Sunbelt XXXI International Network for Social Network ... - INSNA

Bringing Personalized Ties Back In: Their Added Value For Biotech Entrepreneurs And Venture Capitalists In Inter‐organizational NetworksPina Stranger, Alvaro; Lazega, EmmanuelOrganizational NetworksERGM/P*, Inter‐organizational Networks, Multiplexity, Knowledge Transfer, Biotechnology, Venture CapitalFRI.PM1Using a unique dataset collected in France among Biotech entrepreneurs and their venture capital investors (VCs), we measure the added value of personalrelationships at the interorganizational level. Our analyses show that when two entrepreneurs share a personal collaboration tie or a personal friendship tiewith a VC investor, the probability that they will have an advice tie and thus exchange tacit knowledge increases significantly. We confirm the importance ofthis kind of social embeddedness in the Biotech industry where personalized ties – as opposed to institutional and contractual relationships – at the interorganizationallevel had not yet been examined systematically. Our results suggest that strategies of personalization of exchanges are vital for interorganizationallearning. These strategies help entrepreneurs with access to resources, with participation in knowledge building and with co‐orientation ofactivities in this industrial sector.Bringing The Actor Back Into The Network: Examining The Relative Validity Of Actor Attribute‐adjusted Networks On Team PerformanceMurase, Toshio; DeChurch, Leslie A.Sports, Teams and NetworksTeam Performance, Teams, Group StructureSAT.PM2Much research on social networks focuses on the strength and pattern of ties, assuming that actors contribute uniformly to the patterning of networks. Weempirically examine the appropriateness of this approach by examining the relative predictive validity of socio‐cognitive networks calculated with and withoutactor attribute adjustments based on status and influence. We advance and test the core idea that in bounded team and multiteam networks, attributeadjustednetwork calculations lead to better predictions of network effectiveness than do standard calculations. Consider two, 6‐person teams with the samedegree of communication density. In one team interactions mainly occur among high status members whereas in the other team, interactions occur betweenhigh and low status members. The resulting density scores fail to account for the status differential of the actors and in doing so, constitute deficientoperationalizations of density. Thus, using unadjusted scores may lead to inaccurate inferences of network structure‐network effectiveness relationships.These ideas are demonstrated in a sample of 120, 6‐person networks performing a laboratory team task. Power and influence‐related attributes are assessedand used to adjust network indices such as density and structural holes. We then compare the efficacy of these adjusted indices of cognitive, affective, andbehavioral socio‐cognitive networks to non‐adjusted indices in predicting the performance of team networks. Discussion and future directions will be provided.