. In the latter category, a distinction can be made between new and serial entrepreneurs. He attributes an extensive part of the development of EE’s to entrepreneurial support programs. This is contrary to other studies. Therefore, his findings must be compared to other findings. Motoyama, et. al. (2014) Think Locally, Act Locally. This paper revolves around the regional property of entrepreneurship and attempts to improve in-depth insights of local networking activities by testing Feld’s (2012) postulates and additional patterns of One of the main findings is that it is most effective to communicate via local entrepreneurial networks. Politicians, supporters and entrepreneurs should keep this in mind. Moreover, during the creation and progression of support programs stakeholders should investigate what kinds of entrepreneurs are relatively underserved. Data supports Feld’s postulates. It admits the local trait of startup communities and states that it must be led by entrepreneurs Further, results support the inclusion of all levels of entrepreneurs in local networks, but urges distinct events for various life-Motoyama et. al. (2014) also found that local networks thinker exponentially over time. Further, the scholar identified a significant need for peer-based learning and networking. Again different life-cyme stages want different Future studies must examine the applicability of Feld’s postulates in other metropolitan areas particularly in regions in absence of local assets.
AUTHOR(S) (YEAR)
TITLE GAPS FINDINGS SIMILARITIES UNIQUENESS FUTURE RESEARCH
Mason & Brown. (2014) Entrepreneurial Ecosystems and Growth Oriented Entrepreneurship. According to Mason & Brown (2014) extant approaches to induce the number of high-growth firms (HGFs) are relatively fruitless. Solely creating a supportive foundation from policy perspective is not enough. Moreover, transactional support seems ineffective as well, at least in the post startup phase. Distinctive characteristics of an EE are a foundation of major corporations including entrepreneurial blockbusters, an environment where knowledge, money and expertise is available and transferred via entrepreneurial recycling. Moreover, one of the most important people in a rapidly growing entrepreneurial ecosystem is the dealmaker. Someone who takes the role of confidential contact for all participating parties and is active multiple startups. They agree that the EE approach has developed as the most prevailing perspective and confirm that HGFs can experience success in various supportive ecosystems. Other contributory features of EE’s to HGF’s are the presence of startups, its culture, access to investments and large firms, service providers & universities (in the role of feeders). EE’s are mainly statistically analyzed what creates a lack of in-depth knowledge about the origin and process of becoming self-sufficient. Consequently, EE’s should be explored from a holistic perspective with specific attention to entrepreneurial actors, connectors, resource providers and the facilitating EE environment. Future studies should explore EE’s in-depth from specific angles. Moreover, measurement for EE’s should be developed and their must be thought about what to assess and on which scale. Stam (2014) The Dutch Entrepreneurial Ecosystem. An increase in the number of entrepreneurs has not led to a raise in innovation and/or productivity growth. This is described as the Dutch paradox. Stam studies this phenomenon and examines the knowledge regarding EE’s. The entrepreneurial ecosystems approach sets entrepreneurs in the center, however it stresses the context in which entrepreneurial action is activated or restricted. In local community’s entrepreneurs and entrepreneurial actors lead, while other components can affect output and outcomes. Stam (2014) confirms Feld’s separation between leaders and feeders. Moreover, he also validates Isenberg’s claim that EE elements should be viewed from a holistic perspective. And he insinuates that national and global connections are potentially equally important as local one’s. To understand the dynamics of entrepreneurial ecosystems Stam (2014) adds the cycle of innovation to its model. At it’s core it is about building on previous innovations, discoveries and applications. New studies must benchmark whether the literary synthesize made by Stam (2014) is correct and prospective research should further deepen the insights about EE’s. Motoyama & Watkins. (2014) Examining Connections in the Startup Ecosystem Motoyama & Watkins (2014) investigate how local entrepreneurial ecosystems emerge by studying different actors, their decisions and actions in relation to startup ecosystem success. Relations between entrepreneurs were most significant. Incubators and other support teams were collaborating extensively and had many duplications of roles. Financial and function support was most weighty and mentoring was most miscellaneous. Last, Motoyama & Watkins (2014) underline that co-location led to connections between entrepreneurs that would not The collaboration between EE stakeholders and support organizations was key in the early-stage development of novice startups, since they were linked to key people, firms or resources. The most obvious form was peer-based support between novice and This study reveals four relationships between EE actors. Connections amid entrepreneurs, between official support institutions, links between founders and key support institutions and finally between entrepreneurs and other Future research should continue the exploration of relations within local startup ecosystems to better comprehend the emerge of entrepreneurial
2.3 Synthesizing literature
A critical analysis of prior literature exposed three research gaps which are significant for progressing the detailed understanding of key connections in high-growth entrepreneurial ecosystems.
Gap 1: limited knowledge of the core roles in high-growth startup communities. Feld’s postulate about the entrepreneur-led startup community creates a new perspective and changes the research direction for further understanding startup communities into a more people-oriented approach. However, several studies criticize Feld’s thought and provide examples that the leading role is not solely restricted to entrepreneurs, since there are also other key roles responsible for ecosystem success (Mason & Brown, 2014; Isenberg, 2014). To elaborate, Napier & Hansen (2011) report that the individual presence of entrepreneurial actors has no significant impact on achieving sustainable high-growth entrepreneurial activity, while on the contrary, a strong network of key actors has. In addition, the scholars state that successful entrepreneurs remain active in high-growth startup ecosystem in various roles and thereby provide a positive stimulus to the overall aggregated knowledge, experience and resource. Both Stam (2014) and Mason & Brown (2014) support this assumption Mason & Brown (2014) define this concept as entrepreneurial recycling. However, despite these insights, the literature still lacks significant in-depth knowledge about the contribution of core roles in high-growth startup communities.
Gap 2: deficient insight into connections among actors and the influence of EEs.
An extensive number of researchers studied the components of EE’s and the impact on entrepreneurial activity, however often from a wrong angle (Vogel, 2013b; Motoyama & Watkins, 2014). As earlier discussed, several scholars designate the entrepreneurial ecosystem approach as the framework for best understanding the link between entrepreneurial ecosystem elements and entrepreneurial activity (Stam, 2014; Mason & Brown, 2014). The approach positions entrepreneurial actors at the centre and underlines the contextual elements by which entrepreneurial activity is stimulated or restricted. This means different actors can be responsible for ecosystem success and not solely entrepreneurial actors. Further, while the framework takes
various systemic conditions into account, including network (Stam, 2014), it neglects an investigation into the effect of EE components on interactions between actors. More specifically, there is inadequate knowledge about the connection among actors and how different EE elements influence connections for achieving rapid growth. Gap 3: poor know-how of the link between peer-based learning and support and achieving high-growth. Entrepreneurial ecosystems consist of actors and components that together form a system which should spur entrepreneurial activity and economic prosperity (Isenberg, 2010; Stam, 2014). In reality attempts to create thriving EE often fail. Consequently, a vast amount of scholars has tried to explain differences in the performance of entrepreneurial hotbeds from a systemic perspective (Vogel, 2013b). From a static top-down perspective the presence of funding & finance, human capital and culture are often identified as crucial elements for building successful entrepreneurial ecosystems (WEF, 2013; Mason & Brown, 2014). However, more recent findings indicate that research should take a bottom-up perspective to explain the local variations in startup ecosystems (Mason & Brown, 2014). Static data does not help to thoroughly understand the dynamics of ecosystem elements and interactions between actors within the system, let alone provide the knowledge to create sustainable high-growth EE’s. In addition, Motoyama & Watkins (2014) found that the main contribution of St. Louis’s startup ecosystem to high-growth entrepreneurial activity is peer-based learning and support between novice and experienced entrepreneurs. So, little is known about how this works and further research could shed more light on interactions in ecosystems vital to achieve early high-growth.
3 SITUATING THE CASE OF ISRAEL
_____________________________________________________________________________________________________
The previous section discussed the current body of knowledge relevant for understanding EE’s and assessed prior literature to expose multiple research gaps. The first objective of this chapter is to form a research approach that responds to the deficiencies in literature. And the second objective is to situate the context of the research by succinctly describing the national business conditions and most significant historical occurrences. 3.1 Situating the case This paper has three sub-questions that help to overcome the limited insights about the functioning of high-growth startup ecosystems. First, there is comparatively little knowledge on the entrepreneur-led angle of the high-growth ecosystems (Napier & Hansen, 2011; Feld, 2012, Mason & Brown, 2013). As evangelized by several researchers linked to the Kaufmann Foundation, a less static and more minimalistic approach to entrepreneurship will enrich the detailed comprehension necessary to develop viable startup ecosystems (Motoyama et. al., 2014; Motoyama & Watkins, 2014). Moreover, multiple scholars point out new research on startup ecosystems should not focus on ecosystem elements but aim attention at entrepreneurs and other key actors (Feld, 2012; Mason & Brown, 2014). Therefore, following the recommendation of Mason & Brown (2014), this study aims to identify, explore and describe the entrepreneurial actors, resource-providers and connectors in high-growth entrepreneurial hotbeds. The first sub-question is: “who are the entrepreneurial actors, resource providers and connectors in high-growth startup communities?”.
