| Autor: |
Damij, Nadja, Hafner, Ana, Modic, Dolores |
| Zdroj: |
IEEE Transactions on Engineering Management; 2024, Vol. 71 Issue: 1 p13251-13265, 15p |
| Abstrakt: |
With new technological advances such as the advent of big data, new opportunities are arising for companies. The dynamic nature of external environments is also causing the need to revise the necessary employees’ skills. This article focuses on exploring the data skills in the context of intellectual property (IP) processes. By combining the resource-based view with a process approach, we designed our novel activity-to-skills framework to identify data skills. We posit that data skills are nonhomogenous and are not singular occurrences. Subsequently, we extend the taxonomy of required data skills by defining five types of data skills, as well as deepening the understanding of how these skills are distributed within IP activities and interwoven with nondata skill types. IP data skills come to the forefront most in IP commercialization activities. We develop implications for innovation managers based on interviews with elite informants—prominent IP experts—seven of them heads of their respective IP departments. |
| Databáze: |
Supplemental Index |
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