{"title":"Prediction of Talent Demand in Air Transportation Industry—Taking Yunnan as an Example","authors":"Jiaoyan Tang, Xinyou Liu","doi":"10.2991/assehr.k.211122.101","DOIUrl":null,"url":null,"abstract":"The scientific prediction of the future demand for air transportation talents is the basis of air transportation talent training planning. Based on the close relationship between air transportation employment and air passenger turnover, and the trend continuity of air passenger turnover, the talent density, trend extrapolation and regression analysis method were comprehensively used to quantitatively predict air transportation specialized talents in 2030 and 2040. The results showed that the employment number of air transportation in Yunnan Province would increase greatly in the future, and the talent density would continue to improve. Besides, the demand for air transportation specialized talents would also increase significantly. Currently, the enrollment scale of air transportation related majors in Yunnan colleges and universities basically meets the needs, while the structure of specialized talents in air transportation industry should be optimized.","PeriodicalId":298236,"journal":{"name":"Proceedings of the 7th International Conference on Social Science and Higher Education (ICSSHE 2021)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th International Conference on Social Science and Higher Education (ICSSHE 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/assehr.k.211122.101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The scientific prediction of the future demand for air transportation talents is the basis of air transportation talent training planning. Based on the close relationship between air transportation employment and air passenger turnover, and the trend continuity of air passenger turnover, the talent density, trend extrapolation and regression analysis method were comprehensively used to quantitatively predict air transportation specialized talents in 2030 and 2040. The results showed that the employment number of air transportation in Yunnan Province would increase greatly in the future, and the talent density would continue to improve. Besides, the demand for air transportation specialized talents would also increase significantly. Currently, the enrollment scale of air transportation related majors in Yunnan colleges and universities basically meets the needs, while the structure of specialized talents in air transportation industry should be optimized.