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Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review

Author

Listed:
  • Yong Qin

    (Sichuan University)

  • Zeshui Xu

    (Sichuan University)

  • Xinxin Wang

    (Sichuan University)

  • Marinko Skare

    (Juraj Dobrila University of Pula)

Abstract

In today’s environment of the rapid rise of artificial intelligence (AI), debate continues about whether it has beneficial effects on economic development. However, there is only a fragmented perception of what role and place AI technology actually plays in economic development (ED). In this paper, we pioneer the research by focusing our detective work and discussion on the intersection of AI and economic development. Specifically, we adopt a two-step methodology. At the first step, we analyze 2211 documents in the AI&ED field using the bibliometric tool Bibliometrix, presenting the internal structure and external characteristics of the field through different metrics and algorithms. In the second step, a qualitative content analysis of clusters calculated from the bibliographic coupling algorithm is conducted, detailing the content directions of recently distributed topics in the AI&ED field from different perspectives. The results of the bibliometric analysis suggest that the number of publications in the field has grown exponentially in recent years, and the most relevant source is the “Sustainability” journal. In addition, deep learning and data mining-related research are the key directions for the future. On the whole, scholars dedicated to the field have developed close cooperation and communication across the board. On the other hand, the content analysis demonstrates that most of the research is centered on the five facets of intelligent decision-making, social governance, labor and capital, Industry 4.0, and innovation. The results provide a forward-looking guide for scholars to grasp the current state and potential knowledge gaps in the AI&ED field.