Second, as mentioned in the introduction, many attempts to create self-sustaining EE’s fail. Research from the perspective of entrepreneurial ecosystem elements alone can’t explain how entrepreneurial ecosystems sustain and thrive. Deepening our understanding about the effects of ecosystem components on the interactions between key actors could further clarify this interwoven system. Therefore, the next sub-question investigates “what entrepreneurial ecosystem elements significantly
empower the interaction of actors in high-growth startup communities?”. The question follows Feld’s postulate about the entrepreneur-led startup community, but emphasizes the power of context, as stressed by the majority of (regional) entrepreneurship academics (Isenberg, 2010; Feld, 2012; Stam, 2014). More specifically, the focus is primarily on peer-based learning and -support. New insights reveal these two interactions as most significant (Motoyama & Watkinks, 2014).
Third, the paper reasons from the holistic entrepreneurial ecosystem approach but focuses its exploration on the local interactive section of the system as urged by Mason & Brown (2013). According to Mason & Brown (2014) the main contributions of key actors in startup ecosystems are learning and support. This demarcation allows to explore interactions linked to learning and support in detail, while, on the contrary, the findings can be put back into the holistic framework. Which empowers scholars to benchmark the conclusions in retrospective (ANDE, 2014). Moreover, this perspective contributes to Stam’s (2014) suggestion to clarify distinctions between causes and consequences in investigating the relation among entrepreneurial activity and EE elements. Hence, the third sub-question examens: “how does peer-based learning and -support contributes to early high-growth entrepreneurial activity?”
To finalize, the purpose of this thesis is to identify, integrate and further develop the concept of entrepreneurial ecosystems by constructing a business case around the Israeli high-growth startup ecosystem. In this analysis, specific emphasis is put on the connection between early high-growth entrepreneurs and key connections. A comprehensive research into critical occurrences, experiences and motivations that induced high-growth generates a rich information portrait, which serves as the basis for answering the research question, “what are the key connections in high-growth startup ecosystems?”
Figure 3.1: Conceptual framework Before this paper continues to the methods and data a portray of the fundamental Israeli economic and social conditions is given, since it allows to reframe the findings back into the countries context (Vogel 2013a; Stam, 2014). Entrepreneurial Ecosystem Elements Interactions Peer-based learning & support Entrepreneurial Actors Connector Resource Provider Hi gh -gr ow th en trep ren eu ria l a ctiv ity (A gg re ga te d) va lu e cr ea tio n
3.2 About the Israeli region
The Israeli business environment
Israel is a small country with 7 million inhabitants and exists since 1948 (Senor & Singer, 2009). From the 90s the state of Israel is known as the leading technology cluster outside the U.S (Vinig, 2002; De Haan, 2008). The Global Competitive Index exhibits that several factors in Israel’s business environment stand out compared to other countries; its innovation capacity, adaptability, quantity and quality of scientific research and workforce in terms of IT skills and number of qualified engineers (KPMG, 2014; UNPD, 2012). Consequently, the Israeli high-tech industry represents 35% of total industrial exports (excl. diamonds), the tech industry realized a growth of 226% in 10 years’ time (2003-2013) and the technology industry attained a 3.2% increase in jobs in 2014, 1.7 percent point more than in 2013 (Nocamels, 2014a). Development of technology sector
The foundation of Israel's technological sector emerged via a path-dependent development process and is shaped through a series of events (Vinig, 2002). In the 1950s the government introduced the build-up of technology as application in the military. The development of the technology sector substantially accelerated after the Arab boycott and French arms embargo, which were imposed because of the 6-day war in 1967. As a reaction Israel initiated its own (high-tech) defence industry (Vinig, 2002; De Haan, 2008; Senor & Singer, 2009). Subsequently, in the 80s and 90s when a major cut in the military budget led to the resignation of highly skilled tech people (1988) the creation and advancement of the military and arms industry has led to many spin-offs, new technologies and entrepreneurs (De Haan, 2008; Senor & Singer, 2009). Moreover, a Russian immigration stream of well-educated technology people (1992-1995) further strengthened the Israeli workforce. So during the time of global shortages for professionals in electro technique and software engineers, multinationals turned their attention to Israel as a domicile for innovation and R&D (De Haan, 2008; Senor & Singer, 2009). Large-scale cooperation with foreign companies led to commercialization of the Israeli market, high foreign direct
investments (FDIs), access to international networks and distribution channels and knowledge transfer from MNCs (De Haan, 2008).
