A Research Funding Allocation Scheme in Multi-Layer Networks for the Growth of Talents

Talent training is a critical issue of social development. Particularly, talent training in research-oriented universities plays a key role in human resources management. However, achieving effective talent development with minimal macro-regulation becomes a challenging problem that has yet to be solved. As an administrator, the allocation of talent project funding is a viable point of focus, although it is difficult to analyze due to the complex structure of the universities. Inspired by the complex networks, we model the academic talent training problem in universities as a multi-layer network in this paper, and the characteristics which may influence the development of faculty are investigated. Then, the development of each scholar is fitted by a growth curve in the life-course pattern, based on which a research funding allocation scheme is proposed from the perspective of human resources managers. In the proposed scheme, the funding quotas of multiple levels are allocated to different colleges at the proper time to obtain the global optimization of talent training for the whole university. The simulation results show that the proposed funding allocation scheme can improve the final academic ability and the normalized score of outstanding scholars compared with those of the traditional proportion-based allocation scheme.