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Bachelor Thesis
A Systematic Comparison of the US and EU
Startup Ecosystems of Cultivated Meat
Chair of Entrepreneurship, Innovation and Technological
Transformation
Prof. Dr. Dries Faems
Maxim L. Mommerency
Submission date (Vallendar, May 23rd, 2020)
Julia Ines Schimanietz Gilda Emilia Lukacs
Abstract II Abstract One of the most pressing challenges facing modern society is the need to feed the growing world’s population with increasingly limited resources. Cultivated meat has the potential to mitigate precisely this challenge, while simultaneously minimizing negative externalities such as environmental destruction. Hence, our research provides a detailed analysis of the current developments in the cultivated meat industry. Specifically, we provide an in-depth comparison of the United States and the European Union entrepreneurial ecosystems of cultivated meat. The resulting empirical findings originate from the geographic mapping of ecosystem indicators, comprising (a) cultivated meat startups, (b) investors, and (c) research institutions, and from qualitative expert interviews. The evaluation of the synthesized findings indicates that the US entrepreneurial ecosystem is more mature than the EU ecosystem and thus exhibits superior performance in most ecosystem domains. However, both ecosystems face the same core challenges. These challenges comprise the need to achieve regulatory approval, cost-parity, and open access knowledge-sharing. Consequently, we provide generalizable best practices and tailored recommendations to overcome these challenges based on the implications of the systematic analysis. Keywords: Cultivated Meat, Cell-Based Meat, Cellular Agriculture, Ecosystem Mapping, Entrepreneurial Ecosystem, Matchmaking
Table of Contents III
Table of Contents
Abstract .............................................................................................................................II
Table of Contents ............................................................................................................ III
Table of Figures ............................................................................................................... V
Table of Tables ................................................................................................................ V
Table of Abbreviations .................................................................................................... V
1 Intro ............................................................................................................................ 1
2 Literature Review: Entrepreneurial Ecosystems ........................................................ 3
2.1. History of Entrepreneurial Ecosystem Theory ....................................................... 3
2.1.1 Origin of the Entrepreneurial Ecosystem Concept ..................................... 4
2.2 Definition of Key Concepts ............................................................................... 6
2.2.1 The Entrepreneurial Ecosystem .................................................................. 7
2.3 Conditions for Successful Entrepreneurial Ecosystems ..................................... 8
2.3.1 Definition of EE Success ............................................................................ 8
2.3.2 EE Frameworks in Comparison .................................................................. 9
2.4 How to Measure the Success of an EE ............................................................. 10
2.5 Implications for Policymakers ......................................................................... 11
2.6 Role of Universities.......................................................................................... 13
3 Literature Review: Cultivated Meat ......................................................................... 16
3.1 History and Key Terminology ......................................................................... 16
3.2 Triple Bottom Line Evaluation ........................................................................ 19
4 Methodology ............................................................................................................ 23
4.1 Purpose of Research Method ........................................................................... 23
4.2 Design of Research Method ............................................................................. 23
5 Findings .................................................................................................................... 27
5.1 Visualization of Ecosystem Clusters ................................................................ 27
5.1.1 Global Perspective .................................................................................... 27
5.1.2 Quantitative Breakdown ........................................................................... 28
5.1.3 Visualization of Investment Landscape .................................................... 29
5.2 Analysis of the Most Important Hubs .............................................................. 29
5.2.1 Identified Hubs in the US Ecosystem ....................................................... 29
5.2.2 Identified Hubs in the EU Ecosystem ....................................................... 33
5.3 Spider Web Framework Analysis .................................................................... 37
5.3.1 US Spider Web Analysis .......................................................................... 38
5.3.2 EU Spider Web Analysis .......................................................................... 47
5.4 Visualization of Qualitative Findings .............................................................. 55
6 Discussion ................................................................................................................ 56
6.1 Summary of Findings ....................................................................................... 56
Table of Contents IV
6.2 Practical Implications and Recommendations ................................................. 58
6.3 Case Application: Germany ............................................................................. 62
6.4 Theoretical Implications: NGOs as Matchmakers ........................................... 66
7 Conclusion................................................................................................................ 68
7.1 Limitations of Research Approach ................................................................... 68
7.2 Recommendations for Further Research .......................................................... 69
8 Final Remarks .......................................................................................................... 71
Bibliography ................................................................................................................... 72
Appendix ......................................................................................................................... 80
Delineation of Contributions .......................................................................................... 86
Declaration of Authorship .............................................................................................. 87
Table of Figures V Table of Figures Figure 1: The Triple Bottom Line Framework _______________________________ 19 Figure 2: Global Map of Entrepreneurial Ecosystem Indicators __________________ 27 Figure 3: Investor's Headquarters in the EU (left) vs. the US (right) ______________ 29 Figure 4: Visualization of the US Cultivated Meat Ecosystem ___________________ 30 Figure 5: Visualization of the EU Cultivated Meat Ecosystem ___________________ 33 Figure 6: Magnification of the EU Cultivated Meat Ecosystem __________________ 37 Figure 7: Modified Framework: Domains of the Entrepreneurship Ecosystem ______ 55 Figure 8: Visualization of Causalities ______________________________________ 62 Table of Tables Table 1: Scoring System for EE Evaluation _________________________________ 25 Table 2: Scores of the Evaluated EEs for Cultivated Meat ______________________ 38 Table of Abbreviations CAS Cellular Agriculture Society EE Entrepreneurial Ecosystem EFSA European Food Safety Authority FBS Fetal Bovine Serum FDA Food & Drug Administration FAO Food and Agriculture Organization GMO Genetically Modified Organism GHG Greenhouse Gas HGF High-Growth Firm RIS Regional Innovation Systems GFI The Good Food Institute TEA Total Entrepreneurial Activity USDA Unites States Department of Agriculture
Intro 1
1 Intro
"[R]aising meat takes a great deal of land and water and has a substantial
environmental impact. Put simply, there's no way to produce enough meat for
9 billion people. However, we can't ask everyone to become vegetarians"
- Bill Gates, 2013
One of the most critical questions of the 21st century is whether the world will be able to
feed 9 billion people by 2050 (Holt-Giménez, 2019; Gates, 2019). This daunting
challenge has two main contributors. Firstly, experts prognosticate a sharp population
increase to occur within the next thirty years (e.g., United Nations, 2019). Secondly,
researchers warned about a problematic, unsustainable shift in food consumption patterns.
