Consumer driven product technology function deployment using social media and patent mining

Amy J.C. Trappey, Charles V. Trappey, Chin Yuan Fan*, Ian J.Y. Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


The capability of identifying real-time customer needs is critical for manufacturers that provide short life cycle consumer products such as smart phones. Companies need to form research and development (R&D) strategies to improve key functional features for short lifespan products to reflect the adoption of innovative technologies and changing customer expectations. With the pervasive use of the Internet, this research crawls and analyzes the online voice of customers (VoC), overcoming the time lag of offline surveys, to identify and prioritize product functions for deployment using extended quality function deployment (eQFD) models. In this research, the novel analytics of the manufacturer's patent portfolio is added as an additional eQFD dimension to map ranked functional improvements to a manufacturer's R&D capabilities. Thus, a computer supported eQFD system is developed to perform the unique mappings and gap analyses between the VoC, the prioritized product functions, and the manufacturer's patent portfolio. The newly developed eQFD methodology and its novel discoveries are demonstrated in detail using a case study of three smart phones launched during the same time frame. The products include the Samsung Galaxy S7, the Huawei Honor 5X, and the ASUS Zenfone 3. The newly developed methodology is generally applicable to support VoC-centric product function deployment and R&D strategic planning in other domains.

Original languageEnglish
Pages (from-to)120-129
Number of pages10
JournalAdvanced Engineering Informatics
StatePublished - Apr 2018


  • Data mining
  • Latent semantic analysis
  • Patent analysis
  • Quality function deployment (QFD)
  • Voice of the customer
  • Web mining

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