PurposeThe purpose of this paper is to review the literature and offer a more generalizable empirical investigation on the performance impact of implementing Industry 4.0, and the way important contingency factors (plant size, multinational status, country context) affect implementation efforts.Design/methodology/approachFollowing a systematic literature review, the empirical research is based on a large-scale survey of 705 manufacturing plants from 22 countries. Structural equation modeling is employed to discover the relationships between the main constructs of interest, complemented with subgroup analyses to offer a more detailed understanding of the main effects.FindingsWe provide evidence that technologies enabling Industry 4.0 have a positive impact on operational performance, including cost, quality, delivery and flexibility performance. Results of the analyses further indicate that (1) larger firms invest more in implementing Industry 4.0 technologies, (2) manufacturing firms in less competitive countries, especially in the South-East Asian region invest significantly more effort than competitive countries, while (3) multinational companies have no advantage over local firms.Research limitations/implicationsThe survey data employed in this study refers to the early years of companies embracing Industry 4.0 solutions, and thus does not contain the most recent advances in manufacturing technologies.Originality/valueThe paper represents one of the first studies in the literature to assess on a large-scale survey the performance impact of Industry 4.0 technologies, as well as the main contingency factors affecting the implementation of these technologies.

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The paper aims at exploring the prerequisites for a beneficial knowledge transfer between manufacturing plants of multinational companies (MNCs), by taking the characteristics of the knowledge sending and knowledge receiving plant into consideration. This research seeks to understand how efforts undertaken by manufacturing plants, and how collaborative tools and coordination mechanisms influence a successful knowledge transfer. The study includes thirteen case studies conducted in manufacturing plants from four different European countries (i.e., Switzerland, Romania, Albania, and Macedonia). Given the exploratory nature of this study, the authors used a qualitative research approach. The main method of data collection involved multiple semi-structured interviews at manufacturing plants, uniformly applied in each country in order to observe general patterns across different cases. Their results show that the personal interaction between knowledge sending and receiving plants is more important for a successful knowledge transfer than information systems or prior related knowledge.