Abstract

In this paper, cluster analysis is used to obtain the similarity coefficients as well as measurement scales among marketing characteristic variables in order to find the degree of stickiness of corporate marketing accurately. In order to avoid the over-fitting problem in the process of marketing research based on cluster analysis, it is necessary to optimize the attribute dependence through a rough set base and further explore the application of cluster analysis in marketing research. In the research design of marketing professional talent cultivation by integrating intelligent data analysis, the cleaning of research data can avoid the problem of initial data null value as well as duplication, and the evaluation database and data mining process are explained in the research. According to the marketing professional talent cultivation standards, to determine the research evaluation indexes, and to research and analyze the marketing professional talent cultivation path under the integration of industry and education. The results show that the regression coefficient of teaching form and student satisfaction of marketing teaching is 0.302, and the significance level Sig value is 0.000 (<0.01). That is, the teaching form has a significant positive influence on the satisfaction of marketing majors individually. This study enhances the ability to integrate industry and education in vocational colleges and universities, driving the local economy and realizing a win-win situation between schools and enterprises.

Details

Title
Research on Talent Cultivation Path for Marketing Majors under the Integration of Industry and Education Based on Intelligent Data Analysis
Author
Wang, Yang 1 

 Guangzhou Panyu Polytechnic, Guangzhou, Guangdong, 511483, China 
Publication year
2024
Publication date
2024
Publisher
De Gruyter Poland
e-ISSN
24448656
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3191140211
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.