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首页> 外文期刊>Journal of Intelligent Manufacturing >Integrating correspondence analysis with Grey relational model to implement a user-driven STP product strategy for smart glasses
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Integrating correspondence analysis with Grey relational model to implement a user-driven STP product strategy for smart glasses

机译：将对应分析与Gray关系模型相集成，以实现用户驱动的智能眼镜STP产品策略

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摘要

To enhance customer retention and customer acquisition, product differentiation, product configuration and product recommendation are of importance to help firms implement segmentation-targeting-positioning strategies. In reality, however, user perceptions of product features are usually vague and diverse by individuals. Consequently, for a manufacturer, learning an efficient way to balance the trade-offs between satisfying customer needs and optimizing product varieties has become much more challenging than before. In order to overcome the aforementioned difficulty, this paper presents a novel framework to assist firms in determining the optimal product varieties of smart glasses with consideration of diverse requirements of three distinct segments (i.e. home entertainment, medical healthcare, and industry service). In particular, correspondence analysis is employed to indicate which product attributes best characterize a specific segment for achieving product differentiation. Then, by means of Grey relational model, the top three priorities with regard to three segments are systematically identified for conducting product configuration. Lastly, Bayes theorem is utilized to assign a potential buyer to his/her most similar segment for accomplishing unsupervised product recommendation.
机译：为了提高客户保留率和客户获取率，产品差异化，产品配置和产品推荐对于帮助公司实施细分定位和定位策略至关重要。然而，实际上，用户对产品功能的看法通常是模糊的并且是个人不同的。因此，对于制造商而言，学习一种有效的方法来平衡满足客户需求和优化产品种类之间的权衡已变得比以往更具挑战性。为了克服上述困难，本文提出了一个新颖的框架来帮助企业确定智能眼镜的最佳产品品种，同时考虑到三个不同细分市场（即家庭娱乐，医疗保健和行业服务）的不同要求。特别地，采用对应分析来指示哪些产品属性最能表征特定细分，以实现产品差异化。然后，通过灰色关联模型，系统地确定了有关三个细分市场的前三个优先事项，以进行产品配置。最后，利用贝叶斯定理将潜在购买者分配到他/她最相似的细分市场，以完成无监督产品推荐。

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