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

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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.

论文关键词:Product line design,Fuzzy conjoint analysis,Preference uncertainty,Genetic algorithm

论文评审过程:Available online 3 August 2010.

论文官网地址:https://doi.org/10.1016/j.eswa.2010.07.106