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Artificial intelligence enabled product–service innovation: past achievements and future directions
University of Vaasa, School of Management, PO Box 700, 65101, Vaasa, Finland.ORCID iD: 0009-0006-3448-6370
University of Vaasa, School of Management, PO Box 700, 65101, Vaasa, Finland.ORCID iD: 0000-0003-2094-7974
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.ORCID iD: 0000-0003-3255-414X
2025 (English)In: Review of Managerial Science, ISSN 1863-6683, E-ISSN 1863-6691, Vol. 19, p. 2149-2192Article, review/survey (Refereed) Published
Abstract [en]

This study intends to scrutinize the role of Artificial Intelligence (AI) in Product-Service Innovation (PSI). The literature on AI enabled PSI, other related innovation business models, product-service systems, and servitization has grown significantly since 2018; therefore, there is a need to structure the literature in a systematic manner and add to what has been studied thus far. Product-service innovation is used to represent the relevance of achieving innovation in business models dealing with innovation outcomes including artificial intelligence. This study used bibliographic coupling to analyze 159 articles emerging from the fields of computer sciences, engineering, social sciences, decision sciences, and management. This review depicts structures of the literature comprising five (5) clusters, namely, (1) technology adoption and transformational barriers, which depicts the barriers faced during the adoption of AI-enabled technologies and following transformation; (2) data-driven capabilities and innovation, which highlights the data-based capabilities supported through AI and innovation; (3) digitally enabled business model innovation, which explained how AI-enabled business model innovation occurs; (4) smart design changes and sustainability, which reveals the working of AI in product service environments with different design changes and transformations based on sustainability; and (5) sectorial application, which highlights industry examples. Each cluster is comprehensively analyzed based on its contents, including central themes, models, theories, and methodologies, which help to identify the gaps and support suggestions for future research directions.

Place, publisher, year, edition, pages
Springer Nature, 2025. Vol. 19, p. 2149-2192
Keywords [en]
Artificial intelligence, Business models and strategy, Digitalization and digital transformation, Product-service innovation, Product-service system, Servitization
National Category
Business Administration Artificial Intelligence
Research subject
Entrepreneurship and Innovation
Identifiers
URN: urn:nbn:se:ltu:diva-105347DOI: 10.1007/s11846-024-00757-xISI: 001203993900001Scopus ID: 2-s2.0-85190709366OAI: oai:DiVA.org:ltu-105347DiVA, id: diva2:1856396
Note

Validerad;2025;Nivå 2;2025-06-26 (u5);

Full text license: CC BY 4.0;

Available from: 2024-05-06 Created: 2024-05-06 Last updated: 2025-10-21Bibliographically approved

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Parida, Vinit

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