Group-based decision support systems (GDSS) (Gray et al., 2011) and knowledge management systems (KMS) (Alavi & Leidner, 2001) are specialised IT systems focused respectively on supporting team decision-making processes (through support for intelligence, design and choice phases) and on team-based or organisation-based knowledge preservation, dissemination and utilisation processes (supporting mainly the implementation and learning phases of an extended decision-making process). Both IT technologies have reached a mature stability.
However, when a new application domain appears, new scientific, engineering and managerial challenges are exposed. Service systems is an emergent relevant construct posited by the service science area – an emergent research area endorsed by important worldwide institutions. Service systems have been defined as dynamic configurations of people, technologies, organisations and shared information that create and deliver value to customers, providers and other stakeholders (Spohrer et al., 2008). Service science aims to discover the underlying logic of complex service systems and to establish a common language and shared frameworks for service innovation (IfM and IBM, 2008). In important service sectors are explicitly and implicitly embedded multiples service systems such as universities in the higher education sector, hospitals in the healthcare sector, mobile companies in the telecom sector, banks in the financial sector and sport leagues in the entertainment sector, among others. In all of these service systems, the participation of teams is inherent for knowledge and decision-intensive tasks.
Thus, in this special issue we pursue the goal of advancing our scientific knowledge of service systems through the support provided by GDSS and KMS to teams in these and other service systems. Exploratory, theory building, theory testing and applied high-quality research papers are welcome for the issue.
Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 107-136.
Gray, P., Johansen, B., Nunamaker, J., Rodman, J., &, Wagner, G. (2011). GDSS Past, Present, and Future. In: D. Schuff, D. Paradice, F. Burstein, D. Power and R. Sharda (Eds), Decision Support: An Examination of the DSS Discipline, Springer, pp. 1-24.
IfM and IBM (2008). Succeeding through Service Innovation: Developing a Service Perspective for Education, Research, Business and Government. Cambridge, United Kingdom: University of Cambridge Institute for Manufacturing.
Spohrer, J., Maglio, P. P., Bailey, J. and Gruhl, D. (2007). Steps toward a science of service systems. IEEE Computer, 40(1), 71–77.
Suitable topics include, but are not limited to, the following:
- Innovative applications of GDSS or KMS for service systems in core service sectors (education, healthcare, financial, telecom, entertainment, etc.)
- GDSS or KMS development methodologies including service science concepts
- GDSS or KMS value frameworks including service science concepts
- GDSS or KMS development tools useful for service systems (commercial or open source)
- Surveys on GDSS and KMS applications for service systems
- Theories on decision making in service sectors
- Case studies of knowledge management in service sectors
- Theory on technology-supported decision making or knowledge management in service sectors
- Human factors in technology use for group-based decision making in service sectors
- GDSS or KMS for green IT services
- GDSS or KMS for sustainable services
Paper submission for review: 15 October, 2014
Review results: 30 November, 2014
Revised paper submission: 31 January, 2015
Final acceptance: 28 February, 2015
Final version submission: 15 March, 2015