Identifying the technological knowledge depreciation rate using patent citation data: a case study of the solar photovoltaic industry.

Autor/inn/en	Liu, Jie; Grubler, Arnulf; Ma, Tieju; Kogler, Dieter F.
Titel	Identifying the technological knowledge depreciation rate using patent citation data: a case study of the solar photovoltaic industry.
Quelle	In: Scientometrics, (2020) 1, S.93-115 PDF als Volltext Verfügbarkeit
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0138-9130
DOI	10.1007/s11192-020-03740-x
Schlagwörter	Knowledge depreciation; Patent citation; Solar PV
Abstract	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.
Erfasst von	OLC
Update	2023/2/05