Predicting online e-marketplace sales performances: a big data approach

Li, Boying and Ch’ng, Eugene and Chong, Alain Yee-Loong and Bao, Haijun (2016) Predicting online e-marketplace sales performances: a big data approach. Computers & Industrial Engineering, 101 . pp. 565-571. ISSN 0360-8352

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Abstract

To manage supply chain efficiently, e-business organizations need to understand their sales effectively. Previous research has shown that product review plays an important role in influencing sales performance, especially review volume and rating. However, limited attention has been paid to understand how other factors moderate the effect of product review on online sales. This study aims to confirm the importance of review volume and rating on improving sales performance, and further examine the moderating roles of product category, answered questions, discount and review usefulness in such relationships. By analyzing 2,939 records of data extracted from Amazon.com using a big data architecture, it is found that review volume and rating have stronger influence on sales rank for search product than for experience product. Also, review usefulness significantly moderates the effects of review volume and rating on product sales rank. In addition, the relationship between review volume and sales rank is significantly moderated by both answered questions and discount. However, answered questions and discount do not have significant moderation effect on the relationship between review rating and sales rank. The findings expand previous literature by confirming important interactions between customer review features and other factors, and the findings provide practical guidelines to manage e-businesses. This study also explains a big data architecture and illustrates the use of big data technologies in testing theoretical framework.

Item Type: Article
Keywords: E-business, product reviews, moderation effect, big data architecture
Schools/Departments: University of Nottingham Ningbo China > Faculty of Business > Nottingham University Business School China
University of Nottingham Ningbo China > Faculty of Science and Engineering > School of Computer Science
Identification Number: https://doi.org/10.1016/j.cie.2016.08.009
Depositing User: YUAN, Ziqi
Date Deposited: 04 Jan 2018 13:14
Last Modified: 06 Jun 2018 08:45
URI: http://eprints.nottingham.ac.uk/id/eprint/48878

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