The impact of image is widely investigated in various research fields. However, its effect in online health communities is rarely studied. In this research, the authors develop a theoretical model to assess the impact of physicians' image on patients' choices in online health communities.
The authors developed a web crawler based on R language program to collect more than 40,000 physicians' images and other related information from their homepages in Haodf.com–a leading online health community in China. The features of physicians' images are computed by Face++ Application Programming Interface (API) through the following variables: beauty, smile and skin status.
The empirical results derive the following findings: (1) physician's beauty or physical attractiveness has no significant effect on patients’ choice; (2) Smile has a positive effect on patients’ choices; (3) Physician's skin status also positively affects patients' choices; (4) Physician's professional capital strengthens the effect of beauty, smile and skin status on patients' choices; (5) Beauty and skin status are the substitutes for each other, and smile and skin status are the substitutes for each other too.
Also, this study provides implications for both physicians and online health community platform managers.
This study provides new evidence in understanding the impact of physician's online image and contributes to the literature on signaling theory, impression management theory and patients' choices.
