Methoden vergelijken

	Systematische literatuurstudie met tijdsneden	Systematische Literatuurstudie
Vakgebied	Scientometrie	Scientometrie
Familie	Process / pipeline	Process / pipeline
Jaar van ontstaan	2010s	1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines)
Grondlegger	Adapted from systematic review methodology; temporal segmentation formalized in bibliometric practice (Zupic & Cater, 2015; Aria & Cuccurullo, 2017)	Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004)
Type	Systematic review variant with temporal segmentation	Evidence synthesis methodology
Oorspronkelijke bron	Zupic, I., & Cater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472.	Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401.
Aliassen	temporal systematic review, period-based systematic review, chronological systematic review, time-segmented literature review	SLR, systematic review, evidence synthesis review, structured literature review
Verwant	5	5
Samenvatting	A time-sliced systematic literature review applies the rigorous search, screening, and synthesis protocol of a standard systematic review while dividing the retrieved corpus into discrete temporal periods — time slices — and analyzing each period separately. This design reveals how a research field has developed across time: which topics emerged, grew, or declined; how key authors and journals shifted; and how intellectual structures evolved from one era to the next.	A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic.