We investigate how the interplay between academic researchers’ and innovators’ entrepreneurial intentions and open innovation activities fosters their market commercialization activities. We qualitatively analyse five case studies of European research consortia to propose potential theoretical mechanisms that limit or abet market commercialization activities. Our results show that inbound and coupled open innovation activities compensate for lower entrepreneurial intentions among scientists. However, establishing partnerships remains challenging, particularly in pre-prototyping phases. Noticeably, our findings point towards prosocial motivation as an enabler to make innovation outcomes more publicly available.

@en

Up until now, the question of how innovation policy deals with agency and power distributed between human and artificial intelligence has not been addressed conclusively so far. The systems failure approach often used to motivate and justify innovation policy broadly acknowledges and addresses problems stemming from the emergence and use of AI. Yet it insufficiently addresses three questions that make AI a game changer for innovation policy, i.e. (1) how to deal with ethical issues of using AI, (2) how AI-driven innovation policy can stimulate research processes leading to either exploitation or exploration, and (3) whether and how deep learning of AI might crowd-out human decisions. To solve these issues we suggest that innovation policy uses a visible hand in the context of AI, i.e. (1) to involve clearly legitimized stakeholders in the design of ethical guidelines - and avoid outsourcing this important task to expert councils, (2) to use policy measures that can distinguish between exploration and exploitation of AI, and (3) to employ a coordinated approach of involving stakeholders in several steps ensuring the implementation of their shared values in AI-driven decision processes. The invisible hand of innovation policy can neither rely on policy actions nor market relationships only but has to rely on their joint use.@en

Policymakers and analysts are heavily promoting data marketplaces to foster data trading between companies. Existing business model literature covers individually owned, multilateral data marketplaces. However, these particular types of data marketplaces hardly reach commercial exploitation. This paper develops business model archetypes for the full array of data marketplace types, ranging from private to independent ownership and from a hierarchical to a market orientation. Through exploratory interviews and case analyses, we create a business model taxonomy. Patterns in our taxonomy reveal four business model archetypes. We find that privately-owned data marketplaces with hierarchical orientation apply the aggregating data marketplace archetype. Consortium-owned data marketplaces apply the archetypes of aggregating data marketplace with additional brokering service and consulting data marketplace. Independently owned data marketplaces with market orientation apply the facilitating data marketplace archetype. Our results provide a basis for configurational theory that explains the performance of data marketplace business models. Our results also provide a basis for specifying boundary conditions for theory on data marketplace business models, as, for instance, the importance of network effects differs strongly between the archetypes.
@en

Scholars’ balancing act between research and application leads to trade-offs between commercial and research output. Yet what some scholars may consider as poles apart might lead to super-additive outcomes for others. Based on a survey carried out at three leading European universities of technology we investigate the influence of scholars’ research orientation and networks on their output productivity. Our results point to a very specific group of ambidextrous scholars that is comparatively small. The scholars in this group are able to successfully balance research and application. In contrast, all scholars focusing on either pure basic or pure applied research face a trade-off between publications and innovations. In general, our findings suggest that the output productivity of all scholars is the higher the better their research orientation fits with their network activities. In particular, ambidextrous scholars rely on effectively accessing and utilizing their network to increase commercial and research output.

@en

Recent disruptions caused by the digital age and increasing calls for Responsible Research and Innovation have overturned supposed certainties of how to assess research and innovation. This paper shows that: (1) Responsible Research and Innovation requires a system approach; and (2) digital transformation brings additional complications and opportunities. Particularly, privacy issues as well as the risk of discrimination and manipulation severely increase in the digital age. Simultaneously, big data and internet of things solutions offer multiple opportunities of following research and innovation processes more closely, thereby offering chances to sufficiently integrate the values of all stakeholders.@en

