Abstract

Compared with common intelligent service, full-scene intelligent service has its uniqueness in high integration, synergy, and technological spillover. However, the traditional service or business model theories cannot precisely elaborate its sociotechnical contextual nature and value creation logic. To fill this knowledge gap, we provide initial insights into the value co-creation logic in full-scene intelligent service by exploring the value co-creation elements using a data-driven text mining approach. We analyzed 171 business reports on the full-scene intelligent service by the topic modeling using the Latent Dirichlet Allocation (LDA). The findings reveal three main clusters: value proposition, participants, and connection platform. This study presents a theoretical framework for a further exploratory case study and quantitative research on full-scene intelligent service. This study also helps small and medium-sized enterprises to explore and exploit value co-creation opportunities.

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