Conference Agenda

A key objective of innovation policies supporting large, syndicated projects for collaborative innovation is to facilitate boundary-spanning knowledge exchange across individuals, organizations, sectors, and regions. This exchange helps recombine existing knowledge and generate new insights. Despite policymakers increasingly adopting large-scale, often self-governing funding formats, empirical evidence on their effectiveness in fostering collaboration and innovation remains limited. To address this gap, we examine Innovation Spaces in Germany—large consortia of inter-organizational R&D projects under a shared funding initiative aimed at advancing the bioeconomy. We surveyed interpersonal knowledge-exchange networks within three Innovation Spaces, each focused on distinct technical domains: (i) bioeconomy in metropolitan areas, (ii) biobased textiles, and (iii) bioeconomy in marine environments. Using the situational organizational network analysis (SONA) approach, we analyzed knowledge exchange among 200 individuals spanning 56 projects and 170 organizations. Our network analysis investigates how governance practices influence collaboration levels and the extent to which learning relationships transcend individual project boundaries.

How do employers, competing in the same markets, come to cooperate? In dyads, cooperation evolves if pairs of actors interact repeatedly, because it is mutually beneficial. Third actors support such dyadic cooperation by circulating information on actors' past behavior allowing actors to avoid non-cooperators. This paper focuses on the role of these third actors in cooperative networks. It shows that third actors establish local hierarchies (transitive triads), rather than horizontal connections (cycles). Local hierarchies may reflect actors' desire to achieve prestige by connecting to higher-standing actors. Empirically, the paper analyzes how employers cooperate in networks by exchanging information on prospective employees (referral networks). It analyzes eight local referral networks in two different economic sectors based on exponential random graph models. Results show that triadic closure in these networks takes a hierarchical (transitive) form, rather than one of horizontal exchange (cycles). It also shows that employers in these triads are more prestigious. This finding is interesting considering the literature highlighting reciprocity as an important factor facilitating cooperation.

The social network literature shows that brokers accrue benefits from their position, but often overemphasize the informal organization and overlooks formal arrangements, in addition, it overwhelmingly focuses on individual performance, rather than collective outcomes. I argue that returns to brokerage are heterogenous across brokers and that this is as a result of the effects of the formal organization. I also suggest that understanding the effect of brokerage on collective outcomes is important as most of the relevant outcomes for firms are collective ones. I theorize that collective return to brokerage will be greater when associated with formal positions of leadership. I test this in the context of creative performance of projects using a network of French movie crews (comprising directors, producers, art directors, editors, and cinematographers) between 1996 and 2010. I find that the network position of the team leader—the movie director—has a positive effect on collective creative performance: leaders in a brokerage position enhance collective creative performance. I explore the implication of this theory for managers and discuss paths for future research.

Management literature highlights two key mechanisms for forming collaborative partnerships between firms: fostering trust through repeated interactions (relation-based mechanism) and building capabilities by expanding and specializing in diverse resource pools (resource-based mechanism). This study investigates how firms balance and transition between these mechanisms over time. While both mechanisms are integral throughout a firm’s development, their relative importance evolves. For firms with limited investment experience, relation-based mechanisms are essential for fostering trust and mitigating uncertainties. However, as firms accumulate experience and develop coordination capabilities, they increasingly rely on resource-based mechanisms to broaden and specialize their resources. This study examines this dynamic interplay using a longitudinal dataset of 3,401 venture capital (VC) firms in China from 1994 to 2023. By employing relational event models, we capture the endogenous processes underlying network formation. Findings reveal that relational reciprocity and inertia initially drive new syndicate formation, while geographical distance and industry overlap between VC firms pose barriers. However, as firms gain experience, they gradually reduce their reliance on reciprocity and inertia while seeking geographically distant or industrially overlapping partners. The paper goes beyond viewing partnership formation as a one-time consideration and offers a dynamic perspective in which firms balance relationship building with resource accumulation.

Network perception deals with the understanding of an individual´s perception of their surrounding networks and the comprehension of relational ties. The mental representations of relationships in a person´s mind can be captured by assessing an ego´s cognitive social structures (CSS). The deviation between actual and perceived networks, one´s cognitive network accuracy, plays a crucial role for the gathering of resources, goal attainment, and power in a social network. This means in turn, that the degree of accurately perceiving the social network, shapes interpersonal interactions. Structural mechanisms have been shown to influence social network patterns (e.g., advice seeking, friendship) among professionals in actual networks. Our study aims to shed light on the role of structural network patterns, such as homophily, triadic closure and preferential attachment, for perceived networks in professional settings. We introduce a novel perspective on CSS by exploring network mechanisms as drivers for (mis-) perceived social networks in the context of entrepreneurship through exponential random graph models (ERGM).

We recruited 93 students from three distinct classes, who were enrolled in an entrepreneurship course at a prestigious business school (response rate 89,25%). The survey participants were part of a long-term international MBA program tailored for senior corporate executives and experienced entrepreneurs, creating a unique data set. Our preliminary results indicate varying levels of homophily and triadic closure on the perceiver level, as well as accuracy depending on the personal attributes of the perceiver.