The Construction Of Competency Model Based On Factor Analysis And Neural Network Model

As the recombination of communications industry and 3G licence issued in China, competition becomes fierce between the three major communication operators. Because of the communications industry strongly dependents on technology innovation,the requirement of technical staff those who have outstanding post competency is become bigger and bigger. Therefore, competence-based human resource management thinking can be used to the area of technical post in communications industry, and there is important theoretical and practical significance on the establishment of the competence model of technical staff in communication operators.Firstly, this research discussed the structure of the competence model of communication operators' technical staff by EFA,open questionnaire research method,semi-structural interview,experts discussion and literature research etc. After giving out formal questionnaires, we got a four-factor structure of the competence model of communication operators' technical staff by Principal Component Analysis with Software SPSS. With the purpose of making innovations and breakthroughs in validating competence model and establishing prediction competence model, this article presents a prediction competence model of communication operators'technical staff based on BP neural network model. construction,training and emulation show that the prediction competence model has predictive power and generalization ability,thus we can efficiently implement the integrated intelligent evaluation of the technical staff competence in communication operators, and we can offer a new artificial intelligence'method for the validation and evaluation of technical staff' competence in communication operators. In addiction,we also discussed the influence of demographics tested on the six factors. Tough three of the study,we get the main conclusions as follows:1,The structure of the technical staff competence in communication operators has six factors and sixteen competency items:Intercourse Character(Intercourse initiative,Cognitive empathy,Expression ability,Receptive ability); Emotion Character(Emotional regulation ability,Emotional stability); Thinking Characteristics (Deduced thinking,Induced thinking); Team Working Characteristics(Support,dependence); Organizational Identification (Satisfaction,Belongingness,Sense of honor); Achievement Orientation(Pursuit of excellence,Pursue of challenge).2,We successfully construct the prediction competence model of communication operators' technical staff With BP Neural Network Technique. Through network training and study,the actual output and desired output achieve consistent,it shows that the prediction competence model achieve the ideal condition. 3,Emulating the prediction competence model of communication operators' technical staff through artificial intelligence emulation technology. The result indicate that the predictive power and generalization ability of the prediction model are well.thereby,we can efficiently implement the integrated intelligent evaluation of the technical staff' competence in communication operators.4,There are significant differences on the general competency among different professional title; The different grade positions have significant difference in Emotion Character,Thinking Characteristics and Organizational Identification among different education,age and workingage.