Examining the influence of online reviews on consumers' decision-making: A heuristic-systematic model

Kem Z.K. Zhang, Sesia J. Zhao*, Christy M K CHEUNG, Matthew K.O. Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

214 Citations (Scopus)

Abstract

Along with the growth of Internet and electronic commerce, online consumer reviews have become an important source of information that assists consumers to make purchase decision. However, theoretical development and empirical testing in this area of research are still limited, which greatly hinder us from understanding the influence of online reviews. Drawing upon the heuristic-systematic model from the literature of dual-process theories, we develop a research model to identify factors that are important to consumers' purchase decision-making. The model is empirically tested with 191 users of an existing online review site. We find that argument quality of online reviews (systematic factor), which is characterized by perceived informativeness and perceived persuasiveness, has a significant effect on consumers' purchase intention. In addition, we find that source credibility and perceived quantity of reviews (heuristic factors) have direct impacts on purchase intention. The two heuristic factors further demonstrate positive influences on argument strength. This result is consistent with the proposition of bias effect in the heuristic-systematic model, which elucidates the interrelationship between heuristic and systematic factors. Based on the findings, we discuss implications for both researchers and practitioners.

Original languageEnglish
Pages (from-to)78-89
Number of pages12
JournalDecision Support Systems
Volume67
DOIs
Publication statusPublished - Nov 2014

Scopus Subject Areas

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management

User-Defined Keywords

  • Consumer decision-making
  • Electronic word-of-mouth
  • Heuristic-systematic model
  • Online reviews

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