[Purpose/significance] To explore the influencing factors of the users′ transfer behavior between humanhuman surrogate search behavior and human-machine surrogate search behavior, providing theoretical foundations
and practical strategies for optimizing generative artificial intelligence. [Method/process] First, semi-structured interviews were conducted with 30 respondents focusing on critical incidents of users′ surrogate information seeking behaviors. Second, based on the critical incident technique and the COM-B model, the influencing factors of transfer behavior in surrogate information seeking were identified and the influence factor model was constructed. Finally, the combined weights of the entropy weight method and the coefficient of variation method were calculated using the geometric mean, in order to compare the differences in the influence of each factor before and after the transfer behavior. [Result/conclusion] The influencing factors of both types of transfer behavior include capability factors (physical capability and psychological capability), opportunity factors (physical opportunity and social opportunity), and motivation factors (automatic motivation and reflective motivation), and these factors differ before and after the transfer.