Understanding Consumer Engagement in Digital Sport Commerce: A Kano-SERVQUAL Evaluation of Interactive Features and Platform Quality

Digital sport platforms increasingly mediate consumer experience through AI-driven interfaces, yet it remains unclear which interactive elements consumers treat as baseline expectations versus genuine engagement drivers. An integrated Kano-SERVQUAL model was applied to evaluate the service quality of virtual cycling platforms in this context. An online survey was conducted with 458 adults who regularly used a virtual cycling platform. Service quality attributes demonstrated a five-dimensional structure: tangibles, reliability, responsiveness, assurance, and empathy. Twenty service attributes were classified following Kano’s model, and Better–Worse coefficients and a combined impact score were calculated to identify strategic priorities. Twenty attributes clustered into four distinct regions based on Timko’s Better–Worse matrix. One-Dimensional Quality (High Better, High Worse) included technical infrastructure attributes such as content updates, platform composition, data consistency, connection stability, and server stability under large-scale connections. Attractive Quality (High Better, Low Worse) was characterized by differentiating features, including event diversity, reflection of user suggestions, tutorial guide clarity, verified workout programs, and post-ride reports. Must-Be Quality (Low Better, High Worse) comprised graphics quality, UI convenience, and avatar design baseline attributes whose absence triggers high dissatisfaction, along with pedal resistance response (Reverse quality). Indifferent Quality (Low Better, Low Worse) encompassed attributes including technical support, testing tools, competitive systems, reward systems, and personalized recommendations, representing lower priority features. Thus, consumer engagement with AI-mediated digital sport platforms is structurally non-linear, requiring attribute-differentiated management strategies that distinguish trust-critical interface reliability from engagement-driving personalization. These findings offer theoretical implications for consumer decision-making in interactive digital commerce, though trust, engagement, and decision-making were not directly measured as outcome variables in this study.