This paper proposes to use Virtual Reality scenarios to explore the reaction of stakeholders within an innovation process in the context of the introduction of robots working in close collaboration with users. The goal is to design the system upfront in such a way, that it is not perceived as a threat to the worker or his/her job. Within the responsible research and innovation approach, the introduction of new technology needs to be accompanied by a careful investigation of the thoughts and feelings of all stakeholders. Especially workers who are currently not working with robots but their workspace is currently undergoing an Industry 4.0 driven transformation, experience fear, that this new technology will make their jobs redundant. On the other hand, it can be observed, that successful robot interaction processes, on the one hand, increase the overall productivity, but also can enhance human well-being. The feeling of 'teamwork' with the artificial intelligence entity can develop to be equally positive and motivating. To be able to design future workspaces which will result in a 'teamwork' perception instead of the 'fear' perception, the use of VR can be applied.

@en

In the applied sciences and in engineering there is often a significant overlap between work at universities and in industry. For the individual scholar, this may lead to serious conflicts when working on joint university–industry projects. Differences in goals, such as the university’s aim to disseminate knowledge while industry aims to appropriate knowledge, might lead to complicated situations and conflicts of interest. The detailed cases of two electrical engineers and two architects working at two different universities of technology illustrate the kinds of problems individual scholars face in university–business collaborations. These cases are based on qualitative interviews and additional data and demonstrate that, while value conflicts emerge on the organizational level, it is primarily the individual researcher who must deal with such conflicts. This analysis adds to existing studies in two ways: first, it explicitly addresses normative issues framed in terms of ethical and social values, thereby going beyond the common social-science perspective of university–business collaboration. Secondly, it provides qualitative insights, thereby identifying details and issues not apparent in quantitative studies. In particular, it is evident that university–industry collaborations are prone to value conflicts not only in research but also in education and job training.

@en

Prior analyses of face-to-face contacts in collaborations have focused on one substitute only. Instead, we analyse various potential substitutes for face-to-face contacts in collaborations. Based on 45 interviews with academics from five leading European universities of technology our findings show that face-to-face contacts are closely intertwined with other mechanisms of coordination and communication for collaboration, particularly modern communication tools, proximity, and brokerage. Generally, to add personal and social proximity to their collaborations academics in our sample rely on face-to-face contacts. In their relationships with industrial partners, face-to-face contacts remain crucial to overcome cognitive and organizational distance. Yet when working with their peers, a number of partial substitutes for face-to-face contacts exist, knowingly combinations of temporary geographical proximity and modern communication tools. Moreover, PhD students can play a crucial role as junior brokers, overcoming a lack of face-to-face contacts between partners jointly supervising them while working in different locations.

@en

The development and deployment of technologies depend upon collaborations concurrently relying on proximity between partners. By employing publication data of German nanotechnology, we augment former findings on the relationship between proximity and collaboration in three ways. First, we shed light on how the various forms of proximity affect different stages of collaboration. Particularly, we split geographical proximity into pure physical and systemic proximity. By doing so, we can show that pure physical proximity plays a role early on, as it positively influences the formation of collaborations. In contrast, systemic proximity affects collaborations later on by inducing higher output. Second, innovation systems shape collaboration networks. We learn that specific features of publicly funded German research organizations influence the formation and output of collaborations via organizational proximity or a lack thereof. Third, cognitive proximity has by far the strongest magnitude of effect on both the formation and the output of collaborations. Particularly, existing partnership being cognitively diverse have a lot of potential. Therefore, research policy and university management might consider to stimulating current partnerships, being cognitively different.

@en

We look into the question whether heterogeneity stemming from research orientation, gender, or disciplinary and cultural differences with their PhD supervisors helps or hampers academics’ careers. Based on a sample of 248 academics at two leading European universities of technology, we combine multinomial logit models and sequential logit models to understand career advancement. Our results show that heterogeneity stemming from research orientation is helpful. Academics who bridge between the quest for fundamental understanding and socio-economic relevance attain career success. Yet heterogeneity stemming from gender hinders careers: female academics face problems securing tenured positions and full professorships. Mentor–mentee heterogeneity only helps in early career transitions, but hampers advancement later on. Our insights offer suggestions to policymakers, university managers, and academics, because they help to identify promising academics, the right support for sitting staff members, measures correcting for gender imbalances, and can inform strategic choices regarding research orientation and PhD supervisors.

