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An approach to rule extraction for product service system configuration that considers customer perception

Author

Listed:
  • H.J. Long
  • L.Y. Wang
  • S.X. Zhao
  • Z.B. Jiang

Abstract

At present, manufacturers tend to bundle a product with its related services as a product service system, to meet customer needs and achieve competitive advantage. Configuring a product service system involves selecting and combining appropriate product and service components, to satisfy individual customer needs. One crucial step to rapidly configure a product service system is to develop formalised configuration rules, which show the relationships between product service components and customer needs, including those expressed as perception needs. In this study, a rough set-based approach is proposed to acquire configuration rules. First, an information table is built by combining the results of factor analysis and questionnaire survey. Then, customer segmentation is accomplished by clustering. Based on the information table and customer segmentation, a dominance-based rough set approach is used to extract the configuration rules. Finally, a weighbridge is selected for the case study to validate the proposed approach.

Suggested Citation

  • H.J. Long & L.Y. Wang & S.X. Zhao & Z.B. Jiang, 2016. "An approach to rule extraction for product service system configuration that considers customer perception," International Journal of Production Research, Taylor & Francis Journals, vol. 54(18), pages 5337-5360, September.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:18:p:5337-5360
    DOI: 10.1080/00207543.2015.1078012
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    Cited by:

    1. Paolo Gaiardelli & Giuditta Pezzotta & Alice Rondini & David Romero & Farnaz Jarrahi & Marco Bertoni & Stefan Wiesner & Thorsten Wuest & Tobias Larsson & Mohamed Zaki & Philipp Jussen & Xavier Boucher, 2021. "Product-service systems evolution in the era of Industry 4.0," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 177-207, March.
    2. Tomczyk, Arkadiusz T. & Buhalis, Dimitrios & Fan, Daisy X.F. & Williams, Nigel L., 2022. "Price-personalization: Customer typology based on hospitality business," Journal of Business Research, Elsevier, vol. 147(C), pages 462-476.
    3. Zaifang Zhang & Darao Xu & Egon Ostrosi & Hui Cheng, 2020. "Optimization of the Product–Service System Configuration Based on a Multilayer Network," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    4. Wang, Qingwei & Zheng, Meimei & Lee, Ka-Man & Shi, Xiaoqian & Shen, Yichi & Pan, Ershun, 2024. "Optimal product and after-sales service decisions considering risk attitudes under price-dependent uncertain demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).

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