Dynamic Structures of Knowledge Production: Citation Rates in Hydrogen Technologies

TL;DR

This paper models the dynamic structure of patent citation networks to understand knowledge production in hydrogen technologies, revealing subdomain differences and organizational factors influencing innovation rates.

Contribution

It introduces a survival model linking network structure to technological improvement, highlighting Katz-centrality as a predictor of knowledge production in patent networks.

Findings

Distribution patents have the lowest knowledge production rate.

Katz-centrality outperforms subdomain classification in predicting citations.

Organizational differences affect invention and development in hydrogen technologies.

Abstract

We explore a dynamic patent citation network model to explain the established link between network structure and technological improvement rate. This model, a type of survival model, posits that the *dynamic* network structure determines the *constant* improvement rate, requiring consistent structural reproduction over time. The model's hazard rate, the probability of a patent being cited, represents "knowledge production," reflecting the output of new patents given existing ones. Analyzing hydrogen technology patents, we find distinct subdomain knowledge production rates, but consistent development across subdomains. "Distribution" patents show the lowest production rate, suggesting dominant "distribution" costs in $H_2$ pricing. Further modeling shows Katz-centrality predicts knowledge production, outperforming subdomain classification. Lower Katz centrality in "distribution" suggests inherent organizational differences in invention. Exploitative learning (within-subdomain citations) correlates with higher patenting opportunity costs, potentially explaining slower "distribution" development, as high investment needs may incentivize monopolization over knowledge sharing.