A1369
Title: Econometric modeling of doctors knowledge contribution in online healthcare platforms
Authors: Hongying Tan - Southwestern University of Finance and Economics (China) [presenting]
Abstract: Doctors' knowledge contribution in online healthcare consultation is examined using a platform-based dataset from a leading online medical service in China. An econometric framework is developed in which doctors' knowledge contribution is modeled as a function of patient-generated interaction signals, including instrumental communication intensity, negative emotional expression, and response time, together with platform incentive variables, including monetary rewards and psychological rewards. Fixed effects estimators are used to control for unobserved physician-level heterogeneity, and a two-stage least squares estimation approach is adopted to address potential endogeneity. Interaction terms between patient signals and incentive variables are included to capture heterogeneous behavioral responses across physicians. Results show that instrumental communication intensity and negative emotional expression are positively associated with doctors' knowledge contribution, while response time has a negative association. Monetary and psychological rewards strengthen the effect of instrumental communication intensity, while psychological rewards weaken the negative effect of response time. Heterogeneity analysis indicates variation across physician characteristics and medical contexts. The results provide evidence on how interaction signals and incentive mechanisms jointly shape knowledge contribution behavior in online healthcare platforms.
