کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1859478 | 1530556 | 2016 | 9 صفحه PDF | دانلود رایگان |
• We study the role of production efficiency (PE) and research topic selectivity in the evolution of performance in academia.
• In our model, agents compete to publish and become cited by occupying the nodes of an artificial citation network.
• Our agent-based model is calibrated by using datasets from the APS journals and the arxiv.org online preprint repository.
• Individual performance is strongly affected by PE, whereas topic selectivity cannot significantly enhance academic success.
• With even minimal reductions of research efficiency gaps, fairly profound boosts of scientific careers can be achieved.
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.
Journal: Physics Letters A - Volume 380, Issues 7–8, 22 February 2016, Pages 828–836