Cite Article
Cite Article
MLA
Gao, Di Kevin, et al. "AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps." IJBAN vol.11, no.1 2024: pp.1-19. http://doi.org/10.4018/IJBAN.338367
APA
Gao, D. K., Haverly, A., Mittal, S., Wu, J., & Chen, J. (2024). AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps. International Journal of Business Analytics (IJBAN), 11 (1), 1-19. http://doi.org/10.4018/IJBAN.338367
Chicago
Gao, Di Kevin, et al. "AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps," International Journal of Business Analytics (IJBAN) 11, no.1: 1-19. http://doi.org/10.4018/IJBAN.338367
Export Reference
International Journal of Business Analytics (IJBAN) The International Journal of Business Analytics (IJBAN) is an indispensable resource for practitioners and academics that work in Business Analytics and related fields. Business Analytics is commonly viewed from three major perspectives: descriptive, predictive, and prescriptive. Business Analytics provides the framework to exploit the synergies among traditionally-diverse topics, such as the fields of data mining, quantitative methods, OR/MS, DSS, and so forth, in a more practical, application-driven format. The journal bridges the gap among different disciplines such as data mining, business process optimization, applied business statistics, and business intelligence/information systems. The journal supports and provides tools to allow companies and organizations to make frequent, faster, smarter, data-driven, and real-time decisions.
View source title