Talent Recruitment Index System And Decision-making Model In The Internet Industry

Excellent talents are the core wealth of enterprises.Personnel recruitment is the key means for the company to continuously supplement fresh blood and continue to grow.High work intensity and rapid changes are the obvious characteristics of the Internet industry.How to select talents in line with the corporate culture and future development direction has become a difficult problem under the rapidly changing external environment.Talent recruitment is essentially a very complex decision-making problem.On the one hand,the talent recruitment index system used to measure the quality of talents needs to be determined according to the unique characteristics of each industry;On the other hand,due to the uncertainty,hesitation and fuzziness of human thinking,the recruiter's evaluation of candidates will be affected by many uncertain factors in subjective and objective aspects,which will lead to the fact that the accurate mathematical model in decision-making can no longer meet people's demand for the description of uncertainty and hesitation in actual recruitment.In addition,with the rapid development of the Internet industry,new jobs are emerging,such as database administrator,interaction designer and so on.A wide range of positions make the recruitment process in the Internet industry more and more complex.It is difficult to select the most suitable talents among the candidates by relying solely on a certain recruiter.To meet the demand of the description about hesitation and fuzziness and reflect the wisdom of group decision-making,this paper uses TOPSIS evaluation method in fuzzy language environment to select the most suitable person for company.The main contents of the research are as follows:(1)Based on the CIPP(Context Evaluation?Input Evaluation?Process Evaluation?Product Evaluation)model,a talent recruitment index system for the Internet industry is established.First,a talent recruitment index system is established by taking CIPP model as the framework,referring to a large number of relevant literature and combining with my own experience.Then,Delphi method is used for expert consultation to improve the reliability and scientificity of the index.According to experts' suggestions,the indicators are continuously improved to provide reference for talent selection standards in the Internet industry.(2)This paper studies the properties of hesitant fuzzy language term set,mainly including the related concepts,distance measurement and comparison methods of hesitant fuzzy language term set.In the comparison method of hesitant fuzzy language term sets,the hesitant index is introduced.On this basis,the comparison size and distance measurement method of hesitant fuzzy language term sets are defined from a new perspective.(3)TOPSIS(Technology for Order Preference by Similarity to an Idea Solution)method is applied to the hesitant fuzzy language environment in talent recruitment.In this method,based on the expert trust network,the improved PageRank algorithm is used to calculate the expert weight.This method solves the problem of artificial expert weight.Then,in order to reflect the wisdom of group decision-making,the group G2 method is used to determine the index weight.Finally,the ranking results of the schemes are obtained through the hesitation fuzzy language TOPSIS method to determine the best candidate for the post.