Exploring psychological dependency on romantic companion robots in the single economy: Implications for digital intimacy and consumer services

The emergence of the single economy, combined with advances in artificial intelligence (AI), has given rise to AI technologies centred on romantic companion robots (RCRs). These technologies are profoundly reshaping young users' perceptions and experiences of intimate relationships. Drawing on the stimulus–organism–response (S–O–R) theoretical framework, this study employs a multi-method approach that integrates partial least squares structural equation modelling (PLS-SEM), artificial neural networks (ANNs), and necessary condition analysis (NCA) to develop and validate a composite pathway model of users' psychological dependence on RCRs. Using the ‘Xingye’ RCR application as a case study, 457 valid responses were collected to evaluate the effects of six key stimulus variables – perceived personalisation, anthropomorphism, interactivity, hedonic motivation, intimacy, and moral perception – on user trust and satisfaction. Moreover, this study examined the mediating roles of trust and satisfaction in shaping psychological dependence. Results from PLS-SEM supported all hypothesised relationships, confirming trust and satisfaction as critical mediators. ANN analysis further revealed significant nonlinear effects of intimacy, moral perception, and interactivity on trust and satisfaction. In addition, NCA identified intimacy and interactivity as necessary conditions for the formation of psychological dependence. Furthermore, immersion tendency significantly moderates the relationship between interactivity and trust, while demographic factors such as gender, age, and education level exert differential influences. Overall, these findings advance empirical understanding of human–robot intimacy in the era of digital affective technologies and provide theoretical foundations and practical implications for the personalised design, ethical regulation, and market deployment of RCR products.