@inproceedings{61310,
  abstract     = {{Service systems engineering relies on structured, top-down approaches to designing and
innovating service systems. In today’s dynamic environments—shaped by digital transformation,
evolving provider–user interactions, and shifting societal demands—these approaches face limitations in enabling continuous, context-sensitive innovation. Continuous Value Shaping emerges as a conceptual extension to service systems engineering, promoting more adaptive and co-evolutionary forms of service system development. This study examines how Continuous Value Shaping manifests through a multiple case study of three public sector projects. We identify distinct manifestations and constellations of the concept’s principles that complement classical
SSE practices. As the first empirical exploration of Continuous Value Shaping, the study refines its
conceptual foundation and enhances its accessibility for researchers and practitioners. We conclude with seven empirically derived propositions that inform future service systems engineering initiatives and demonstrate how Continuous Value Shaping supports the dynamic alignment of service systems with societal and systemic demands.}},
  author       = {{Schäfer, Jannika Marie and Rajko, Polina and Angelova, Daniela and Böhmann, Tilo}},
  booktitle    = {{Proceedings of the 59th Hawaii International Conference on System Sciences (HICSS 2026)}},
  keywords     = {{Continuous Value Shaping, Service Systems Engineering, Service Science, Public Sector, Service Innovation}},
  location     = {{Maui, Maui, Hawaii, USA}},
  publisher    = {{Association for Information Systems (AIS), IEEE Computer Society Press, University of Hawaii (Manoa)}},
  title        = {{{From Engineering to Shaping: A Multiple Case Study on Advancing Service Systems Engineering through Continuous Value Shaping}}},
  year         = {{2026}},
}

@article{67182,
  abstract     = {{Generative artificial intelligence (GenAI) challenges core concepts in service science by blurring boundaries among resources, actors, and beneficiaries. Using service-dominant logic (SDL) as a theoretical lens, we review the distinctive properties of these concepts, introduce the agent concept into SDL, and analyze GenAI’s precise role in service exchange processes. We employ a two-phase research approach: First, we conduct a systematic literature review to derive defining properties of resources, actors, beneficiaries, and agents. We then assess eight contemporary GenAI systems against these properties. Our evidence indicates that GenAI is best understood as an operant resource and, depending on design and context, as an actor and agent. Conversely, GenAI does not qualify as a beneficiary, as it is neither individually capable of phenomenologically experiencing and determining value nor a social system of individuals with such capacities. Our findings propose an update to SDL’s core concepts and understanding, as well as a nuanced conceptual clarification of GenAI’s role, offering guidance for researchers and practitioners seeking to understand and design service interactions that incorporate GenAI.}},
  author       = {{Schäfer, Jannika Marie and Hansmeier, Philipp and zur Heiden, Philipp and Beverungen, Daniel}},
  journal      = {{Electronic Markets}},
  keywords     = {{Generative artificial intelligence, Service-dominant logic, Service science, Actor, Beneficiary, Agent}},
  number       = {{78}},
  publisher    = {{Springer Nature}},
  title        = {{{Resource, actor, beneficiary, or agent? A service‑dominant perspective on generative artificial intelligence}}},
  doi          = {{https://doi.org/10.1007/s12525-026-00932-w}},
  volume       = {{36}},
  year         = {{2026}},
}

@article{4684,
  abstract     = {{Recent years have seen the emergence of physical products that are digitally networked with other products and with information systems to enable complex business scenarios in manufacturing, mobility, or healthcare. These “smart products”, which enable the co-creation of “smart service” that is based on monitoring, optimization, remote control, and autonomous adaptation of products, profoundly transform service systems into what we call “smart service systems”. In a multi-method study that includes conceptual research and qualitative data from in-depth interviews, we conceptualize “smart service” and “smart service systems” based on using smart products as boundary objects that integrate service consumers’ and service providers’ resources and activities. Smart products allow both actors to retrieve and to analyze aggregated field evidence and to adapt service systems based on contextual data. We discuss the implications that the introduction of smart service systems have for foundational concepts of service science and conclude that smart service systems are characterized by technology-mediated, continuous, and routinized interactions.}},
  author       = {{Beverungen, Daniel and Müller, Oliver and Matzner, Martin and Mendling, Jan and vom Brocke, Jan}},
  issn         = {{14228890}},
  journal      = {{Electronic Markets}},
  keywords     = {{Boundary object, Internet of things, Service science, Smart products, Smart service}},
  pages        = {{7--18}},
  publisher    = {{SpringerNature}},
  title        = {{{Conceptualizing smart service systems}}},
  doi          = {{10.1007/s12525-017-0270-5}},
  volume       = {{29}},
  year         = {{2019}},
}