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The Potential Of Ai In B2b E-Commerce: A Structured Literature Review

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  • Harald Konnerth

Abstract

Unlike B2C E-Commerce, the exploration of E-Commerce in the B2B domain has not been as extensive, although B2B business models are expanding, and the number of purely online transactions is steadily increasing. The following application areas highlight the potential of Artificial Intelligence (AI) in B2B commerce for enhancing efficiency and improving the customer experience. Personalization enables individual product recommendations and tailored offers. AI analyzes data to predict customer needs and provide recommendations while automating repetitive tasks such as order processing and customer support. AI-powered systems assist customers in product search and ordering, and aid in dynamic pricing to maximize revenue. This paper summarizes the existing literature through a structured literature review in the context of B2B E-Commerce.

Suggested Citation

  • Harald Konnerth, 2023. "The Potential Of Ai In B2b E-Commerce: A Structured Literature Review," Economy & Business Journal, International Scientific Publications, Bulgaria, vol. 17(1), pages 114-133.
    • Handle: RePEc:isp:journl:v:17:y:2023:i:1:p:114-133
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    References listed on IDEAS

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    1. Hong Pan & Hanxun Zhou, 2020. "Study on convolutional neural network and its application in data mining and sales forecasting for E-commerce," Electronic Commerce Research, Springer, vol. 20(2), pages 297-320, June.
    2. K.H. Leung & C.C. Luk & K.L. Choy & H.Y. Lam & Carman K.M. Lee, 2019. "A B2B flexible pricing decision support system for managing the request for quotation process under e-commerce business environment," International Journal of Production Research, Taylor & Francis Journals, vol. 57(20), pages 6528-6551, October.
    3. Ruiqi Wei & Catherine Pardo, 2022. "Artificial intelligence and SMEs : How can B2B SMEs leverage AI platforms to integrate AI technologies?," Post-Print hal-04325639, HAL.
    4. Yumeng Miao & Rong Du & Jin Li & J. Christopher Westland, 2019. "A two-sided matching model in the context of B2B export cross-border e-commerce," Electronic Commerce Research, Springer, vol. 19(4), pages 841-861, December.
    5. M. Sivaram & V. Porkodi & A. Jayanthiladevi, 2022. "Digital commerce in enterprises," International Journal of Enterprise Network Management, Inderscience Enterprises Ltd, vol. 13(1), pages 37-43.
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    More about this item

    Keywords

    artificial intelligence; machine learning; e-commerce; electronic-commerce; b2b; business-to-business;
    All these keywords.

    JEL classification:

    • A - General Economics and Teaching

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