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    Which product description phrases affect sales forecasting? An explainable AI framework by integrating WaveNet neural network models with multiple regression

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    Publication date
    2023
    End of Embargo
    2025-02-24
    Author
    Chen, S.
    Ke, S.
    Han, S.
    Gupta, S.
    Sivarajah, Uthayasankar
    Keyword
    Text mining
    Sales forecasting
    WaveNet neural network
    Explainable AI
    Cross-border e-commerce
    Rights
    © 2023 Published by Elsevier B.V. All rights reserved. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
    Peer-Reviewed
    Yes
    Open Access status
    embargoedAccess
    
    Metadata
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    Abstract
    The rapid rise of many e-commerce platforms for individual consumers has generated a large amount of text-based data, and thus researchers have begun to experiment with text mining techniques to extract information from the large amount of textual data to assist in sales forecasting. The existing literature focuses textual data on product reviews; however, consumer reviews are not something that companies can directly control, here we argue that textual product descriptions are also important determinants of consumer choice. We construct an artificial intelligence (AI) framework that combines text mining, WaveNet neural networks, multiple regression, and SHAP model to explain the impact of product descriptions on sales forecasting. Using data from nearly 200,000 sales records obtained from a cross-border e-commerce firm, an empirical study showed that the product description presented to customers can influence sales forecasting, and about 44% of the key phrases greatly affect sales forecasting results, the sales forecasting models that added key product description phrases had improved forecasting accuracy. This paper provides explainable results of sales forecasting, which can provide guidance for firms to design product descriptions with reference to the market demand reflected by these phrases, and adding these phrases to product descriptions can help win more customers.
    URI
    http://hdl.handle.net/10454/19575
    Version
    Accepted manuscript
    Citation
    Chen S, Ke S, Han S et al (2023) Which product description phrases affect sales forecasting? An explainable AI framework by integrating WaveNet neural network models with multiple regression. Decision Support Systems. Accepted for Publication.
    Link to publisher’s version
    https://doi.org/10.1016/j.dss.2023.114065
    Type
    Article
    Notes
    The full-text of this article will be released for public view at the end of the publisher embargo on 24 Feb 2025.
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    Management and Law Publications

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