Namely, that people are continuously increasing their demand for animal protein in the
form of meat (Gates, 2019).
As a result, the need for a substantial transformation of the meat industry has increased
over the past decade. Consequently, alternative protein companies emerged, aiming to
provide solutions to the problems of increasing resource constraints. Notably, cells
cultivated in bioreactors constitute the perhaps most promising alternative protein source.
Hence, so-called cultivated meat companies offer consumers genuine meat, but take
raising and slaughtering animals out of the food supply chain. Therefore, cultivated meat
can provide consumers with more convenience than a vegetarian or vegan diet, while
simultaneously enabling them to consume more sustainable products. Thus, we decided
that the investigation of the ecosystem conditions facing cultivated meat should be the
purpose of our research.
Noteworthily, the term Entrepreneurial Ecosystem (EE) and its underlying concepts date
back to the 1980s and 1990s. Until today, EEs continue to remain a 'hot topic' in
entrepreneurial and social sciences, with lots of new publications trying to grasp their
complex interrelations (e.g., Spigel & Harrison, 2017). However, researchers frequently
express disagreement about definitions and causations in this field. Hence, a lack of
consistency and consolidation of findings constitute the main limitation in this domain.
Further, entrepreneurial ecosystems do not only face contemporary challenges in theory
but also in practice. For instance, the cultivated meat ecosystem faces practical challenges
resulting from a global economy.
Despite the promising future potential of cultivated meat to disrupt the $2 trillion meat
market, cultivated meat startups can still not sell their products commercially, even
though the technology has been in existence for almost a decade (Bashi et al., 2019). As
Intro 2 a consequence, we identified the present inconsistencies in EE literature and the lack of academic research regarding the development of cultivated meat ecosystems as an essential research gap. Our work's core objective is the detailed mapping and qualitative investigation of the Europen Union (EU) and the United States (US) ecosystems of cultivated meat and the subsequent application of our findings to the German EE. Specifically, we will provide generalizable recommendations and best practices, as well as a case application to the German cultivated meat ecosystem. Consequently, our research findings are relevant for policymakers and industry practitioners, such as entrepreneurs, investors, life science companies, and meat industry incumbents. Further, our contribution offers a relevant implication for future academic literature on entrepreneurial ecosystems with regards to matchmaking. The main findings of our research include that the EU and the US ecosystems are the most developed entrepreneurial ecosystems globally. However, the US has a few unique advantages over the EU. The strengths of the US ecosystems constitute a resilient entrepreneurial culture, facilitative support systems, as well as favorable market conditions and networks. Meanwhile, the EU ecosystem does not outperform the US in any domain. However, its comparative strengths are its culture, market conditions, and nurturing foundation of human capital. Moreover, the main implication of our findings is that regulatory approval, cost-parity with meat products, and the availability of open access research constitute the key milestones that both cultivated meat ecosystems need to achieve in the future. In the following, we will begin with a review of existing academic literature on EE theory. The goal of the literature review is to compare and contrast existing theories in order to provide a structured overview of the research community's status quo. Subsequently, we will summarize the current state of the cultivated meat industry, followed by the presentations of findings of the EE mapping of the cultivated meat industry, which we performed using Crunchbase and BatchGeo. Next, we will supplement the findings with insights from semi-structured expert interviews. Finally, we will provide theoretical and practical recommendations to help overcome the identified challenges.
Literature Review: Entrepreneurial Ecosystems 3 2 Literature Review: Entrepreneurial Ecosystems The review of existing academic literature aims to provide a comprehensive overview of patterns and contrasts inherent in existing theories. For this purpose, we will outline the origin of the EE terminology and define its key concepts. Subsequently, the literature review will focus on outlining conditions and measures for EE success before taking deep dives into the role of policy and universities. 2.1. History of Entrepreneurial Ecosystem Theory Biological vocabulary has found its way into business discourse, especially in entrepreneurship. For example, the terminology of seed capital has become standard entrepreneurial vocabulary. In the 1990s, another biological term was added to the business jargon to conceptualize the geographical interconnectedness of different actors and institutions, namely the entrepreneurial ecosystem. Regarding the historical development of the term, the first publications legitimized the concept of ecosystems as an operator in the broader business context, as opposed to the entrepreneurship context. In contrast, most recent research efforts focused on the consolidation of findings and the creation of generalizable terminology. James Moore was one of the first researchers who used the metaphor of an ecosystem in his publications in the 1980s and 1990s (Spigel & Harrison, 2017). According to Moore, the concept bridges the interconnectedness of resources such as "capital, partners, suppliers, and customers" (1993, p.75). Moreover, Moore's findings suggested that "a company be viewed not as a member of a single industry but as part of a business ecosystem that crosses a variety of industries" (Moore, 1993, p.76). Consequently, the focus of research shifted from the individual entrepreneur and her startup towards the local framework conditions surrounding her. This shift in focus is a distinctive property of EE literature (Spigel & Harrison, 2017). A more recent approach to the ecosystem metaphor was taken by Isenberg in 2011. He used it to ameliorate the process of creating strategies for successful entrepreneurship. Specifically, his Entrepreneurship Ecosystem Strategy proposes a framework made of six pillars (Appendix A) and conceptualizes the causes of regional concentrations of entrepreneurship. Since then, these pillars have inspired further modern research approaches (e.g., Spigel & Harrison, 2017; Mason & Brown, 2014).
