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How automated machines influence employment in manufacturing enterprises?
Jiang, Hong; Ge, Yingfan; Yang, Chunhao; Yu, Hongxin.
Afiliación
  • Jiang H; School of Management, Shanghai University of Engineering Science, Shanghai, China.
  • Ge Y; School of Finance, Shanghai University of Finance and Economics, Shanghai, China.
  • Yang C; School of Management, Shanghai University of Engineering Science, Shanghai, China.
  • Yu H; Faculty of Business Economics, Shanghai Business School, Shanghai, China.
PLoS One ; 19(3): e0299194, 2024.
Article en En | MEDLINE | ID: mdl-38442127
ABSTRACT
This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Comercio / Industrias País/Región como asunto: Asia Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Comercio / Industrias País/Región como asunto: Asia Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: China