Disentangling the factors driving electronic word-of-mouth use through a configurational approach

Bibliographic Data

ID12420714
AuthorsPing Wang (0000-0001-6354-2235, Central China Normal University, corresponding author), Hongxiu Li (0000-0002-7447-1222, Tampere University), Liu Yong (0000-0002-0228-8971, Aalto University)
Year2020
Volume30
Issue3
Pages925-943
Publication date2020-02-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternet Research (JOURNAL)
Journal identifiersISSN: 1066-2243 • E-ISSN: 2054-5657
PublisherEmerald Publishing Limited (PUBLISHER • GB)
DOI10.1108/intr-01-2019-0031
OpenAlexW3006815374
LanguageEN
Citations received3
References cited55

Purpose The purpose of this paper is to show how different combinations of the subdimensions of electronic word-of-mouth (eWOM) information quality (consisting of its accuracy, completeness, relevance, timeliness, and sidedness) may affect consumers' eWOM use behavior from a configurational approach. Design/methodology/approach Based on a synthesis of past literature, five precursors of eWOM use were considered. A fuzzy-set qualitative comparative analysis (fsQCA) was employed to understand the configurations that lead to travel-related eWOM use. The study was conducted with 311 consumers from an online travel service company. Findings Findings identified six solutions that explain eWOM use. EWOM accuracy, completeness, and sidedness are found to be core conditions reinforcing consumers' use of eWOM in combination with different peripheral conditions, including the subdimensions of eWOM information quality and the traits of the consumers (such as social media use time and gender). Practical implications Factors related to eWOM information quality and traits of the consumers, when considered in combination, predict eWOM use behavior in particular sets of conditions. Originality/value This work enriches the eWOM literature by providing an in-depth understanding of eWOM use from a configuration perspective. Configuration analysis serves as a better tool for explaining the complex relationships among variables than a regression analysis approach does. Additionally, in response to the need to move beyond multiple regression analysis to algorithmic approaches, this study shifts the emphasis from a symmetric paradigm to an asymmetric perspective for data analysis focused on eWOM use

Advertising · Business · Completeness (order theory · Information quality · Information system · Originality · Perspective (graphical · Qualitative comparative analysis · Quality (philosophy · Regression analysis · Computer Science · Digital Marketing and Social Media · Mathematics · Psychology · Social Psychology · Technology Adoption and User Behaviour · Wine Industry and Tourism · Artificial Intelligence

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