So sánh phương pháp

	Tổng quan tài liệu có hệ thống theo lát cắt thời gian	Phân tích đồng trích dẫn (Co-Citation Analysis)
Lĩnh vực	Trắc lượng khoa học	Trắc lượng thư mục
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2010s	1973
Người khởi xướng	Adapted from systematic review methodology; temporal segmentation formalized in bibliometric practice (Zupic & Cater, 2015; Aria & Cuccurullo, 2017)	Henry Small
Loại	Systematic review variant with temporal segmentation	Method
Công trình gốc	Zupic, I., & Cater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472.	Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269.
Tên gọi khác	temporal systematic review, period-based systematic review, chronological systematic review, time-segmented literature review	co-citation mapping, historiograph, direct citation, citation pair analysis
Liên quan	5	5
Tóm tắt	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.	Co-citation analysis is a method that identifies the intellectual structure of a research domain by examining how frequently pairs of documents are cited together in other publications. When two papers are frequently cited together in the literature, they are considered co-cited, indicating they are conceptually related or influential within the same research community. Developed by Henry Small in 1973, co-citation analysis maps the 'invisible colleges' of science—networks of researchers working on related problems—and reveals how knowledge domains evolve over time.