Deciphering Individuals’ Preference for User Generated Content: An Empirical Test of the Impact of Personality on Users’ Processing of Online Review Information

Fei Liu, Bo Xiao, Eric T.K. Lim, Chee Wee Tan

Research output: Unpublished conference presentation (presented paper, abstract, poster)Conference presentation (not published in journal/proceeding/book)Academic researchpeer-review

Abstract

The explosive growth of user generated content presents a window of opportunity for online service providers (i.e., online review website) to utilize both forms of review information, namely numerical rating and opinionated review to facilitate trust building with users. Nevertheless, users’ trust in a website can be undermined by the irreconcilable dissonance between both forms of review information and their personality preferences. Consequently, it is important for websites to personalize the provision of numerical rating and opinionated review in order to convey trustworthiness to users through online consumer review. To empirically validate our research mode, we conducted a field study on a custom developed online review website with a sample of 170 college students. Results suggest that dissonance between numerical rating and opinionated review, as well as individuals’ preferences for self-reference and content relevance when processing online review information moderate the positive relationship between online consumer review and trust.

Original languageEnglish
Publication statusNot published / presented only - 2015
Externally publishedYes
Event2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015 - Fort Worth, United States
Duration: 13 Dec 201516 Dec 2015

Conference

Conference2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015
Country/TerritoryUnited States
CityFort Worth
Period13/12/1516/12/15

Keywords

  • Cognitive Dissonance
  • MBTI
  • Online Consumer Review
  • Personality Preference
  • Trust

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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