July 2016 Download this article as a PDF

Q. How can a university drive an open innovation ecosystem?

A. Increasingly, universities are seeking ways to play a more proactive role in the transfer of knowledge from academia to industry (and vice versa) and to create opportunities for direct collaboration in innovation activities with diverse stakeholders. The concept of an "open innovation ecosystem" holds promise as a means for universities to play a driving role in creating such opportunities and realizing broader outcomes not possible under traditional models of university–industry interactions. The origins of the innovation ecosystem and open innovation concepts yield insights into how universities can play a driving role in future collaborations toward outcomes of common interest.

Scholars use the term “innovation ecosystem” to refer to a network of relationships through which information and talent flow through systems of sustained value co-creation (Russell, 2011). However, the simple context of industrial ecosystems characterized by large industries and a set of smaller entities working for them was not enough to accelerate knowledge generation and it has been deeply transformed with the evolution of the so-called “open innovation ecosystems”.

The role of open innovation in the triple helix model

Here, we define the notion of “openness” as “the pooling of knowledge for innovative purposes where the contributors have access to the inputs of others and cannot exert exclusive rights over the resultant innovation” (Chesbrough & Appleyard, 2007). In these ecosystems, other actors play also a crucial role, such as research organizations (both public and private) or public administrations. They are based on rich interactions among stakeholders where the majority of them (because subcontracting chains could also appear) adhere to open innovation principles (Chesbrough & Brunswicker, 2013), as areas of “coopetition” combining cooperation and competition connected to an institutional framework.

To be considered as open innovation, it is necessary to allow for free movement of ideas and to allow for co-creation of products and services with a flexible intellectual property regime. The capacity of analyzing to what extent an open innovation ecosystem is truly open remains based on very high-level qualitative perceptions. The open innovation process, as it was proposed by Chesbrough (2006), is not limited to enterprises or research centres; other actors play a prominent role as (organized) users’ communities, shaping the so-called user-driven open innovation (Gassmann, 2010). Under this concept of co-creation, selected users take active part in the innovation process and help in reducing the time-to-market of advanced products and services (von Hippel, 2005). 

The introduction of this new component in the innovation process represents an evolution of the well-known “triple helix” model (Etzkowitz & Leydesdorff, 2000), which is formed by a trilateral network of university–industry–government relations towards a “quadruple helix” model. Even if authors disagree on the exact definition of the quadruple helix model (e.g., Arnkil et al., 2010; Carayannis & Campbell, 2009; Füzi, 2013; MacGregor et al., 2009), all of them point to the user and community as the new protagonist to be addressed. In the university context, the appearance of “users” in the innovation process has been usually related to living labs. A living lab is an open innovation environment in a real-life setting, in which user-driven innovation is fully integrated within the co-creation process of new services, products and societal infrastructures (European Commission, 2009). Here, in the context of university-driven open innovation ecosystems, we refer to the approach in which university, industry, public administration, and user community collaborate in a shared (virtual or physical) space to addressing common interests.

University-driven open innovation ecosystems

Historically, industry-driven ecosystems appeared when one large company has the will and capability to attract many other actors (public and private) around it to facilitate and increase its rate of innovation. These companies usually provide platforms or subsystems where other companies or actors can develop their own products or services (faster and cheaper) but also to share ideas with other members of the ecosystem. The cases of Phillips in Eindhoven (The Netherlands), Siemens Deutsche Telecom in Munich (Germany), or Microsoft in Seattle (USA) are well known examples. Even when the origins of these industry-driven ecosystems had a clear geographical reference framework, their evolution (and the wide use of information and communication technology tools) has relativized the links to narrow territories to involve other actors located in other regions, even organized in “satellite ecosystems” located in other countries in order to improve access to local talent or to gain other specific advantages.

The same ideas can be applied to university-driven ecosystems generated when one worldwide recognized research university acts as an attractor for developing and transferring disruptive ideas through spin-offs or other partnerships with consolidated high-tech companies. The well-known cases of MIT in Boston (Massachusetts, USA) or Stanford University in Palo Alto (California, USA) are examples imitated in other places over the world. In the United Kingdom, something similar is happening in the Cambridge and Oxford universities, for example. Here, the driver depends on the high quality of deal flow of disruptive technologies coming from the university and the cultural context where these ideas could grow up. More recent cases in Sweden around Lund University or in Switzerland around the federal universities such as the École Polytechnique Fédérale de Lausanne in Lausanne or the Eidgenössische Technische Hochschule in Zurich constitute good examples of converging interests between national or federal authorities and the universities themselves with the support of industrial partners across the concept of a triple helix.

