Can users embed their user experience in user-generated images? Evidence from JD.com

Lu Zhao, Mingli Zhang, Jianbo Tu, Jialing Li and Yan Zhang

Journal of Retailing and Consumer Services, 2023, vol. 74, issue C

Abstract: Nowadays, massive user-generated images (UGIs) are posted online to convey users' experiences with specific brands or products. Thus, this visual information is precious, as it conveys users' actual and subjective feelings about brands and products. Because of the unprecedented quantity of images and the heterogeneity of their content, it is quite challenging for brand marketers and retailers to probe into subjective user experience in large-scale UGIs. To address this gap, this study aims to identify the connection between user experience and different image semantic features (i.e. centrality and richness) by using deep learning models. By employing objective data (8963 images) from JD.com and using deep learning algorithms (faster R-CNN), we found that users with positive user experience prefer to generate high-centrality and high-richness pictures. Our study enriches the relevant literature and provides valuable practical implications for brand marketers and e-commerce retailers. Based on findings of this work, relevant stakeholders can understand their users’ experience better from objective UGIs and devise corresponding recommendation and service strategies.

Keywords: User experience; User-generated images; Deep learning model; Image semantic feature; e-commerce platform (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:74:y:2023:i:c:s0969698923001261

DOI: 10.1016/j.jretconser.2023.103379

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