참고문헌
- Andreotta, A. J., Kirkham, N., & Rizzi, M. (2022). AI, big data, and the future of consent. Ai & Society, 37(4), 1715-1728. https://doi.org/10.1007/s00146-021-01262-5
- Cha, S. S. (2023). A Study of AI Impact on the Food Industry. The Korean Journal of Food & Health Convergence, 9(4), 19-23.
- Duarte, V., Zuniga-Jara, S., & Contreras, S. (2022). Machine Learning and Marketing: A Systematic Literature Review. IEEE Access.
- Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California management review, 61(4), 5-14. https://doi.org/10.1177/0008125619864925
- Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50. https://doi.org/10.1007/s11747-020-00749-9
- Kamal, M., & Himel, A. S. (2023). Redefining Modern Marketing: An Analysis of AI and NLP's Influence on Consumer Engagement, Strategy, and Beyond. Eigenpub Review of Science and Technology, 7(1), 203-223.
- Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business horizons, 62(1), 15-25. https://doi.org/10.1016/j.bushor.2018.08.004
- Li, X., Liu, H., Wang, W., Zheng, Y., Lv, H., & Lv, Z. (2022). Big data analysis of the internet of things in the digital twins of smart city based on deep learning. Future Generation Computer Systems, 128, 167-177. https://doi.org/10.1016/j.future.2021.10.006
- Liu, F., Li, M., Wang, Q., Yan, J., Han, S., Ma, C., ... & McClements, D. J. (2023). Future foods: Alternative proteins, food architecture, sustainable packaging, and precision nutrition. Critical Reviews in Food Science and Nutrition, 63(23), 6423-6444. https://doi.org/10.1080/10408398.2022.2033683
- Murdoch, B. (2021). Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Medical Ethics, 22(1), 1-5. https://doi.org/10.1186/s12910-021-00687-3
- Patricio, D. I., & Rieder, R. (2018). Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review. Computers and electronics in agriculture, 153, 69-81. https://doi.org/10.1016/j.compag.2018.08.001
- Rai, A. (2020). Explainable AI: From black box to glass box. Journal of the Academy of Marketing Science, 48, 137-141. https://doi.org/10.1007/s11747-019-00710-5
- Robert, R., Kentish-Barnes, N., Boyer, A., Laurent, A., Azoulay, E., & Reignier, J. (2020). Ethical dilemmas due to the Covid-19 pandemic. Annals of intensive care, 10, 1-9. https://doi.org/10.1186/s13613-019-0618-4
- Smaros, J., Lehtonen, J. M., Appelqvist, P., & Holmstrom, J. (2003). The impact of increasing demand visibility on production and inventory control efficiency. International journal of physical distribution & logistics management, 33(4), 336-354. https://doi.org/10.1108/09600030310478801
- Stone, M., Aravopoulou, E., Ekinci, Y., Evans, G., Hobbs, M., Labib, A., ... & Machtynger, L. (2020). Artificial intelligence (AI) in strategic marketing decision-making: a research agenda. The Bottom Line, 33(2), 183-200. https://doi.org/10.1108/BL-03-2020-0022
- Yoo, T. Y., Cha, S. S. (2023). Foodservice Trend Predictions and Implications in 2024. The Korean Journal of Food & Health Convergence, 9(6), 21-26.
- Zhang, C., Bengio, S., Hardt, M., Recht, B., & Vinyals, O. (2021). Understanding deep learning (still) requires rethinking generalization. Communications of the ACM, 64(3), 107-115