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26 Seiten, Note: 1,3
2. Technology Transfer from Science to Industry
3. Academic Entrepreneurship
4. Technology Transfer Offices
5. What drives scientists to become entrepreneurs?
6. Research Design
6.1 Max Planck Society
6.2 Max Planck Innovation GmbH as a Technology Transfer Organization
7.1 Interview – Company A
7.2 Interview – Company B
7.3 Interview – Company C
7.4 Interview – Company D
9. Conclusion, Managerial Implications and Outlook
In the modern society there is an increasing recognition of science’s influence on economic growth. For example Feller (1990) states that universities are increasingly seen as “engines of economic growth” by governments.
Within the last decades universities have turned from focusing only on their two main missions, research and teaching, towards a third mission: commercialization (Etzkowitz, 1998).
This is mainly based on the fact, that universities’ incentive systems have begun to turn the “classical” system towards a commercialization driven system.
Hence, science-industry relations have evolved in various ways.
The most examined linkages between science and industry are patenting and licensing as well as academic entrepreneurship, but there are also other linkages such as consultancy, training and joint research (D’Este & Patel, 2007).
However, the most visible form of technology transfer from science to industry is academic entrepreneurship (Landry, Amara, & Rherrad, 2006).
Despite the fact that precise definitions of academic entrepreneurship vary within literature, the basic idea always remains the same: a scientist who founds a company based on its research results, a so-called spin-off.
Within the last years research organizations established so called technology transfer offices (TTOs), which shall support technology transfer from science to industry.
TTOs manage and protect the intellectual property of a scientific organization and furthermore facilitate the commercialization of intellectual property gathered by research-based results through licensing, patenting or consultancy of spin-offs.
Research made huge contributions concerning drivers for scientists to become academic entrepreneurs. It was found, that drivers could be separated into macro and micro units of analysis (Di Gregorio & Shane, 2003).
Macro units focus on the influence of university and department policies on academic entrepreneurship.
Micro units address the personal level of a scientist and its propensity to found a spin-off. D’Este and Patel (2007) were able to provide empirical evidence that micro units have a stronger impact on academic entrepreneurship. Interesting findings in this area have been made for instance by Bercovitz and Feldman (2007) and Tartari, Perkmann, and Salter (2014) who both found, that the influence of peer groups on scientists’ attitude towards academic entrepreneurship is significant.
However, literature is still lacking studies regarding the influence of TTOs on scientist’s propensity to create a spin-off. In order to examine this lacking topic, the following question shall be answered:
“How is a scientist’s propensity to create a spin-off influenced by consultancy from technology transfer offices?”
In order to answer this research question I conducted four interviews at spin-off companies from the Max Planck Society, one of the leading research organizations in fundamental research. All examined spin-offs received support during their process of foundation by the Max Planck Innovation GmbH, the in-house technology transfer office of the Max Planck Society.
It can be revealed, that for those spin-offs support was of fundamental importance for the success of creation. Support is needed mainly in the beginning of the creation process and is of most importance in the areas of patent-management, market screening, legal aspects in general and contract-management.
In what follows I will first give an introduction and literature review regarding the topics of technology transfer from science to industry, academic entrepreneurship, technology transfer offices and the drivers of scientists to become academic entrepreneurs. Only then I will introduce the research design, present my results and eventually I will draw a conclusion reveal my study’s limitations and give an outlook for further research.
The main characteristic of universities has always been its autonomy. It grants scientists to operate independently within an “open-science” community and is ruled by the belief that their discoveries and/or developments should be placed in the public domain (Merton, 1973).
However, since the 1980s many universities have transformed themselves from the “ivory tower” towards universities strongly connected to industry and support their scientists in entrepreneurial behavior.
This is because the incentive system has begun to deviate from the “classical” academic incentive system, which is basically driven by freedom of inquiry, peer esteem, promotions, research grants and scientific prizes (Tartari & Breschi, 2012) towards a commercialization driven incentive system to fulfill their third mission “commercialization” besides “teaching” and “research”.
Commonly the increase of patenting and licensing activities by American universities is regarded as a consequence of policy changes such as the Bayh-Dole Act (Henderson, Jaffe, & Trajtenberg, 1998; Jaffe & Lerner, 2001; Jensen & Thursby, 2001). However Mowery, Nelson, Sampat, and Ziedonis (2001) found that the Bayh-Dole Act has not been the primary factor but the rise in biotechnology or computer science that changed research goals towards an industry- and/or commercialization related perspective.
