Optimal Treadmill Attributes Configuration: A Text Mining Approach
DOI:
https://doi.org/10.23055/ijietap.2025.32.4.10923Keywords:
Text mining, Sentiment analysis, Product attributes, Attribute configuration, Ideal configurationAbstract
New product development aims to create products aligning with consumer preferences, yet discrepancies exist between consumers’ ideal product attributes and manufacturers’ perceptions. Previous studies primarily utilized regression equations or conjoint analysis to determine product attributes’ impact on consumer utility, with limited discussion on optimal attribute combinations. This study adopts a configurational approach using product attribute configuration as the analysis unit. We hypothesize that an ideal configuration exists for treadmill attributes, where products closer to this configuration achieve higher sales. Using text mining to convert online reviews into numerical data, we construct regression equations based on configuration-ideal distance. Results confirm the existence of an ideal treadmill attribute configuration, providing concrete guidance for new product development.
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