AI applications in business: Trends and insights using bibliometric analysis
The International Journal of Management Education, ISSN: 1472-8117, Vol: 22, Issue: 3, Page: 101075
2024
- 57Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures57
- Readers57
- 57
Article Description
Artificial intelligence in the business plays key role in the current world. To track the research output, we conducted bibliometric analysis on the Artificial Intelligence (AI) applications in business from 1977 to 2023. The main objective of this study is to examine publication trends, influential authors, impactful sources, global contributions, and prevalent keywords, themes employing rigorous statistical methodologies. SCOPUS database was searched with AI and Business term from the starting period and biblioshiny and Vos Viewer software used for the analysis. Key findings reveal a rising trend in AI applications in business publications. Leading journals emerge, and the USA, United Kingdom, and China lead in global contributions. Frequently used keywords encompass ethics, machine learning, and big data. Thematic mapping categorizes themes, unveiling motor, niche, emerging, and basic themes. This analysis provides a comprehensive overview for researchers, policymakers, management educators and industry practitioners, shedding light on the dynamic landscape of AI and its intersection with business.
Bibliographic Details
Elsevier BV
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