@en

The proximity framework serves to analyse and understand how collaborations form and develop over time, and how these affect innovation and learning. The framework has inspired and informed empirical studies in several contexts, contributing to our understanding of the dynamics of dyadic collaborations, industrial clusters and districts, and regional innovation systems, to name but a few. Recent conceptual and empirical advances have called attention to the role of personal proximity and social proximity in such collaborations. In addition to other forms of proximity, these two dimensions could make up the glue that holds knowledge networks together. In the introduction to this special issue, we elaborate upon this proposition, setting out a point-of-departure for the three empirical studies collected in this issue. We summarize the findings of these papers, and develop a research agenda from those findings that may guide proximity researchers to novel research problems and useful research designs.

@en

Entrepreneurs are often envisioned as small private start-up firms operating against all odds. Here, we investigate how in the context of the Triple Helix various entrepreneurs form communities and drive institutional and technological change. To theoretically shape a socialized view of entrepreneurship, we use the Triple Helix approach. Our empirical basis is a highly regulated sector driven by various agents, i.e. the Dutch energy system. As it depends very much on natural gas and relies less on renewables compared to similar countries, we analyse two cases where entrepreneurs drove the uptake of renewable energy sources. In our paper, we investigate how entrepreneurs from the private, public and academic sectors drive the evolution of the Triple Helix. From our results, two general features of entrepreneurship in the Triple Helix emerge. First of all, private stand-alone enterprises do not mirror entrepreneurs at large. Second, networks of various entrepreneurs are much more common and much more complex than usually anticipated. More specifically, we find that there are rather divergent developments in Dutch energy systems. Whereas in the case of Aardwarmte Den Haag, a number of key players collaborated in order to realize one specific technology, in the LochemEnergie case, we see a project-to-project approach supported by subsidies. In both cases, a variety of entrepreneurs from the private, public and academic sectors with different roles, goals, incentives, resources, knowledge and policy levers drive the development of their energy system. It depends on the actual situation on who has the incentives and resources to be in charge and act and to include others when it seems necessary. Entrepreneurs in such a set-up require particular skills including the ability to engage with their (knowledge) network, identify gaps, attract new participants and motivate the new and existing participants. Entrepreneurs managing these networks handle a whole range of semi-unpredictable actors and environmental factors that also influence each other; therefore, they can be defined as truly complex sociotechnological systems. As the development of local energy initiatives unfold along the way, entrepreneurs have to be flexible and open to organizational change. While large organizations such as municipalities or large multinational companies are usually less flexible, they might create space for smaller entrepreneurial activities by supporting individuals, start-ups or academics in finding novel solutions. At the same time, a major role for public entrepreneurs lies in stimulating and subsidizing entrepreneurs and their networks.The analytical framework provided here can be used to study the principles of the Triple Helix concept in a dynamic environment in which technological innovation requires the expertise and capabilities of multiple types of actors. Its function is not only to identify roles and types of entrepreneurs and their incentives, but to also assess which resources (knowledge, skills, subsidies) they can contribute to the initiative.@en

Previous studies investigating proximity and collaboration have not clarified personal elements, such as working or communication style. Here, we show that personal proximity—close similarity in terms of personal traits and behavioral patterns—substantially affects the whole life cycle of research collaborations. We conduct a multi-case study of Dutch nanotechnology researchers. We select our interviewees through a bibliometric analysis and focus on the most central Dutch nanotechnology researchers in the global network. Our results reveal that social proximity and temporary geographical proximity have indirect effects enabling potential partners to assess their personal proximity. Sufficient levels of personal proximity often make or break the deal, provided that partners’ cognitive and organizational proximity—which are major drivers of research collaborations—suffice. Introducing personal proximity to analyze research collaborations puts previous findings on proximity dimensions’ effect on collaboration in a new perspective.

@en