Role of Artificial Intelligence and Machine Learning in E-commerce: a Literature Review
Resumen In an era where digital transformation is accelerating rapidly, artificial intelligence and machine learning have emerged as transformative forces, especially in e-commerce. This paper presents a comprehensive literature review that delves into the fundamentals of e-commerce, artificial intelligence, and machine learning, highlighting their key advantages and practical applications. By examining a broad array of studies, this research evaluates the critical role of artificial intelligence and machine learning in reshaping e-commerce and explores the potential these technologies hold for enhancing customer engagement and driving sales. The paper underscores how e-commerce companies leverage artificial intelligence-driven innovations to influence customer behaviour, enhance personalised marketing, and streamline purchasing pathways. However, the path to successful artificial intelligence integration is not without obstacles. Challenges such as organisational resistance, skills shortages, technical limitations, and awareness gaps are notable barriers. Despite these hurdles, the findings suggest that adopting artificial intelligence and machine learning tools positions e-commerce companies for long-term success, offering significant competitive advantages and fostering sustainable growth in an increasingly digital world.
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Grünbichler, R. (2023). Implementation barriers of artificial intelligence in companies. In Proceedings of FEB Zagreb International Odyssey Conference on Economics and Business (pp. 193–203). University of Zagreb.
Hagberg, J., Sundstrom, M., & Egels-Zandén, N. (2016). The digitalization of retailing: An exploratory framework. International Journal of Retail & Distribution Management, 44, 694–712. https://doi.org/10.1108/IJRDM-09-2015-0140
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He, X., & Liu, Y. (2024). Knowledge evolutionary process of artificial intelligence in e-commerce: Main path analysis and science mapping analysis. Expert Systems with Applications, 238, 121801. https://doi.org/10.1016/j.eswa.2024.121801
Heimbach, I., Kostyra, D., & Hinz, O. (2015). Marketing automation. Business & Information Systems Engineering, 57(2), 129–133. https://doi.org/10.1007/s12599-015-0370-8
Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
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