TY - JOUR
T1 - Managerial Responses to Online Reviews
T2 - A Text Analytics Approach
AU - Sheng, Jie
AU - Amankwah-Amoah, Joseph
AU - Wang, Xiaojun
AU - Khan, Zaheer
PY - 2019
Y1 - 2019
N2 - This study tests the effects of online managerial responses and returning customers’ future satisfaction (measured as review ratings) by performing social media text analytics on a hotel sample. Essentially, this paper provides insight into meaningful differences in future ratings between responding and non-responding hotels, as well as differences in response styles between ratings improvement and non-improvement. The results indicate that: (1) subsequent ratings are higher if customers receive responses to their previous online reviews; (2) increase in ratings is more significant among low-satisfaction customers, and a decrease in ratings is mitigated if responses are provided; (3) responding to loyal customers – those who have visited and rated the same hotel more than three times – has a limited impact on ratings; (4) responses are longer and sentiment is slightly lower in scenarios where subsequent ratings are improved, but there is no significant difference in the effect of response speed between the two groups; (5) changes in ratings also affect styles of responding to current reviews – if customer satisfaction has improved, response length tends to be shorter and sentiment level tends to be higher. The findings offer both theoretical and managerial implications by demonstrating the utility of social media text analytics.
AB - This study tests the effects of online managerial responses and returning customers’ future satisfaction (measured as review ratings) by performing social media text analytics on a hotel sample. Essentially, this paper provides insight into meaningful differences in future ratings between responding and non-responding hotels, as well as differences in response styles between ratings improvement and non-improvement. The results indicate that: (1) subsequent ratings are higher if customers receive responses to their previous online reviews; (2) increase in ratings is more significant among low-satisfaction customers, and a decrease in ratings is mitigated if responses are provided; (3) responding to loyal customers – those who have visited and rated the same hotel more than three times – has a limited impact on ratings; (4) responses are longer and sentiment is slightly lower in scenarios where subsequent ratings are improved, but there is no significant difference in the effect of response speed between the two groups; (5) changes in ratings also affect styles of responding to current reviews – if customer satisfaction has improved, response length tends to be shorter and sentiment level tends to be higher. The findings offer both theoretical and managerial implications by demonstrating the utility of social media text analytics.
UR - http://www.scopus.com/inward/record.url?scp=85065431493&partnerID=8YFLogxK
UR - https://kar.kent.ac.uk/69093/
U2 - 10.1111/1467-8551.12329
DO - 10.1111/1467-8551.12329
M3 - Article
AN - SCOPUS:85065431493
VL - 30
SP - 315
EP - 327
JO - British Journal of Management
JF - British Journal of Management
SN - 1045-3172
IS - 2
ER -