Working Paper Abstract
Diagnosing Adoption Dynamics: A Structural Approach to Diffusion Modeling
Abstract
Why do similar product launches succeed rapidly in some markets while languishing in others? Managers facing slow adoption often confront a diagnostic problem: the same aggregate curve can reflect different underlying causes. The problem may lie in population composition, weak signaling, delayed follower response, or the absence of visible social proof. Standard diffusion models are limited because they do not connect who adopts to how adoption unfolds.
This paper develops a coordination-game framework in which heterogeneous consumers balance social proof against aspirational imitation. The equilibrium yields a reduced-form specification with structurally interpretable coefficients. Persistence reflects mass-market conformity pressure; second-order dynamics capture delayed follower response to innovator behavior; shock responsiveness depends on early-adopter share and behavioral heterogeneity. This mapping turns adoption data into a root-cause diagnostic tool and links diagnostics to managerial levers, including early-adopter targeting, influencer partnerships, visibility design, and social-proof reinforcement. Parameter recovery is evaluated through Monte Carlo simulation, and the framework is applied across contexts ranging from linguistic innovation to online discourse. The contribution is a practical bridge between diffusion modeling and intervention design.
Keywords: adoption diagnostics, diffusion modeling, market heterogeneity, coordination games, social proof, consumer behavior