Psychological dispositions and product barriers as drivers of digital voice assistant resistance: a dual-method approach

Digital voice assistants (DVAs) continue to underperform industry adoption forecasts due to persistent consumer resistance. Existing literature examines product-related barriers and consumer dispositional traits in isolation, overlooking how psychological tendencies interact with functional product hurdles to produce resistance. This study employs a dual-methodological design combining Partial Least Squares Structural Equation Modelling (PLS-SEM) and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) on a sample of 1,363 Indian consumers to address this gap. PLS-SEM validates a parallel mediation model in which dispositional traits including routine-seeking nature, cognitive rigidity, emotional resistance, short-term focus, and status quo satisfaction influence resistance both directly and through product-related barriers. Results indicated that 25 of the 29 structural paths were statistically significant. Notably, the Realization Barrier emerged as the strongest mediating mechanism. fsQCA further identifies three asymmetric configurational pathways sufficient to produce resistance, establishing equifinality in the resistance process. The findings demonstrate that resistance arises from distinct combinations of individual traits and product barriers rather than a single linear pathway and reveal that commonly cited barriers such as the Usage Barrier are contextual rather than universal. These insights advance innovation resistance literature and offer practitioners a basis for targeted, segment-specific adoption interventions.