E3S Web Conf.
Volume 292, 20212021 2nd International Conference on New Energy Technology and Industrial Development (NETID 2021)
|Number of page(s)||6|
|Section||New Energy Economy and Energy Blockchain Application|
|Published online||09 September 2021|
Research on the Package Feature Selection of Talent Attracting Factors in International Trade in Guangdong-Hong Kong-Macao Greater Bay Area
1 School of Finance and Economics, Guangdong University of Science and Technology, Dongguan, China
2 School of Public Administration, Xinhua college of sun yat-sen University, Tianhe, Guangzhou, China
3 School of Management, Xinhua college of sun yat-sen University, Tianhe, Guangzhou, China
4 Tourism Business College, Guangzhou Panyu Vocational and Technical College, Guangzhou, China
* Corresponding author: firstname.lastname@example.org
This paper designs a survey questionnaire based on the Guangdong-Hong Kong-Macao Greater Bay Area’s demand for talents in international trade, adds job types, filters through package features, and performs feature filtering with the error filter criteria set in this paper, and conducts logistic regression analysis on talent types, so as to realize the classification and dynamic analysis of talents. The dynamic needs of various types of talents in international trade in the Guangdong-Hong Kong-Macao Greater Bay Area are drawn, and specific measures such as increasing salaries and benefits, reducing living costs, providing housing subsidies, solving children's employment problems, and ensuring quality of life are proposed for the development of international trade talents. Reducing the cost of talent migration can promote them to make more contributions to the Guangdong-Hong Kong-Macao Greater Bay Area. This will help the Guangdong-Hong Kong-Macao Greater Bay Area government to attract outstanding international trade talents and formulate detailed and feasible strategies, which has certain reference significance.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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