Dynamic Structures of Knowledge Production: Citation Rates in Hydrogen Technologies

Fuente: arXiv
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Main Authors: Dekker, David, Christopoulos, Dimitirs, McGregor, Heather
Format: Preprint
Published: 2025
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author Dekker, David
Christopoulos, Dimitirs
McGregor, Heather
author_facet Dekker, David
Christopoulos, Dimitirs
McGregor, Heather
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2502_00797
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Dynamic Structures of Knowledge Production: Citation Rates in Hydrogen Technologies
Dekker, David
Christopoulos, Dimitirs
McGregor, Heather
General Economics
Economics
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.
title Dynamic Structures of Knowledge Production: Citation Rates in Hydrogen Technologies
topic General Economics
Economics
url https://arxiv.org/abs/2502.00797