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

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Pages (from-to)925-943
Number of pages19
Issue number3
Publication statusPublished - 23 Feb 2020
Publication typeA1 Journal article-refereed


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.


  • Configuration analysis, eWOM use, FsQCA, Fuzzy-set qualitative comparative analysis

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