Suggested Citation

  • Yong Qin & Zeshui Xu & Xinxin Wang & Marinko Skare, 2024. "Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 1736-1770, March.
    • Handle: RePEc:spr:jknowl:v:15:y:2024:i:1:d:10.1007_s13132-023-01183-2
    DOI: 10.1007/s13132-023-01183-2
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    as
    1. Marco Vivarelli, 2014. "Innovation, Employment and Skills in Advanced and Developing Countries: A Survey of Economic Literature," Journal of Economic Issues, Taylor & Francis Journals, vol. 48(1), pages 123-154.
    2. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    3. Vallaster, Christine & Kraus, Sascha & Merigó Lindahl, José M. & Nielsen, Annika, 2019. "Ethics and entrepreneurship: A bibliometric study and literature review," Journal of Business Research, Elsevier, vol. 99(C), pages 226-237.
    4. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    5. Tang, Xuli & Li, Xin & Ding, Ying & Song, Min & Bu, Yi, 2020. "The pace of artificial intelligence innovations: Speed, talent, and trial-and-error," Journal of Informetrics, Elsevier, vol. 14(4).
    6. Philippe Aghion & Céline Antonin & Simon Bunel, 2019. "Artificial Intelligence, Growth and Employment: The Role of Policy," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 149-164.
    7. Skiba, Marta & Mrówczyńska, Maria & Bazan-Krzywoszańska, Anna, 2017. "Modeling the economic dependence between town development policy and increasing energy effectiveness with neural networks. Case study: The town of Zielona Góra," Applied Energy, Elsevier, vol. 188(C), pages 356-366.
    8. Francesca Iandolo & Francesca Loia & Irene Fulco & Chiara Nespoli & Francesco Caputo, 2021. "Combining Big Data and Artificial Intelligence for Managing Collective Knowledge in Unpredictable Environment—Insights from the Chinese Case in Facing COVID-19," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(4), pages 1982-1996, December.
    9. Shiwei He & Rui Song & Sohail S. Chaudhry, 2014. "Service-oriented intelligent group decision support system: Application in transportation management," Information Systems Frontiers, Springer, vol. 16(5), pages 939-951, November.
    10. Kakatkar, Chinmay & Bilgram, Volker & Füller, Johann, 2020. "Innovation analytics: Leveraging artificial intelligence in the innovation process," Business Horizons, Elsevier, vol. 63(2), pages 171-181.
    11. Yong Qin & Xinxin Wang & Zeshui Xu & Marinko Škare, 2021. "The impact of poverty cycles on economic research: evidence from econometric analysis," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 152-171, January.
    12. Marko Jakšič & Matej Marinč, 2019. "Relationship banking and information technology: the role of artificial intelligence and FinTech," Risk Management, Palgrave Macmillan, vol. 21(1), pages 1-18, March.
    13. Bretas, Vanessa P.G. & Alon, Ilan, 2021. "Franchising research on emerging markets: Bibliometric and content analyses," Journal of Business Research, Elsevier, vol. 133(C), pages 51-65.
    14. Eduard Anton & Thuy Duong Oesterreich & Julian Schuir & Leslie Protz & Frank Teuteberg, 2021. "A Business Model Taxonomy for Start-Ups in the Electric Power Industry — The Electrifying Effect of Artificial Intelligence on Business Model Innovation," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 1-54, May.
    15. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    16. Xinxin Wang & Yurui Chang & Zeshui Xu & Zidong Wang & Visakan Kadirkamanathan, 2021. "50 Years of international journal of systems science: a review of the past and trends for the future," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(8), pages 1515-1538, June.
    17. Chattopadhyay, Pallavi Banerjee & Rangarajan, R., 2014. "Application of ANN in sketching spatial nonlinearity of unconfined aquifer in agricultural basin," Agricultural Water Management, Elsevier, vol. 133(C), pages 81-91.
    18. Gaur, Ajai & Kumar, Mukesh, 2018. "A systematic approach to conducting review studies: An assessment of content analysis in 25years of IB research," Journal of World Business, Elsevier, vol. 53(2), pages 280-289.
    19. Li, Jingrui & Wang, Rui & Wang, Jianzhou & Li, Yifan, 2018. "Analysis and forecasting of the oil consumption in China based on combination models optimized by artificial intelligence algorithms," Energy, Elsevier, vol. 144(C), pages 243-264.
    20. Cobo, M.J. & López-Herrera, A.G. & Herrera-Viedma, E. & Herrera, F., 2011. "An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field," Journal of Informetrics, Elsevier, vol. 5(1), pages 146-166.
    21. Ju, Keyi & Su, Bin & Zhou, Dequn & Zhang, Yuqiang, 2016. "An incentive-oriented early warning system for predicting the co-movements between oil price shocks and macroeconomy," Applied Energy, Elsevier, vol. 163(C), pages 452-463.
    22. Ben Vermeulen & Jan Kesselhut & Andreas Pyka & Pier Paolo Saviotti, 2018. "The Impact of Automation on Employment: Just the Usual Structural Change?," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    23. Elias G. Carayannis & Klitos Christodoulou & Panayiotis Christodoulou & Savvas A. Chatzichristofis & Zinon Zinonos, 2022. "Known Unknowns in an Era of Technological and Viral Disruptions—Implications for Theory, Policy, and Practice," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 587-610, March.
    24. Germán González Rodríguez & Jose M. Gonzalez-Cava & Juan Albino Méndez Pérez, 2020. "An intelligent decision support system for production planning based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1257-1273, June.
    25. Jane M. Binner & Alicia M. Gazely & Shu‐Heng Chen & Bin‐Tzong Chie, 2004. "Financial Innovation and Divisia Money in Taiwan: Comparative Evidence from Neural Network and Vector Error‐Correction Forecasting Models," Contemporary Economic Policy, Western Economic Association International, vol. 22(2), pages 213-224, April.
    26. Moll, Jodie & Yigitbasioglu, Ogan, 2019. "The role of internet-related technologies in shaping the work of accountants: New directions for accounting research," The British Accounting Review, Elsevier, vol. 51(6).
    27. Cen, Zhongpei & Wang, Jun, 2019. "Crude oil price prediction model with long short term memory deep learning based on prior knowledge data transfer," Energy, Elsevier, vol. 169(C), pages 160-171.
    28. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    29. Uzlu, Ergun & Kankal, Murat & Akpınar, Adem & Dede, Tayfun, 2014. "Estimates of energy consumption in Turkey using neural networks with the teaching–learning-based optimization algorithm," Energy, Elsevier, vol. 75(C), pages 295-303.
    30. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    31. Dwivedi, Yogesh K. & Hughes, D. Laurie & Coombs, Crispin & Constantiou, Ioanna & Duan, Yanqing & Edwards, John S. & Gupta, Babita & Lal, Banita & Misra, Santosh & Prashant, Prakhar & Raman, Ramakrishn, 2020. "Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life," International Journal of Information Management, Elsevier, vol. 55(C).
    32. Hsin-Ning Su & Pei-Chun Lee, 2010. "Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 65-79, October.
    33. Zhang, Yucheng & Zhang, Meng & Li, Jing & Liu, Guangjian & Yang, Miles M. & Liu, Siqi, 2021. "A bibliometric review of a decade of research: Big data in business research – Setting a research agenda," Journal of Business Research, Elsevier, vol. 131(C), pages 374-390.
    34. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    35. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    36. Rust, Roland T., 2020. "The future of marketing," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 15-26.
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