• Online information quality (IQ) plays a critical role in influencing the quality of consumers' experience and decisions in the online environment. Much research has been conducted in the literature to understand the impact of consumers' perceptions of online IQ on various factors that define the online user experience. This article reviews this existing research and provides a holistic view of this literature culminating in a macro model of online IQ that outlines the current status of research in this area and highlights under-researched areas worthy of future research. Through this comprehensive analysis of 452 articles, we draw several overarching contributions. First, we find that most online IQ research employs an explaining & predicting approach (i.e., explain what is occurring and provide testable predictions with causal relationships) as opposed to a design & action approach (i.e., design tools or frameworks for online IQ assessment). Second, our review reveals that a large proportion of papers have focused on the U.S. and student segments. Third, this review reveals that online IQ research focuses largely on online IQ consequences, with few studies focusing on perceived online IQ antecedents. Based on these findings, we suggest that future studies in this area: (i) Focus more on design a (ii) Use a diversity of sampling populations; and (iii) Focus on the antecedents of the IQ construct as well as moderators for the relations between perceived online IQ and relevant factors. A comprehensive review of 452 articles on online IQ is carried out.A macro model of online IQ antecedents, consequents and moderators is devised.Researchers are encouraged to employ a design & action approach.Researchers are encouraged to use a diversity of sampling populations.More research is needed on the online IQ in information service domain. ()
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  • 2016-06-24 ()
  • 10.1016/j.chb.2015.09.027 ()
  • 991 ()
  • 11 ()
  • en ()
  • 2016-02-01 ()
  • Pergamon ()
  • 20882 ()
  • 494 ()
  • 972 ()
  • A macro model of online information quality perceptions ()
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