TY - JOUR
T1 - Does the dispersion of online review ratings affect review helpfulness?
AU - Lee, Soyeon
AU - Lee, Saerom
AU - Baek, Hyunmi
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2021/4
Y1 - 2021/4
N2 - The impact of online consumer reviews on online purchase decisions has increased with the growth of e-commerce. This paper tries to explain how rating dispersion impacts the process of review consumption based on the heuristic systematic model. For this research, 10,198 online consumer reviews for 516 DVD products were collected from Amazon.com using a web data crawler. Our results show that when trusting average ratings (i.e., when rating dispersion is low), the incentive to read individual reviews decreases because of the principle of least effort. In this case, consumers consider average ratings to be representative of collective intelligence, so rating inconsistency negatively impacts review helpfulness. On the other hand, when average ratings are not trusted (i.e., when rating dispersion is high), the incentive to read individual reviews increases because of the principle of sufficiency. When it happens, extreme ratings affects review helpfulness more because extreme opinions are not ambiguous. Our findings provide new perspectives to address the inconsistent findings of the previous studies on rating and review helpfulness, and the practical implications for e-commerce platforms.
AB - The impact of online consumer reviews on online purchase decisions has increased with the growth of e-commerce. This paper tries to explain how rating dispersion impacts the process of review consumption based on the heuristic systematic model. For this research, 10,198 online consumer reviews for 516 DVD products were collected from Amazon.com using a web data crawler. Our results show that when trusting average ratings (i.e., when rating dispersion is low), the incentive to read individual reviews decreases because of the principle of least effort. In this case, consumers consider average ratings to be representative of collective intelligence, so rating inconsistency negatively impacts review helpfulness. On the other hand, when average ratings are not trusted (i.e., when rating dispersion is high), the incentive to read individual reviews increases because of the principle of sufficiency. When it happens, extreme ratings affects review helpfulness more because extreme opinions are not ambiguous. Our findings provide new perspectives to address the inconsistent findings of the previous studies on rating and review helpfulness, and the practical implications for e-commerce platforms.
KW - Extreme rating
KW - Online consumer review
KW - Rating dispersion
KW - Rating inconsistency
KW - Review helpfulness
UR - http://www.scopus.com/inward/record.url?scp=85099250571&partnerID=8YFLogxK
U2 - 10.1016/j.chb.2020.106670
DO - 10.1016/j.chb.2020.106670
M3 - Article
AN - SCOPUS:85099250571
SN - 0747-5632
VL - 117
JO - Computers in Human Behavior
JF - Computers in Human Behavior
M1 - 106670
ER -