| Autor: |
Marius Băban, Călin-Florin Băban |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Alexandria Engineering Journal, Vol 104, Iss , Pp 515-528 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1110-0168 |
| DOI: |
10.1016/j.aej.2024.08.022 |
| Popis: |
Determining the importance of major antecedents of open innovation between such distinct partners as industry and universities influences the decision-making regarding resources and effort allocation to their improvement, according to the strategic objectives of the firms. For this purpose, the present paper proposes an approach for conducting their importance-performance analysis based on fuzzy set theory and neural networks. Considering a hierarchical component model that integrates the components of the major antecedents, this study advances a research framework that first involves the operationalization of the collected data as fuzzy numbers. Then, the SHapley Additive exPlanation-based method estimates the derived importance of each component in the hierarchical component model using an optimal two-layers back-propagation network. Finally, a nine quadrants division of the importance-performance analysis developed on the basis of relevance and determinance measures of the analyzed antecedent components, delineates the prioritization of their potential improvements. A case study aims to demonstrate the developed research framework, illustrating its effectiveness and flexibility in decision-making related to the improvement of such antecedents. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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