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Paper Number
2569
Paper Type
short
Description
User-generated reviews (UGR) are valuable in online markets, but not all reviews impact prospective customers equally. Reviews rated more helpful are more persuasive and valuable than others. Literature has examined how consumers evaluate the helpfulness of online reviews. We examine and demonstrate that content and non-content cues are important to driving the helpfulness of online reviews and that these two cues are incongruently influential to perceived helpfulness regarding salience stimuli readers’ attention. Specifically, a high salience of content cues (acceptable long and concrete content) and a high salience of non-content cues draw readers' attention, subsequently influencing the higher perceived helpfulness compared with the low and the high content and non-content cues, respectively. Our findings provided evidence that information cues stemming from attributes of UGR can compensate interchangeably with information cues retrieved from the content of UGR.
Recommended Citation
Nguyen, Tien Thuy; Tripathi, Arvind; and Wong, Randy, "Why are some reviews perceived as more helpful than others?" (2023). ICIS 2023 Proceedings. 19.
https://aisel.aisnet.org/icis2023/user_behav/user_behav/19
Why are some reviews perceived as more helpful than others?
User-generated reviews (UGR) are valuable in online markets, but not all reviews impact prospective customers equally. Reviews rated more helpful are more persuasive and valuable than others. Literature has examined how consumers evaluate the helpfulness of online reviews. We examine and demonstrate that content and non-content cues are important to driving the helpfulness of online reviews and that these two cues are incongruently influential to perceived helpfulness regarding salience stimuli readers’ attention. Specifically, a high salience of content cues (acceptable long and concrete content) and a high salience of non-content cues draw readers' attention, subsequently influencing the higher perceived helpfulness compared with the low and the high content and non-content cues, respectively. Our findings provided evidence that information cues stemming from attributes of UGR can compensate interchangeably with information cues retrieved from the content of UGR.
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Comments
21-UserBehavior