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Perception value of product-service systems: Neural effects of service experience and customer knowledge

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  • Zhao, Meina
  • Wang, Xuqi

Abstract

Digital trends in product-service system (PSS) development focus on developing win-win solutions for both companies and customers, particularly when considering human behavior issues. It is useful for the PSS provider to know the PSS value creation mechanism when customers are buying and utilizing a PSS, particularly in the service-dominant logic (SDL) and cognitive neuroscience perspective. This study solved the PSS implementation that satisfied the demands of both customers and manufacturers and the value cocreation mechanism during product and service configuration with the impacts of consumer learning and the service experience. The proposed neuroscience methodology is based on an ERP (event-related potential) experiment using PSS stimuli, representing the perception value creation process during customer decision making and the PSS configuration process. The effectiveness of the service experience is more important than customer knowledge during PSS value perception due to positive emotions with pleasant memories for the service experience and the conflicting cognition process of customer learning. The combination of service science and neurology may measure and observe human behavior and psychology through the brain science method and effectively solve the human factors in service science. The findings suggest a more objective and personalized understanding of PSS value perception, particularly the practical requirements of a resulted-oriented PSS and an application-oriented PSS.

Suggested Citation

  • Zhao, Meina & Wang, Xuqi, 2021. "Perception value of product-service systems: Neural effects of service experience and customer knowledge," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
  • Handle: RePEc:eee:joreco:v:62:y:2021:i:c:s0969698921001831
    DOI: 10.1016/j.jretconser.2021.102617
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    4. Zhang, Dianfeng & Shen, Zifan & Li, Yanlai, 2023. "Requirement analysis and service optimization of multiple category fresh products in online retailing using importance-Kano analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    5. Song, Yongming & Li, Yanhong & Zhu, Hongli & Li, Guangxu, 2023. "A decision support model for buying battery electric vehicles considering consumer learning and psychological behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    6. Zhiwei Xu & Siqi Liu, 2024. "Decoding consumer purchase decisions: exploring the predictive power of EEG features in online shopping environments using machine learning," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    7. Wang, Cuicui & Li, Yiyang & Fu, Weizhong & Jin, Jia, 2023. "Whether to trust chatbots: Applying the event-related approach to understand consumers’ emotional experiences in interactions with chatbots in e-commerce," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    8. Xu, Zhiwei & Zhang, Miao & Zhang, Pengfei & Luo, Jiawen & Tu, Mengting & Lai, Yuanhang, 2023. "The neurophysiological mechanisms underlying brand personality consumer attraction: EEG and GSR evidence," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

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