Industrial robot application and total factor productivity of manufacturing enterprises

In the context of intensifying global competitiveness and rapid technological advancement, industrial robots have emerged as a pivotal component in the integration of digital technology, exerting a vital influence on the transformation and enhancement of the manufacturing industry. The question of whether this transformative shift can significantly enhance total factor productivity (TFP) and accelerate the transformation of the manufacturing industry has attracted substantial academic attention. This study employs micro-panel data drawn from Chinese A-share listed manufacturing enterprises from 2007 to 2022 to examine the implications of industrial robot application on TFP and the underlying mechanisms. The results of our study indicate that industrial robots have a positive influence on TFP, and this effect persists over time. The results of the mechanism tests indicate that industrial robot application facilitates an increase in human capital, confirming their "talent aggregation effect". Moreover, the application of industrial robots enhances enterprises' innovative capabilities, thereby validating their "innovation effect". Further examination of heterogeneity indicates that the enhancing impact of applying industrial robots on TFP is more pronounced among enterprises with high labor productivity, those that are state-owned, and enterprises operating in high-tech sectors. This research contributes to the understanding of the impact of industrial robot application on TFP, which is of considerable practical significance for emerging economies seeking to transform traditional enterprise factors, accelerate new technology integration, and steer the digital transformation of manufacturing.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-09-24
DOI
https://doi.org/10.1371/journal.pone.0331378
Citations
1
Primary Topic
Firm Innovation and Growth
Type
article
Field-Weighted Citation Impact
3.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Industrial robot application and total factor productivity of manufacturing enterprises

Zhenhua Wang, Shuangshuang Liu, Minghui Zhao
1 citations
PLoS ONE
Firm Innovation and Growth
3.13
article

Industrial robot application and total factor productivity of manufacturing enterprises

Zhenhua Wang, Shuangshuang Liu, Minghui Zhao
article en
1 citations

Abstract

In the context of intensifying global competitiveness and rapid technological advancement, industrial robots have emerged as a pivotal component in the integration of digital technology, exerting a vital influence on the transformation and enhancement of the manufacturing industry. The question of whether this transformative shift can significantly enhance total factor productivity (TFP) and accelerate the transformation of the manufacturing industry has attracted substantial academic attention. This study employs micro-panel data drawn from Chinese A-share listed manufacturing enterprises from 2007 to 2022 to examine the implications of industrial robot application on TFP and the underlying mechanisms. The results of our study indicate that industrial robots have a positive influence on TFP, and this effect persists over time. The results of the mechanism tests indicate that industrial robot application facilitates an increase in human capital, confirming their "talent aggregation effect". Moreover, the application of industrial robots enhances enterprises' innovative capabilities, thereby validating their "innovation effect". Further examination of heterogeneity indicates that the enhancing impact of applying industrial robots on TFP is more pronounced among enterprises with high labor productivity, those that are state-owned, and enterprises operating in high-tech sectors. This research contributes to the understanding of the impact of industrial robot application on TFP, which is of considerable practical significance for emerging economies seeking to transform traditional enterprise factors, accelerate new technology integration, and steer the digital transformation of manufacturing.

PLoS ONEVol. 20(9)
University of International Business and Economics (CN), Capital Medical University (CN), Agricultural Information Institute (CN), Chinese Academy of Agricultural Engineering (CN), Chinese Academy of Agricultural Sciences (CN), Beijing Friendship Hospital (CN)
Openalex Percentile: Top 6%
Firm Innovation and Growth
3.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.