Entrepreneurial infrastructure development
In the 1990s the government initiated two key project necessary to create a sustainable foundation for Israel’s EE; establishing the YOZMA fund and building a national tech incubator program (Vinig, 2002; Senor & Singer, 2009) Firstly, the YOZMA fund was a government initiative in collaboration with the private sector to support the maturation of the alternative financial industry by co-investing to stimulate early credibility and mitigate risk for international investors (De Haan, 2008; Avnimelech, 2009). Secondly, the national technology incubator program was essential to connect venture capitalists and promising entrepreneurs in a relatively new and undefined business environment (De Haan, 2009). Important was the essential behaviour of government to initially focus on stimulating the entrepreneurial ecosystems infrastructure and then in 1998 withdraw to let further development over to market forces (Avnimelech, 2009). Today’s insights reveal that this sequence of development was significant for developing Israel’s thriving entrepreneurial ecosystem (Isenberg 2010; Feld, 2012; Stam, 2014).
The strengths of a high-growth startup community
Nowadays, Israel has developed into one of the strongest technology hotbeds in the world. Tel Aviv’s EE is ranked 2nd place after Silicon Valley and has the highest startup density in the world (Startup Economy Report, 2012). There are interesting movements in the Israeli entrepreneurial ecosystem. To start, in 2015, 74 Israeli companies were listed on the tech-oriented NASDAQ (Nasdaq, 2015). A notable trend is that startups are acquired in a faster pace than ever, according to No camels (2014a) within an average of 3.95 years, this compared to 8,59 years in 2009. Furthermore, a significant rise of VC confidence in Israel's high-tech industry due to excessive return on investments (ROI)(EY,2014). On average, VCs with a share in one of the 70 acquired companies doubled their money 6.2 times. By comparison, in Europe this was 2.2 times in the same period (No Camels, 2014a).
Table 3.2: Entrepreneurial ecosystem ranking 2012 (Startup Genome, 2012)
Threats to the entrepreneurial ecosystem
Despite all the positive signs, there are also upcoming challenges for the Israeli entrepreneurial ecosystem. Potentially, the biggest challenges are to be found in the national political and economic atmosphere, since these settings causes some of the best people to leave the country. This can greatly weaken the tech sector in the long run (Startup Economy Report, 2012). Furthermore, many high-growth technology startups are acquired in an early lifecycle stage or get listed outside of Israel, resulting in a loss of value for the economy as a whole (Startup Economy Report, 2012). From an international perspective, the rise of China, India and fast-growing hub ecosystems as London and NY are forming threats to Israel/Tel Aviv as technology hotbed (Startup Economy Report, 2015). Consequently, Israel needs to reposition its purpose as an relatively small ec osystem to keep a sustainable and valuable role in the future. Table 3.3: Entrepreneurial ecosystem ranking 2015 (Compass, 2015) Rank Entrepreneurial Ecosystem
Performance Funding Support Index Talent Startup Output 1 Silicon Valley 1 1 1 1 1 2 Tel Aviv 12 1 5 5 2 3 Los Angeles 2 6 13 3 4 4 Seattle 6 7 4 2 19 5 New York 8 4 9 12 3 Rank Entrepreneurial Ecosystem
Performance Funding Market Research Talent Startup Experience 1 Silicon Valley 1 1 4 1 1 2 New York 2 2 1 9 4 3 Los Angeles 4 4 2 10 5 4 Boston 3 3 7 12 7 5 Tel Aviv 6 5 13 3 6 6 London 5 10 3 7 13
4 DATA AND METHODS
_____________________________________________________________________________________________________
This chapter explains the investigation process and outlines the methodology for answering the main questions. As earlier mentioned, a qualitative study is selected since it best fits the research objective. Further substantiation of the method and data collection process will be elaborated in the section below. The first part explains the research strategy together with a description of the data. Subsequently, the research execution outlines the sample and data collection process. Next, a discussion elaborates on the data analysis. And finally, four qualitative research criteria reflect on the trustworthiness and rigor of the data and methods. 4.1 Research strategy and design The research is a qualitative study and is built around a project that is both exploratory and descriptive in nature. Exploratory analysis can have two structures; it is either a study in a new research area or it is a new perspective on a particular phenomenon. This paper operates a different perspective on entrepreneurial ecosystems. The analytical objective is to identify, integrate and further develop the concept of entrepreneurial ecosystems by constructing a business case around key connections in Israel’s high-growth startup ecosystem. Typical for exploratory qualitative studies is the iterative design (Miles & Huberman, 1984). This means data collection influences research questions and vice versa, due to continuous learning throughout the process. The research strategy is a case study, a case study is a detailed empirical examination on a person, venture or group (Eisenhardt, 1989). This type of research is well suited to understand and describe the relationship between participants and their real-life setting (Yin, 2003). In our case, high-growth entrepreneurs and key connections in the Israeli entrepreneurial ecosystem. Furthermore, a multiple case study design is implemented since it is a convenient method to recognize the holistic setting while exploring early-stage empirical research in detail (Eisenhardt, 1989; Yin, 2003). A multiple case study design can be defined as a modified design which encompasses two or more cases on the same research aspects (Yin, 2003). The subsequent section briefly outlines and describes the sampling procedure.
