A Study on the Factors Influencing the Usage Intention of Consumer Groups in Smart Chinese Medicine Pharmacies Based on Innovation Diffusion Theory and Structural Equation Modeling

Background The development of smart traditional Chinese medicine (TCM) pharmacies in China is still in the exploratory stage, with limited research on consumer group analysis and factors influencing usage intention. This study aims to explore the factors affecting consumers' willingness to use smart TCM pharmacy services from the consumer perspective. Methods Based on the diffusion of innovation theory, this study analyzes the factors influencing the use of smart TCM pharmacy services. Relative advantage, trialability, observability, social influence, performance expectancy, perceived risk, and consumer innovativeness were treated as latent variables. A survey questionnaire was designed to assess consumers' willingness to use smart pharmacy services, and a model of influencing factors was constructed. Statistical analyses included reliability and validity tests of the questionnaire, discrimination tests, t-tests and one-way ANOVA for differences in usage intention among different individuals, correlation analysis between latent variables and usage intention, and the construction of a structural equation model among influencing factors. Results A total of 175 valid questionnaires were collected; overall reliability was 0.962, with Cronbach's alpha values for each latent variable exceeding 0.7, KMO value = 0.952, and standardized factor loadings for each measurement item under each latent variable greater than 0.4. The t-test and one-way ANOVA results indicated that gender, age, education level, occupation, and income level did not have statistically significant differences in willingness to use smart TCM pharmacy services. Correlation analysis shows that the correlation coefficient between individual innovativeness and willingness to use is 0.893. The correlation coefficients for performance expectancy, social influence, observability, trialability, and perceived usefulness are 0.873, 0.871, 0.830, 0.826, and 0.619 respectively, while perceived risk has a relatively low correlation coefficient of only 0.39. Path analysis indicates that if consumers are willing to try new technologies, products, or services, if medical staff recommend them, and if users are willing to abandon the smart Chinese medicine pharmacy service after unsatisfactory trials, these factors have a significant positive impact on willingness to use. Conversely, the ability to evaluate the smart Chinese medicine pharmacy service after use has a significant negative impact on willingness to use. The structural model shows that individual innovativeness has a significant effect on willingness to use at the 0.05 level, with a standardized path coefficient of 0.531, indicating a positive influence. At the same time, performance expectancy and social influence also have significant positive effects on willingness to use, with standardized path coefficients of 0.365 and 0.278, respectively. Conclusion With the development and application of smart Chinese medicine pharmacies, consumer-related research on influencing factors will become a key focus for future promotion and application. Future efforts should continuously explore mature and stable operational models, enhance the social influence of smart Chinese medicine pharmacies, strengthen recommendation channels through medical staff, provide trial opportunities for individuals with strong innovativeness, and continuously promote the improvement of relevant legal and regulatory systems.