Special Issue
Information Systems Journal
Smart Service Systems: An Interdisciplinary Perspective
Deadline: May 15th, 2017
Special Issue Editors:
Daniel Beverungen, University of Paderborn Christoph F. Breidbach, University of Melbourne
Jens Poeppelbuss, University of Bremen
Virpi Kristiina Tuunainen, Aalto University [corresponding]
Service is a key context for use of information systems (IS), and the need for more research linking information systems research with service has already been established (Rai and Sambamurthy, 2006). Similarly, information systems are a key enabler to many services, and understanding its wider implications emerged as a key research priority for service science (Ostrom, et al., 2010). Over the last few years, both fields explored the intersection of information and communication technology (ICT) and service more broadly. While this resulted in several special issues pertaining to selected aspects of either service (e.g. Huang and Rust, 2013) or ICT (e.g. Barrett et al., 2015), the academic discourse related to technology-enabled service (e.g. Breidbach, et al., 2013) remains fragmented, and is still largely constrained to individual disciplinary silos.
The emerging interdisciplinary field of Service Science intends to weave together disparate theories and methods from multiple disciplines, to develop a scientific foundation for systematic service innovation (Maglio and Breidbach, 2014). Future service innovation, however, will depend on the effective understanding and use of data and technology in service (Maglio, 2015). We currently approach a tipping point where ICTs are beginning to augment the physical with a virtual world, resulting in smart service systems (e.g Medina-Borja, 2015).
For this special issue, we build upon the National Science Foundation (2014, p. 5), and define smart service systems as value co-creating configurations of people, technologies, organizations and information that are capable of independent learning, adapting, and decision-making. Smart service systems, therefore, possess self-detecting, self-diagnosing, self-correcting, self-monitoring, self- organizing, self-replicating, and/or self-controlling functions and capabilities based on data that has been received, transmitted, and/or processed. Smart service systems emerge in contexts as diverse as smart manufacturing (Industry 4.0), smart health, smart mobility, smart logistics or smart living. As the boundaries between a physical world enhanced by ICT, and the service that these systems provide to humans are blurred (e.g. Normann, 2001), new markets and business models emerge (Ng 2014). And with that, substantial opportunities for future research.
As the concepts of service and smartness are beginning to intertwine (e.g. Perera, et al., 2014), understanding smart service systems requires i) adopting a human-centered perspective on service, including novel explorations of human behavior, culture, and attitudes as it pertains to smart service; ii) exploring how new sensors, cognitive computing, or types of artificial intelligence may be implemented into existing service systems, thus transforming those into smart cities, smart health, or