How universities can drive open innovation ecosystems

Elements put in place by universities to create long-term innovation ecosystems can be very different in form, function, and efficiency. In addition, important but difficult-to-measure challenges appear, such as the role that social networks can have in strengthening certain ties between the different components of the ecosystem. It is important to remember that when Henry Chesbrough introduced the term "open innovation" in 2003, he recognized innovation as a nonlinear phenomenon and shifted the focus of innovation away from companies and towards individuals.  For this perspective, the introduction of co-creation spaces in university campuses appears as a useful element to bring together students, scientists, entrepreneurs, and other industry partners that inspire each other with different perspectives on the same subject (Huhtelin & Nenonen, 2015). These supportive spaces with relevant services are needed to support open innovation with other stakeholders.

University-driven open innovation ecosystems also can promote informal technology transfer between academia and industry (Frenkel et al., 2015), in contrast to more formal licensing and collaborative agreements. Behind those processes lives the need to create a sense of pride in membership, which reinforces links between participants and generates long-term partnerships.   This idea underlies the philosophy of the so-called “co-location centres” of the knowledge innovation communities  launched by the European Institute of Innovation and Technology to enforce knowledge triangle activities with an emphasis on entrepreneurship (EIT, 2012). Therefore, as happens in knowledge innovation communities, it is necessary to incorporate other actors that support the funding of promising research results to convert them into commercial products or services. 

We understand a university-driven open innovation ecosystem  as having the following characteristics:

  • a stable network of actors led by a university in which industry, public administration, and a user community are also present at different levels of commitment
     
  • a common (virtual or physical) space in which know-how and talent flow through the adherence to open innovation principles
     
  • a common strategy and support tools driven by the university to accelerate immature technologies through systems of sustained value co-creation
     
  • a commonly accepted governance scheme where each actor keeps its independence but alignment of objectives is pursued
     
  • the university acting as the "glue" and taking responsibility for maintaining common infrastructures and programmes
     
  • emphasis on applied research and technology development and not on fundamental research
     
  • public support due to the not-for-profit entities  (universities) playing a driving role
     
  • technology specialization to ensure the smooth connection to research activities performed by the university
     
  • long-term commitments to ensure innovation activities merge with educational support (i.e., Master and PhD theses) aligned to industrial interests 
     

Thus, many different types of university-driven open innovation ecosystems could be created that will differ along specific dimensions. Through our research, we are currently developing and using the following eight dimensions to reflect several drivers for the ecosystem evolution.  Each needs to be simultaneously considered to understand and pursue the global aims defined for one specific ecosystem:

  1. Industrial empowerment:  the level of presence of large high-tech industries (or many technology-based small and medium-sized enterprises) with territorial commitments in terms of R&D, manufacturing facilities, interaction with other entities, and high-level educated (technical) employment. 
     
  2. Technology specialization: the existence of one or more key enabling technologies where public and private stakeholders of the ecosystem have demonstrable knowledge to develop and cooperate with.
     
  3. User involvement: the participation of innovative users (early adopters of products and services) who could participate in demonstrators, pilots, public procurement, etc. 
     
  4. Long-term commitments: the existence of formal agreements between actors in order to facilitate long-term cooperation (in education, research or innovation) based on common commitments with enough time to produce the intended results.
     
  5. Geographic scope: the links and impacts in one specific territory where public administrations could complement the actions performed by executing actors. 
     
  6. Public support: the availability of well-funded programmes for research and innovation from local, regional, or national administrations focused on the region or area where the ecosystem is located. 
     
  7. Openness: the existence of an open innovation culture embedded in key industrial or academic partners of the ecosystem to co-operate and co-create new products and services with other entities. 
     
  8. Sectorial specialization: the concentration of enterprises (and capabilities of public departments) in one specific industrial or entrepreneurial sector.  
     

Altering these dimensions in strategic ways may allow a university to drive an open innovation ecosystem towards individual and system-level goals. In our own research, the next step is to use such dimensions to evaluate and compare the performance of different university-driven open innovation ecosystems.

 

Acknowledgements

This Q&A was developed from a paper presented at the 2016 ISPIM Innovation Forum in Boston, United States of America, March 13–16. ISPIM – the International Society for Professional Innovation Management – is a network of researchers, industrialists, consultants, and public bodies who share an interest in innovation management.

 


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Keywords: ecosystems, Open innovation, public–private partnerships, technology transfer, university–industry cooperation