Few studies have explored the effect of helpful reviews on sales. This research proposes a two-step flow framework and adopts a multi-level model to examine the effect of reviews and their “helpful” votes on sales. We posit that the helpfulness votes amplify the effect of extreme reviews and that such effect is stronger for experience products (than for search products). Further, we conjure that negative reviews and their helpfulness votes are more impactful than positive reviews. Then, we expect that in comparison with the estimated review quality, the voted helpfulness of reviews is inflated, thus can backfire if manipulated.
|Number of pages||23|
|Publication status||Published - 6 Dec 2019|
|Event||2019 AIB Southeast Asia Regional Conference - Radisson Blu Cebu, Cebu City, Philippines|
Duration: 5 Dec 2019 → 7 Dec 2019
|Conference||2019 AIB Southeast Asia Regional Conference|
|Period||5/12/19 → 7/12/19|
- helpful review
- consumer behavior
- helpfulness vote
- review quality
- text analysis
- machine learning
BAO, Z., CUI, G., & PENG, L. (2019). Examining the Effect of Helpful Reviews on Product Sales: A Multi-level Model and Text Analysis. Paper presented at 2019 AIB Southeast Asia Regional Conference, Cebu City, Philippines.