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  • The world we live in today is constantly changing, with new technologies and innovations being introduced all the time. Through the continuation and innovation of Chinese medicine theories, scientific research methods, and progress, Traditional Chinese Medicine continues to evolve and develop more innovative Modern Chinese Medicine. In this research, Molecular Chinese Medicine is studied as a new form of Chinese medicine, intended to provide a more pleasant and safe experience for consumers. Thus, the objective of this study is to identify both positive and negative perceptions that contribute to the adoption of innovative technologies and their related products. In order to reach this goal, a robust value-based theoretical model is used. To examine behavioural intentions to adopt Molecular Chinese Medicine (MCM) in Macau, this study combines quantitative and qualitative methods. Thus, a Value-based Acceptance Model (VAM) was used to determine Macau citizens' attitudes towards Molecular Chinese Medicine, including their perceptions of its usefulness, enjoyment, technicality, and perceived fee, in relation to the perceived value of the product, which may ultimately determine adoption intentions. Structural Equation Modeling (SEM) was used to process a sample of 194 Macau residents. The data analysis supported our model's explanatory and predictive power and helped describe the characteristics of the local population. Our results provide insight into the acceptance of innovative products that may be useful in designing more accurate strategies and facilitating the introduction of MCM to Macau and similar markets. It was found that low perceived fees demonstrated a relatively strong positive correlation with potential users' perceived value, whereas usefulness and enjoyment showed a medium-strong positive correlation. Also, a strong positive correlation was found between potential consumers' perception of the value of Molecular Chinese Medicine and their intention to adopt it

Last update from database: 5/17/24, 9:26 PM (UTC)

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