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Fuzzy product line design model while considering preference uncertainty: A case study of notebook computer industry in Taiwan

机译:考虑偏好不确定性的模糊产品线设计模型:以台湾笔记本电脑行业为例

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摘要

Enterprises evaluate customers' preferences of high-tech products to appropriately adjust product lines when the technologies are ready for commercialization. Conjoint analysis (CA) is usually applied to measure customers' preferences while the product line design model (PLDM) is used to simulate customers' purchase decisions based on these preferences. The optimal product line extension scheme (PLES) can then be found. For customers unfamiliar with a new technology, it is difficult to precisely appraise preferences for new products. This paper proposes fuzzy PLDM that combines fuzzy theory with CA to take preference uncertainty into consideration. To precisely apply fuzzy preferences, fuzzy rating is used to simulate customers' purchase decisions. This paper focuses on the notebook industry in Taiwan. Optimal PLES are obtained under Fuzzy and Crisp scenarios. The results show that customers with high preference uncertainty have different purchase decisions under above scenarios, which leads to a great inconsistency between the optimal PLES obtained from Fuzzy and Crisp scenarios. The Fuzzy scenario takes preference uncertainty into consideration and uses stricter standards to judge whether customers buy products with new technology.
机译:当技术准备商业化时,企业会评估客户对高科技产品的偏好,以适当地调整产品线。联合分析(CA)通常用于衡量客户的偏好,而产品线设计模型(PLDM)用于基于这些偏好来模拟客户的购买决策。然后可以找到最佳产品线扩展方案(PLES)。对于不熟悉新技术的客户,很难准确评估新产品的偏好。提出了一种模糊PLDM算法,将模糊理论与CA相结合,考虑了偏好不确定性。为了精确地应用模糊偏好,使用模糊评级来模拟客户的购买决策。本文重点介绍台湾的笔记本行业。在Fuzzy和Crisp场景下获得最佳PLES。结果表明,在上述情况下,具有高度不确定性的客户具有不同的购买决策,这导致从模糊和清晰的情况下获得的最佳PLES之间存在很大的不一致。模糊方案考虑了偏好不确定性,并使用更严格的标准来判断客户是否购买了采用新技术的产品。

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