Literature Review: Entrepreneurial Ecosystems 4 2.1.1 Origin of the Entrepreneurial Ecosystem Concept To carry forward the biological metaphors, the newly established branch of EE literature draws from a broad stem. These influences range from "economic geography [and] economics" (Mason & Brown, 2014, p. 26) to "regional science, [...] industrial clusters, [...] regional innovation systems (RIS)", (Spigel & Harrison, 2017, p. 153) to the market failure approach (Stam, 2015). Hence, we will outline the main similarities the EE literature shares with its lineage before highlighting its distinctive properties. Firstly, one common trait appears to be the focus of the branches of literature on the same phenomenon, namely on how exactly entrepreneurship is intertwined with its external environment (Spigel & Harrison, 2017). In other words, a shared trait with, for example, RIS and industrial cluster literature is the recognition that "there are forces beyond the boundaries of an organization but within those of a region that can contribute to a firm's overall competitiveness." (Stam & Spigel, 2016, p. 3). Similarly, systems theory emphasizes a bottom-up explanation of the performance of regional economies and moves away from the individualistic perception of the entrepreneur (Moore, 1993; Stam & Spigel 2016). Secondly, especially Porter's cluster theory has valuable implications for EEs. Namely that "paradoxically, the enduring competitive advantages in a global economy lie increasingly in local things" (1998, p. 77). Similarly, in EE theory, the regional concentrations and competitive advantages of high-performing, new ventures can be explained by advantages emerging from their local context, such as information spillovers (Spigel & Harrison 2017). Thirdly, RIS literature adds more detail to the explanation. Namely, the emphasis on networks for resource generation, organization's roles in producing human capital, and the importance of policy (Spigel & Harrison, 2017; Isenberg, 2011). In summary, similar to its lineage, EE theory focuses on a bottom-up, contextual analysis of economic performance. This focus adds the importance of resources, such as human capital and policy, to the crucial factors contributing to high-performance entrepreneurship. In spite of many shared features with the literature it originated from, the EE approach also comprises many distinctive properties. However, according to Isenberg (2011), EE theory does not necessarily render its lineage complacent. Instead, EE theory serves as a "complement, or even pre-condition to, cluster strategies, innovation systems, knowledge-based economies, and national competitiveness policies" (p. 1).
Literature Review: Entrepreneurial Ecosystems 5 The first addition to the concepts that the EE evolved from is the importance of knowledge. For example, Spigel and Harrison (2017) added knowledge about entrepreneurial processes to the importance of market and technical knowledge, which was already present in RIS and cluster literature. Second, EE theory distinguishes itself from previous concepts through industry agnosticism. While cluster frameworks are usually preoccupied with the analysis of the flow of resources within industry barriers, EE theory has a geographical focus in the most literal sense. Specifically, it comprises all industries within a specific region (e.g., Isenberg, 2011; Stam & Spigel, 2016; Spigel & Harrison, 2017). Third, in most of the previous management literature, such as the RIS or the market failure approach, "the role of entrepreneurs remains a black box" (e.g., Stam & Spigel, 2016, p.11). In contrast, the title of the EE concept is indicative of the importance of the entrepreneur. However, the entrepreneur needs to be analyzed in a productive balance with her surroundings. Fourth, another distinguishing aspect of EE literature is the narrow understanding of entrepreneurship. For example, Sussan and Acs (2017) used the terms "routine and high- growth entrepreneurship" (p. 58). Similarly, Isenberg (2011) asserted that one should distinguish between self-employment in the form of small and medium-sized enterprises (SMEs) (routine entrepreneurship), and entrepreneurship (high-growth entrepreneurship). Furthermore, while the focus on entrepreneurs is a distinctive feature of EE literature, Stam and Spigel (2016) have also emphasized the importance of other stakeholders as essential feeders of the ecosystem. Lastly, most recent EE theories adopt a process view of markets and entrepreneurship (Spigel & Harrison, 2017). For instance, the market failure approach follows the ideal of a static market equilibrium, while EE theory describes markets as an evolving process (Stam & Spigel, 2016). We will discuss the resulting policy implications further in subsection 2.5. To conclude, the concept of entrepreneurial ecosystems is distinct from its origin due to the importance of knowledge about entrepreneurial processes, industry agnosticism, the narrow definition of the entrepreneur, and finally, a process view of markets and entrepreneurship.
