Robotics technology and firm-level employment adjustment in Japan

Ni, Bin; Obashi, Ayako

doi:10.1016/j.japwor.2021.101054

Cited by 23 publications

(19 citation statements)

References 11 publications

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“…However, multiple regression analysis reveals that robots have reduced employment in traditional industries such as agriculture and mining. This study supports evidence from previous observations [ 11 , 12 , 41 , 42 ] that industrial robots are a skilled-biased technology change.…”

Section: Resultssupporting

confidence: 92%

Effect of Industrial Robots on Employment in China: An Industry Level Analysis

Zhao

Said

Ismail

et al. 2022

Computational Intelligence and Neuroscience

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China has been the world’s largest market for industrial robots since 2013. Industrial robots improve accuracy, safety, and efficiency in industrial production but have a substantial impact on the labor market. This investigation uses the task-based model to explore the relationship between industrial robots and employment across industries. This study uses industrial robot data from the International Federation of Robotics and employment data from the China Statistical Yearbook from 2010 to 2019 to examine robot applications’ influencing mechanisms on labor demand in different industries in China. The results show a significant positive correlation between robots’ exposure and labor demand for IT, health and social services, science research and technical services, and management of water conservancy and environmental industries. Based on the results, the use of robots promotes high-skilled talent employment and some third-sector employment, like education, food and beverages, utilities, household appliances, and transport. However, multiple regression analysis reveals that the use of robots has reduced employment in traditional industries such as agriculture and mining.

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Section: Resultssupporting

confidence: 92%

Effect of Industrial Robots on Employment in China: An Industry Level Analysis

Zhao

Said

Ismail

et al. 2022

Computational Intelligence and Neuroscience

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“…, 2020). Moreover, even the diffusion of robots at the industry level may negatively affect employment in labor-intensive firms (Ni and Obashi, 2021).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Bessen et al, 2020;Domini et al, 2021), other studies stress the possibility of a decrease (e.g. Bonfiglioli et al, 2020;Ni and Obashi, 2021). Specifically, the adoption of industrial robots may significantly reduce firm employment (Ballestar et al, 2021) as they inhibit employment growth (Jung and Lim, 2020) and cause an increase in efficiency and a decline in demand for labor (Bonfiglioli et al, 2020).…”

Section: Interpreting Innovation In Automation Through the Sew Perspe...mentioning

confidence: 99%

How do non-economic goals and priorities affect family firm’s propensity to innovate in automation? The role of ownership, board of director, young successor and generation

Bannò

D’Allura

Filippi

et al. 2022

EJIM

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PurposeThis study examines the propensity to innovate in automation of family firms (FFs) based on the socio-emotional wealth (SEW) perspective.Design/methodology/approachThis study’s analysis is based on three aspects. First, the authors consider three main non-economic goals and priorities of FFs: the family’s relationship with employees (read as to care for their satisfaction and well-being); the inner pride of building and maintaining the family and firm image and reputation; and the inner feeling to be socially responsible. Second, the authors consider how these goals and priorities vary among FFs according to four dimensions: family ownership, the presence of family members on the board of directors, the involvement of young successors, and the presence of founding and later generations. Finally, the consequences of automation are considered: lower firm employment, lower employees’ satisfaction and well-being, and higher firm productivity. The analysis is based on a sample of 4,150 Italian firms.FindingsThe analysis revealed that FFs are less prone to innovate in automation than non-FFs. Specifically, family ownership, the presence of family members on the board of directors, and the presence of founding generation are negatively associated with innovation in automation. Instead, the involvement of young successors and the presence of later generation are positively associated with innovation in automation.Originality/valueTo the authors’ knowledge, this study is the first investigation that, based on SEW, examines how FFs act on the decision to innovate in automation, thereby providing empirical evidence.

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“…Most of the existing research on artificial intelligence and industrial robots has focused on the labor market, economic growth, carbon emissions, etc. [ 10 , 11 , 12 ]. However, empirical research between AI and energy efficiency is relatively rare.…”

Section: Introductionmentioning

confidence: 99%

Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China

Liu

et al. 2022

IJERPH

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Improving energy efficiency is an important way to achieve low-carbon economic development, a common goal of most nations. Based on the comprehensive survey data of enterprises above a designated size in Guangdong Province, this paper studies the impact of artificial intelligence on the energy efficiency of manufacturing enterprises. The results show that: (1) artificial intelligence, as measured by the use of industrial robots, has significantly improved the energy efficiency of manufacturing enterprises. This conclusion is still robust after introducing data on industrial robots in the United States over the same time period as the instrumental variable for the endogeneity test. (2) The mechanism test shows that artificial intelligence mainly promotes the improvement in energy efficiency by promoting technological progress; the impact of artificial intelligence on the technological efficiency of enterprises is not significant. (3) Heterogeneity analysis shows that the age of the manufacturing enterprises inhibits a promoting effect of artificial intelligence on energy efficiency; manufacturing enterprises’ performance can enhance the promoting effect of artificial intelligence on energy efficiency, but this promoting effect can only be shown when the enterprise performance is positive. The paper clarifies both the impact of artificial intelligence on the energy efficiency of manufacturing enterprises and its mechanism of action; this will help provide a reference for future decision-making designed to improve manufacturing enterprises’ energy efficiency.

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Robotics technology and firm-level employment adjustment in Japan

Cited by 23 publications

References 11 publications

Effect of Industrial Robots on Employment in China: An Industry Level Analysis

Effect of Industrial Robots on Employment in China: An Industry Level Analysis

How do non-economic goals and priorities affect family firm’s propensity to innovate in automation? The role of ownership, board of director, young successor and generation

Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China

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