Activity-to-Skills Framework in the Intellectual Property Big Data Era

Nadja Damij, Ana Hafner, Dolores Modic*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
68 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)13251-13265
Number of pages15
JournalIEEE Transactions on Engineering Management
Volume71
Early online date22 Jun 2022
DOIs
Publication statusPublished - 2024

Keywords

  • Big Data
  • Big data
  • Companies
  • IP networks
  • Interviews
  • Patents
  • Task analysis
  • Technological innovation
  • data skills
  • innovation
  • intellectual property management
  • process management

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