Heterogeneity and the Dynamics of Technology Adoption

Working Paper: NBER ID: w17253

Authors: Stephen P. Ryan; Catherine Tucker

Abstract: We estimate the demand for a videocalling technology in the presence of both network effects and heterogeneity. Using a unique dataset from a large multinational firm, we pose and estimate a fully dynamic model of technology adoption. We propose a novel identification strategy based on post-adoption technology usage to disentangle equilibrium beliefs concerning the evolution of the network from observed and unobserved heterogeneity in technology adoption costs and use benefits. We find that employees have significant heterogeneity in both adoption costs and network benefits, and have preferences for diverse networks. Using our estimates, we evaluate a number of counterfactual adoption policies, and find that a policy of strategically targeting the right subtype for initial adoption can lead to a faster-growing and larger network than a policy of uncoordinated or diffuse adoption.

Keywords: Technology Adoption; Network Effects; Heterogeneity; Dynamic Models

JEL Codes: C10; L10; O32


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
employees exhibit significant heterogeneity in both adoption costs and network benefits (J32)heterogeneity influences the likelihood of adopting the technology (L15)
employees with similar job functions and ranks (M51)preference for similarity in communication (L15)
employees gain substantial welfare from accessing a diverse network (J29)varied employee types enhance calling opportunities (J29)
targeted adoption policies focus on specific subtypes of employees (J68)faster and larger network growth compared to uncoordinated adoption strategies (D85)
equilibrium network benefits allow for policy simulations (D85)elucidate how different seeding strategies affect network evolution (D85)
heterogeneity in adoption costs and network benefits (D85)influences the likelihood of adopting the technology (O33)

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