Can users embed their user experience in user-generated images? Evidence from JD.com |
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| Institution: | 1. Academy of Mathematics and Systems Science Chinese Academy of Sciences, Beijing, China;2. Beihang University, School of Economics and Management, Beijing, China;3. North China University of Technology, School of Economics and Management, Beijing, China;4. Chemical Industry Press, Beijing, China;5. Beijing Forestry University, Beijing, China;1. Swinburne University of Technology, Australia;2. Charles Sturt University, Australia;1. Department of Marketing, Stetson-Hatcher School of Business, Mercer University, Macon, GA, 31207, USA;2. Department of Marketing, Arthur J. Bauernfeind College of Business, Murray State, Murray, KY, 42071, USA;3. Department of Marketing, College of Business, Bryant University, 1150, Douglas Pike, Smithfield, RI, 02917, USA;4. Department of Marketing and Supply Chain Management, Fogelman College of Business and Economics, University of Memphis, 3675 Central Ave, Memphis, TN 38152, USA;1. Univ. Grenoble Alpes, Grenoble INP, CERAG, 38000, Grenoble, France;2. Excelia Business School, CERIIM, La Rochelle, France;1. Institute for Economic Research, Hebei University of Economics and Business, Shijiazhuang 050061, China;2. College of Management and Economics, Tianjin University, Tianjin 300072, China |
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| 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. |
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| Keywords: | User experience User-generated images Deep learning model Image semantic feature e-commerce platform |
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