Reach for the stars: disentangling quantity and quality of inventors’ productivity in a multifaceted latent variable model

Federico Caviggioli () and Boris Forthmann ()
Additional contact information
Federico Caviggioli: Politecnico di Torino
Boris Forthmann: University of Münster

Scientometrics, 2022, vol. 127, issue 12, No 11, 7015-7040

Abstract: Abstract Star inventors generate superior innovation outcomes. Their capacity to invent high-quality patents might be decisive beyond mere productivity. However, the relationship between quantitative and qualitative dimensions has not been exhaustively investigated. The equal odds baseline (EOB) framework can explicitly model this relationship. This work combines a theoretical model for creative production with recent calls in the patentometrics literature for multifaceted measurement of the ability to create high-quality patents. The EOB is extended and analyzed through structural equation modeling. Specifically, we compared a multifaceted EOB model with a single latent variable for quality, and a two-dimensional model that distinguishes between technological complexity and value of invention portfolios. The two-dimensional model had better fit but weaker factor scores (for the “value” latent variable) than the unidimensional model. These findings suggest that both the uni- and the two-dimensional approaches can be directly used for extending research on star inventors, while for practical high-stakes assessments the two-dimensional model would require further improvements.

Keywords: Intellectual productivity; Creativity; Patent quality; Star inventors (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-022-04328-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:127:y:2022:i:12:d:10.1007_s11192-022-04328-3

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-022-04328-3

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().