Astrid Heidemann Lassen and Bjørge Timenes Laugen
The purpose of this paper is to test the effect of internal and external collaboration on the degree of newness (incremental/radical) in innovation projects. This adds to the…
Abstract
Purpose
The purpose of this paper is to test the effect of internal and external collaboration on the degree of newness (incremental/radical) in innovation projects. This adds to the understanding of the particular patterns of open innovation (OI) and what characterizes the innovation emerging through this approach.
Design/methodology/approach
Tests are performed on the effect of internal and external collaboration on the degree of newness (incremental/radical) in innovation projects. This adds to the understanding of the particular patterns of OI and what characterizes the innovation emerging through this approach. The empirical analysis is based on a data set including responses from 512 Danish engineers.
Findings
The results show that external collaboration has significantly different effects on the degree of newness depending on the type of external partners involved, and they also show that radical innovation output is positively related to involving the R&D department (internal) and universities (external involvement) and negatively related to involving suppliers.
Originality/value
The results provide a more detailed understanding of how different OI patterns affect the development of incremental vs radical innovation in existing organizations. In particular, three findings add new insights into how OI affects innovation to reach the highest degree of newness: high importance of collaboration with external partners with distinct interests and skills; low reliance on existing customers and suppliers for the development of radical innovation; and narrow and focused internal involvement rather than broad internal involvement.
Details
Keywords
Astrid Heidemann Lassen and Maria Stoettrup Schioenning Larsen
The number of small and medium-sized manufacturing companies that have successfully embraced the digital transformation envisioned by the Fourth Industrial Revolution (Industry…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
Details
Keywords
Gustavo Hermínio Salati Marcondes de Moraes, Bruno Fischer, Sergio Salles-Filho, Dirk Meissner and Marina Dabic
Knowledge-intensive entrepreneurial firms (KIE) strongly rely on scientific and strategic research and development (R&D) capabilities to achieve higher performance levels. Hence…
Abstract
Purpose
Knowledge-intensive entrepreneurial firms (KIE) strongly rely on scientific and strategic research and development (R&D) capabilities to achieve higher performance levels. Hence, the purpose of this paper is to disentangle the effects of scientific capabilities and strategic R&D on KIE performance; and how the constituent elements of these dimensions can be configured to generate conditions for high performance.
Design/methodology/approach
The authors’ empirical setting involves companies that submitted projects to the Innovative Research in Small Businesses (PIPE) program in Brazil. The authors then run partial least square structural equation modeling to verify how scientific and strategic R&D capabilities influence the performance construct. Second, the authors apply fuzzy-set qualitative comparative analysis to identify configurations that are equifinal in terms of generating superior performance.
Findings
Findings indicate a strong association between scientific capabilities and KIE performance. The configurational approach outlines the existence of multiple paths to success, but human capital stands as a core condition throughout estimations.
Practical implications
The authors’ assessment has implications for how KIE firms are managed according to their organizational profiles and trajectories. Also, it advances the authors’ comprehension on how entrepreneurship policies can better target these distinct profiles.
Originality/value
The authors’ analysis provides new evidence on the inherent complexity behind the generation of high performance in KIE when addressing their portfolios of knowledge-related capabilities. More than that, the authors were able to identify the existence of heterogeneous profiles that can equally lead to higher levels of performance.