July 2006 - Vol. 49 No. 7

This special section on services science is intended to broaden and challenge traditional thinking about services and service innovation. To the majority of computer scientists, whether in academia or industry, the term "services" is associated with Web services and service-oriented architectures. However, there is a broader story to be told of the remarkable growth of the service sector, which has come to dominate economic activity in most advanced economies over the last 50 years.Globalization, increasing automation, the growth of the Internet, and the dynamic componentization of business are driving the reconfiguration of service value networks at a scale and pace never before seen in history. The opportunity to innovate in services, to realize business and societal value from knowledge about service, to research, develop, and deliver new information services and business services, has never been greater. The challenges are both the multidisciplinary nature of service innovation, which combines business, technology, social-organizational, and demand innovation as well as the lack of formal representations of service systems.

The services sector has grown over the last 50 years to dominate economic activity in most advanced industrial economies, yet scientific understanding of modern services is rudimentary. Here, we argue for a services science discipline to integrate across academic silos and advance service innovation more rapidly.

The future of the service economy depends on worldwide appreciation, dedication, and encouragement of innovation as a key component.

We are in the midst of the fourth services transformation. The core story is the application of rule-based IT tools to service activities; it is not about the growth in the quantity or the value of the activities we label as services. The application of IT has the potential to transform the services component of […]

Using an ontological approach to better exploit services at the technical and business levels.

Over the past several decades mathematical models of supply chains have been developed and used for resource planning. Significant gains in supply chain efficiency have been attributed to the use of such models, together with the supporting IT infrastructure. Manufacturing resource planning (MRP), which automated the calculations of material requirements within manufacturing, evolved into enterprise resource planning (ERP), which monitors manufacturing enterprise processes and provides an information base for mathematically based advanced planning.

Computer scientists work with formal models of algorithms and computation, and someday service scientists may work with formal models of service systems. The four examples here document some of the early efforts to establish a new academic discipline and new profession.