Bibliometrics-based decision trees (BBDTs) based on bibliometrics-based heuristics (BBHs): Visualized guidelines for the use of bibliometrics in research evaluation
Year: 2019
Type: article
Abstract: Fast-and-frugal heuristics are simple strategies that base decisions on only a few predictor variables. In so doing, heuristics may not only reduce complexity but also boost the accuracy of decisions, their speed, and transparency. In this paper, bibliometrics-based decision trees (BBDTs) are introduced for research evaluation purposes. BBDTs visualize bibliometrics-based heuristics (BBHs), which are judgment strategies solely using publication and citation data. The BBDT exemplar presented in this paper can be used as guidance to find an answer on the question in which situations simple indicators such as mean citation rates are reasonable and in which situations more elaborated indicators (i.e., [sub-]field-normalized indicators) should be applied.
Source: Quantitative Science Studies
DOI: 10.1162/qss_a_00012
Author: Lutz Bornmann
Institution: Max Planck Society
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $800
OpenAlex ID: W2996684141