Dynamic Technology Adoption in a Hierarchical Network : A Structural Empirical Approach
Séminaire-midi CIREQ-Concordia 2017-2018
conjoint avec le Department of Economics, Université Concordia
salle H-1154 (Université Concordia, 1455, boul. de Maisonneuve ouest, 11e étage)
Responsable : Tatyana Koreshkova (Concordia University)
Abstract
We study the question of technology adoption in the setting of a high level programming language – Python, and model the adoption process from Python version 2 to version 3. Python 3 provides more advanced but incompatible features. The adoption of Python 3 faces not only the classical chicken-and-egg problem due to network effects, but also adoption costs due to a hierarchical network through dependency requirements. With a complete dataset of package characteristics for all historical releases and user downloads, we build and estimate a dynamic model of technology adoption where each package developer makes an irreversible decision to adopt Python 3. The rich dataset allows us to draw the complete hierarchical structure of the packages, and we group packages into various layers based on the dependency relationship. Then we test the effect of various policies on the diffusion of Python 3 adoption through the whole network.