Another reason was provided for instance by Cohen, Nelson, and Walsh (2002) and Siegel, Waldman, and Link (2003) who found evidence that fiscal budget constraints in developing and developed countries force policy makers to impose higher efforts in technology commercialization via patenting or licensing on universities.
Hence, universities and its scientists face the pressure to devote more effort to technology commercialization in various ways.
Most of academic literature focuses on technology transfer from science to industry whereby intellectual property rights are exploited via academic entrepreneurship (spin-offs), patenting and incomes from licensing agreements or royalties (D’Este & Patel, 2007). However other forms of technology transfer are also existent such as joint research, training and consultancy (D’Este & Patel, 2007). Two additional collaboration approaches are presented by (Klofsten & Jones-Evans, 2000), sponsored research and contract research.
A meta-analysis by Perkmann et al. (2013) provides an overview on the engagement of scientists in those different forms of collaboration. They show, that one of the most common ways of collaborating with industry is consultancy. However, depending on the geographical framework the percentage of academics involved in consultancy varies substantially. For instance in Ireland 68% of the academics were involved in consultancy (Klofsten & Jones-Evans, 2000) whereas in Germany only 20% of the academics where involved in consultancy (Haeussler & Colyvas, 2011).
The meta-analysis reveals as well that academic entrepreneurship is a way of collaboration which was mentioned amongst all examined studies although it was only used by a smaller percentage of academics (Perkmann et al., 2013). Academic entrepreneurship describes the process of founding companies based on research results and following Landry et al. (2006) academic entrepreneurship is the most visible form of technology transfer from science to industry.
The definition of the terms of an academic entrepreneur and academic entrepreneurship vary within literature.
The traditional definition of academic entrepreneurship, as for example given by S. A. Shane (2004), describes either a university spin-off or the university-industry transfer of research and/or technology and/or development in order to promote innovation.
Another traditional definition has been introduced by D’Este, Mahdi, and Neely (2010), who define an academic entrepreneur as an university scientist “who engages in the commercialization of the result of his/her research, largely by patenting and/or setting up a business” (D’Este et al., 2010, p. 2).
Barth and Schlegelmilch (2013) provide a meta-analysis of different definitions of academic entrepreneurs and academic entrepreneurship and find that the majority of academic entrepreneurship is represented by spin-offs or start-ups that refer to developments and/or innovative ideas that have been revealed at the university.
Therefore, within this work, the term “academic entrepreneurship” will refer to commercialization of research results by scientists in terms of founding a spin-off based on their research results.
The importance of spin-offs is not negligible.
For example S. A. Shane (2004) shows several advantages of a spin-off founded by an academic entrepreneur, as it encourages economic development, supports the university by accomplishing its third mission by enhancing the commercialization of research results, is a high potential company, and regarding the investors perspective of view a spin-off is more profitable than licensing to already established firms.
Zucker, Darby, and Brewer (1998) state that spin-off companies are beneficial for local economic development and that they support to locally agglomerate economies.
Another argument is provided by Wright, Clarysse, Lockett, and Knockaert (2008) who state that spin-offs generate local employment which is particularly referred to as high skilled employment.
Due to the increasing pressure regarding the fulfillment of the third mission and in order to facilitate technology transfer, many research organizations established technology transfer offices. Those technology transfer offices also support scientists in the spin-off creation process.
Technology Transfer Offices (TTOs) manage and protect the intellectual property of a scientific organization such as a university or research organization. The TTOs facilitate commercialization of intellectual property gathered by research-based results through licensing, patenting or management of spin-off creations.
Furthermore TTOs constitute an instrument to support scientists by avoiding potential conflicts of interest between their primary tasks of research and teaching and their commercialization activities (Debackere & Veugelers, 2005).
Another important function of TTOs is to help scientists to gather pre-seed R&D funding (Max Planck Innovation, 2015) and to reduce the asymmetric information problem by sorting unprofitable from profitable innovations (Debackere & Veugelers, 2005).
As I will focus on the aspect of academic entrepreneurship I will not further review TTOs regarding their activities in licensing and patenting, however a good overview on these topics is provided by Phan and Siegel (2006).
