Context
Additive Manufacturing (AM) is a set of technologies that creates objects from layered 3D model data. AM now reaches production status. The EU is increasingly setting its sights on AM, because it could give firms the means to re-shore production from low-wage regions and create sustainable growth in the EU.
Literature
Generally, the adoption of manufacturing technologies by companies is influenced by a range of drivers and barriers (Tornatzky and Fleischer, 1990; Martínez Sánchez, 1991; Rogers, 2003; Del Rio Gonzales, 2005; Darbanhosseiniamirkhiz and Ismail, 2012). The existing literature on the diffusion of AM however mainly focuses on the technological potential of AM and new fields of application (e.g. (EC, 2014, 2016; Gebhardt, 2000, 2013; Hague, 2006; Tuck and Hague, 2006; Hotza et al., 2014; Bopp, 2010; Yan et. al., 2009). Studies that focus on the user perspective of adoption of AM and its related determinants and barriers, however, are very scarce. To the best of the authors’ knowledge, the study presented by Som et al., 2016 is the only one that investigates the uptake of AM from the user side with a qualitative, case-study based approach.
Literature Gap
Existing literature focuses on its technological potential and new fields of application. The only Study which focuses on the uptake of AM from the user perspective in Germany by using a qualitative research design is provided by Som et al. 2016. So there is need for EU-wide quantitative studies.
Research Questions
The paper addresses this research gap by the following research questions:
(1) To which extent has AM for rapid prototyping and rapid manufacturing diffused across European manufacturing firms?
(2) What are firm-level determinants related to the adoption of AM (rapid prototyping and/or rapid manufacturing) in European manufacturing firms?
Methodology
The paper is based on a quantitative analysis of firm-level data. Descriptive statistics are used to analyse the diffusion of AM among European manufacturing firms in terms of usage, year of introduction, planned use and re-investments of existing equipment. Subsequently, determinants and drivers of AM’s adoption by firms are analysed by a series of multivariate regression models. The selection of the independent variables is based on the diffusion model by Rogers (2003) and includes different technology-related, organisational and external factors that could influence the adoption of AM.
Empirical Material
The secondary analyses are based on firm-level data from the European Manufacturing Survey (EMS) which is conducted by a consortium of European research organisations and coordinated by the Fraunhofer Institute for Systems and Innovation Research ISI. The latest survey in 2015/2016 was carried out in 9 European countries and covers data from more than 3,300 manufacturing firms.
With regards to the diffusion of AM, the dataset includes the following variables:
1) Use of additive manufacturing technologies for rapid prototyping (yes/no, year of introduction, planned used, re-investments since first use)
2) Use of additive manufacturing technologies for mass production (yes/no, year of introduction, planned used, re-investments since first use)
3) Position in the value chain
4) Competitive strategy
5) Use of other advanced manufacturing technologies
6) Innovation activities & R&D
7) Type of product development
8) Production characteristics
9) Age
10) Qualification structure of workforce
11) Country
12) Industry
13) Firm size
14) Vertical range of manufacturing
Results
Firstly, the paper shows to what extent AM has been adopted by European Manufacturing firms over time, and whether the diffusion is related to firms’ specific structural characteristics. The results will show whether and in which respect early adopting firms of AM differ from late-comers or non-users in terms of technology-related, organization-related or external characteristics. Additionally, the results will also highlight possible path dependencies of technology usage. More specific, results will show whether firms who have used rapid prototyping in the past, have a higher propensity to use AM in series production as well.
Contribution to Scholarship
The paper contributes to the research on the diffusion of advanced manufacturing technologies in Europe in general, and for the case of AM in particular. It is expected to close the addressed research gap by providing current empirical insights on the adoption and its internal and external determinants of AM on the firm level. Based on this, it will be discussed whether existing theories and models of technology adoptions can be applied to the field of AM. The findings also provide new insights into the diffusion mechanism of AM on the firm level by looking into the path dependencies and cross-enabling role of existing technological and organisational frameconditions that influence the uptake.
Contribution to Practice
By providing novel insights on the adoption of advanced manufacturing technologies by European manufacturing firms, policy maker will gain a better understanding of the diffusion mechanisms as a basis to design/improve support schemes in the field of innovation and technology policy.
Business practitioners can use the findings to get a comprehensive and reliable picture about the technological maturity of AM especially in the field of series production as well as assess their own company in comparison to other firms in the European industry. Finally, managers’ awareness about technological and organisational antecedents of adopting AM is increased.
Fitness
By focusing on the diffusion of AM into the European industry and by providing a better understanding of how such innovative manufacturing technologies are adopted by firms, the paper directly addresses the bridge between applied research on manufacturing technologies and industry.
Bibliography
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Som, O., Thielmann, A., Schnabl, E., Daimer, S., Berghäuser, H., Rothengatter, O. (2016): Anwendungs- und Entwicklungsperspektiven der additiven Fertigung für den Wirtschaftsstandort Deutschland, Gutachten an den Deutschen Bundestag, Büro für Technikfolgenabschätzung beim Deutschen Bundestag TAB, Berlin.
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