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Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions

Marcello M. Mariani Orcid Logo, Isa Machado Orcid Logo, Vittoria Magrelli Orcid Logo, Yogesh Dwivedi Orcid Logo

Technovation, Volume: 122, Start page: 102623

Swansea University Author: Yogesh Dwivedi Orcid Logo

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DOI (Published version): 10.1016/j.technovation.2022.102623

Abstract

Artificial Intelligence (AI) is increasingly adopted by organizations to innovate, and this is ever more reflected in scholarly work. To illustrate, assess and map research at the intersection of AI and innovation, we performed a Systematic Literature Review (SLR) of published work indexed in the Cl...

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Published in: Technovation
ISSN: 0166-4972
Published: Elsevier BV 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa61035
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first_indexed 2022-09-05T17:55:03Z
last_indexed 2023-01-13T19:21:35Z
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spelling v2 61035 2022-09-05 Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions d154596e71b99ad1285563c8fdd373d7 0000-0002-5547-9990 Yogesh Dwivedi Yogesh Dwivedi true false 2022-09-05 BBU Artificial Intelligence (AI) is increasingly adopted by organizations to innovate, and this is ever more reflected in scholarly work. To illustrate, assess and map research at the intersection of AI and innovation, we performed a Systematic Literature Review (SLR) of published work indexed in the Clarivate Web of Science (WOS) and Elsevier Scopus databases (the final sample includes 1448 articles). A bibliometric analysis was deployed to map the focal field in terms of dominant topics and their evolution over time. By deploying keyword co-occurrences, and bibliographic coupling techniques, we generate insights on the literature at the intersection of AI and innovation research. We leverage the SLR findings to provide an updated synopsis of extant scientific work on the focal research area and to develop an interpretive framework which sheds light on the drivers and outcomes of AI adoption for innovation. We identify economic, technological, and social factors of AI adoption in firms willing to innovate. We also uncover firms' economic, competitive and organizational, and innovation factors as key outcomes of AI deployment. We conclude this paper by developing an agenda for future research. Journal Article Technovation 122 102623 Elsevier BV 0166-4972 Innovation; Artificial intelligence; Systematic literature review; Bibliometric analysis 10 9 2022 2022-09-10 10.1016/j.technovation.2022.102623 COLLEGE NANME Business COLLEGE CODE BBU Swansea University 2023-06-12T15:46:13.6776710 2022-09-05T18:50:38.6244828 Faculty of Humanities and Social Sciences School of Management - Business Management Marcello M. Mariani 0000-0002-7916-2576 1 Isa Machado 0000-0003-1024-0537 2 Vittoria Magrelli 0000-0002-9647-8425 3 Yogesh Dwivedi 0000-0002-5547-9990 4 61035__27809__fbb4ea9ddbe246a1a9aec02d20ac8600.pdf 61035.pdf 2023-06-12T15:44:53.8302852 Output 6305000 application/pdf Version of Record true © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). true eng http://creativecommons.org/licenses/by/4.0/
title Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions
spellingShingle Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions
Yogesh Dwivedi
title_short Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions
title_full Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions
title_fullStr Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions
title_full_unstemmed Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions
title_sort Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions
author_id_str_mv d154596e71b99ad1285563c8fdd373d7
author_id_fullname_str_mv d154596e71b99ad1285563c8fdd373d7_***_Yogesh Dwivedi
author Yogesh Dwivedi
author2 Marcello M. Mariani
Isa Machado
Vittoria Magrelli
Yogesh Dwivedi
format Journal article
container_title Technovation
container_volume 122
container_start_page 102623
publishDate 2022
institution Swansea University
issn 0166-4972
doi_str_mv 10.1016/j.technovation.2022.102623
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
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description Artificial Intelligence (AI) is increasingly adopted by organizations to innovate, and this is ever more reflected in scholarly work. To illustrate, assess and map research at the intersection of AI and innovation, we performed a Systematic Literature Review (SLR) of published work indexed in the Clarivate Web of Science (WOS) and Elsevier Scopus databases (the final sample includes 1448 articles). A bibliometric analysis was deployed to map the focal field in terms of dominant topics and their evolution over time. By deploying keyword co-occurrences, and bibliographic coupling techniques, we generate insights on the literature at the intersection of AI and innovation research. We leverage the SLR findings to provide an updated synopsis of extant scientific work on the focal research area and to develop an interpretive framework which sheds light on the drivers and outcomes of AI adoption for innovation. We identify economic, technological, and social factors of AI adoption in firms willing to innovate. We also uncover firms' economic, competitive and organizational, and innovation factors as key outcomes of AI deployment. We conclude this paper by developing an agenda for future research.
published_date 2022-09-10T15:46:11Z
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