Main Article Content

Abstract

This study aims to examine the effect of E-Wom among customers on purchase intentions on information media pages that provide information about products on Tripadvisor. This research uses purposive sampling technique. There were 270 respondents in this study. The model was analyzed by using structural equation modeling (SEM) with AMOS program. This study found that informative perceptions support E-Wom, persuasive perceptions support E-Wom, source expertise does not support E-Wom, trust in sources supports E-Wom, E-Wom usefulness supports e-Wom adoption, E-Wom adoption supports purchase intention, and the relationship between usefulness and decisions on purchase intention are mediated by E-Wom adoption.

Keywords

E-Wom perceived informativeness perceived persuasiveness source expertise source trustworthiness purchase intention

Article Details

How to Cite
Intansari, D. D., & Roostika, R. (2022). The Impact of Electronic Word-of-Mouth on Purchase Intention in Tripadvisor . Selekta Manajemen: Jurnal Mahasiswa Bisnis & Manajemen, 1(1), 123–137. Retrieved from https://journal.uii.ac.id/selma/article/view/23708

References

  1. Baber, A. T. (2016) ‘Online word-of-mouth antecedents, attitude and intention-to-purchase electronic products in Pakistan’, Telematics and Informatics, 33(2), pp.388–400. https://doi.org/10.1016/j.tele.2015.09.004
  2. Cheung, C. M. (2008) ‘The adoption of online opinions in online customer communities’’, Internet Research, 18(3), pp. 229–247. https://doi.org/10.1108/10662240810883290
  3. Cheung, M. L. (2009) ‘Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations’, International Journal of Electronic Commerce, 13(4), pp.9–38. https://doi.org/10.2753/JEC1086-4415130402
  4. Cheung, R. (2014) ‘The Influence of Electronic Word-of-Mouth on Information Adoption in Online Customer Communities’, Global Economic Review: Perspectives on East Asian Economies and Industries, 43(1), pp.42–57. https://doi.org/10.1080/1226508X.2014.884048
  5. Erkan, I. and. Evans, C. (2016) ‘The influence of eWOM in social media on consumers’ purchase intentions: An extended approach to information adoption’, Computers in Human Behavior, 61, pp.47–55. https://doi.org/10.1016/j.chb.2016.03.003
  6. Fang, Y. H. (2014) ‘Beyond the credibility of electronic word of mouth: Exploring eWOM adoption on social networking sites from affective and curiosity perspectives’. International Journal of Electronic Commerce, 18(3), pp.67-102. https://doi.org/10.2753/JEC1086-4415180303
  7. Gunawan, D. D. (2015) ‘Viral effects of social network and media on consumers’ purchase intention’, Journal of Business Research, 68(11), pp.2237–2241. https://doi.org/10.1016/j.jbusres.2015.06.004
  8. Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2010) ‘Multivariate Data Analysis’ (7th ed.). New York: Prentice Hall.
  9. King, A. R. (2014) ‘What We Know and Don’t Know About Online Word-of-Mouth : A Review and Synthesis of the Literature’, Journal of Interactive Marketing, 28(3), pp.167–183. https://doi.org/10.1016/j.intmar.2014.02.001
  10. Larson, K. and Watson, R. (2011) ‘The value of social media: toward measuring social media strategies’, ICIS 2011 Proceedings. 10. https://aisel.aisnet.org/icis2011/proceedings/onlinecommunity/10
  11. Sussman, S. W. (2003) ‘Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption’, Information System Research, 14(1), pp. 47–65. https://doi.org/10.1287/isre.14.1.47.14767
  12. Tien, D. H. (2019) ‘Examining the influence of customer-to-customer electronic word-of-mouth on purchase intention in social networking sites’, Asia Pacific Management Review, 24(3), pp. 238–249. https://doi.org/10.1016/j.apmrv.2018.06.003
  13. wearesocial.com. (2020, January). Retrieved from Digital 2020 - We Are Socia: https://wearesocial.com/digital-2020.
  14. Zhu, D. H. (2016) ‘Understanding the influence of C2C communication on purchase decision in online communities from a perspective of information adoption model’, Telematics and Informatics, 33(1), pp. 8–16. https://doi.org/10.1016/j.tele.2015.06.001

Most read articles by the same author(s)

<< < 1 2