Emotional needs and service process optimization in combined medical and elder care: A TRIZ approach

The development of services that combining medical and elder care (CMEC) lacks an innovative drive for and service consideration of emotional needs. In order to help in advancing continuous development in CMEC through sustained innovation, this study focuses on Kansei engineering and employs the theory of inventive problem-solving (TRIZ), emotional data–mining tools, and failure modes and effects analysis (FMEA). It outlines a three-phase process for innovative optimization of CMEC services. In Phase 1, we use a web-crawler algorithm to extract texts introducing numerous CMEC institutions listed on a large-platform in China called Chuxin Elder Care. After the preprocessing of the data, we extract emotion-related vocabulary, which represents the emotional needs of the elderly, from these texts and convert them into high-dimensional vectors using a word-to-vector (Word2Vec) algorithm. Next, we use a K-Means++ algorithm to derive emotional clusters, thereby constructing a list of core emotional vocabulary. In Phase 2, using this list, we combine service blueprints, fuzzy theory, and FMEA to locate where service failure occurs in the existing CMEC service process. In Phase 3, we map the reasons for service failure to TRIZ optimization and deterioration parameters and deduce innovation principles with a contradiction matrix. Based on these principles and core emotional needs, we propose innovative solutions to these service failures. The study reveals that the emotional needs of elderly people who receive CMEC services have not been adequately addressed. But, by employing Kansei engineering and TRIZ, the CMEC service process can be optimized effectively.