@inbook{8ea19880e3b346cc9a06f0e761314e07,
title = "Using image-based and text-based information for sales prediction: A deep neural network model",
abstract = "This paper is to investigate how text-based and image-based information influence product sales in electronic markets. We apply signaling theory to elaborate the role of image-based and text-based information in consumers' purchase decisions and use deep neural networks model to analyze different types of information in online sales websites. We collect information about 4, 368 furniture products from Amazon and find that both image-based and text-based information influence consumers' purchase decisions, but the former one is more crucial. This paper makes contributions to e-commerce literature by elaborating the signaling role of available information in sales websites, highlighting the importance of considering both text-based and image-based information in the data analysis, and demonstrating how to apply advanced deep learning techniques and models in e-commerce studies.",
keywords = "Deep learning, Image, Neural network model, Signaling theory, Text, Unstructured data",
author = "Ying Wang and Yue Guo and Jaeki Song",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Information Systems. All rights reserved. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; 24th Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018 ; Conference date: 16-08-2018 Through 18-08-2018",
year = "2018",
language = "English",
isbn = "9780996683166",
series = "Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018",
publisher = "Association for Information Systems",
booktitle = "Americas Conference on Information Systems 2018",
address = "United States",
}