01678nas a2200205   4500000000100000008004100001260001500042653002600057653001700083653002600100653002000126100002200146700002400168245010400192856007200296300001400368490000700382520106900389022001401458       2011                            d  c2011-05-0110aComplex organizations10aPeer effects10aResearch productivity10aSocial networks1 aCraig M. Rawlings1 aDaniel A. McFarland00aInfluence flows in the academy: Using affiliation networks to assess peer effects among researchers  uhttps://www.sciencedirect.com/science/article/pii/S0049089X10001985  a1001-10170 v403 aLittle is known about how influence flows in the academy, because of inherent difficulties in collecting data on large samples of friendship and advice-seeking networks over time. We propose taking advantage of the relative abundance of “affiliation network” data to assess aggregate patterns of how individual and dyadic characteristics channel influence among researchers. We formulate and test our approach using new data on 2034 faculty members at Stanford University over a 15-year period, analyzing different affiliations as potential influence channels for changes in grant productivity. Results indicate that research productivity is more malleable to ongoing interpersonal influence processes than suggested in prior research: a strong, salient tie to a colleague in an authority position is most likely to transmit influence, and most forms of influence are likely to spill over to behaviors outside those jointly produced by collaborators. However, the genders and institutional locations of ego-alter pairs significantly affect how influence flows.  a0049-089X