The Development Direction of the Citizenization of the Agricultural Migrant Population from the Perspective of Classified Citizenization
- DOI
- 10.2991/978-2-494069-31-2_335How to use a DOI?
- Keywords
- Classified citizenization; The Boston Matrix Method; Agricultural migrant of population
- Abstract
Economic and technological advances have caused numerous rural surplus laborers to leave the land and flock to the cities in search of survival opportunities. The transition of the agricultural population from farmer to citizen is a long and multi-factor process.This study selected the statistic of Chengdu City in the 2018 China Migrants Dynamic Survey (CMDS), and introduced the Boston Matrix Method to divide the agricultural migrant population of Chengdu into Cash cows, Dogs, Stars and Question Marks groups according to the economic level and the willingness of the citizens. And the group characteristics and development direction were analyzed to help improve the efficiency of the citizenization of the agricultural migrant population.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yanxin Diao AU - Jianyu Zhang PY - 2022 DA - 2022/12/29 TI - The Development Direction of the Citizenization of the Agricultural Migrant Population from the Perspective of Classified Citizenization BT - Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022) PB - Atlantis Press SP - 2850 EP - 2859 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-31-2_335 DO - 10.2991/978-2-494069-31-2_335 ID - Diao2022 ER -