Measuring destabilization and consolidation in scientific knowledge evolution

Jiexun Li () and Jiyao Chen ()
Additional contact information
Jiexun Li: Western Washington University
Jiyao Chen: Oregon State University

Scientometrics, 2022, vol. 127, issue 10, No 11, 5819-5839

Abstract: Abstract The dynamic process of knowledge evolution can be divided into two routes: (1) new knowledge is cumulatively built upon past scientific achievements, and (2) the new replaces the old in a non-cumulative fashion. While existing measures such as citation counts are central to assessing the impact of articles and the viability of research streams, they do not quantify the two routes of knowledge evolution. In this research we develop two indexes, destabilization (D) and consolidation (C), that measure the effects that an article may have on the subsequent use of its predecessors—whether it consolidates or destabilizes the existing literature in terms of the influences on its predecessors’ future usage. Using a dataset of 45,616 papers from 24 premium business journals, this study shows that the D and C indexes are complementary to the citation count to measure the impact of a scientific article and capture the two directions of knowledge evolution.

Keywords: Knowledge management; Destabilization index; Consolidation index; Directions of knowledge impact; Network approach; Knowledge evolution (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-022-04479-3 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:10:d:10.1007_s11192-022-04479-3

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

DOI: 10.1007/s11192-022-04479-3

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 ().