Diffusion Models for Peer-to-Peer (P2P) Media Distribution: On the Impact of Decentralized, Constrained Supply.

Author List: Hosanagar, Kartik; Han, Peng; Tan, Yong;
Information Systems Research, 2010, Volume 21, Issue 2, Page 271-287.
In peer-to-peer (P2P) media distribution, users obtain content from other users who already have it. This form of decentralized product distribution demonstrates several unique features. Only a small fraction of users in the network are queried when a potential adopter seeks a file, and many of these users might even free-ride, i.e., not distribute the content to others. As a result, generated demand might not always be fulfilled immediately. We present mixing models for product diffusion in P2P networks that capture decentralized product distribution by current adopters, incomplete demand fulfillment and other unique aspects of P2P product diffusion. The models serve to demonstrate the important role that P2P search process and distribution referrals-payments made to users that distribute files-play in efficient P2P media distribution. We demonstrate the ability of our diffusion models to derive normative insights for P2P media distributors by studying the effectiveness of distribution referrals in speeding product diffusion and determining optimal referral policies for fully decentralized and hierarchical P2P networks.
Keywords: distributed systems; free-riding; mixing model of diffusion; P2P; peer-to-peer file diffusion; supply-constrained diffusion
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List of Topics

#249 0.207 network networks social analysis ties structure p2p exchange externalities individual impact peer-to-peer structural growth centrality participants sharing economic ownership embeddedness
#23 0.119 channel distribution demand channels sales products long travel tail new multichannel available product implications strategy allows internet revenue technologies times
#89 0.117 product products quality used characteristics examines role provide goods customization provides offer core sell key potential stronger insights design initial
#226 0.112 models linear heterogeneity path nonlinear forecasting unobserved alternative modeling methods different dependence paths efficient distribution probabilities demonstrate observed heterogeneous probability
#49 0.110 adoption diffusion technology adopters innovation adopt process information potential innovations influence new characteristics early adopting set compatibility time initial current
#187 0.078 learning model optimal rate hand domain effort increasing curve result experts explicit strategies estimate acquire learn referral observational skills activities
#131 0.073 media social content user-generated ugc blogs study online traditional popularity suggest different discourse news making anonymity marketing videos choices page
#134 0.072 users end use professionals user organizations applications needs packages findings perform specialists technical computing direct future selection ability help software