Robotisation in the automotive sector: a study on the drivers for automation

Publication Type:

Conference Paper


Gerpisa colloquium, Paris (2021)


During the past decade, the advent of Industry 4.0 technologies has been reshaping the trade-offs between different production and organisational models, influencing the space and opportunities for structural change. Despite a considerable hype in the studies about automation replacing jobs, among which there are those studying skill and routine biases for technological change, little focus has been given on the drivers that lead to more automation and digitalisation. The broad realm of the fourth industrial revolution, especially the narrower manufacturing-based Industry 4.0 (Sung, 2018), is very much about the digitalisation of existing systems, a process in which complete automation is a previous necessary step. Technological adoption is a complex, multifaceted phenomenon that presents different characteristics across countries, industries, firms and time (Rosenberg, 1970, 1976; Rogers, 1995; Davies, 1986; De Pietro et al., 1990). This paper began by introducing the concept of technological change and continued by examining technology diffusion and adoption in the automotive sector. The purpose of this research is to go beyond the hype of new technologies and trying to understand the drivers of robotisation; this type of analysis could very much complement that part of the literature on the effects of robot adoption.

The unique set of primary data presented in this paper draws on an extensive period of fieldwork in South Africa where more than 35 interviews were collected across 28 different types of firms, both OEMs and suppliers, along different stages of the automotive value chain. The interviews were conducted following a questionnaire sent before the meeting, and the answers were then enriched during the plant visits, where the researcher could see and ask questions regarding the functioning of new technologies. The deep involvement in terms of multiple players for each stage of the value chain increased our analysis's external validity (Yin, 2009; Gibbert et al., 2008).

This design approach allows us to have a multifaceted perspective and a holistic view of such an interrelated phenomenon as technology adoption. Moreover, the case study approach is particularly useful as we are at the early stages of research (Gibbert et al., 2008) in the field of the newest (fourth industrial revolution) technologies’ adoption. While the field of technology adoption is not recent nor new, the element of novelty is in relation to the adoption of the most recent technologies. The qualitative approach was thus chosen as the topic and the research questions constitute an empirical enquiry that investigates a contemporary phenomenon in depth and within its real-life contexts (Yin and Davis, 2007).

The rich set of primary information collected on the field resulted in a new framework to study the determinants of technology adoption at the final assemblers and the suppliers’ level. Three main drivers emerged: (i) volume, in relation to productivity increases, (ii) improved quality, concerning task precision, (iii) safety and ergonomics.
(i) Volume has been unanimously reported as a crucial driver for automation, mainly as it justifies the economic investment while making the firm more productive. For suppliers, this seems to be the most critical element, and the absence of volume prevents making a certain type of investment that would allow for more productivity.
(ii) Improved quality is a crucial driver as specific operations are increasingly difficult to be undertaken in more manual ways. International standards and firms’ internal standards have an important role in the quality that specific processes need to reach.
(iii) Ergonomics and safety were reported as two critical drivers for OEMs and suppliers, especially Japanese firms.

The paper further discusses how these drivers affect the supply chain through a cascade effect within the analysis of these drivers. The latter aspects also stem from how companies use technologies and spillovers that these may have along the value chain.

Practical and theoretical implications

This analysis provides further evidence on the drivers that lead to robots’ adoption and further automation and digitalisation. Technologies are not adopted for the mere fact of being ‘at disposal’, nor for being – in theory – inputs that would allow higher productivity. They are adopted if the material, technological and business conditions within firms make it a feasible and manageable option. By introducing an analysis on the technical and material related type of drivers, which we found to be determinant in adopting industrial robots in the sector where most industrial robots are adopted, we indicate a direction for future research. The process of understanding the socio-economic drivers of industrial robots’ adoption cannot neglect the role of industrial processes in determining the opportunity – and the necessity – to adopt industrial robots.


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