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With the ever-increasing popularity of online consumer reviews, understanding what makes an online review believable has attracted increased attention from both academics and practitioners. Drawing on the elaboration likelihood model (ELM), this study examines four information cues used to evaluate the credibility of online reviews: Argument quality, source credibility, review consistency, and review sidedness, under different levels of involvement and expertise. We conducted an online survey that involved users of Epinions.com, a popular online consumer review website, to test the research model empirically. Consistent with previous research, the results reveal that argument quality, a central cue, was the primary factor affecting review credibility. Participants also relied on peripheral cues such as source credibility, review consistency, and review sidedness when evaluating online consumer reviews. Review sidedness had a stronger impact on review credibility when the recipient had a low involvement level and a high expertise level. However, the other interaction effects were not significant. We discuss the theoretical and practical implications of these results.

Many online review systems adopt a voluntary voting mechanism to identify helpful reviews to support consumer purchase decisions. While several studies have looked at what makes an online review helpful (review helpfulness), little is known on what makes an online review receive votes (review voting). Drawing on information processing theories and the related literature, we investigated the effects of a select set of review characteristics, including review length and readability, review valence, review extremity, and reviewer credibility on two outcomes-review voting and review helpfulness. We examined and analyzed a large set of review data from Amazon with the sample selection model. Our results indicate that there are systematic differences between voted and non-voted reviews, suggesting that helpful reviews with certain characteristics are more likely to be observed and identified in an online review system than reviews without the characteristics. Furthermore, when review characteristics had opposite effects on the two outcomes (i.e. review voting and review helpfulness), ignoring the selection effects due to review voting would result in the effects on review helpfulness being overestimated , which increases the risk of committing a type I error. Even when the effects on the two outcomes are in the same direction, ignoring the selection effects due to review voting would increase the risk of committing type II error that cannot be mitigated with a larger sample. We discuss the implications of the findings on research and practice.

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Mobile devices (e.g., PDAs and smartphones) are increasingly emerging as part of daily life, particularly with university students. The City University of Hong Kong has embarked on a long-term program to develop and integrate mobile learning activities into the context of undergraduate courses. This paper reports on the development, introduction and evaluation of a portfolio of collaborative mobile learning applications. Results support convictions that intrinsic and extrinsic motivation to embrace mobile applications correlates with enhanced performance, albeit with constructive alignment of student learning interests as a moderator.