Artificial intelligence in business and economics research: trends and future
Abstract
Artificial Intelligence is a disruptive technology developed during the 20th century, which has undergone an accelerated evolution, underpinning solutions to complex problems in the business world. Neural Networks, Machine Learning, or Deep Learning are concepts currently associated with terms such as digital marketing, decision making, industry 4.0 and business digital transformation. Interest in this technology will increase as the competitive advantages of the use of Artificial Intelligence by economic entities is realised. The aim of this research is to analyse the state-of-the-art research of Artificial Intelligence in business. To this end, a bibliometric analysis has been implement using the Web of Science and Scopus online databases. By using a fractional counting method, this paper identifies 11 clusters and the most frequent terms used in Artificial Intelligence research. The present study identifies the main trends in research on Artificial Intelligence in business and proposes future lines of inquiry.
First published online 29 October 2020
Keyword : artificial intelligence, business, economics, bibliometrics, research trends, decision-making
How to Cite
Ruiz-Real, J. L., Uribe-Toril, J., Torres, J. A., & De Pablo, J. (2021). Artificial intelligence in business and economics research: trends and future. Journal of Business Economics and Management, 22(1), 98-117. https://doi.org/10.3846/jbem.2020.13641
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Huang, Z., Chen, H., Hsu, C.-J., Chen, W.-H., & Wu, S. (2004). Credit rating analysis with support vector machines and neural networks: A market comparative study. Decision Support Systems, 37(4), 543–558. https://doi.org/10.1016/S0167-9236(03)00086-1
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Jan, M. N., & Ayub, U. (2019). Do the Fama and French five-factor model forecast well using ANN? Journal of Business Economics and Management, 20(1), 168–191. https://doi.org/10.3846/jbem.2019.8250
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LeBaron, B., Arthur, W. B., & Palmer, R. (1999). Time series properties of an artificial stock market. Journal of Economic Dynamics and Control, 23(9–10), 1487–1516. https://doi.org/10.1016/S0165-1889(98)00081-5
Lee, L. W., Dabirian, A., McCarthy, I. P., & Kietzmann, J. (2020). Making sense of text: Artificial intelligence-enabled content analysis. European Journal of Marketing, 54(3), 615–644. https://doi.org/10.1108/EJM-02-2019-0219
Lee, Y. K., & Park, D. W. (2018). Design of internet of things business model with deep learning artificial intelligence. International Journal of Grid and Distributed Computing, 11(7), 11–22. https://doi.org/10.14257/ijgdc.2018.11.7.02
Li, B., Hou, B., Yu, W., Lu, X., & Yang, C. (2017). Applications of artificial intelligence in intelligent manufacturing: A review. Frontiers of Information Technology & Electronic Engineering, 18(1), 86– 96. https://doi.org/10.1631/FITEE.1601885
Luo, H., Du, B., Huang, G. Q., Chen, H., & Li, X. (2013). Hybrid flow shop scheduling considering machine electricity consumption cost. International Journal of Production Economics, 146(2), 423–439. https://doi.org/10.1016/j.ijpe.2013.01.028
Maknickiene, N., & Maknickas, A. (2013). Financial market prediction system with Evolino neural network and Delphi method. Journal of Business Economics and Management, 14(2), 403–413. https://doi.org/10.3846/16111699.2012.729532
Marinchak, C. L. M., Forrest, E., & Hoanca, B. (2018). The impact of artificial intelligence and virtual personal assistants on marketing. In D. B. A. M. Khosrow-Pour (Ed.), Encyclopedia of information science and technology (4th ed., pp. 5748–5756). IGI Global. https://doi.org/10.4018/978-1-5225-2255-3.ch499
McCarthy, J. (1960). Programs with common sense (pp. 300–307). RLE and MIT Computation Center.
Miles, R. E., & Snow, C. C. (1986). Organizations: New concepts for new forms. California Management Review, 28(3), 62–73. https://doi.org/10.2307/41165202
MIT Sloan Management Review. (2017). Reshaping business with artificial intelligence. Closing the gap between ambition and action. https://sloanreview.mit.edu/projects/reshaping-business-with-artificial-intelligence/
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