Back to Search
Start Over
Measuring SMEs’ Propensity for Open Innovation Using Cognitive Mapping and MCDA.
- Source :
- IEEE Transactions on Engineering Management; Apr2021, Vol. 68 Issue 2, p396-407, 12p
- Publication Year :
- 2021
-
Abstract
- Open innovation (OI) has captured increasing interest over recent decades as this approach is linked to higher level organizational ambidextrous strategy, and has become a prerequisite for achieving competitive advantages. Assessing firms’ propensity for OI has, however, turned out to be an increasingly challenging endeavor. This is particularly true for small and medium-sized enterprises (SMEs) due to the myriad of factors that influence these companies’ capability for innovation. To overcome this challenge, this paper sought to integrate two operational research/management science techniques—cognitive mapping and the Choquet integral (CI) (a nonadditive measure and information aggregator)—to identify and prioritize relevant criteria for evaluating SMEs’ propensity for OI, and improving their organizational ambidexterity. To facilitate a real-world application, information was first collected from SME managers and entrepreneurs who agreed to participate in face-to-face group meetings, allowing realism to be incorporated in the decision-making process. The results were validated by both the panel members and project director of COTEC Portugal—a leading think-and-action network for advancing technology diffusion and business innovation cooperation. The findings include that cognitive mapping facilitates the identification and understanding of cause-and-effect relationships between the determinants of OI in SMEs. The CI, in turn, introduces realism into the construction of value functions and the respective assessments of SMEs. The limitations and implications of the proposed system are also discussed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00189391
- Volume :
- 68
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Engineering Management
- Publication Type :
- Academic Journal
- Accession number :
- 148745597
- Full Text :
- https://doi.org/10.1109/TEM.2019.2895276