Literature Review: Entrepreneurial Ecosystems 6 2.2 Definition of Key Concepts After the summary of the history and origin of the terminology, we will outline key concepts that are relevant for the analysis of EE performance. Initially, we will link the biological ecosystem to its business analog and clarify the entrepreneurship terminology. Subsequently, we will propose a synthesis of the terms to finally provide a comprehensive definition of an entrepreneurial ecosystem. According to its textbook definition, an ecosystem in its most literal sense is a "system that includes all living organisms (biotic factors) in an area as well as its physical environment (abiotic factors) functioning together as a unit"1. Sussan and Acs (2017) have provided a very comprehensive application of this concept by noting that in a business context, the biotic factors describe agents including entrepreneurs or investors, while institutions such as government bodies constitute abiotic factors. Thus, resources such as venture capital (VC) or knowledge serve as nutrients of the ecosystem. As discussed, the entrepreneur is the focus of the entrepreneurial ecosystem. More specifically, entrepreneurship in the EE context exclusively refers to high-growth entrepreneurship and excludes routine entrepreneurship (Sussan & Acs, 2017). Accordingly, the entrepreneur is a "person who is continually pursuing economic value through growth and, as a result, is always dissatisfied with the status quo" (Isenberg, 2011, p. 2). Thus, risk is an intrinsic property of entrepreneurship. For instance, there exists a time lag in the potential materialization of favorable results in the future, in contrast to risky investments, which entrepreneurs have to make in the present (Isenberg, 2011; Ansari et al., 2016). Further, resourcefulness is a characteristic of entrepreneurship. According to Stangler and Bell-Masterson (2015), the "essence of entrepreneurial strategy" (p. 3) lies in the entrepreneurs' achievement of excellent results under severely constrained resources. Moreover, many researchers built their theories based on Schumpeter's work on entrepreneurship (e.g., Sussan & Acs, 2017; Mason & Brown, 2014). The Schumpeterian entrepreneur is the impersonation of high-growth, high-risk entrepreneurship (Sussan & Acs, 2017). Further, Kirzner (1999) has described entrepreneurship as "essentially disruptive, destroying the pre-existing state of equilibrium." 1 https://www.biologyonline.com/dictionary/ecosystem
Literature Review: Entrepreneurial Ecosystems 7 2.2.1 The Entrepreneurial Ecosystem The term entrepreneurial ecosystem builds the synthesis of the definitions of ecosystems and entrepreneurship, as outlined above. It implies that ecosystems can explain high- growth entrepreneurship. "[E]ntrepreneurship tends to be geographically concentrated in specific regions, cities, neighborhoods, and even buildings" (Isenberg, 2011, p. 10). Thus, the interconnectedness of entrepreneurial actors, organizations, and processes that constitute the local environment plays a central role (Mason & Brown, 2014). Hence, the analysis of such ecosystems should be conducted bottom-up, without undue focus on the individual entrepreneur (Moore, 1993; Stam, 2015). As discussed, another unique property of EE theory is its focus on high-growth entrepreneurship. Mason and Brown (2014) have used the term blockbuster entrepreneurs to describe individuals with the largest potential to produce extremely high-growth firms (HGFs). Similarly, Stam et al. (2012) emphasized that ambitious entrepreneurs should be the center of attention as "someone who engages in the entrepreneurial process with the aim to create as much value as possible" (p. 26). For instance, ambitious entrepreneurs attach extremely high value to extraordinary performance and are constantly dissatisfied with the status quo (Isenberg 2011; Stam et al., 2012). Therefore, high ambition, not business-ownership, should be the differentiating factor of entrepreneurship (Isenberg, 2011). Further, most EE literature supplements the concept of Schumpeterian entrepreneurs with the Kirznerian approach. Kirzner's entrepreneur does not necessarily disrupt the existing equilibrium. Instead, she engages in arbitrage because she is the first to notice that market conditions have changed (Sussan and Acs, 2017). Thus, in contrast to Schumpeter, the Kirznerian entrepreneur's business model can be, but need not be, based on disruptive innovation (Kirzner, 1999; Isenberg, 2011). In summary, the purpose of an entrepreneurial ecosystem goes beyond the individualistic enrichment of the entrepreneur. Ideally, HGF creation leads to a virtuous spiral of positive externalities for society as a whole, and simultaneously attracts more entrepreneurial activity (Isenberg, 2011; Stam, 2015). Another noteworthy property of the EE approach is a process view on ecosystem emergence. Researchers who have treated the process of EE development as a control variable, have been criticized for their static approaches (e.g., Mason & Brown, 2014, Stam & Spigel 2016). Thus the notion of a system perspective is inherent in the textbook definition of an ecosystem. As such, systems entail a constant (co-) evolution instead of
Literature Review: Entrepreneurial Ecosystems 8 a snapshot in time (Isenberg, 2011; Mason & Brown, 2014; Sussan & Acs, 2017). Further, in biology, ecosystems can be referred to as closed systems, i.e., self-sustaining systems. This self-sustainment is a success factor of entrepreneurial ecosystems. For example: "Spillovers are positive feedback, and all engineers know that a system with positive feedback sometimes hits a tipping point in which it becomes self-generating or self- sustaining" (Isenberg, 2011, p. 9). Consequently, once EEs enter an upward spiral with net positive resource inflows into the system, they eventually become resilient to severe threats such as economic shocks (Spigel & Harrison, 2017). While researchers have taken different approaches to this dynamic process, they agree that causalities play a central role in ecosystem success (e.g., Isenberg, 2011; Stam & Spigel, 2016). In fact, Stangler and Bell-Masterson (2015) noted that the interconnectedness of elements in an EE is just as important as the elements by themselves. Consequently, literature has shown that a dynamic process view needs to take high interdependence into account. To conclude, the delineation of key terminology has shown that a focus on ambitious entrepreneurs, a dynamic process view of EE development, and the recognition of high interdependence constitute distinctive characteristics of EE theory. 2.3 Conditions for Successful Entrepreneurial Ecosystems 2.3.1 Definition of EE Success In this subchapter, we will specify what success means in the case of EEs and subsequently outline the underlying conditions for success. As discussed, some scholars regard innovation as the ultimate outcome of the EE model (Stam, 2015). In contrast, others emphasize that entrepreneurship does not need to be innovative to be successful (e.g., Kirzner, 1999; Isenberg, 2011). However, researchers agree that sustainability is essential for entrepreneurial ecosystems to flourish. In general, the sustainability of EEs describes a self-reinforcing process of continuous new venture creation, which challenges the status quo in a virtuous cycle of positive externalities (Isenberg, 2011; Sussan and Acs, 2017). Hence, high-growth successful venture creation ultimately leads to a sustainable, resilient ecosystem. Researchers and organizations have developed many frameworks to define the underlying processes and elements that contribute to EE success. In the following, we will thus outline emerging patterns and shared ideas.
