DEVELOPMENT OF A DATA-DRIVEN SMART PRODUCT SERVICE SYSTEM FRAMEWORK UTILIZING UNSUPERVISED LEARNING MODEL - Chiu, Ming-Chuan; Chang, Cheng-Yen; Kuo, Tsai-Chi; Huang, Jih-Hung; Gupta, Saraj; Akman, Gulsen (International Journal of Industrial Engineering: Theory, Applications and Practice, 2021)
Many studies have addressed traditional product-service system (PSS) design, but a combination of data-oriented PSS with emerging technologies to achieve a Smart PSS that can respond to a continuously changing environment remains absent. Therefore, this study proposes a systematic framework that utilizes text analytic techniques to capture PSS via a data-oriented service blueprint for use in identifying improvement opportunities and proposes an improvement plan merging a PSS design process and Bidirectional Encoder Representations from Transformers (BERT), which can handle context-sensitive services with smart and connected products in a dynamic environment. By utilizing a data-driven service blueprint and unsurprised learning model, a Smart PSS is transformed. Experiment shows this tourism recommendation generates enhanced service quality and customer satisfaction.