TTOs within literature are often criticized as they seem to fulfill the needs of large firms rather than those of small, entrepreneurial firms (Siegel, Waldman, Atwater, & Link, 2004) as they are typically focused on the cash maximization within a short-term perspective (Gideon D. Markman, Phan, Balkin, & Gianiodis, 2005). However Bercovitz, Feldman, Feller, and Burton (2001) state that U.S. universities keeping TTOs tend to have a higher level of science-industry relations. In contrast to this finding studies on TTOs in the European Union do not find distinct evidence on their effectiveness and influence on science-industry relations (Polt, Gassler, Schibany, Rammer, & Schartinger, 2001). A cause for those diverging research results might be the finding by Colyvas et al. (2002), who showed that technology transfer from universities did not take place through formal communication channels of the TTOs but rather through already existing networks between scientists and their respective contacts within industry.
Phan and Siegel (2006) state that technology transfer from science to industry is dependent on three basic factors: institutional, organizational and individual factors.
They also state that the importance of each factor on the effectiveness of technology transfer is likely to vary by “history, academic value system, and technological depth” (Phan & Siegel, 2006, p. 132) for the respective institution.
From the institutional perspective of view, Lockett and Wright (2005) make the conclusion that the expenditures of universities on intellectual property protection and the TTOs capabilities in supporting business development of spin-offs are positively correlated with spin-off creation.
In the following of their study Lockett and Wright (2005) did not find empirical evidence for the influence of the quantity of TTO employees or TTO’s age on the spin-off creation rate.
Another interesting research regarding the institutional factor was provided by Moray and Clarysse (2005) who conducted a study on spin-off creation at the Inter University Micro Electronics Centre in Belgium where they found that institutional changes, particularly the technology transfer policy, have a significant effect on the type of spin-off being created.
Regarding the organizational factor Gideon D Markman, Gianiodis, Phan, and Balkin (2005) found that the rate of spin-off creation is significantly dependent on the process speed of the TTO defined by the “fastness” a TTO, can commercialize research results. They show that this “fastness” is mainly dependent on three key factors: the resources of the TTO, the TTO’s competence to identify licenses and the participation of the inventors as academic entrepreneurs. Other organizational factors have been identified by Siegel et al. (2003): adequate faculty tenure, adequate royalty and equity distribution, promotion policies and the structure of the staff, as they state that a mixture of scientists, lawyers and managers is required for a high performing TTO.
Also Lockett, Wright, and Franklin (2003) contributed to the research on the organizational factors, as they found that universities and TTOs that had been more successful in creating spin-offs, had clearer spin-off strategies as well as greater expertise and networks.
The last factor influencing technology transfer is the individual factor which refers to the characteristics and motivators of the academic entrepreneur itself. Despite the fact, that research contributed very much regarding the question “what drives scientists to become academic entrepreneurs?”, as it can be found in the following section, there is still a lack in literature regarding the influence of TTOs on a scientist’s propensity to create a spin-off.
This is the contribution my work shall made; I want to give first insights into the influences of consultancy from TTOs on scientists. By this I want to examine how a scientist’s individual attitudes and its propensity to start a spin-off is influenced by the consultancy of a TTO.
Research revealed, that the distribution of science-industry activities among scientists is highly biased, resulting in a few scientists who are engaged in the majority of technology transfer activities (Agrawal & Henderson, 2002; Balconi, Breschi, & Lissoni, 2004).
Empirical studies on the determinants of academic entrepreneurship, such as the creation of spin-offs, separate in two different ways of analysis, analysis of the macro units that influence the spin-off creation, such as the university or the department, and analysis of the micro units, which refers to the individual level of the scientists (Di Gregorio & Shane, 2003).
Those studies focusing on the macro units tend to examine the influence of university or department policies on academic entrepreneurship.
In the following I will not have a further look at these macro units of analysis as D’Este and Patel (2007) were able to provide empirical evidence that scientist’s individual characteristics have a stronger impact on technology transfer rather than macro units.
Research regarding the micro unit can be subdivided into three different sections of analysis. Levin and Stephan (1991), Roberts (1991), Zucker et al. (1998) and S. Shane and Khurana (2003) for example examined the scientist’s research resources whereas S. Shane (2001) examined the impact of characteristics of the scientist’s research projects and findings on the propensity to create a spin-off.
The third approach that can be made within this micro unit is the scientist’s individual characteristics.
Bercovitz and Feldman (2007) argue that prior participation in knowledge transfer positively influences the fact to continue participating in knowledge transfer. However, they state that scientist’s behavior regarding spin-off creation is tremendously dependent on the local working environment. In particular this means, that scientists tend to adapt the behavior of the local working environment.
