Robotization and labour dislocation in the manufacturing sectors of OECD countries: a panel VAR approach

Compagnucci, Fabiano; Gentili, Andrea; Valentini, Enzo; Gallegati, Mauro

doi:10.1080/00036846.2019.1659499

Cited by 16 publications

(16 citation statements)

References 24 publications

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“…The forecasted growth in manufacturing employment, labor productivity, education, coexistent with the robot shipment growth, suggests that outlined negative trends of the number of employees and labor productivity in the researched period were only temporary, and we believe that was due to the lack of opportunity and knowledge on how to exploit robotization for the maximum efficiency. These findings oppose the U.S. Bureau of Labor of Statistics (2019a) data presented in Table 1 and also disagree with the claims of other authors (e.g., Compagnucci et al, 2019).…”

Section: Turing?contrasting

confidence: 98%

“…Namely, in some reports (e.g., in WEO, 2018a) only positive consequences of Industry 4.0 are put to the front. On the other hand, there are also negative views detected in the literature (e.g., in Compagnucci et al, 2019). Based on an initial analysis of certain economic indicators, social indicators, and considering ethical consequences, we first shared negative views.…”

Section: Introductionmentioning

confidence: 98%

“…Although Acemoglu and Restrepo (2017) demonstrated high and robust negative effects of robotization on employment and wages, and Compagnucci et al (2019) used IFR data to demonstrate that the introduction of ro-bots plays a key role in slowing down human labor and compensation growth, while Cho and Kim (2018) used IFR data for the multiple regression considering the triangular relationship of employment-working-hours-wages, to show that job destruction due to robotization is not yet very remarkable. In contrast, Cséfalvay (2020) claims "Recent studies clearly show that robotization is associated with economic growth and productivity gains.…”

mentioning

confidence: 99%

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Impacts of the Transformation to Industry 4.0 in the Manufacturing Sector: The Case of the U.S.

Rojko¹,

Erman²,

Jelovac³

2020

Organizacija

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Background and purpose: The transformation to Industry 4.0 increases the number of robots installed within industries, which brings great shifts in industrial ecosystems. For this reason, our research goal was to analyze the key performance indicators to investigate the economic and social sustainability of the changes in production.Methodology: The combination of official (World Bank, U.S. Bureau of Labor Statistics) and publicly available (Federal Reserve Economic Data, Industrial Federation of Robotics) data was used for statistical data processing, including comparison, correlation, cross-correlation and vector autoregression analysis, to present the past developments and also to predict future trends within the U.S. manufacturing sector.Results: In contrast to robust industry robotization observed in the 2008–2018 period, the share of manufacturing output and employment declined. Nonetheless, the vector autoregression model forecast shows, that the U.S. manufacturing sector has arrived at a turning point, after which robotization can increase employment and labor productivity of workers, while also stimulating further growth of their education levels.Conclusion: The transition to Industry 4.0 has a major impact on increasing demands for new knowledge and skills for increased productivity. Accordingly, forecasted growths of analyzed manufacturing indicators suggest that negative impacts of robotization in the recent past were only temporary, due to the entrance to the Industry 4.0 era. Nonetheless, additional policies to support sustainable industry development are required.

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Section: Turing?contrasting

confidence: 98%

Section: Introductionmentioning

confidence: 98%

mentioning

confidence: 99%

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Impacts of the Transformation to Industry 4.0 in the Manufacturing Sector: The Case of the U.S.

Rojko¹,

Erman²,

Jelovac³

2020

Organizacija

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“…To meet demands of the manufacturing industry and its issues related to competition, industrial automation has been utilized in a huge range of different applications to assist fabrication environments day-by-day. Inside this context, the use of robots looks for an efficient, reliable and precise production system (Brogardh, 2007; Compagnucci et al, 2019; Lakshmi and Bahli, 2020; Pagliosa et al, 2019), besides for automating repetitive work or performing tasks that are dangerous or hostile for people (Shibata, 2004).…”

Section: Introductionmentioning

confidence: 99%

R&D roadmap for process robotization driven to the digital transformation of the industry 4.0

Barbosa

Silva

2020

Concurrent Engineering

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This paper lays emphasis on a proposal of a tailor-made roadmap that manages the knowledge related to automation skills to be applied during the concurrent engineering phase. The approach of this Research and Development (R&D) roadmap is a particular guideline in a structured form that uses the concepts of Plan-Do–Check–Act (PDCA) method integrated to other quality tools and know-how in robotization, for management of this specific knowledge. This research work aims to guide the staff (project managers, engineers and technicians) who work multidisciplinary in concurrent engineering environment about the robot’s implementation steps and significant tips related to the deployment phases that can be beneficial when this proposed roadmap is applied. Also, it was developed to assist the robot’s installation and their validation on shop floor, aiming the best class of industrial processes regarding the automation. The main contribution and novelty of this paper is to propose a R&D roadmap that drives and assists the multidisciplinary work teams since the identification of robotization opportunities till the assurance of quality requirements established for the concerned process, in addition to a continuous improvement program to carry it on. Besides that, this work provides a high relevance in terms of knowledge management related to robotization expertise, spread of practical skills in concurrent engineering context and an unprecedented innovative contribution at science frontier.

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“…Using EU Labour Force Survey data instead of EU KLEMS data,Klenert et al (2020) find no relationship between the increased use of robots and changes in total employment levels or in the share of low-skill employment between 1995 and 2015 in 14 countries of the European Union. Negative effects for employment are instead found byCompagnucci et al (2019), who focus on 16 OECD countries over the period-2016, and Blanas et al (2020, who investigate the impact of software and robots on the within-industry share of routine workers in 10 high-income countries over the period1982-2005. 6 As we shall explain, if one had access to data capturing the universe of individual employment conditions, one could go even further and build a measure of local exposure to robots that disregards the industrial structure and is based exclusively on activities and tasks, thereby exploiting workers' heterogeneity within and across firms.…”

mentioning

confidence: 99%

Stop Worrying and Love the Robot: An Activity-Based Approach to Assess the Impact of Robotization on Employment Dynamics

et al. 2021

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Robotization and labour dislocation in the manufacturing sectors of OECD countries: a panel VAR approach

Cited by 16 publications

References 24 publications

Impacts of the Transformation to Industry 4.0 in the Manufacturing Sector: The Case of the U.S.

Impacts of the Transformation to Industry 4.0 in the Manufacturing Sector: The Case of the U.S.

R&D roadmap for process robotization driven to the digital transformation of the industry 4.0

Stop Worrying and Love the Robot: An Activity-Based Approach to Assess the Impact of Robotization on Employment Dynamics

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