【全文链接】

Bai Yang, Ying Liu, Wei Chen. A twin data-driven approach for user-experience based design innovation [J]. International Journal of Information Management, 2023, 102595.

https://doi.org/10.1016/j.ijinfomgt.2022.102595

【第一作者】

杨柏，重庆工商大学工商管理学院教授，博导，研究方向: 经济转型与增长和能源经济与政策。

【论文摘要】

Data-driven innovation has received increasing attention, which explores big data technologies to gain more insights and advantages for product design. In user experience (UX) based design innovation, user-generated data and archived design documents are two valuable resources for various design activities such as identifying opportunities and generating design ideas. However, these two resources are usually isolated in different systems. Additionally, design information typically represented based on functional aspects is limited for UX-oriented design. To facilitate experience-oriented design activities, we propose a twin data-driven approach to integrate UX data and archived design documents. In particular, we aim to extract UX concepts from product reviews and design concepts from patents respectively and to discover associations between the extracted concepts. First, a UX-integrated design information representation model is proposed to associate capabilities with key elements of UX at the concept, category, and aspect levels of information. Based on this model, a twin data-driven approach is developed to bridge experience information and design information. It contains three steps: experience aspect identification using an attention-based LSTM (Long short-term memory) network, design information categorization based on topic clustering using BERT (Bidirectional Encoder Representations from Transformers) and LAD (Latent Dirichlet allocation) model, and experience needs and design information integration by leveraging word embedding techniques to measure concept similarity. A case study using healthcarerelated experience and design information has demonstrated the feasibility and effectiveness of this approach.