Additive manufacturing–enabled innovation in small- and medium-sized enterprises: the role of readiness in make-or-buy decisions

Abstract

PurposeThe digital transition process is an important strategic initiative for manufacturing companies to ensure continued competitiveness. The purpose is to investigate the relationship between firms' additive manufacturing (AM) readiness and product and process innovation and how this process is mediated by firms' make-or-buy decisions regarding performing AM processes internally or buying AM services from external partners.Design/methodology/approachThe paper is based on a questionnaire survey including full answers from 157 small- and medium-sized manufacturing companies.FindingsResults show a positive relationship between AM readiness and both product and process innovation. Results also reveal that firms with higher readiness invest more in in-house AM, which in turn promotes innovation. There was no significant association between AM readiness and the use of external AM services. Nonetheless, buying external AM services is still associated positively with innovation.Research limitations/implicationsData in the questionnaire survey are provided by single respondents from each company and are only based on Danish respondents.Practical implicationsThe results indicate that firms' product and process innovation benefits from higher AM readiness derive from increased investment in in-house AM rather than from increased use of external AM services. This also signifies that firms with lower levels of AM readiness buy external AM services and derive the innovation benefits hereof.Originality/valueThe paper delivers new, empirically found knowledge about how small- and medium-sized manufacturing can improve innovation by both making and buying AM services.

Antecedents of Industry 4.0 capabilities and technological innovation: a dynamic capabilities perspective

“…Industry 4.0 capabilities are used to support innovation organizationally within facilities and organizations by developing innovative capabilities using advanced analysis and modeling methods that improve the performance of research and development activities (Hizam-Hanafiah and Soomro, 2021) and the ability of this technology to enhance exploration activities by supporting big data analysis with a set of advanced applied methods that provide new knowledge about hidden patterns in this data (Al-Khatib and Ramayah, 2023). Industry 4.0 capabilities also help provide prototypes that are less expensive, faster and more accurate than traditional methods, contributing to reducing costs and encouraging technological innovation (Stentoft et al , 2023).…”

“…Furthermore, real-time data analysis leads to wiser and smarter decisions at the required time, enhancing the ability to present new ideas and innovations (Mubarak and Petraite, 2020). In addition, additive manufacturing can be used to develop prototypes of the required innovations and reduce the costs of technological innovation activities (Stentoft et al , 2023).…”