Investigating transitive influences on WOM: from the product network perspective

Kun Chen (), Peng Luo () and Huaiqing Wang ()
Additional contact information
Kun Chen: South University of Science and Technology
Peng Luo: Harbin Institute of Technology
Huaiqing Wang: South University of Science and Technology

Electronic Commerce Research, 2017, vol. 17, issue 1, No 8, 149-167

Abstract: Abstract As is popular in e-commerce, consumers share their product experiences and opinions on the Web by assigning rating stars or writing reviews. The information constitutes word of mouth (WOM) about products. An increasing number of studies have sought to understand how WOM metrics are related to product sales. However, current research focuses mainly on single-product-oriented WOM metrics, which do not consider the complex relationships between products. Given the underlying influential impacts between related products, we propose a market-structure-based WOM metric that integrates the product comparison network and transitive influence measures. An empirical study based on data from Amazon.com shows that the proposed transitive WOM metric outperforms other traditional WOM metrics on predicting product sales, and its unique features are also demonstrated. The findings provide important insights into social influence theory and electronic commerce research. In practice, the research provides a method of measuring product WOM from a whole-market perspective, which is especially important for market structure analysis.

Keywords: Network analysis; Sentiment analysis; Consumer reviews; Word-of-mouth (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10660-016-9241-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:17:y:2017:i:1:d:10.1007_s10660-016-9241-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660

DOI: 10.1007/s10660-016-9241-8

Access Statistics for this article

Electronic Commerce Research is currently edited by James Westland

More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().