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Identifying the technological knowledge depreciation rate using patent citation data: a case study of the solar photovoltaic industry
Author(s)
Date Issued
2021
Date Available
2023-08-14T11:52:22Z
Abstract
Technological knowledge can be created via R&D investments, but it can also be eroded through depreciation. Knowing how fast knowledge depreciates is important for various reasons for practitioners and decision makers alike; especially if it comes to questions regarding how to “recharge” knowledge production processes within an ever changing global system. In this study, we use patent citation data to identify technological knowledge depreciation rates by adjusting for exogenous citation inflation and by disentangling the preferential-attachment dynamics of citation growth. Solar photovoltaic (PV) technology is employed as a case study. The rates calculated with our method are comparable to the few available estimates on technology depreciation rates in the PV industry. One of the advantages of the proposed method is that its underlying data are more readily available, and thus more replicable for the study of the knowledge depreciation rates in other relevant technology fields.
Sponsorship
European Commission Horizon 2020
Science Foundation Ireland
Other Sponsorship
National Nature Science Foundation of China
Type of Material
Journal Article
Publisher
Springer
Journal
Scientometrics
Volume
126
Start Page
93
End Page
115
Series
UCD Spatial Dynamics Lab Working Paper Series
Copyright (Published Version)
2020 Akadémiai Kiadó, Budapest, Hungary
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
File(s)
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Name
Liu Grubler Ma and Kogler 2021 Identifying the technological knowledge depreciation rate using patent citation data - The solar photovoltaic industry.pdf
Size
1.33 MB
Format
Adobe PDF
Checksum (MD5)
06f806adb1b43d77d2522566422de352
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