Design and Optimisation of Research Performance Allocation Based on Principal Component Analysis

Shengzhen Ding; Xuanyu Chen; Weipeng Chen; Shaofeng Chen

doi:10.54097/9dtecg85

Authors

Shengzhen Ding
Xuanyu Chen
Weipeng Chen
Shaofeng Chen

DOI:

https://doi.org/10.54097/9dtecg85

Keywords:

Principal Component Analysis (PCA); Research Performance Allocation; Variance Contribution Ratio; Data Normalisation; Bonus Allocation Scheme.

Abstract

In the field of scientific research, scientific and reasonable scientific research performance allocation can mobilise the enthusiasm of researchers to the greatest extent, which is conducive to promoting the effective transformation and vigorous development of science and technology. In this paper, for the problem of scientific research performance allocation, the model of principal component analysis is established to be used for programme design, and the 2023 scientific research achievement incentives of 20 scientific research post employees are evaluated. A reasonable scheme is formulated to determine the priority of bonus distribution by the ranking of scientific research achievements and to distribute the bonus by using the law of two-eighths.

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