The increasing importance of information technology (IT) services in the global economy prompts researchers in the field of information systems (IS) to give special attention to the foundations of managerial and technical knowledge in this emerging arena of knowledge. Already we have seen the computer science discipline embrace the challenges of finding new directions in design science toward making services-oriented computing approaches more effective, setting the stage for the development of a new science--service science, management, and engineering (SSME). This paper addresses the issues from the point of view of service science as a fundamental area for IS research. We propose a robust framework for evaluating the research on service science, and the likely outcomes and new directions that we expect to see in the coming decade. We emphasize the multiple roles of producers and consumers of services-oriented technology innovations, as well as value-adding seller intermediaries and systems integrators, and standards organizations, user groups, and regulators as monitors. The analysis is cast in multidisciplinary terms, including computer science and IS, economics and finance, marketing, and operations and supply chain management. Evaluating the accomplishments and opportunities for research related to the SSME perspective through a robust framework enables in-depth assessment in the present, as well as an ongoing evaluation of new knowledge in this area, and the advancement of the related management practice capabilities to improve IT services in organizations. INSETS: Text Box 1. An Example: SaaS, ASPs, and CRM;Text Box 2. The Services-as-Art Perspective on Service Science....
Information technology (IT) services providers are exposed to exogenous risks faced by the industry as a whole, and endogenous risks from their current portfolio of IT contracts. This exposure may lead to cost overruns or legal responsibility for service-level breeches. Providers can leverage information about their risk positions implied by their IT services contract portfolios to gain strategic advantage over their competitors. We build theory in support of a new construct, profit-at-risk, for evaluating the trade-offs between contract profitability and service-level risk, stemming from financial economics theory and models. We simulate an IT services contract portfolio, and show how managers can reduce organizational risk by forgoing profit-maximizing contracts in lieu of more conservative service-level agreements, yet still achieve high returns. Our approach provides decision support for ex ante contract evaluation and negotiation, and a means to conduct ex post efficiency evaluation. It also aligns IT service management with best practices in financial management.
Although the use of real options for valuation of information technology (IT) investments has been documented, little research has been conducted to examine its relevance for valuing and prioritizing a portfolio of projects. Complexities of IT projects along with the effect of project interdependencies raise several challenges in applying real options for prioritization of IT investments. We examine a large U.S.-based energy utility firm in a deregulated environment that is considering investment in a portfolio of 31 projects to provide a range of Internet-enabled energy services to customers. Using real data on expected project benefits and costs for different competitive scenarios, we develop a nested options model that extends prior research by incorporating the impact of project interdependencies to calculate the option value of all projects. Our nested options model provides a better understanding of project interdependencies on valuation and prioritization decisions, and provides insights into the business value of IT infrastructure projects that provide the managerial flexibility to launch future projects. We present a real options portfolio optimization algorithm for dynamic multiperiod portfolio optimization by incorporating the project values based on real options analysis in a portfolio management model with budget constraints.