Literature Review: Entrepreneurial Ecosystems 9 2.3.2 EE Frameworks in Comparison Two prominent frameworks from Isenberg (2011) and the World Economic Forum (WEF) (2013) describe the fundamental principles for cultivating EEs. Their frameworks share the pillars of facilitative policy, markets, financial and human capital, culture, as well as supports. Moreover, the WEF explicitly states the pillars of education and training in its framework, which remain implicit in Isenberg's work (Appendix A). Building on these works, Stam and Spigel introduced the Entrepreneurial Ecosystem Model (Appendix B) to add causality to the pillars mentioned above (2016, p. 9). The model separates input factors of EEs into framework and systemic conditions. Specifically, framework conditions describe the leading contextual causes of value creation, which comprise social, informal institutions, and physical enablers or inhibitors of human interaction. Contrastingly, systemic conditions are more closely related to the heart of the organization, such as leadership or finance. In their model, entrepreneurial activity, "the process by which individuals create opportunities for innovation" (p. 2), is an intermediate output, leading to innovation as the ultimate outcome via upward causation. Notably, the authors mitigated the risk of oversimplifying the causalities by also acknowledging downward and intra-layer causation. Consistent with the previously outlined process view on the entrepreneurial ecosystem, Spigel and Harrison (2017) have added a dynamic life cycle perspective to the EE model through their Process Theory Framework. Hence, over its life cycle, an EE either develops into a resilient ecosystem (i.e., success) or a weakened ecosystem (i.e., failure). The authors characterize a thriving ecosystem through high levels of connectivity, the creation and flow of entrepreneurial resources, and a net positive inflow of resources into the ecosystem (Appendix C). This model emphasizes the importance of the accessibility and recycling of resources, as well as learning from failure. Moreover, "the flow [functionality] of resources in the ecosystem is as relevant for its success as their presence [strength]." (Spigel & Harrison, 2017, p. 163). This statement implies that, for example, the existence of venture capitalists is not sufficient; they must also be approachable. Furthermore, the recycling of resources fosters EE growth (Isenberg, 2011; Mason & Brown, 2014; Stam, 2015). For instance, successful entrepreneurs usually stay in their ecosystem after they exit a startup, and thus become routine entrepreneurs or mentors. In EE literature, experts frequently describe mentors as dealmakers, i.e., people who have the know-how and connections necessary to support young companies (Isenberg, 2011; Mason & Brown, 2014). Lastly,
Literature Review: Entrepreneurial Ecosystems 10 entrepreneurial failure contributes to value creation in the form of knowledge recycling. For instance, failure results in knowledge creation as well as the redistribution of financial and human resources. In summary, successful EEs comprise high connectivity between all elements, which results in mutually beneficial spillovers and recycling of knowledge. Consequently, this will yield a net positive inflow of new, accessible entrepreneurial resources. 2.4 How to Measure the Success of an EE After the comparison of conducive conditions for EE success, we will summarize different approaches to success measurement before reviewing the EE approach's policy implications. As discussed, EE success is defined as a process through which an ecosystem becomes self-sustaining (Isenberg, 2011). Hence, where performance measurement is concerned, there is no straightforward, measurable goal due to the multifaceted underlying conditions. Consequently, challenges for success-measurement include tailoring measurements to the relevant audience and the underlying motivation. For example, performance indicators would differ based on underlying motivations, such as increasing exit multiples versus increasing innovation (Stangler & Bell-Masterson, 2015). Additionally, data is often not available at the desired level of analysis, and those who measure EE performance need to find a balance between too much and too little measurement (Stangler & Bell-Masterson, 2015; Mason & Brown, 2014). The Global Entrepreneurship Index (GEI) is a rather traditional form of EE success measurement and comprises the pillar of total entrepreneurial activity (TEA). However, it does not separate high-growth entrepreneurship from self-employment and is thus negatively correlated to economic growth and development (Acs et al., 2017). Further, Spigel and Harrison (2017) refuted the circular argument of new firm formation as a success measure and called for a more process-based measure for EE success. A more promising indicator for successful EE formation seems to be the number of unicorns in a region. For instance, Acs et al. (2017) have shown that this measure can outpace sophisticated measures of self-employment, such as the TEA (Acs et al., 2017). Hence, the authors identified the number of unicorns per 10 million inhabitants as a suitable measure for EE performance (Acs et al., 2017). Similarly, Isenberg (2011) proposed that "one new high potential venture entering the system every year, for about every 50,000 to 150,000 people" (p. 9), should be used as a rule of thumb.
