Although it has been proven that textual features of review content have an impact on review usefulness/enjoyment, visual features of review content have been paid less attention. We therefore identify three major photographic components of images (i.e., color, composition, and image category) embedded in an online restaurant review (ORR)and investigate their influence on both review usefulness and review enjoyment. Color is measured by calculating pixel intensities of a photo, composition is measured by analyzing a photo using the role of thirds, and image category is classified by employing the Google Vision API. This study is expected to build a new layer on the literature on ORRs by suggesting a new way to identify and measure photographic components, combining two research areas of photography and image mining. Practically, research findings will suggest a way to make more useful/enjoyable ORRs for general users and provide practical implications for managers in the hospitality and tourism industry.
저자
Lin Li [ School of Management, Kyung Hee University Seoul, South Korea ]
Gang Ren [ School of Business Administration, Kookmin University Seoul, South Korea ]
Taeho Hong [ College of Business Administration, Pusan National University Busan, South Korea ]
Sung-Byung Yang [ School of Management, Kyung Hee University Seoul, South Korea ]
Corresponding Author
