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Artificial intelligence capabilities for circular business models: Research synthesis and future agenda
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.ORCID iD: 0000-0001-9434-5429
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. USN Business School, University of South-Eastern Norway, Vestfold, Norway.ORCID iD: 0000-0001-5464-2007
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. USN Business School, University of South-Eastern Norway, Vestfold, Norway; Department of Management, University of Vaasa, Vaasa, Finland.ORCID iD: 0000-0003-3255-414X
Department of Computer Science, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim, Norway; SINTEF Digital, Department of Technology Management, Trondheim, Norway.
2024 (English)In: Technological forecasting & social change, ISSN 0040-1625, E-ISSN 1873-5509, Vol. 200, article id 123189Article in journal (Refereed) Published
Abstract [en]

This study explores the interlink between AI capabilities and circular business models (CBMs) through a literature review. Extant literature reveals that AI can act as efficiency catalyst, empowering firms to implement CBM. However, the journey to harness AI for CBM is fraught with challenges as firms grapple with the lack of sophisticated processes and routines to tap into AI's potential. The fragmented literature leaves a void in understanding the barriers and development pathways for AI capabilities in CBM contexts. Bridging this gap, adopting a capabilities perspective, this review intricately brings together four pivotal capabilities: integrated intelligence capability, process automation and augmentation capability, AI infrastructure and platform capability, and ecosystem orchestration capability as drivers of AI-enabled CBM. These capabilities are vital to navigating the multi-level barriers to utilizing AI for CBM. The key contribution of the study is the synthesis of an AI-enabled CBM framework, which not only summarizes the results but also sets the stage for future explorations in this dynamic field.

Place, publisher, year, edition, pages
Elsevier Inc. , 2024. Vol. 200, article id 123189
Keywords [en]
AI future research agenda, Artificial intelligence, Business model innovation, Circular business models
National Category
Business Administration
Research subject
Entrepreneurship and Innovation
Identifiers
URN: urn:nbn:se:ltu:diva-103988DOI: 10.1016/j.techfore.2023.123189ISI: 001167365900001Scopus ID: 2-s2.0-85182439398OAI: oai:DiVA.org:ltu-103988DiVA, id: diva2:1832317
Funder
Swedish Research Council Formas, 2020-01791Vinnova
Note

Validerad;2024;Nivå 2;2024-02-16 (joosat);

Funder: Norwegian Research Council;

Full text license: CC BY

Available from: 2024-01-29 Created: 2024-01-29 Last updated: 2024-11-20Bibliographically approved

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Madanaguli, ArunSjödin, DavidParida, Vinit

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