IDEAS home Printed from https://ideas.repec.org/p/osf/thesis/a3zwu.html
   My bibliography  Save this paper

Innovation in Artificial Intelligence and the Catalyst of Open Data Sharing: Literature Review and Policy implications

Author

Listed:
  • Dam, John
  • Rickon, Henry

Abstract

This literature review aims to elucidate the nuanced relationship between data openness and innovation within the field of Artificial Intelligence (AI). As the significance of AI continues to expand across various sectors, understanding the role of open data in fostering innovation becomes increasingly critical. Through this review, we systematically explore and analyze the wealth of existing literature on the topic. We address key concepts, theoretical perspectives, and empirical findings, shedding light on the multi-dimensional facets of data openness, including accessibility and usability, and their impact on AI innovation. Furthermore, the review highlights the practical implications and potential strategies to leverage data openness in propelling AI innovation. We also identify existing gaps and limitations in current literature, suggesting avenues for future research. This comprehensive review contributes to the evolving discourse in AI studies, offering valuable insights to researchers, data managers, and AI practitioners alike.

Suggested Citation

  • Dam, John & Rickon, Henry, 2023. "Innovation in Artificial Intelligence and the Catalyst of Open Data Sharing: Literature Review and Policy implications," Thesis Commons a3zwu, Center for Open Science.
    • Handle: RePEc:osf:thesis:a3zwu
    DOI: 10.31219/osf.io/a3zwu
    as

    Download full text from publisher

    File URL: https://osf.io/download/646387781a5dd505351f0a74/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/a3zwu?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    2. Charles Ayoubi & Boris Thurm, 2023. "Knowledge diffusion and morality: Why do we freely share valuable information with Strangers?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(1), pages 75-99, January.
    3. Zoltán J. Ács & Pontus Braunerhjelm & David B. Audretsch & Bo Carlsson, 2015. "The knowledge spillover theory of entrepreneurship," Chapters, in: Global Entrepreneurship, Institutions and Incentives, chapter 7, pages 129-144, Edward Elgar Publishing.
    4. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2018. "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 23-57, National Bureau of Economic Research, Inc.
    5. Bresnahan, Timothy, 2010. "General Purpose Technologies," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 761-791, Elsevier.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Naudé, Wim, 2020. "From the Entrepreneurial to the Ossified Economy: Evidence, Explanations and a New Perspective," GLO Discussion Paper Series 539, Global Labor Organization (GLO).
    2. Ian Goldin & Pantelis Koutroumpis & François Lafond & Julian Winkler, 2024. "Why Is Productivity Slowing Down?," Journal of Economic Literature, American Economic Association, vol. 62(1), pages 196-268, March.
    3. Wim Naudé, 2022. "From the entrepreneurial to the ossified economy," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 46(1), pages 105-131.
    4. Pereira, Joana & Tavalaei, M. Mahdi & Ozalp, Hakan, 2019. "Blockchain-based platforms: Decentralized infrastructures and its boundary conditions," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 94-102.
    5. Lööf, Hans, 2022. "What prevents spillovers from the pool of knowledge?," Working Paper Series in Economics and Institutions of Innovation 489, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    6. Feld, Lars P. & Schmidt, Christoph M. & Schnabel, Isabel & Truger, Achim & Wieland, Volker, 2019. "Den Strukturwandel meistern. Jahresgutachten 2019/20 [Dealing with Structural Change. Annual Report 2019/20]," Annual Economic Reports / Jahresgutachten, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, volume 127, number 201920, September.
    7. Tachia Chin & Muhammad Waleed Ayub Ghouri & Jiyang Jin & Muhammet Deveci, 2024. "AI technologies affording the orchestration of ecosystem-based business models: the moderating role of AI knowledge spillover," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    8. Tabesh, Pooya & Mousavidin, Elham & Hasani, Sona, 2019. "Implementing big data strategies: A managerial perspective," Business Horizons, Elsevier, vol. 62(3), pages 347-358.
    9. Konon, Alexander & Fritsch, Michael & Kritikos, Alexander S., 2018. "Business cycles and start-ups across industries: An empirical analysis of German regions," Journal of Business Venturing, Elsevier, vol. 33(6), pages 742-761.
    10. Kariem Soliman, 2021. "Are Industrial Robots a new GPT? A Panel Study of Nine European Countries with Capital and Quality-adjusted Industrial Robots as Drivers of Labour Productivity Growth," EIIW Discussion paper disbei307, Universitätsbibliothek Wuppertal, University Library.
    11. Giancarlo Giudici & Massimiliano Guerini & Cristina Rossi-Lamastra, 2019. "The creation of cleantech startups at the local level: the role of knowledge availability and environmental awareness," Small Business Economics, Springer, vol. 52(4), pages 815-830, April.
    12. Boeker, Warren & Howard, Michael D. & Basu, Sandip & Sahaym, Arvin, 2021. "Interpersonal relationships, digital technologies, and innovation in entrepreneurial ventures," Journal of Business Research, Elsevier, vol. 125(C), pages 495-507.
    13. R. Sandra Schillo & Ajax Persaud & Meng Jin, 2016. "Entrepreneurial readiness in the context of national systems of entrepreneurship," Small Business Economics, Springer, vol. 46(4), pages 619-637, April.
    14. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    15. Naudé, Wim & Nagler, Paula, 2022. "The Ossified Economy: The Case of Germany, 1870-2020," IZA Discussion Papers 15607, Institute of Labor Economics (IZA).
    16. Stefano D’Angelo & Angelo Cavallo & Antonio Ghezzi & Francesco Di Lorenzo, 2024. "Understanding corporate entrepreneurship in the digital age: a review and research agenda," Review of Managerial Science, Springer, vol. 18(12), pages 3719-3774, December.
    17. Mikaela Backman & Charlie Karlsson, 2016. "Determinants of self-employment among commuters and non-commuters," Papers in Regional Science, Wiley Blackwell, vol. 95(4), pages 755-774, November.
    18. Xiangfei Yuan & Haijing Hao & Chenghua Guan & Alex Pentland, 2022. "Which factors affect the performance of technology business incubators in China? An entrepreneurial ecosystem perspective," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-20, January.
    19. Rolando Rubilar-Torrealba & Karime Chahuán-Jiménez & Hanns de la Fuente-Mella & Mercedes Marzo-Navarro, 2022. "Econometric Modeling to Measure the Social and Economic Factors in the Success of Entrepreneurship," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    20. Mark Knell & Simone Vannuccini, 2022. "Tools and concepts for understanding disruptive technological change after Schumpeter," Jena Economics Research Papers 2022-005, Friedrich-Schiller-University Jena.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:thesis:a3zwu. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://thesiscommons.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.