The work aims to explore a user-need-oriented AR interaction design approach for plastic packaging of liquid foods and beverages, to improve information communication, interactive experience, and recycling guidance. A user need translation pathway supported by KANO, AHP, and QFD was developed. The KANO model was used to classify user needs, AHP was applied to calculate need weights, and QFD was employed to translate the weighted needs into AR packaging design elements. A PET tea beverage bottle was selected for design implementation, followed by user experience evaluation and recognition performance testing. Recognition stability, a clear interaction entry point, and a concise operation process were identified as foundational needs, while ingredient information presentation, product traceability, and lightweight AR access were identified as key optimization needs. The evaluation results showed that AR interactive packaging received higher ratings than conventional packaging in information comprehension, interaction satisfaction, and willingness to recycle, while maintaining relatively stable recognition performance under different test conditions. In conclusion, the proposed design pathway connects user need identification, weight calculation, and AR design element translation, providing a methodological reference for information extension, interactive experience optimization, and recycling guidance in plastic packaging for liquid foods and beverages.
Key words
liquid foods and beverages /
plastic packaging /
smart packaging /
AR interaction /
green recycling
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