Julia Brennecke

The interplay between formal project memberships and informal advice seeking in knowledge-intensive firms: A multilevel network approach

Abstract In this study we investigate the interplay between knowledge workers’ formal project team memberships and their informal interactions from a multilevel network perspective. Conceptualizing knowledge workers’ affiliation with project teams as a membership network and their interactions as an advice network, we discuss how shared project team memberships as well as multiple memberships influence patterns of informal exchange in knowledge-intensive organizations. To empirically determine the impact of formal organization on informal exchange we apply exponential random graph models for multilevel networks to relational data collected on 434 R&D employees working on 218 project teams in a high-tech firm in Germany. Our results show that employees sharing project memberships create advice ties to each other but do not exchange advice reciprocally. In addition, we find a negative relationship between having a high number of project memberships and informally seeking or providing advice.

Duality Beyond Dyads: Multiplex Patterning of Social Ties and Cultural Meanings

Abstract The social and cultural duality perspective suggests dual ordering of interpersonal ties and cultural similarities. Studies to date primarily focus on cultural similarities in interpersonal dyads driven by principles such as homophily and contagion. We aim to extend these principles for sociocultural networks and investigate potentially competing micro-principles that generate these networks, taking into account not only direct dyadic overlap between interpersonal ties and cultural structures, but also the indirect interplay between the social and the cultural. The empirical analysis utilizes social and semantic network data gathered through ethnographic studies of five creative organizations around Europe. We apply exponential random graph models (ERGMs) for multiplex networks to model the simultaneous operation of several generative principles of sociocultural structuring yielding multiplex dyads and triads that combine interpersonal ties with meaning sharing links. The results suggest that in addition to the direct overlap of shared meanings and interpersonal ties, sociocultural structure formation is also affected by extra-dyadic links. Namely, expressive interpersonal ties with common third persons condition meaning sharing between individuals, while meaning sharing with common alters leads to interpersonal collaborations. Beyond dyads, the dual ordering of the social and the cultural thus operates as asymmetrical with regard to different types of interpersonal ties. The paper shows that in addition to direct dyadic overlap, network ties with third parties play an important role for the co-constitution of the social and the cultural. Moreover, we highlight that the concept of network multiplexity can be extended beyond social networks to investigate competing micro-principles guiding the interplay of social and cultural structures.

Knowledge Networks in High-Tech Clusters: A Multilevel Perspective on Interpersonal and Inter-organizational Collaboration

This study contributes to research on knowledge networks in high-tech clusters by adding a multilevel perspective. We show that while informal individual-level and formal organizational-level knowledge networks created by nested actors partly follow their own structural logic, they are at the same time logically intertwined. Interpersonal knowledge ties influence the maintenance of formal R&D collaborations and vice versa. To fully understand knowledge exchange in high-tech clusters it is therefore necessary to take a multilevel network perspective. Our study shows how these organizational-level and individual-level knowledge networks are mutually influential. Focusing on knowledge networks emerging in the context of regional clusters, we highlight how R&D collaborations among organizations impact the interpersonal exchange of knowledge among managers and researchers and vice versa. Taking a multilevel network perspective, we extend the existing understanding of knowledge networks by demonstrating that individuals who are willing to share their knowledge with colleagues belong to organizations involved in many R&D collaborations. These managers and their organizations thus benefit from each others’ central positions in the networks by having access to extensive sources of external knowledge. However, the opposite holds true when managers and researchers informally ask for knowledge from many of their colleagues. Our results show that extensive knowledge-seekers belong to organizations with fewer formal R&D collaborations. This can either be a sign of them trying to compensate for the lack of organizational-level collaborations or that they are harming their organizations’ chances to find collaboration partners. Finally, if two organizations collaborate on a joint R&D project there is a good chance that their managers and researchers also informally exchange knowledge with each other. Formal and informal knowledge networks thus overlap and open up the potential to realize synergies. We draw conclusions about whether individuals acquire knowledge independent of the opportunity structures provided by their organizations and thus fully exploit the possibilities provided by clusters.

The Firm’s Knowledge Network and the Transfer of Advice among Corporate Inventors

Knowledge networks consisting of links between knowledge elements and social networks composed of interactions between inventors both play a critical role for firm innovation. Taking a multilevel network approach, this study integrates research on the two types of networks and investigates how the knowledge network of a firm influences work-related interactions among its inventors. To this end, we associate inventors with specific knowledge elements in the firm’s knowledge network and examine how this association affects the inventors’ popularity and activity in a work-related advice network. Empirically, we combine survey data on 135 inventors working in a multinational high-tech firm with information derived from the firm’s 1031 patents. Results from multilevel exponential random graph models (ERGM) show that different dimensions of the inventors’ knowledge derived from the knowledge network shape their embeddedness in the advice network in unique ways. Our study demonstrates how structural features of ...