A Data-Driven Dynamic Programming Model for Research Position Demand Forecasting

Yongjia Xie, Dengsheng Wu (), Yuanping Chen, Wenbin Jiao and Jianping Li
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Yongjia Xie: Chinese Academy of Sciences
Dengsheng Wu: Chinese Academy of Sciences
Yuanping Chen: Chinese Academy of Sciences
Wenbin Jiao: Chinese Academy of Sciences

Annals of Data Science, 2017, vol. 4, issue 1, No 2, 19-30

Abstract: Abstract It has been worthy of notice that the number of scientific researchers has experienced a rapid growth in China. Meanwhile, the strict restriction to the total number and the position structure of researchers has exerted great pressure on the Chinese researchers. The decision makers have noticed this dilemma and a quantitative predicting result for decision support is in need. This paper puts forward a data-driven dynamic programming model to estimate the research position demand gap based on the thought of dynamic programming. This model fully considers the real practice of human resource management in scientific management in China. In the empirical study, the personnel data from 2006 to 2014, which are abstracted from the Academia Resource Planning system of the Chinese Academy of Sciences, are applied to the empirical analysis to estimate the human resource demand gap in the 13th Five Year Plan. The results show that there is a big demand gap of the research position on the whole in the next five years.

Keywords: Scientific research management; Dynamic programming; Human resource demand forecasting (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s40745-016-0095-7

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