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The number of small and medium-sized manufacturing companies that have successfully embraced the digital transformation envisioned by the Fourth Industrial Revolution (Industry 4.0) remains low. This paper argues that one reason is the significant innovation required in manufacturing systems to undergo such a transformation. This innovation demands capabilities vastly different from those traditionally employed for continuous improvements in manufacturing systems. The conventional development of manufacturing systems emphasizes resilience, robustness, and efficiency, typically thriving in stable and predictable conditions. However, developing a manufacturing system under highly complex and unpredictable circumstances requires new capabilities. We term this “manufacturing innovation”. At this stage, learning from successful cases is a valuable step towards unifying scattered evidence and developing coherent knowledge of how SMEs successfully do manufacturing innovation in the context of Industry 4.0.

We conducted a multiple case study involving seven small and medium-sized Danish manufacturing companies to investigate successful manufacturing innovation in the context of Industry 4.0. Cross-case analysis identified four critical propositions regarding the capabilities contributing positively to manufacturing innovation.

The research findings highlight various capabilities for successful manufacturing innovation in the context of Industry 4.0. They suggest that such significant digital transformation of manufacturing systems begins with radical innovations in enabling processes rather than core processes. A flexible approach facilitates it, often operationalized through iterative methods. Moreover, the accumulation of knowledge from previous manufacturing innovation initiatives forms a foundational basis for strategically approaching Industry 4.0, suggesting that experience in manufacturing development generally enhances the capacity to adopt Industry 4.0 technologies effectively.

The results underscore the need for viewing digital transformation towards Industry 4.0 as a manufacturing innovation process, which relies on significantly different organizational capabilities than those supporting continuous manufacturing development. This insight has two implications for research in this domain; (1) Innovation process models must be developed to support radical systemic innovation, gradual learning and agile processes in manufacturing, and (2) Industry 4. 0 technologies enable new potential, but the actualization of this potential is dependent on organizational competences.

The findings also offer several practical implications. Identifying patterns of best practices provides much-needed inspiration and insight into how manufacturing innovation for Industry 4.0 may be approached. While we agree with studies showing that competencies are one of the biggest challenges for companies to get started, our results also suggest that by using a flexible approach, companies can build competencies gradually and as needed, which can yield the right results over time. Furthermore, the findings suggest that a specific starting point for manufacturing companies may be enabling processes rather than core processes. This new understanding of the types of solutions companies manage to progress with may suggest that the technologies here are more mature or that there is greater motivation to get started. This implication is supported by the result that a long-term strategy is needed, but that it must be operationalized into smaller solutions to avoid biting off more than they can chew initially. While other researchers have also pointed this out, we provide a deeper understanding of why it is necessary and how it can be operationalized.

The article is one of the first to make a qualitative study on multiple cases to understand how manufacturing companies successfully introduced manufacturing innovation for Industry 4.0.

Management research on serendipity, which is defined as a search that leads to an unintended discovery, has increased considerably over the last three decades. In this article, management research on serendipity (up to the end of 2021) is reviewed and synthesised.

A bibliometric analysis was conducted on 85 peer-reviewed articles extracted from the Scopus database, which was then integrated with a systematic literature review.

The bibliometric analysis revealed that management literature on serendipity is framed around four main thematic areas: conceptual boundaries, conditions favouring serendipity and outcomes, foreign market entry and the relationship between serendipity, networks and assets. A systematic literature review was then conducted on each of the identified clusters.

The present article offers a systematised view of the extant body of research on serendipity in management studies. Based on the findings, the main implications and future research agendas are discussed.