Robot adoption and FDIs driven transformation in the automotive industry

Abstract: This paper explores the relationship between inward FDIs and industrial robots adoption, across different segments of the automotive value chain. Using IFR and fDiMarket data at a fine level of disaggregation of the automotive sector, we illustrate to what extent FDIs could act as a trigger for upgrade through advanced production technology diffusion in 34 countries over 2005-2014. We find that different groups of countries and different segments of the value chain are characterised by distinct patterns of FDI and robot adoption. While there exists some correlation between FDIs and robot adoption in the OEMs segment, it seems less so for components. Moreover, some emerging countries are characterised by a much higher correspondence between FDIs and robot adoption than others, possibly revealing an important role played by the industrial ecosystem characterising strong adopters of this process technology

Robotising, but how? Evidence from the automotive sector in South Africa

Purpose: This paper focuses on understanding firm-level determinants of industrial robots' adoption and how these determinants result in heterogenous processes of robotisation across firms within the same sector. The paper presents results from in-depth case studies of final assemblers in the South African automotive sector. Design/methodology/approach: The research has been conducted through multiple case studies with a focus on final assemblers. During the case studies, as well as before and after it, data coming from in-depth semi-structured interviews were triangulated with secondary data available from the international database on industrial robots' adoption and documents provided by firms and institutions. Findings: This paper identifies three firm-level determinants of robotisation – i.e. modularity of the production process, flexibility in the use of technology and stability in product design. The results also showed that firms' robotisation depend on each of these determinants as well as their interdependence. The authors introduce a framework to study interdependence between these technology–organisational choices, which reveals heterogenous patterns of technology deployment and related managerial implications. Originality/value: This research introduces a new framework on factors driving industrial robotisation – a key digital production technology – and offers empirical evidence of the heterogenous deployment of this technology. The authors identify two main manufacturing approaches to robotisation in the automotive sector: one in which the firm designs a robotised process around a certain product design – i.e. the German/American way and one in which the firm designs its product based on certain robotised processes – i.e. the Japanese way. These findings are valuable for both industry, operational research and the scientific community as they reveal heterogeneity on the “how” of robotisation and implications for manufacturing technology management

Unveiling structure and dynamics of global digital production technology

This research pioneers the construction of a novel Digital Production Technology Classification (DPTC) based on the latest Harmonised Commodity Description and Coding System (HS2017) of the World Customs Organisation. The DPTC enables the identification and comprehensive analysis of 127 tradable products associated with digital production technologies (DPTs). The development of this classification offers a substantial contribution to empirical research and policy analysis. It enables an extensive exploration of international trade in DPTs, such as the identification of emerging trade networks comprising final goods, intermediate components, and instrumentation technologies and the intricate regional and geopolitical dynamics related to DPTs. In this paper, we deploy our DPTC within a network analysis methodological framework to analyse countries' engagements with DPTs through bilateral and multilateral trade. By comparing the trade networks in DPTs in 2012 and 2019, we unveil dramat ic shifts in the global DPTs' network structure, different countries' roles, and their degree of centrality. Notably, our findings shed light on China's expanding role and the changing trade patterns of the USA in the digital technology realm. The analysis also brings to the fore the increasing significance of Southeast Asian countries, revealing the emergence of a regional hub within this area, characterised by dense bilateral networks in DPTs. Furthermore, our study points to the fragmented network structures in Europe and the bilateral dependencies that developed there. Being the first systematic DPTC, also deployed within a network analysis framework, we expect the classification to become an indispensable tool for researchers, policymakers, and stakeholders engaged in research on digitalisation and digital industrial policy

Unveiling structure and dynamics of global digital production technology

This research pioneers the construction of a novel Digital Production Technology Classification (DPTC) based on the latest Harmonised Commodity Description and Coding System (HS2017) of the World Customs Organisation. The DPTC enables the identification and comprehensive analysis of 127 tradable products associated with digital production technologies (DPTs). The development of this classification offers a substantial contribution to empirical research and policy analysis. It enables an extensive exploration of international trade in DPTs, such as the identification of emerging trade networks comprising final goods, intermediate components, and instrumentation technologies and the intricate regional and geopolitical dynamics related to DPTs. In this paper, we deploy our DPTC within a network analysis methodological framework to analyse countries' engagements with DPTs through bilateral and multilateral trade. By comparing the trade networks in DPTs in 2012 and 2019, we unveil dramat ic shifts in the global DPTs' network structure, different countries' roles, and their degree of centrality. Notably, our findings shed light on China's expanding role and the changing trade patterns of the USA in the digital technology realm. The analysis also brings to the fore the increasing significance of Southeast Asian countries, revealing the emergence of a regional hub within this area, characterised by dense bilateral networks in DPTs. Furthermore, our study points to the fragmented network structures in Europe and the bilateral dependencies that developed there. Being the first systematic DPTC, also deployed within a network analysis framework, we expect the classification to become an indispensable tool for researchers, policymakers, and stakeholders engaged in research on digitalisation and digital industrial policy

