Abstract
As the way people consume has changed, the focus of customer satisfaction has moved away from engineering and towards sensory preferences (SPs), necessitating a new approach to product development. This paper introduces a novel product development model that incorporates SP factors. First, utilizing literature and expert input, a domain-specific food sensory attribute knowledge graph is built. Then, SPs/non-sensory preferences (NSPs) are extracted from extensive online product evaluations using Latent Dirichlet allocation (LDA) and sentiment analysis. Customer preferences (CPs) are formed by combining quantifiable SPs/NSPs. Following that, CPs are used to design and distribute product components. To improve customer satisfaction, a new product development approach has been developed. Finally, a genetic algorithm is applied to the optimization model in order to determine the best product development approach. This model has been empirically and comparatively demonstrated to be practical and effective.
Published Version
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