Mapping the conceptual structure of innovation in artificial intelligence research: A bibliometric analysis and systematic literature review

被引:19
|
作者
Obreja, Dragos M. [1 ]
Rughinis, Razvan [2 ,3 ]
Rosner, Daniel [2 ]
机构
[1] Univ Bucharest, Fac Sociol & Social Work, Sect 5,90-92 Panduri Rd, Bucharest 050663, Romania
[2] Natl Univ Sci & Technol Politehn Bucharest, Bucharest, Romania
[3] Romanian Acad Scientists, Bucharest, Romania
来源
JOURNAL OF INNOVATION & KNOWLEDGE | 2024年 / 9卷 / 01期
关键词
Bibliometrics; AI innovation; Conceptual structure; Artificial intelligence; Big data; CO-WORD ANALYSIS; INTELLECTUAL STRUCTURE; BUSINESS MODELS; TRENDS; SCIENTOMETRICS; IMPLEMENTATION; TECHNOLOGY; MANAGEMENT; KNOWLEDGE; DESIGN;
D O I
10.1016/j.jik.2024.100465
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study uses bibliometric analysis and a systematic literature review to map the conceptual structure of artificial intelligence innovations (AI-I) in the social sciences between 2000 and 2023. It explicitly focuses on non-economic aspects conducive to AI-I, namely social, technological, cultural, sustainable, personal, moral, and ethical. Our analysis reveals that 1225 articles and proceeding papers have been published, and terms such as "technology," "big data," "management," "performance," "future," and "impact" are the most frequently used when discussing innovation and AI. According to our time-zone analysis, the last two years have shown a significant emphasis on concepts such as "transformation," "corporate social responsibility," and "resource-based view." In terms of citations, the countries that receive the highest number of references in the AI-I field are the United Kingdom, the United States, Germany, Australia, and China. The most prolific authors in terms of publications are David Teece, Erik Brynjolfsson, and Anjan Chatterjee. Given that most studies highlight the economic side of AI-I, we selected the most prolific 163 articles from all social science research areas. These studies legitimize the main non-economic aspects that highlight both certainties and uncertainties conducive to such innovations. Although the technological component is the most popular in our analysis of the non-economic aspects of the AI-I subfield, we find an important emphasis on ethical/ moral dimensions conducive to slow innovation principles. We also observe a growing interest in the cultural dimension, specifically exploring potential factors that can lead to better human acceptance of these innovations. (c) 2024 Published by Elsevier Espana, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
页数:15
相关论文
共 50 条
  • [21] Artificial Intelligence for Cybersecurity: A Systematic Mapping of Literature
    Wiafe, Isaac
    Koranteng, Felix Nti
    Obeng, Emmanuel Nyarko
    Assyne, Nana
    Wiafe, Abigail
    Gulliver, Stephen R.
    IEEE ACCESS, 2020, 8 : 146598 - 146612
  • [22] Mapping research strands of ethics of artificial intelligence in healthcare: A bibliometric and content analysis
    Saheb, Tahereh
    Saheb, Tayebeh
    Carpenter, David O.
    COMPUTERS IN BIOLOGY AND MEDICINE, 2021, 135
  • [23] Conceptual structure and perspectives on "innovation management": A bibliometric review
    Naeini, Ali Bonyadi
    Zamani, Mehdi
    Daim, Tugrul U.
    Sharma, Mahak
    Yalcin, Haydar
    TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2022, 185
  • [24] Mapping inclusive innovation: A bibliometric study and literature review
    Mortazavi, Sina
    Eslami, Mohammad H.
    Hajikhani, Arash
    Vaatanen, Juha
    JOURNAL OF BUSINESS RESEARCH, 2021, 122 : 736 - 750
  • [25] Artificial intelligence in information systems research: A systematic literature review and research agenda
    Collins, Christopher
    Dennehy, Denis
    Conboy, Kieran
    Mikalef, Patrick
    INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2021, 60
  • [26] Artificial intelligence in acute care: A systematic review, conceptual synthesis, and research agenda
    Meyer, Lea Mareen
    Stead, Susan
    Salge, Torsten Oliver
    Antons, David
    TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2024, 206
  • [27] Systematic literature review and retrospective bibliometric analysis on ESG research
    Mukhtar, Bilal
    Shad, Muhammad Kashif
    Ali, Kashif
    Woon, Lai Fong
    Waqas, Ahmad
    INTERNATIONAL JOURNAL OF PRODUCTIVITY AND PERFORMANCE MANAGEMENT, 2025, 74 (04) : 1365 - 1399
  • [28] Using artificial intelligence to make sustainable development decisions considering VUCA: a systematic literature review and bibliometric analysis
    Nikseresht, Ali
    Hajipour, Bahman
    Pishva, Nima
    Mohammadi, Hossein Abbasian
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (28) : 42509 - 42538
  • [29] Using artificial intelligence to make sustainable development decisions considering VUCA: a systematic literature review and bibliometric analysis
    Ali Nikseresht
    Bahman Hajipour
    Nima Pishva
    Hossein Abbasian Mohammadi
    Environmental Science and Pollution Research, 2022, 29 : 42509 - 42538
  • [30] Mapping Innovation Research in Organizations: A Bibliometric Analysis
    Peng, Renzhong
    Chen, Jingshuang
    Wu, Weiping
    FRONTIERS IN PSYCHOLOGY, 2021, 12