E-WOM and consumers’ purchase intention: An empirical study on Facebook

  • Received April 7, 2022;
    Accepted July 25, 2022;
    Published September 22, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.18(3).2022.13
  • Article Info
    Volume 18 2022, Issue #3, pp. 149-158
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This work is licensed under a Creative Commons Attribution 4.0 International License

Nowadays, organizations use social media to promote their services and products. At the same time, they use different tools to convey their messages, such as Facebook. Therefore, this study aims to investigate the factors that affect the e-WOM on Jordanian consumers’ purchase intention over Facebook. The study uses the information acceptance model (IAM) to examine the impact of information credibility, information quality, information adoption, and information usefulness over Facebook on Jordanian consumers’ purchase intention. The study uses cross-sectional quantitative research and is conducted online. The questionnaire was distributed through Facebook and WhatsApp, and the people who used only Facebook were allowed to complete the survey. Out of 327 filled questionnaires, only 304 were valid for further analysis. Collected data were coded in SPSS, and after confirming the validity and reliability of the tool, the correlation between variables was checked. In addition, multiple regressions were used to test the hypotheses. Multiple regression results show that the E-WOM can explain 49.2% of the total variation in the consumers’ purchase intention, where R2 = 0.492. Information adoption has the strongest effect on consumers’ purchase intention (β = 0.489), followed by information usefulness (β = 0.204). In contrast, information credibility and information quality do not have a significant effect on customers’ purchase intention (0.189 and 0.312, respectively). This study helps companies and businesses that have pages on Facebook to understand how consumers engage in the e-WOM on business pages and consider the consumers’ reviews, comments, or posts.

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    • Figure 1. Research model
    • Table 1. Demographic analysis
    • Table 2. Descriptive statistics and reliability test
    • Table 3. Correlations
    • Table 4. Model summary (ANOVA)
    • Table 5. Coefficients
    • Conceptualization
      Shafig Al-Haddad, Lana Harb, Aarab Husni, Maisam Abdelfattah
    • Funding acquisition
      Shafig Al-Haddad, Lana Harb
    • Methodology
      Shafig Al-Haddad, Abdel-Aziz Ahmad Sharabati
    • Project administration
      Shafig Al-Haddad, Maisam Abdelfattah
    • Resources
      Shafig Al-Haddad
    • Supervision
      Shafig Al-Haddad, Abdel-Aziz Ahmad Sharabati
    • Validation
      Shafig Al-Haddad
    • Visualization
      Shafig Al-Haddad
    • Writing – review & editing
      Shafig Al-Haddad, Abdel-Aziz Ahmad Sharabati
    • Formal Analysis
      Abdel-Aziz Ahmad Sharabati, Aarab Husni, Maisam Abdelfattah
    • Data curation
      Lana Harb, Maisam Abdelfattah
    • Investigation
      Lana Harb, Aarab Husni, Maisam Abdelfattah
    • Software
      Lana Harb, Aarab Husni
    • Writing – original draft
      Lana Harb, Maisam Abdelfattah