Literature Review: Entrepreneurial Ecosystems 11 Lastly, several publications have emphasized the importance of benchmarking in the EE context. Intuitively, benchmarking should be performed across locations and across time within ecosystems, because ecosystems do not evolve in a vacuum (Isenberg, 2011; Stangler & Bell-Masterson, 2015). For example, the Four Pillars of EE Vibrancy suggest that benchmarking should focus on density, fluidity, connectivity, and diversity (Stangler & Bell-Masterson, 2015). First, density comprises measures that utilize the regional population as the denominator, thus providing relative measures. Second, fluidity describes the ease of the combination of existing resources to produce novel outcomes. Third, connectivity utilizes figures such as the number of spinoffs or number of connections per dealmaker (Mason & Brown, 2014). Finally, diversity includes measures such as upward and downward income mobility and the net value of immigration versus emigration. Therefore, these four pillars propose an approach similar to the process view of Spigel and Harrison (2017). The Four Pillars of EE Vibrancy also support Isenberg's (2011) assertions that none of the interrelated factors of an EE should be regarded in isolation. Consequently, dynamic, process-oriented measures that take into account the trajectory across locations and over time are the best suitable measures of EE success. 2.5 Implications for Policymakers In 2011, Isenberg described the entrepreneurial ecosystem strategy as the fastest way to achieve economic growth and prosperity. Thus, it is essential to understand how policy can facilitate positive externalities while mitigating adverse results. In fact, according to academic literature, the following two pitfalls are the most common among policymakers. First, every EE is unique. Therefore, policies that, for example, aim to imitate Silicon Valley, set themselves up for failure (Isenberg, 2011; Mason & Brown, 2014; Stam & Spigel, 2016). Instead, policy should take a tailored approach based on the individual assets of the ecosystem. Second, entrepreneurship and non-entrepreneurship policy need to be separated. According to Isenberg (2011), using the same policy for high-growth startups and SMEs neglects the EE's complexity and inhibits growth. Consequently, the above-mentioned need for individual EE policies is indicative of the decreased importance of top-down governmental interventions. In fact, if policies are not tailored to the individual EEs, they can hinder their development and thus impede innovation (Stam & Spigel, 2016). Further, researchers have criticized policies that target isolated elements of the complex system (e.g., Isenberg, 2011). Therefore, experts suggest a shift from market-focused, top-down intervention towards bottom-up policymaking
Literature Review: Entrepreneurial Ecosystems 12 (Mason & Brown, 2014). More simplified: "[T]here is a big difference between building a highway system and telling people where to drive" (Isenberg, 2011, p. 4). In short, governments should focus on bottom-up relational support instead of top-down transactional support. Over the past decade, the focus of policy has changed from increasing the startup rate (quantity) towards improving the potential of entrepreneurs (quality) (Isenberg, 2011; Spigel & Harrison, 2017). Thus, the literature review yielded three guiding principles of policy implications. First, policymakers should assign a high priority to HGFs and ambitious entrepreneurs (Isenberg, 2011; Stam & Spigel, 2016). While HGFs make up a very small percentage of the total number of firms, their contribution to job creation and economic growth is disproportionately large. Besides the direct effects, HGFs also create desirable spillover effects contributing to the generation of knowledge, connectivity, and ideas (Isenberg, 2011; Mason & Brown, 2014). Second, a good policy should make market entry as easy as possible and, at the same time, allow for a natural selection approach to resource allocation, i.e., making high potential ventures survive while letting low potential ventures fail fast (Isenberg, 2011). Third, in order to achieve good results quickly, policymakers should direct resources to specific, concentrated locations to create environments for ambitious entrepreneurship (Isenberg 2010; Isenberg, 2011; Mason & Brown, 2014). Another logical consequence of bottom-up policies in an evolving ecosystem is a time lag in the development of policies. Moreover, a bottom-up approach implies that the government does not tell entrepreneurs where to innovate (Isenberg, 2011; Spigel & Harrison, 2017). Thus, there is usually little regulation when disruptive innovation first occurs, which encourages its development. However, once a disruptive innovation becomes established, the degree of regulation increases until it reaches a tipping point, from where it starts to inhibit innovation through over-regulation. Sussan and Acs (2017) described this phenomenon as an inverted U-shape. However, previous research has shown that the involvement of private sector advisors can mitigate the risk of over- regulation (Isenberg 2011; Sussan and Acs, 2017). Lastly, depending on the execution of EE policy, it can result in net positive or negative externalities. On the one hand, EE policy can lead to negative externalities, such as regional inequalities in the form of gentrification or increased cost of living. On the other hand, good policies can lead to social value creation, which is a lot larger than the individual value that entrepreneurs create for themselves (Stam & Spigel, 2016; Spigel &
Literature Review: Entrepreneurial Ecosystems 13 Harrison, 2017). For instance, if success stories of HGFs are shared, they may inspire an entire generation of new HGFs. In this context, we defined the main challenge that policymakers face as the mandate dilemma. It describes the phenomenon that the government has the mandate for holistic market intervention in the EE, but not the competence. In contrast, the private sector has the required competence, but no mandate (Isenberg, 2011). Consequently, it is advisable to establish an independent third-party organization that is not owned by a specific institution and represents the interests of all relevant stakeholder groups (Isenberg, 2011). This self-liquidating organization should exist until the respective EE becomes self- sustaining. In summary, a nurturing policy should assume a facilitative role. Moreover, a conducive policy for ambitious entrepreneurship should foster an environment where the natural selection of the most promising companies can take its course. Furthermore, quality over quantity of entrepreneurship should have high policy priority (Stam & Spigel, 2016). Lastly, the private sector should be involved to remove unnecessary regulatory barriers. Thus, the mandate dilemma can be resolved by introducing independent third-party organizations that pool stakeholder interests. 2.6 Role of Universities The continuous addition and exchange of diverse and skilled talent is an essential contributor to a successful EE (Isenberg, 2010; World Economic Forum, 2013; Stam & Spigel, 2016). Especially universities have been identified as catalysts (Guerrero et al., 2016) for the successful emergence of EEs. Moreover, they can help to foster the entrepreneurial culture and connectivity within EEs (Isenberg, 2010). The appropriate unit of analysis for EEs is often a source of disagreement among researchers, ranging from a global to a single building level (e.g., Acs et al., 2017). Consequently, Acs et al. (2017) suggested focusing on knowledge instead of physical frontiers for the characterization of ecosystems. For instance, researchers suggested that universities constitute EEs by themselves, as they are connectors of education, research, and knowledge-transfer. Researchers have also described universities as subsystems in a larger context of country or city-level ecosystems (Guerrero et al., 2016; Hayter, 2016). These "nested, loosely organized academic and non-academic intermediaries [...] work collectively and strategically to promote and support academic entrepreneurship" (Hayter, 2016, p. 652).