Unveiling structure and dynamics of global digital production technology networks: A new digital technology classification and network analysis based on trade data

This research pioneers the construction of a novel Digital Production Technology Classification (DPTC) based on the latest Harmonised Commodity Description and Coding System (HS2017) of the World Customs Organisation. The DPTC enables the identification and comprehensive analysis of 127 tradable products associated with digital production technologies (DPTs). The development of this classification offers a substantial contribution to empirical research and policy analysis. It enables an extensive exploration of international trade in DPTs, such as the identification of emerging trade networks comprising final goods, intermediate components, and instrumentation technologies and the intricate regional and geopolitical dynamics related to DPTs. In this paper, we deploy our DPTC within a network analysis methodological framework to analyse countries' engagements with DPTs through bilateral and multilateral trade. By comparing the trade networks in DPTs in 2012 and 2019, we unveil dramatic shifts in the global DPTs' network structure, different countries' roles, and their degree of centrality. Notably, our findings shed light on China's expanding role and the changing trade patterns of the USA in the digital technology realm. The analysis also brings to the fore the increasing significance of Southeast Asian countries, revealing the emergence of a regional hub within this area, characterised by dense bilateral networks in DPTs. Furthermore, our study points to the fragmented network structures in Europe and the bilateral dependencies that developed there. Being the first systematic DPTC, also deployed within a network analysis framework, we expect the classification to become an indispensable tool for researchers, policymakers, and stakeholders engaged in research on digitalisation and digital industrial policy

Unveiling Structure and Dynamics of Global Digital Production Technology Networks: A new digital technology classification and network analysis based on trade data

This research pioneers the construction of a novel Digital Production Technology Classification (DPTC) based on the latest Harmonised Commodity Description and Coding System (HS2017) of the World Customs Organisation. The DPTC enables the identification and comprehensive analysis of 127 tradable products associated with digital production technologies (DPTs). The development of this classification offers a substantial contribution to empirical research and policy analysis. It enables an extensive exploration of international trade in DPTs, such as the identification of emerging trade networks comprising final goods, intermediate components, and instrumentation technologies and the intricate regional and geopolitical dynamics related to DPTs. In this paper, we deploy our DPTC within a network analysis methodological framework to analyse countries' engagements with DPTs through bilateral and multilateral trade. By comparing the trade networks in DPTs in 2012 and 2019, we unveil dramatic shifts in the global DPTs' network structure, different countries' roles, and their degree of centrality. Notably, our findings shed light on China's expanding role and the changing trade patterns of the USA in the digital technology realm. The analysis also brings to the fore the increasing significance of Southeast Asian countries, revealing the emergence of a regional hub within this area, characterised by dense bilateral networks in DPTs. Furthermore, our study points to the fragmented network structures in Europe and the bilateral dependencies that developed there. Being the first systematic DPTC, also deployed within a network analysis framework, we expect the classification to become an indispensable tool for researchers, policymakers, and stakeholders engaged in research on digitalisation and digital industrial polic

Automation and its employment effects: A literature review of automotive and garment sectors

Over the past decade, the interest around automation and digitalisation processes gained considerable attention both due to industrial and productivity related dynamics that stem from such processes and for their effects on employment. A better understanding of such dynamics, away from futuristic and apocalyptic views and closer to what happens at the shopfloor level are crucial to disentangle the effects of automation on labour and to provide insights both at the research and policy making levels. This paper attempts to dig into this subject looking at technological change as an incremental - rather than disruptive - type of process, like the slow and incremental process that characterised previous waves of technological change. Digital and automated technologies are then defined as bundles of innovations, which are selectively integrated into existing systems and for specific objectives. Against this background, this paper contributes to the existing literature in two aspects: it critically engages in a literature review of the recent studies on the effects that automation technologies have on two manufacturing sectors - i.e., automotive and labour - with a focus on the gender dimension that try to emphasise the effects on female workers. Secondly, it presents an in-depth review of the technologies that are widely discussed under the 4.0 label, addressing their degree of automation and their level of disruptiveness of existing systems