Open AccessTalent Demand Forecasting Model with Practicability Based on the Theory of ARIMA
Author(s) -
Bozhong Yu
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/632/5/052025
Subject(s) - autoregressive integrated moving average , demand forecasting , on demand , supply and demand , econometrics , economics , demand characteristics , computer science , microeconomics , time series , operations management , mathematics , statistics , commerce , machine learning
The urban development depends on talents, meanwhile, different types of talent demand affects the development direction of a city. The actual talent demand is affected by many factors, and can reflect the economic capacity of a city to a certain extent. Our goal is to predict the potential talent demand of A-City in the next three years. First, we establish a multiple regression model and come to the conclusion that the relationship between talent demand and job demand is lineal and desired profession has a positive effect on talent demand while desired educational background has a negative effect on talent demand. Based on the above analysis results and the theory of ARIMA, we establish a talent demand forecasting model. Finally, we predict the talent demand and three factors of A-City in the next three years.