The role of research efficiency in the evolution of scientific productivity and impact: An agent-based model
Authored by Xiao-Pu Han, Zhi-Qiang You, Tarik Hadzibeganovic
Date Published: 2016
DOI: 10.1016/j.physleta.2015.12.022
Sponsors:
Chinese National Natural Science Foundation
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Model Code URLs:
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Abstract
We introduce an agent-based model to investigate the effects of
production efficiency (PE) and hot field tracing capability (HFTC) on
productivity and impact of scientists embedded in a competitive research
environment. Agents compete to publish and become cited by occupying the
nodes of a citation network calibrated by real-world citation datasets.
Our Monte-Carlo simulations reveal that differences in individual
performance are strongly related to PE, whereas HFTC alone cannot
provide sustainable academic careers under intensely competitive
conditions. Remarkably, the negative effect of high competition levels
on productivity can be buffered by elevated research efficiency if
simultaneously HFTC is sufficiently low. (C) 2015 Elsevier B.V. All
rights reserved.
Tags
behavior
Dynamics
systems
Science
H-index
Collaboration networks
Advantage
Citation
Metrics
Output