Bercovitz and Feldman (2007) also find that the behavior of the peer group, academic rank in their case, has a substantial impact on scientist’s attitude towards academic entrepreneurship as they state, that technology transfer behavior is calibrated by the behavior of the peer group. This is also found by Stuart and Ding (2006).
Tartari et al. (2014) further investigated on this influence of the peer group and argue that the main cause is social comparison, which means that scientists compare themselves with colleagues at a similar career stage, which leads to a motivation through rivalry and competition. However, Tartari et al. (2014) also found that the impact of social comparison becomes weaker “for individuals who are more senior and for higher-performing individuals” (Tartari et al., 2014, p. 24).
Landry et al. (2006) were able to provide empirical evidence that access to more financial resources (as long as they are not from private firms) and university-industry partnership grants programs have a positive impact on spin-off creation by using a regression model.
However, the findings regarding financial resources have to be further segregated as Landry et al. (2006) and Di Gregorio and Shane (2003) find that increasing financial resources from private firms have a negative impact on academic entrepreneurship. Furthermore findings by Di Gregorio and Shane (2003) as well as by Zucker et al. (1998) show that the local availability of venture capital had no significant influence on the spin-off creation.
Regarding the individual level of a scientist, Landry et al. (2006) showed, that scientists with more intellectual property assets, more experience in research, higher knowledge within consultancy, higher social capital assets, access to larger resources and larger laboratories are positively correlated with spin-off creation.
Another research approach was provided by Krabel and Mueller (2009) who investigated on the drivers of academic entrepreneurship within the Max Planck Society. They found that the most important factors of influence are a prior science-industry linkage via joint research, patenting activity (holding a patent increases the probability to become an entrepreneur by 4 times) and prior founding experience.
Krabel and Mueller (2009) furthermore state, that different channels of technology transfer seem to complement each other, and that scientist’s interpretation of the mission of science influences the likelihood of engaging in academic entrepreneurship. This aspect was further investigated by Tartari and Breschi (2012) who found that scientist’s likelihood to collaborate with industry is negatively influenced by the fear to lose their freedom of research.
In 2007, Zhang found that professors, followed by research scientists, academic directors, and executives, founded most start-ups and/or spin-offs regarding academic entrepreneurship in the United States of America. D’Este and Patel (2007) corroborate these findings as they provided empirical evidence that the academic status has a significant, positive impact on science-industry linkages, such as academic entrepreneurship. Krabel and Mueller (2009) also show, that directors at the Max Planck Society tend to have a higher spin-off creation rate. They give the explanation that this is caused by the improved network of directors which can be successfully, economically exploited. This topic can even be enlarged by the findings of Di Gregorio and Shane (2003) who showed that eminent research organizations tend to have more spin-off creations than other research organizations which is a result of a scientists personal attribute to have a higher credibility and hence positively correlated with academic entrepreneurship (Di Gregorio & Shane, 2003).
Another important finding by Zhang (2007) is that most companies were founded within scientific disciplines where science-industry cooperations are rather common such as Biosciences, Business, Chemistry, Engineering and Medical Sciences. This empirical finding is strengthened by research results of Landry et al. (2006) who state that a scientist’s knowledge assets in computer sciences and engineering rather than in other natural sciences have a positive impact on spin-off creation and by the findings of Krabel and Mueller (2009) who stated that academic entrepreneurship is more common within scientific disciplines where commercialization of research results is a common process.
But not only the scientific discipline is of importance, it was also found, that the spin-off creation rate is positively influenced by the degree of novelty of research (Landry et al., 2006).
Research also shows, that the number of publications, teaching hours per week (Landry et al., 2006) and former work experience in private firms (Krabel & Mueller, 2009) do not have any influence on academic entrepreneurship.
In order examine the influence of TTOs on academic entrepreneurs I conducted 5 hours of interviews with 4 different academic entrepreneurs who were involved in at least one spin-off creation process at the Max Planck Society.
My research is performed within the Max Planck Society (MPS) which is a publicly funded, formally independent non-governmental and non-profit association of German research organizations. The primary goal of the MPS is to complement research that is done within universities or other research facilities by conducting fundamental research in the natural sciences, life sciences, social sciences and the humanities.
Given the number of 18 Nobel laureates and more than 15,000 annual publications within renowned scientific journals it can be assessed that the MPS is a highly reputed research organization and consequently their scientists are a sample of high interest regarding the research question as they:
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