Show simple item record

dc.contributor.authorCubric, Marija
dc.contributor.authorLi, Feng
dc.date.accessioned2024-06-03T08:15:02Z
dc.date.available2024-06-03T08:15:02Z
dc.date.issued2024-06-30
dc.identifier.citationCubric , M & Li , F 2024 , ' Bridging the ‘Concept–Product’ gap in new product development: Emerging insights from the application of artificial intelligence in FinTech SMEs ' , Technovation , vol. 134 , 103017 , pp. 1-16 . https://doi.org/10.1016/j.technovation.2024.103017
dc.identifier.issn0166-4972
dc.identifier.otherJisc: 2011375
dc.identifier.urihttp://hdl.handle.net/2299/27931
dc.description© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/
dc.description.abstractBuilding on the literature on the concept-product gap in new product development, we examine how FinTech SMEs are developing Artificial Intelligence (AI)-based innovations and which organisational or project factors best contribute to the acceleration of AI innovation. The empirical evidence collected from interviews with key stakeholders, practitioners’ forums, and public company documents yields two distinct approaches that differ in their potential for accelerating innovation and reducing the concept-product gap. From a contingency perspective, these two approaches are expanded into four distinct development process configurations, contingent on the business development stage, reliance on 3rd party platforms, availability of high volumes of data, investment level, organisational agility, and level of novelty. The resulting process typology could be used as a diagnostic tool for FinTech SMEs interested in effectively leveraging AI innovation. Using contingency theory, we further develop these insights into a new theoretical framework to explain how AI innovation development unfolds in FinTech SMEs and the rationale for different implementations. Our new process typology and theoretical model can help researchers investigate the mechanisms underlying technological innovation processes. We further identify the specific reasons why the potential of AI for creating new services and disrupting incumbents via digital startups has not been fully realised even in contexts with significant investment and support from public and private business development programmes. This field is still rapidly evolving, and thus, new areas for future research are also highlighted.en
dc.format.extent16
dc.format.extent2543686
dc.language.isoeng
dc.relation.ispartofTechnovation
dc.subjectArtificial intelligence (AI)
dc.subjectFinTech
dc.subjectNew product development (NPD)
dc.subjectSmall and medium enterprise (SME)
dc.subjectGeneral Engineering
dc.subjectManagement of Technology and Innovation
dc.titleBridging the ‘Concept–Product’ gap in new product development: Emerging insights from the application of artificial intelligence in FinTech SMEsen
dc.contributor.institutionHertfordshire Business School
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85194347181&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1016/j.technovation.2024.103017
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record