Cooperation Without Coordination : Influence Dynamics and the Emergence of Synchrony in Inter-Organizational Networks

This paper explores the emergence of synchrony in cooperative inter-organizational networks. While
some research suggests that synchronizing organizational actions like product releases is a form of
collective behavior that generates advantages for organizations, most existing network theory focuses
on dyads and not the larger organizational groups where networked cooperation is relevant. As a
result, we know a lot about resource mobilization and information diffusion across dyads, but very
little about how cooperation occurs in larger networks where collective behaviors like synchrony are
important. Using a simple computational model grounded in prior research on inter-organizational
networks, this paper develops a theoretical framework linking temporal dynamics to network theory
that sheds light on the emergence of synchrony, why it emerges faster in some networks than others,
and how organizations can shape synchrony to their own advantage. Specifically, I find that
synchrony emerges from influence across network ties without the need for a central coordinator or
exogenous technology cycle. It emerges though a series of cooptation events across network ties
wherein social influence accumulates to synchronize some organizations with others. The magnitude
and time to reach synchrony varies predictably with features of network structure such as network size
(N), mean degree (K), and tie strength (e), although an unexpected finding is that clustering (CC)
diminishes synchrony by generating coalitions with rhythms that vary too widely. These dependencies
can be understood with reference to three mechanisms – accelerated, coalitional, and conflicting
influence – that shape cooptation dynamics. Finally, intentional coordination across interorganizational
relationships accelerates the time to synchronize the entire network, creating temporal
spillovers to non-coordinating organizations ; moreover, coordinating organizations benefit from
increased synchrony performance – i.e., they increase the relative likelihood that network
synchronization tips to their own underlying rhythm. The magnitude of this performance advantage
depends on network size (N) and mean degree (K), but not on tie strength (e) or clustering (CC).