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Due to the digital transformation of smart cities (SCs), improved access to digital technologies can enable gathering and utilization of data which can serve as key resources for services to improve citizens’ quality of life. SCs face challenges making data valuable for the design of such data-driven services. Service literature lacks in providing methods to facilitate the design of these services while addressing the requirements of SCs as smart service systems. This paper presents the Data-driven Citizen Journey Map (DCJM), a method which supports designing data-driven services in collaborative Design Thinking (DT) workshops. Following design science research (DSR), we developed and evaluated our method through five iterations of workshops, interviews, and questionnaires with SC experts and students. Our evaluations indicate that the DCJM, including all promoted constructs, is useful to support data-driven service design in SCs and that it can be combined with existing methods in comprehensive service development processes.

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Jan 17th, 12:00 AM

Making Data Valuable for Smart City Service Systems - A Citizen Journey Map for Data-driven Service Design

Due to the digital transformation of smart cities (SCs), improved access to digital technologies can enable gathering and utilization of data which can serve as key resources for services to improve citizens’ quality of life. SCs face challenges making data valuable for the design of such data-driven services. Service literature lacks in providing methods to facilitate the design of these services while addressing the requirements of SCs as smart service systems. This paper presents the Data-driven Citizen Journey Map (DCJM), a method which supports designing data-driven services in collaborative Design Thinking (DT) workshops. Following design science research (DSR), we developed and evaluated our method through five iterations of workshops, interviews, and questionnaires with SC experts and students. Our evaluations indicate that the DCJM, including all promoted constructs, is useful to support data-driven service design in SCs and that it can be combined with existing methods in comprehensive service development processes.