TWIN TRANSITION — A LITERATURE ANALYSIS OF THE RELATIONSHIP BETWEEN TWO MEGATRENDS AND THE ROLE OF ARTIFICIAL INTELLIGENCE
Sustainability and digitalisation can be considered as two megatrends that force companies to innovate in order to remain competitive. The twin transition circumscribes the parallelism of these megatrends, with the aim of achieving a synergistic combination. However, to date, there is a lack of scientific evidence on the relationship between sustainability and digitalisation and on the role of the twin transition for companies. Therefore, this article presents a systematic literature review following the PRISMA methodology to analyse how the concept of twin transition is currently understood, how the two transitions are related, and which organisational, external, and technological contextual factors influence the twin transition in companies. On the technological level, we put special emphasis on the impact of artificial intelligence (AI) for the twin transition, since it may significantly influence the interplay between digitalisation and sustainability. Our findings, derived from 70 scientific publications, reveal that (i) the social dimension of sustainability is mostly underrepresented in the discussion, (ii) the positive impact of digital to sustainable transition is much more evidence-based than vice versa, (iii) establishing the right capabilities, methods, and competences is essential to drive twin transition in companies, and (iv) indirect, positive ecological aspects of AI, as well as direct negative aspects, are predominantly discussed, but without addressing important social aspects. Finally, based on the literature review, we propose a new definition of the term twin transition. Future research is needed to reduce ambivalence and to provide a more profound and evidence-based picture of the assumed relations.
Authors
- Tobias Kopp (ORCID: https://orcid.org/0000-0001-6091-1189)
- Marco Baumgartner (ORCID: https://orcid.org/0000-0002-6184-7091)
- MANUEL NIEVER
Institutions
- Karlsruhe University of Applied Sciences (DE)
Publication Details
- Journal
- International Journal of Innovation Management
- Published
- 2025-05-30
- DOI
- https://doi.org/10.1142/s1363919625400110
- Citations
- 1
- Primary Topic
- Assisted Reproductive Technology and Twin Pregnancy
- Type
- article
- Field-Weighted Citation Impact
- 3.49