Smart Product-Service Systems Solution Design via Hybrid Crowd Sensing Approach

Pai Zheng, Yang Liu, Fei Tao, Zuoxu Wang, Chun Hsien Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)

Abstract

The third wave of information technology (IT) competition has enabled one promising value co-creation proposition, Smart PSS (smart product-service systems). Manufacturing companies offer smart, connected products with various e-services as a solution bundle to meet individual customer satisfaction, and in return, collect and analyze usage data for evergreen design purposes in a circular manner. Despite a few works discussing such value co-creation business mechanism, scarcely any has been reported from technical aspect to realizing this data-driven manufacturer/service provider-customer interaction cost-effectively. To fill this gap, a novel hybrid crowd sensing approach is proposed, and adopted in the Smart PSS context. It leverages large-scale mobile devices and their massive user-generated/product-sensed data, and converges with reliable static sensing nodes and other data sources in the smart, connected environment for value generation. Both the proposed hybrid crowd sensing conceptual framework and its systematic information modeling process are introduced. An illustrative example of smart water dispenser maintenance service design is given to validate its feasibility. The result shows that the proposed approach can be a promising manner to enable value co-creation process cost-effectively.

Original languageEnglish
Article number8826266
Pages (from-to)128463-128473
Number of pages11
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 6 Sep 2019
Externally publishedYes

Keywords

  • crowd sensing
  • data-driven design
  • decision-theoretic rough set
  • Product-service systems
  • servitization
  • value co-creation

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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