An artificial intelligence-enabled industry classification and its interpretation
ISSN: 1066-2243
Article publication date: 29 June 2021
Issue publication date: 15 March 2022
Abstract
Purpose
To overcome the shortcomings of traditional industry classification systems such as the Standard Industrial Classification Standard Industrial Classification, North American Industry Classification System North American Industry Classification System, and Global Industry Classification Standard Global Industry Classification Standard, the authors explore industry classifications using machine learning methods as an application of interpretable artificial intelligence (AI).
Design/methodology/approach
The authors propose a text-based industry classification combined with a machine learning technique by extracting distinguishable features from business descriptions in financial reports. The proposed method can reduce the dimensions of word vectors to avoid the curse of dimensionality when measuring the similarities of firms.
Findings
Using the proposed method, the sample firms form clusters of distinctive industries, thus overcoming the limitations of existing classifications. The method also clarifies industry boundaries based on lower-dimensional information. The graphical closeness between industries can reflect the industry-level relationship as well as the closeness between individual firms.
Originality/value
The authors’ work contributes to the industry classification literature by empirically investigating the effectiveness of machine learning methods. The text mining method resolves issues concerning the timeliness of traditional industry classifications by capturing new information in annual reports. In addition, the authors’ approach can solve the computing concerns of high dimensionality.
Keywords
Acknowledgements
This research was supported by the MSIT(Ministry of Science, ICT), Korea, under the National Program for Excellence in SW), supervised by the IITP(Institute of Information and communications Technology Planning and Evaluation) in 2021 (2021-0-01389).
Citation
Kim, D., Kang, H.-G., Bae, K. and Jeon, S. (2022), "An artificial intelligence-enabled industry classification and its interpretation", Internet Research, Vol. 32 No. 2, pp. 406-424. https://doi.org/10.1108/INTR-05-2020-0299
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited