Technological innovations are becoming increasingly systemic in the complex and interconnected world. The initiation and evolution of systemic innovations take time and include numerous challenges, and the mechanisms through which systemic innovations emerge in the interaction between different technologies represent a research gap. This paper explores the emergence of ceramic additive manufacturing as an example of a systemic manufacturing technology innovation. We implemented an event history analysis of four ceramic-material additive manufacturing technologies. We traced the initiation and evolution paths of each of the four technologies over time and showed a pattern of activities within and across the technologies. The study contributes by revealing that systemic innovations emerge as a result of parallel and sequential development paths of within-technology system components as well as the interaction between multiple technologies. The timing of the coalescing development paths of the system components and technologies appears crucial but serendipitous instead of coordinated. The findings open new pathways for speeding up the emergence of systemic innovations and forthcoming research to support the evolution of additive manufacturing.@en

Four extensive literature reviews on factors for innovation success in terms of market, strategic and social impact for additive manufacturing were performed where the focus lies on three levels of analysis; (inter)organizational, business model, and project.@en

Purpose: This paper addresses the most important factors for the selection of additive manufacturing (AM) technology as a method of production of metal parts. AM creates objects by adding material layer by layer based on 3D models. At present, interest in AM is high as it is hoped that AM contributes to the competitiveness of Western manufacturing industries. Design/methodology/approach: A literature study is conducted to identify the factors that affect the selection of AM technology. Expert interviews and the best–worst method are used to prioritize these factors based on relative factor weights. Findings: Technology, demand, environment and supply-related factors are categorized and further mapped to offer a holistic picture of AM technology selection. According to expert assessments, market demand was ranked highest, although market demand is currently lacking. Research limitations/implications: The composition and size of the expert panel and the framing of some of the factors in light of previous literature cause validity limitations. Further research is encouraged to differentiate the selection factors for different AM implementation projects. Originality/value: The paper presents a more complete framework of factors for innovation selection in general and the selection of AM technology specifically. This framework can serve as a basis for future studies on technology selection in the (additive) manufacturing sector and beyond. In addition to AM-specific factor weights, the paper explains why specific factors are important, reducing uncertainty for managers that have to choose between alternative manufacturing technologies.@en