Will advancement in technologies bring fear and damage human employment? Evidence from China's manufacturing industry.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 15 05 2023
accepted: 25 11 2023
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 26 4 2024
Statut: epublish

Résumé

Advancement in technologies such as robotic industries and artificial intelligence bring fear among human being that jobs will be substituted by robots. Base on the panel data of 28 China's manufacturing industries, this research analyzed the impact of technical progress bias on employment. First, we calculate the technical progress bias index of 28 industries base on the stochastic frontier model with transcendental logarithm function found 16 industries were toward the skilled labor while the remaining 12 industries were toward the unskilled labor. Second, the empirical results show that technical progress bias has a positive impact on the total manufacturing employment and significant positive effect on the unskilled labor, while no significant impact on skilled labor employment. Third, the threshold effect test proves that if taking industry value-added per capita or R&D capital stock as threshold variable, the threshold about the impact exist, making the impact on skilled labor was insignificant.

Identifiants

pubmed: 38669294
doi: 10.1371/journal.pone.0295942
pii: PONE-D-23-14771
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0295942

Informations de copyright

Copyright: © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Peng Wang (P)

School of Business Administration, Henan Polytechnic University, Jiaozuo, Henan, China.

Donghai Li (D)

School of Government Management, Inner Mongolia Normal University, Hohhot, Inner Mongolia, China.

Yangzi Wang (Y)

School of Business, Shandong University, Weihai, China.

Qingjiang Han (Q)

School of Applied Economics, Jiangxi University of Finance and Economics, Nanchang, China.

Yousaf Ali Khan (YA)

Department of Mathematics and Statistics, Hazara University Mansehra, Mansehra, Pakistan.

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