Literature Review: Entrepreneurial Ecosystems 14 Notably, university ecosystems comprise not only academic players such as students and faculty but also entrepreneurs in residence, academic advisors, or partner organizations (Hayter, 2016). Hence, this proximity facilitates knowledge and work transfer within this network, which contributes to high rates of entrepreneurship and, thus, the success of ecosystems (Guerrero et al., 2016; Hayter, 2016). The resulting creation of conducive environments for entrepreneurship results in the evocation of a self-reinforcing virtuous cycle, leading to the attraction of more entrepreneurial capital (Guerrero et al., 2016; Hayter, 2016). Consequently, a variety of researchers have described universities as promising sources of disruptive innovation (World Economic Forum, 2013; Guerrero et al., 2016; Hayter, 2016; Acs et al., 2017; Jahanian, 2018). As discussed, universities produce valuable entrepreneurial talent and thus contribute to new venture formation (World Economic Forum, 2013). Moreover, universities' innovative contexts encourage sustainable, entrepreneurial resource creation through a unique combination of advanced research and training (Guerrero et al., 2016). Therefore, incumbent companies often invest in university research to benefit from new ideas as well as human capital resulting from the process (World Economic Forum, 2013). For instance, US funding for university research and development (R&D) increased from $2.4 billion to $4.2 billion, between 2006 and 2016 (Jahanian, 2018). However, universities do not only serve as talent matchmakers but also incubate innovative ideas themselves (Hayter, 2016; Acs et al., 2017). Consequently, their efforts often lead to the development of spin-off firms, patents, research publications, and consulting services (Cohen et al., 2002). Further, universities can influence innovation beyond the boundaries of their organizations: "[U]niversity leaders have a leading role to play in helping the workforce adapt to the disruptive technologies, ensuring that the new economy works for everyone" (Jahanian, 2018). Moreover, universities share open source information more frequently than companies and thus constitute essential information intermediaries in EEs. For instance, according to Isenberg (2010), they contribute to knowledge-sharing through information platforms and conferences. Hence, knowledge-transfer does not only occur formally through education, but also informally through "business plan competitions, networking events, 'TED talks' by successful academic entrepreneurs, hack-a-thons, and entrepreneurship clubs" (Hayter, 2016, p. 649). In summary, universities facilitate network effects that contribute to strong EEs though the "effective distribution of knowledge, lab[o]r, and capital" (Hayter, 2016; Stam & Spigel, 2016, p. 9).
Literature Review: Entrepreneurial Ecosystems 15 In addition to open source innovation-sharing, universities usually comprise a fruitful ground for innovation as they bring together perspectives of people from diverse cultural backgrounds. For instance, history has shown that immigrants have especially high entrepreneurial propensities and are twice as likely to start a company than the native community (Stangler & Bell-Masterson, 2015; Guerrero et al., 2016). Consequently, universities have started initiatives to attract and incentivize underrepresented minorities to join their organizations. Thereby, universities encourage the exchange of diverse opinions (Jahanian, 2018). Such initiatives are in line with the position of the WEF (2013), who advocates for increased diversity in universities and the workplace. As discussed before, a vibrant ecosystem attracts a net positive inflow of resources. However, critics emphasize how the potential of immigrant talent in universities can only add limited value to the local entrepreneurial ecosystem, if the talent emigrates post- graduation due to a lack of facilitative conditions for entrepreneurship in the local environment (Isenberg, 2011). Consequently, universities are valuable sources of disruptive innovation, open access resources, and diverse skillsets. However, their ability to serve as catalysts for the ecosystem can only be of use if the framework conditions in the ecosystem are facilitative.
Literature Review: Cultivated Meat 16 3 Literature Review: Cultivated Meat After the review of key concepts and implications from EE literature, we will analyze the state of the industry (SOI) of cultivated meat before we move on to the research method. In the following, we will define the key terminology, outline the history of the technology, and provide a triple bottom line overview of the potential impact of cultivated meat. 3.1 History and Key Terminology Undoubtedly, humans need to consume protein for their bodies to function properly (Brazier, 2018). More specifically, protein enables the regulation of cells, tissues, and organs. While many different natural sources of protein exist, animal protein is the most prevalently consumed protein source in our modern society. It is therefore not surprising that the global meat market is worth over $1.7 trillion, feeding a world population of over 7.7 billion people (Bashi et al., 2019; United Nations, 2019). For instance, the six most prominent incumbents in the US meat industry, such as Tyson Foods or Cargill, already account for over $60 billion of the total meat market value (CB Insights, 2019a). In comparison, the alternative protein market is worth $2.2 billion. Hence, it only constitutes a marginal proportion of global protein consumption. In order to keep up with the demand, the meat industry slaughters over 72 billion land animals every year. The inclusion of fish in the equation increases this number to roughly 1.3 trillion animals annually (Zampa, 2018). However, due to continuous population growth, the world's capacity to supply enough meat from traditional animal agriculture will soon reach its limits (Hancox, 2018). Thus, the need for a product alternative of similar nutritional components and taste has emerged, and consequently, meat substitutes have entered the market (Appendix D). Subgroups of this protein category include (a) plant, (b) fungus, (c) insect, and (d) cell-based meat alternatives (Godfray et al., 2019). Within the (a) plant-based protein sector, companies such as Beyond Meat have recently gained immense popularity. According to CB Insights (2019a), the valuation of Beyond Meat multiplied to almost $5 billion since its initial public offering in May of 2019, when the company value was still at $1.5 billion. While most companies in the plant-based protein industry utilize plants such as soy as the main ingredients of their products, the newest biotechnological innovations facilitate the development of (b) fungus into meat-resembling alternatives made from so-called mycoprotein (Quorn, n.d.; Godfray et al., 2019; Bashi et al., 2019).