4.2 Research sample
The inquiry targets technology entrepreneurs in the Israeli high-growth startup ecosystem. According to Miles & Huberman (1984) the research sample should be theoretically relevant and capable to portray an information-rich explanation of the phenomenon and its dynamics. Therefore, participants must comply to specific selection requirements. Participants must be (co-)founders/(co-)owner, leading a technology startup (1-5 years) and experience high-growth (i.e. in number of employees and in turnover) (Du Rietz & Andersson, 2005).
The specific characteristics of the target population and the limited time-span of the data collection process determine cases are best collected via both purposive expert sampling and referral sampling methods. Purposive expert sampling is a non-probability sampling technique that focuses on individuals in a population with specific know-how or experiences in order to answer the research question (Laerd, 2012). In addition, referral sampling is also a non-probability sampling technique, but is used when traits of participants are rare and consequently cases are hard to find or approach (Research-methodology, 2015). The combination of the sampling techniques makes successful data collection more feasible and increases the trustworthiness of the participants (Miles & Huberman, 1984). On the contrary, there is criticism on the combination of purposive sampling technique in association with case study strategy and design, since the mixture is prone to researcher bias. Particularly in comparison to probability sampling techniques (Laerd, 2012). However, negative effects of potential prepossession can be minimized via a carefully chosen selection criteria, a clear theoretical framework and via the selection of expert peer-participants (Laerd, 2012).
Initial access to the research sample is gained via two well-connected local EE stakeholders. These primary contacts serve as a starting point for further access to Israeli high-growth technology entrepreneurs. A sample size of 20 entrepreneurs is chosen and based on a similar research from Motoyama & Watkins (2014), where emphasis is also put on actors in the startup environment. To elaborate, this number of participant was large enough to formulate a satisfactory in-depth discussion and conclusion, therefore this seems an appropriate size.
The sample is 90 percent male, 95 percent between the age of 30 and 39 and 65 percent working in the startup phase of 3–5 years (figure 4.1). Furthermore, all participants worked in the high-tech sector but focused on a wide variety of industries including: fin-tech, advertising, transport, music & video, social network, cyber security, and data storage & cloud computing. In 4 cases, the participant manages multiple startup positions, while acting as active CEO of a high-growth venture (figure 4.1).
Start-up phase Active startup positions Response rate
Figure 4.1 Participant and methodology statistics.
1-2 year 3-5 year 1 positions 2-10 positions particpate reject request
In total 25 entrepreneurs were approached to form a sample size of 20 high-growth
entrepreneurs. 20% of the entrepreneurs did not respond or did not want to engage, primarily due to a lack of time or privacy concerns (figure 4.1). Consequently, coded names are used for both the participating entrepreneurs as well as their startups in order to secure confidentiality. The remainder of this study refers to these coded names (Appendix 8.3).
4.3 Data collection process
Firstly, the research adopts a subjectivist research philosophy to describe the development process and character of the knowledge. Subjectivism means that social developments are generated through the perceptions and the resulting actions of the concerned parties. Furthermore, it underlines that it is necessary to investigate the details of a scene in order to comprehend the dynamics and interactions. This philosophy corresponds to our research objective.
Secondly, this paper uses an inductive research approach and applies a case study and some archival research to collect data. An inductive approach reasons from specific
