Abstract
PurposeThis 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/approachThe 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.FindingsThis 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/valueThis 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.
Subject
Industrial and Manufacturing Engineering,Strategy and Management,Computer Science Applications,Control and Systems Engineering,Software
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