A study on user continuance intention for children’s intelligent companion robots based on BERTopic-PLS-SEM-fsQCA

The children’s intelligent companion robot market faces the industry-wide challenge of “high initial adoption yet low sustained retention.” Existing research has predominantly relied on single-method approaches, leaving the psychological mechanisms and configurational pathways driving user continuance intention insufficiently understood. This study constructs a sequential multi-method research framework integrating “BERTopic thematic mining—PLS-SEM linear validation—fsQCA configurational analysis.” Drawing on 6,405 valid online reviews from JD.com and 440 valid questionnaire responses, the study adopts an integrated theoretical framework combining the Expectation Confirmation Model (ECM) and the Value-based Adoption Model (VAM). BERTopic thematic mining identified six core demand dimensions from consumer reviews: perceived usefulness, perceived enjoyment, visual aesthetics, social/gifting value, technical reliability, and expectation confirmation.

PLS-SEM analysis reveals that satisfaction is the strongest predictor of continuance intention (β = 0.705, p