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

Validation Of A Network‐based Survey Instrument: Multilevel‐models Of Factor And Item Analysis Of Attribute Level DataWalker, Timothy D.; Hite, Julie M.; Sudweeks, Richard; Olsen, Joseph; Hite, Steven J.Collecting Network DataMethods, Statistical Methods, Network Data, Embeddedness, Validation Methods, Strong TiesTHURS.AM1This paper reports on the use of multi‐level (or hierarchical‐linear) models of confirmatory factor analysis and item‐response theory analysis to inform anetwork survey instrument validation study. Multilevel modeling (MLM) allows for the estimation of various group level effects in quantitative analysis. Innetwork settings MLM facilitates the identification, and quantification of various sources of nonindependence. By quantifying possible effects from actor, alter,dyadic, and sub‐group membership nonindependence on attribute data, MLM methods provide the researcher with more robust evidence of construct validityand scale reliability. This study compares the use of MLM models of factor and item analysis, with traditional tools of exploratory factor analysis and classicaltest theory item analysis. This comparison is accomplished in the context of a validation study of the TRENDS instrument. TRENDS is designed to test amultiplex theory of relational embeddedness and has been validated in an iterative process in a population of higher education faculty.Venture Capital Firms: Birds Of A Feather That Flock Together, Really?Gay, BrigitteNetwork DynamicsNetwork Dynamics, Small World, Centrality, Venture Capital, Syndication, Network ModelsTHURS.PM1Transaction networks in the venture capital industry are built up through the extensive use of syndicated investing. The cohesive nature of the networkstructure of venture capital (VC) syndicates has been demonstrated. Many studies emphasize that VC firms resemble “birds of a feather that flock together”and that VC syndicates networks form a “Small‐World” structure. These results by definition negate the fact that some firms may actually shape and controlthe whole network. The analysis of the power structure of VC networks has therefore been generally neglected. Moreover how network structure responds tothe cyclical nature of the VC industry has not been analyzed. We try here to decipher the power structure of VCs syndicates through the dynamic study of VClending in the biotech industry from 1988 to 2008. Our study design is grounded in a set of structural methods and models developed in social networkresearch and statistical physics. We demonstrate that though the macro‐feature of VC networking, cohesion and repeat ties among incumbent firms, stayhallmarks of VC syndication, the network structure continually changes under the control of hubs that deploy syndicate networks like flexible meshes to‘capture’ biotech companies. Importantly, different categories of hubs time their strategy and respond to technical change and the cyclical nature of the VCindustry differently. A unique finding is also that the network evolves from a “Small‐World” to a “Scale‐Free” architecture. This finding, and the use of anextensive set of network metrics, gives new insights into complex network dynamics.