The paper motivates, presents, demonstrates in use, and evaluates a methodology for conducting design science (DS) research in information systems (IS). DS is of importance in a discipline oriented to the creation of successful artifacts. Several researchers have pioneered DS research in IS, yet over the past 15 years, little DS research has been done within the discipline. The lack of a methodology to serve as a commonly accepted framework for DS research and of a template for its presentation may have contributed to its slow adoption. The design science research methodology (DSRM) presented here incorporates principles, practices, and procedures required to carry out such research and meets three objectives: it is consistent with prior literature, it provides a nominal process model for doing DS research, and it provides a mental model for presenting and evaluating DS research in IS. The DS process includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication. We demonstrate and evaluate the methodology by presenting four case studies in terms of the DSRM, including cases that present the design of a database to support health assessment methods, a software reuse measure, an Internet video telephony application, and an IS planning method. The designed methodology effectively satisfies the three objectives and has the potential to help aid the acceptance of DS research in the IS discipline.
We extend critical success factors (CSF) methodology to facilitate participation by many people within and around the organization for information systems (IS) planning. The resulting new methodology, called "critical success chains" (CSC), extends CSF to explicitly model the relationships between IS attributes, CSF, and organizational goals. Its use is expected to help managers to (1) consider a wider range of development ideas, (2) better balance important strategic, tactical, and operational systems in the development portfolio, (3) consider the full range of options to accomplish desired objectives, and (4) better optimize the allocation of resources for maintenance and small systems.
Determining whether investments in information technology (IT) have an impact on firm performance has been and continues to be a major problem for information systems researchers and practitioners. Financial theory suggests that managers should make investment decisions that maximize the value of the firm. Using event-study methodology, we provide empirical evidence on the effect of announcements of IT investments on the market value of the firm for a sample of 97 IT investments from the finance and manufacturing industries from 1981 to 1988. Over the announcement period, we find no excess returns for either the full sample or for any one of the industry subsamples. However, cross-sectional analysis reveals that the market reacts differently to announcements of innovative IT investments than to followup, or noninnovative investments in IT. Innovative IT investments increase firm value, while noninnovative investments do not. Furthermore, the market's reaction to announcements of innovative and noninnovative IT investments is independent of industry classification. These results indicate that, on average, IT investments are zero net present value (NPV) investments; they are worth as much as they cost. Innovative IT investments, however, increase the value of the firm.