1. The Innovation-to-Occupations Ontology: Linking Business Transformation Initiatives to Occupations and Skills
- Author
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Elia, Daniela, Chen, Fang, Zowghi, Didar, and Rizoiu, Marian-Andrei
- Subjects
Computer Science - Artificial Intelligence - Abstract
The fast adoption of new technologies forces companies to continuously adapt their operations making it harder to predict workforce requirements. Several recent studies have attempted to predict the emergence of new roles and skills in the labour market from online job ads. This paper aims to present a novel ontology linking business transformation initiatives to occupations and an approach to automatically populating it by leveraging embeddings extracted from job ads and Wikipedia pages on business transformation and emerging technologies topics. To our knowledge, no previous research explicitly links business transformation initiatives, like the adoption of new technologies or the entry into new markets, to the roles needed. Our approach successfully matches occupations to transformation initiatives under ten different scenarios, five linked to technology adoption and five related to business. This framework presents an innovative approach to guide enterprises and educational institutions on the workforce requirements for specific business transformation initiatives., Comment: 14 pages, 3 figures, Camera-ready version in ACIS 2023
- Published
- 2023