APA (7th ed.) Citation

Hilbert, M., Thakur, A., Flores, P. M., Zhang, X., Bhan, J. Y., Bernhard, P., & Ji, F. (2024). 8–10% of algorithmic recommendations are ‘bad’, but… an exploratory risk-utility meta-analysis and its regulatory implications. International journal of information management, 75, 102743. https://doi.org/10.1016/j.ijinfomgt.2023.102743

Chicago Style (17th ed.) Citation

Hilbert, Martin, Arti Thakur, Pablo M. Flores, Xiaoya Zhang, Jee Young Bhan, Patrick Bernhard, and Feng Ji. "8–10% of Algorithmic Recommendations Are ‘bad’, but… an Exploratory Risk-utility Meta-analysis and Its Regulatory Implications." International Journal of Information Management 75 (2024): 102743. https://doi.org/10.1016/j.ijinfomgt.2023.102743.

MLA (9th ed.) Citation

Hilbert, Martin, et al. "8–10% of Algorithmic Recommendations Are ‘bad’, but… an Exploratory Risk-utility Meta-analysis and Its Regulatory Implications." International Journal of Information Management, vol. 75, 2024, p. 102743, https://doi.org/10.1016/j.ijinfomgt.2023.102743.