TY - JOUR
T1 - Information enhancement or hindrance? Unveiling the impacts of user-generated photos in online reviews
AU - Li, Hengyun
AU - Zhang, Lingyan
AU - Guo, Rui (Ami)
AU - Ji, Haipeng
AU - Yu, Bruce X.B.
N1 - Funding Information:
The authors acknowledge the support of research funds from the National Natural Science Foundation of China (71902169) and The Hong Kong Polytechnic University Departmental General Research Fund (Project No. G-UALR).
Publisher Copyright:
© 2022, Emerald Publishing Limited.
PY - 2023/6/9
Y1 - 2023/6/9
N2 - Purpose: This study aims to investigate the promoting effects of the quantity and quality of online review user-generated photos (UGPs) on perceived review usefulness. The research further tests the hindering effect of human facial presence in review photos on review usefulness. Design/methodology/approach: Based on review samples of restaurants in a tourist destination Las Vegas, this study used an integrated method combining a machine learning algorithm and econometric modeling. Findings: Results indicate that the number of UGPs depicting a restaurant’s food, drink, menu and physical environment has positive impacts on perceived review usefulness. The quality of online review UGPs can also enhance perceived review usefulness, whereas facial presence in these UGPs hinders perceived review usefulness. Practical implications: Findings suggest that practitioners can implement certain tactics to potentially improve consumers’ willingness to share more UGPs and UGPs with higher quality. Review websites could develop image-processing algorithms for identifying and presenting UGPs containing core attributes in prominent positions on the site. Originality/value: To the best of the authors’ knowledge, this study is the first to present a comprehensive analytical framework investigating the enhancing or hindering roles of review photo quantity, photo quality and facial presence in online review UGPs on review usefulness. Using the heuristic-systematic model as a theoretical foundation, this study verifies the additivity effect and attenuation effect of UGPs’ visual elements on judgements of online review usefulness. Furthermore, it extends scalable image data analysis by adopting a deep transfer learning algorithm in hospitality and tourism.
AB - Purpose: This study aims to investigate the promoting effects of the quantity and quality of online review user-generated photos (UGPs) on perceived review usefulness. The research further tests the hindering effect of human facial presence in review photos on review usefulness. Design/methodology/approach: Based on review samples of restaurants in a tourist destination Las Vegas, this study used an integrated method combining a machine learning algorithm and econometric modeling. Findings: Results indicate that the number of UGPs depicting a restaurant’s food, drink, menu and physical environment has positive impacts on perceived review usefulness. The quality of online review UGPs can also enhance perceived review usefulness, whereas facial presence in these UGPs hinders perceived review usefulness. Practical implications: Findings suggest that practitioners can implement certain tactics to potentially improve consumers’ willingness to share more UGPs and UGPs with higher quality. Review websites could develop image-processing algorithms for identifying and presenting UGPs containing core attributes in prominent positions on the site. Originality/value: To the best of the authors’ knowledge, this study is the first to present a comprehensive analytical framework investigating the enhancing or hindering roles of review photo quantity, photo quality and facial presence in online review UGPs on review usefulness. Using the heuristic-systematic model as a theoretical foundation, this study verifies the additivity effect and attenuation effect of UGPs’ visual elements on judgements of online review usefulness. Furthermore, it extends scalable image data analysis by adopting a deep transfer learning algorithm in hospitality and tourism.
KW - Facial presence
KW - Heuristic-systematic model
KW - Machine learning
KW - Review photo quality
KW - Review photo quantity
KW - Review usefulness
UR - http://www.scopus.com/inward/record.url?scp=85143351722&partnerID=8YFLogxK
U2 - 10.1108/IJCHM-03-2022-0291
DO - 10.1108/IJCHM-03-2022-0291
M3 - Journal article
AN - SCOPUS:85143351722
SN - 0959-6119
VL - 35
SP - 2322
EP - 2351
JO - International Journal of Contemporary Hospitality Management
JF - International Journal of Contemporary Hospitality Management
IS - 7
ER -