Open AccessThe Incentive System of the Subject Librarians in the University Library
Author(s) -
Chunping Wang,
Song Lili
Publication year - 2021
Publication title -
international journal of emerging technologies in learning/international journal: emerging technologies in learning
Language(s) - English
Resource type - Journals
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v16i03.20469
Subject(s) - incentive , subject (documents) , principal (computer security) , construct (python library) , task (project management) , information economics , computer science , empirical research , preference , selection (genetic algorithm) , microeconomics , knowledge management , business , economics , artificial intelligence , management , library science , mathematics , statistics , programming language , operating system
Based on the principal-agent theory, we introduce the specific task ability, construct the optimization model of the incentive system of the subject librarians, and discuss how to design the incentive system to achieve "win-win". According to the best incentive system, the variables are selected and measured by real data. An empirical model is established based on the econometrics theory, and the related theoretical conclusions are tested according to the empirical results. It is found that when the information is asymmetric, the best incentive system is composed of the optimal fixed income and the optimal value share. The higher the level of ability, managers should strengthen incentives and the subject librarians will increase the intensity of their efforts; the lower risk preference and the higher random selection, managers should weaken incentives and the subject librarians will reduce their efforts.