Literature Review: Cultivated Meat 17 Another approach to fill the gap between supply and demand within the protein industry comprises the (c) processing of insects into various products such as insect flour, or meat alternatives (Van Huis et al., 2013). While circa 80% of countries already consume insects on a regular basis, consumer acceptance for this protein source remains hard to achieve in the remaining countries (Van Huis et al., 2013). The last alternative protein source and focus of the subsequent ecosystem mapping is (d) cultivated meat. While cultivated meat consists of animal tissue identical to conventional meat, its production does not require the raising and slaughtering of animals. Instead, it comprises the extraction of a small number of cells from an animal through a biopsy under anesthesia and the subsequent cultivation in a laboratory setting (Emery, 2018; Mosa Meat, n.d.). Market leaders in the cultivated meat industry include Memphis Meats, Mosa Meat, and BlueNalu. Notably, meat has been the predominant source of protein consumed by developed countries for several decades. Hence, consumers frequently use the terminologies of meat and protein interchangeably. However, since the beginning of the 21 st century, the perception of the meat industry has slowly transformed into the protein industry (Bashi et al., 2019). For instance, according to a McKinsey & Company industry report, there has been a sharp increase in the public's interest in animal protein alternatives. Further, Bashi et al. (2019) have uncovered that the main drivers of changes in consumer behavior are health and environmental concerns, as well as animal welfare. To some, the connection between alternative proteins and reduced environmental impact might not be straightforward. However, Professor Joseph Poore from Oxford University conducted one of the most comprehensive studies on modern agriculture, which included 40,000 farms as well as 1,600 processors, packaging types, and retailers (Carrington, 2018). According to Carrington (2018), Poore concluded that "[a] vegan diet is probably the single biggest way to reduce your impact on planet Earth, not just greenhouse gases, but global acidification, eutrophication, land use, and water use." Despite this, individuals such as Bill Gates (2013) are aware of the dilemma that we might not be able to satisfy the increasing demand for meat, "[y]et we can't ask everyone to become vegetarians." Hence, cultivated meat constitutes an alternative that satisfies the same needs, while only using a fraction of the resources required in conventional meat production. Consequently, Emery (2018) identified cultivated meat as a disruptive technology with the potential to solve "one of the greatest challenges of the 21st century" (p. 1). Namely, to feed the growing population's hunger for more meat with limited resources.
Literature Review: Cultivated Meat 18 While in this context, we will refer to the previously-mentioned protein source as cultivated meat, industry experts also call it clean, in vitro, lab-grown, synthetic, or cell- based meat (Lynch & Pierrehumbert, 2019). The first-ever cultivated meat burger was revealed in 2013 by Mark Post, professor of vascular physiology at Maastricht University. Mark Post also holds the position of CSO of the Dutch company Mosa Meat, which has revolutionized the alternative protein industry and inspired the rise of many more companies (Rodríguez Fernández, 2020). Three years later, in early 2016, Memphis Meats introduced its first cultivated meatball. Subsequently, in 2017 the world's first cultivated chicken and duck were showcased, followed by Aleph farms who released their new-to-the-world cultivated steak in 2018 (Liberatore, 2016; CB Insights, 2019a; Rodríguez Fernández, 2020). The technology behind such innovative products has been described by Mosa Meat (n.d.) as follows: After the extraction of a few stem cells from the muscle of an animal (called myosatellites hereafter), the myosatellites are placed in a medium containing nutrients and naturally-occurring growth factors. These myosatellites then proliferate into trillions of cells in a bioreactor. Finally, they merge to form larger muscle fibers, which can, thereafter, be processed like conventional pieces of meat. While this process is still costly and time-consuming, cultivated meat companies continuously work hard to find scalable solutions for fast commercialization. However, expensive ingredients, such as the fetal bovine serum (FBS), which constitutes a crucial ingredient for some cell-cultivation technologies, have hindered the reduction of production costs so far (CB Insights, 2019a). Nevertheless, the promising potential of large-scale production of cultivated meat, to replace factory farms and slaughterhouses, motivates researchers to continue searching for solutions for the common obstacles (CB Insights, 2019a). Additionally, cultivated meat is superior to its plant-based competitors in several domains, such as digestibility, amino acid balance, and taste (Appendix E). Further, genetic engineering allows for enhancements and adaptions of the nutritional benefits of cultivated meat, compared to conventional meat (Bashi et al., 2019). Finally, compared to traditional meat, cultivated meat can be produced more efficiently. For instance, it takes a farmer seven weeks to raise 20,000 chickens, while cell-cultivation technologies allow the cultivation of a million times as much chicken meat over the same time (Emery, 2018).
Literature Review: Cultivated Meat 19 3.2 Triple Bottom Line Evaluation After the delineation of the history of the cultivated meat industry, we will take a triple bottom line approach to evaluate the overall impact of this nascent technology, as well as its future potential. For this purpose, we conducted a spotlight analysis of the (a) economic, (b) societal, and (c) environmental impact of cultivated meat, as depicted in Figure 1 below. Figure 1: The Triple Bottom Line Framework Source: Own adaptation based on the concept of Elkington, 1994 Firstly, from an (a) economic standpoint, cultivated meat aims to compete with the global conventional meat industry. Noteworthily, cultivated meat has not yet been commercialized. Therefore, retail profits are not subject of analysis. Instead, the most crucial factors are costs, efficiency, and time to market. For the future, MarketsandMarkets (2019) predict that the cultivated meat market will be valued at $214 million by 2025, reaching $593 million by 2032. With this being only a small fraction of the aforementioned $1.7 trillion valuation of the meat market, it is open for interpretation whether this number is satisfactory under consideration of population growth and resource scarcity (Bashi et al., 2019). Moreover, cultivated meat has not yet achieved cost- and price-parity with conventional meat or plant-based meat. For example, according to McKinsey & Company, the current cost of producing cultivated meat, measured by $/kg of 100% protein, is $300 compared to $2/kg of 100% soy protein (Bashi et al., 2019). However, according to historical data, there is reason to believe that achieving price-parity is realistic in the near future. For
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