The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Applications of artificial intelligence in business management, e-commerce and finance
Abstract
Abstract In the e-commerce and financial industries, AI has been deployed to achieve better customer experience, efficient supply chain management, improved operational efficiency, and reduced mate size, with the main goal of designing standard, reliable product quality control methods and the search for new ways of reaching and serving customers while maintaining low cost. Machine learning and deep learning are two of the most often used AI approaches. Individuals, businesses, and government agencies utilize these models to anticipate and learn from data. Machine learning models for the complexity and diversity of data in the food industry are being developed at the moment. This article discusses machine learning and artificial intelligence applications in e-commerce, corporate management, and finance. Sales growth, profit maximization, sales forecast, inventory management, security, fraud detection, and portfolio management are some of the major uses.
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1 retracted
Retracted: Artificial Intelligence Based Smart Facial Expression Recognition Remote Control System
Ganesh, R. S., Jausmin, K. J., Srilatha, J., Indumathy, R., Naved, M. I., & Ashok, M. (2021) · International Conference on Computing Methodologies and Communication (ICCMC) · doi:10.1109/iccmc51019.2021.9418031 · Cited by 29
Self-citationRetractedMachine learning: Algorithms, real-world applications and research directions
Sarker, I. H. (2021) · SN Computer Science · doi:10.1007/s42979-021-00592-x · Cited by 5,583
Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.08.019 · Cited by 1,096
Artificial Intelligence in Business: From Research and Innovation to Market Deployment
Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2020) · Procedia Computer Science · doi:10.1016/j.procs.2020.03.272 · Cited by 310
Di Vaio, A., Boccia, F., Landriani, L., & Palladino, R. (2020) · Sustainability · doi:10.3390/su12124851 · Cited by 292
Application of Artificial Intelligence in Healthcare: Chances and Challenges
Manne, R., & Kantheti, S. C. (2021) · Current Journal of Applied Science and Technology · doi:10.9734/cjast/2021/v40i631320 · Cited by 202
Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2019) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.1905.02092 · Cited by 166
Machine Learning Algorithms in Healthcare: A Literature Survey
Ferdous, M., Debnath, J., & Chakraborty, N. R. (2020) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt49239.2020.9225642 · Cited by 82
Efficient Conversion Prediction in E-Commerce Applications with Unsupervised Learning
Szabó, P. G., & Genge, B. (2020) · International Conference on Software, Telecommunications and Computer Networks (SoftCOM) · doi:10.23919/softcom50211.2020.9238344 · Cited by 10
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Rashid, A. B., & Kausik, M. A. K. (2024) · Hybrid Advances · doi:10.1016/j.hybadv.2024.100277 · Cited by 764
AI and sustainable business model innovation: A systematic literature review
Sharma, A., Khokhar, M., Duan, Y., Bibi, M., Sharma, R., & Muhammad, B. (2025) · Sustainable Futures · doi:10.1016/j.sftr.2025.101204 · Cited by 19
Metadata
- Authors
- Pallathadka, H., Ramirez-Asis, E. H., Loli-Poma, T. P., Kaliyaperumal, K., Ventayen, R. J. M., & Naved, M.
- Venue
- Materials Today: Proceedings
- Publisher
- Elsevier BV
- Published
- 2023
- Volume
- 80
- Pages
- 2610-2613
- ISSN
- 2214-7853 (ISSN-L)
- OpenAlex
- W3182797139
- Cited by
- 258
- References
- 9
- FWCI
- 15.00
- Type
- journal article
- Language
- en
- Open access
- closed
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- Pallathadka, H., Ramirez-Asis, E. H., Loli-Poma, T. P., Kaliyaperumal, K., Ventayen, R. J. M., & Naved, M. (2023). Applications of artificial intelligence in business management, e-commerce and finance. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.06.419
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.