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Product–service systems (PSSs) have great potential for competitiveness and sustainability. Customers’ requirements cannot be directly used in the design of a PSS. Accurate identification of customer requirements, especially hidden requirements in the product life cycle, and transformation of customer requirements into specific engineering characteristics for PSS design are urgent problems. This study proposed a systematic and whole-process framework employing specific identification processes and methods, as well as a big data analysis. A set of refined and integrated methods were used to better identify customer requirements and to transform the customer requirements into specific engineering characteristics more accurately and efficiently. We also used customers’ online review data—a huge information resource to be explored—and big data technology to improve the requirement information identification process. A case study was implemented to verify our methodology. We obtained the engineering characteristics of a smartphone PSS matching the customer requirements as well as the exact importance rankings of customer requirements and engineering characteristics. The analysis results revealed that the proposed methodology allowed PSS designers to assess the PSS requirements more specifically and accurately by providing an intuitive evaluation of the role and importance of the requirements, engineering characteristics, and their mutual interactions that were hidden or indirect.
Liu et al. (Mon,) studied this question.