Team:LMU-TUM Munich/Supporting Entrepreneurship




Abstract

Biotechnology entrepreneurship is important for bringing beneficial scientific discoveries to the awareness and use of society. Although iGEM is an open source competition that does not in itself focus on business creation, it begs to question what the possibilities could be if it did. Entrepreneurship uses the market to find a problem and solve it. By using business methods as a scaling method, biotechnology can provide solutions for a larger variety of problems and to a greater number of people. In sum, biotech entrepreneurship is a mechanism for spreading good ideas and making useful products available to those that need them.

Furthermore, understanding enabling factors in biotech entrepreneurship can help bring awareness to biotech and promote entrepreneurship for iGEM participants and scientists everywhere. Therefore, the aim of this research is to establish the most significant enabling factors in relation to biotech and synthetic biology (SynBio). From there, future steps can be made to promote entrepreneurship in the scientific realm.

The analysis will begin with a presentation of the hypothesis, research model and objectives. The next sections provide a qualitative and quantitative analysis of the research. The concluding sections involve a list of suggestions and next-steps on how the data can be used for entrepreneurship.

Research Question, Research Objective and Research Design

Our theory holds that if certain enabling factors exist for biotech business creation and success, then biotech businesses will be founded. If this is true, then further research is needed to understand the enabling factors in biotech entrepreneurship in order to further promote its success. We assume that the factors that facilitate business creation and biotech innovation also extend to the realm of biotech entrepreneurship.

Research Objective 1: Establishing a theoretically grounded framework to understand the enabling factors that facilitate entrepreneurship in biotechnology.

Research Objective 2: Substantiate the theoretical framework and investigate the motives, barriers and decision criteria that leads to business creation in biotechnology and SynBio.

Research Objective 3: Establish the most important factors that lead to or prevent business creation in biotechnology and synthetic biology within the context of iGEM.

Research Model

To answer the objectives, this research draws on a combined multi-method empirical study, linking a qualitative and quantitative approach to understand entrepreneurship in biotechnology and SynBio. By combining qualitative and quantitative data, the research benefits from the advantages of both approaches. Qualitative data can capture the causal process of a certain phenomenon and substantiate the hypothesis derived from literature in order to answer research questions behind the enabling factors in biotechnology entrepreneurship (Eisenhardt 1989, Eisenhardt and Graebner 2007, Miles and Huberman 1994, Yin 1984). On the other hand, quantitative data allows testing on a large scale as a greater spectrum of observations can be tested. This strategic combination will create a better understanding of significant factors in biotech entrepreneurship.

The next sections will establish 1) the background research used to develop the theory and structure the data collection, including literature and advising, 2) a qualitative research approach, 3) a quantitative research approach, 4) an analysis of the combined qualitative and quantitative data, a 5) a conclusion and discussion regarding enabling factors in biotech plus 6) suggestions for the biotech industry and iGEM to enable more scientists to found a company.

    • MODEL 1: Research Model**


Literature analysis

Advising

Once the paradigms of important factors were established for entrepreneurship, experts in biotech and entrepreneurship were contacted for further consultation. The advisors included academic advisors and professors in synthetic biology, representatives of BioM (the biotech cluster in Munich, Germany), entrepreneurial advisors from the startup accelerator TechFounders and current and past participants of iGEM. All of these advisors contributed to the research methodology as well as the quantitative survey and qualitative interview design.

Research Approach

First, 11 of qualitative interviews were held to better understand the factors that affected Founders and non-Founders from the iGEM population. Second, a quantitative survey was designed to analyze the significance of different variables in business creation in biotech (specifically in iGEM). From the survey a statistical analysis was performed to measure the degree to which the variables affected founding a business.

The survey analyzes current and past iGEM participants, who are working in relatively the same, with similar education levels, time frames and resources.

Potential Limitations of the Data

Although the sample size (n = 140) is decent for data analysis, a larger sample size could potentially provide better results. Furthermore, as there were only a handful of business founded from iGEM (less than 20), the sample size of Founders from iGEM remains small due to this limitation. However, this only strengthens the reasoning for conducting research on this topic, to understand why so few teams have founded businesses and what can be improved to make it more common in the future.

Qualitative Data Approach

For the qualitative data, 11 past iGEM participants were interviewed, 4 of which founded a business (Founders) and 7 who had not (non-Founders). The goal of the interviews was to understand the Founders/non-Founders decision process and the factors that influenced or barred the way to business founding. The chapter is organized 1) a list of interviews with Founders, 2) a table of the core questions and responses from the Founders, 3) a list of interviews with non-Founders and 4) a table of the core questions and responses from the non-Founders.

Founder Interviews

Analysis and Discussion of Founder Interviews

Analysis and Discussion of Founder Interviews

Quantitative Data

How we analyze the data

Results

Results: Qualitative Data Method

Results: Quantitative Data Method

Results: Summary

Conclusion and Suggestions to the iGEM community

References

This team completed LMU-TUM_Munich's survey on Entrepreneurship in the iGEM community.

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LMU & TUM Munich

Technische Universität MünchenLudwig-Maximilians-Universität München

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