Approaching Artificial Intelligence in business and economics research: a bibliometric panorama (1966–2020)

ABSTRACT

This study takes stock of business and economics research on Artificial Intelligence (AI) and provides a dynamic panorama of the overall knowledge structure of this ever-growing body of work ever since its inception in 1966. Our bibliometric analysis based on the full archive of 1024 studies identifies the main trends of and the major intellectual contributors to the extant knowledge of AI in business and economics research. Specifically, our results show that (1) AI-focused business and economics research wintnessed growth over three stages, particularly with a sharp increase after 2017. (2) While this body of research has gained tremendous momentum across the globe, the United States is by far the center of knowledge generation. (3) Research collaborations are still limited in this area. (4) Research topics flourished, ranging from early decision support systems, neural networks, and scheduling methods to more recent machine learning, automation, and big data. This study also identifies fruitful avenues for further business and economics research with an AI focus.

KEYWORDS:

• Artificial intelligence
• business research
• intellectual trends
• bibliometric panorama

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 This date falls in the revision period of this manuscript. Data were re-extracted and analyses updated for the revised manuscript.

Additional information

Funding

The work was supported by National Natural Science Foundation of China [Grant Number: 72002002].

Notes on contributors

Dong Yang

Dr. Yang Dong is associate professor at the School of Management, Anhui University of Finance and Economics (China). He received his PhD from Dongbei University of Finance and Economics (China), Dr. Dong’s research interests include technology management, strategy, artificial intelligence, and bibliometrics.

W. G. (Will) Zhao

Dr. W. G. (Will) Zhao earned his Ph.D. from EM Lyon Business School (France) and conducted his postdoctoral research at Stanford University (USA). Prior to joining University of Waterloo (Canada), Dr. Zhao received his tenure at Lakehead University (Canada). An interdisciplinary scholar, Dr. Zhao’s primary research interests lie in analyzing the organizational aspects of creativity, innovation, and entrepreneurship. His work on organization theory has appearedin prestigious outlets such as Research in the Sociology of Organizations, and his most recent research on artificial intelligence has been published in leading journals such as IEEE Transactions on Cybernetics.

Jingjing Du

Dr. Jingjing Du is full professor at the School of Management, Anhui University of Finance and Economics (China). She received her PhD from the University of Science and Technology of China. Dr. Du’s research interests center on organization and digital transformation.

Yimin Yang

Dr. Yimin Yang (IEEE SM) is faculty affiliate at the Vector Institute for Artificial Intelligence (Canada) and assistant professor in Computer Science at Lakehead University (Canada). Prior to his professorship, Dr. Yang was a postdoctoral fellow at University of Windsor (Canada). He is an Associate Editor of the IEEE Transactions on Circuits and Systems for Video Technology and of Neurocomputing. Dr. Yang’s research interests include machine learning, neural networks and signal processing. His work appeared in leading artificial intelligence journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence.