DEVELOPMENT OF A DATA-DRIVEN SMART PRODUCT SERVICE SYSTEM FRAMEWORK UTILIZING UNSURPRISED LEARNING MODEL


Kuo T., Chiu M., Huang J., Chang C., Gupta S., Akman G.

International Journal Of Industrial Engineering-Theory Applications And Practice, vol.28, no.1, pp.130-142, 2021 (Journal Indexed in SCI Expanded)

  • Publication Type: Article / Article
  • Volume: 28 Issue: 1
  • Publication Date: 2021
  • Title of Journal : International Journal Of Industrial Engineering-Theory Applications And Practice
  • Page Numbers: pp.130-142

Abstract

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.