Design Science in Information Systems Research

Abstract:

    • Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science.
    • The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior.
    • The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts.
    • Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology.
    • Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research.
    • In the designscience paradigm knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact.
    • Three recent exemplars in the research literature are used to demonstrate the application of these guidelines.
    • We conclude with an analysis o f the challenges of performing high-quality design-science research in the context of the broader IS community.

Information Systems Research Framework:

Design-Science Research Guidelines:

Discussion & Conclusions:

    • Philosophical debates on how to conduct IS research (e.g., positivism vs. interpretivism) have been the focus of much recent attention (Klein and Myers 1999; Robey 1996; Weber 2003).
      • The major emphasis of such debates lies in the epistemologies of research, the underlying assumption being that of the natural sciences.
      • That is, somewhere some truth exists and somehow that truth can be extracted, explicated, and codified.
      • The behavioral-science paradigm seeks to find "what is true." In contrast, the design-science paradigm seeks to create "what is effective." While it can be argued that utility relies on truth, the discovery of truth may lag the application of its utility.
      • We argue that both design-science and behavioralscience paradigms are needed to ensure the relevance and effectiveness of IS research.
      • Given the artificial nature of organizations and the information systems that support them, the design-science paradigm can play a significant role in resolving the fundamental dilemmas that have plagued IS research: rigor, relevance, discipline boundaries, behavior, and technology (Lee 2000).
    • Information systems research lies at the intersection of people, organizations and technology (Silver et al. 1995).
      • It relies on and contributes to cognitive science, organizational theory, management sciences, and computer science.
      • It is both an organizational and a technical discipline that is concerned with the analysis, construction, deployment, use, evaluation, evolution, and management of information system artifacts in organizational settings (Madnick 1992; Orlikowski and Barley 2001).
    • Within this setting, the design-science research paradigm is proactive with respect to technology.
      • It focuses on creating and evaluating innovative IT artifacts that enable organizations to address important information-related tasks.
      • The behavioral-science research paradigm is reactive with respect to technology in the sense that it takes technology as "given." It focuses on developing and justifying theories that explain and predict phenomena related to the acquisition, implementation, management, and use of such technologies.
      • The dangers of a design-science research paradigm are an overemphasis on the technological artifacts and a failure to maintain an adequate theory base, potentially resulting in "well-designed" artifacts that are useless in real organizational settings.
      • The dangers of a behavioral-science research paradigm are overemphasis on contextual theories and failure to adequately identify and anticipate technological capabilities, potentially resulting in theories and principles addressing outdated or ineffective technologies.
      • We argue strongly that IS research must be both proactive and reactive with respect to technology.
      • It needs a complete research cycle where design science creates artifacts for specific information problems based on relevant behavioral science theory and behavioral science anticipates and engages the created technology artifacts.
    • Hence we reiterate the call made earlier by March et al. (2000) to align IS designscience research with real-world production experience.
      • Results from such industrial experience can be framed in the context of our seven guidelines.
      • These must be assessed not only by IS design-science researchers but also by IS behavioral-science researchers who can validate the organizational problems as well as study and anticipate the impacts of created artifacts.
      • Thus, we encourage collaborative industrial/academic research projects and publications based on such experience.
      • Markus et al. (2002) is an excellent example of such collaboration.
      • Publication of these results will help accelerate the development of domain independent and scalable solutions to large-scale information systems problems within organizations.
      • We recognize that a lag exists between academic research and its adoption in industry.
      • We also recognize the possible ad hoc nature of technology-oriented solutions developed in industry.
      • The latter gap can be reduced considerably by developing and framing the industrial solutions based on our proposed guidelines.
    • It is also important to distinguish between "system building" efforts and designscience research. Guidelines addressing evaluation, contributions, and rigor are especially important in providing this distinction.
      • The underlying formalism required by these guidelines helps researchers to develop representations of IS problems, solutions, and solution processes that clarify the knowledge produced by the research effort.
    • As we move forward, there exist a number of exciting challenges facing the designscience research community in IS.
      • A few are summarized here.
        • There is an inadequate theoretical base upon which to build an e ngineering discipline of information systems design (Basili 1996).
        • The field is still very young lacking the cumulative theory development found in other engineering and socialscience disciplines.
        • It is important to demonstrate the feasibility and utility of such a theoretical base to a managerial audience that must make technology-adoption decisions that can have far-reaching impacts on the organization.
      • Insufficient sets of constructs, models, methods, and tools exist for accurately representing the business/technology environment.
        • Highly abstract representations (e.g., analytical mathematical models) are criticized as having no relationship to "real-world" environments.
        • On the other hand, many informal, descriptive IS models lack an underlying theory base.
        • The trade-offs between relevance and rigor are clearly problematic; finding representational techniques with an acceptable balance between the two is very difficult.
      • The existing knowledge base is often insufficient for design purposes and designers must rely on intuition, experience, and trial-and-error methods.
        • A constructed artifact embodies the designer's knowledge of the problem and solution.
        • In new and emerging applications of technology the artifact itself represents an experiment.
        • In its execution, we learn about the nature of the problem, the environment, and the possible solutions – hence the importance of developing and implementing prototype artifacts (Newell and Simon 1976).
      • Design-science research is perishable.
        • Rapid advances in technology can invalidate design-science research results before they are implemented effectively in the business environment or, just as importantly to managers, before adequate payback can be achieved by committing organizational resources to implementing those results.
        • Two examples are the promises made by the artificial intelligence community in the 1980’s (Feigenbaum and McCorduck 1983) and the more recent research on object-oriented databases (Chaudhri and Loomis 1998).
        • Just as important to IS researchers, design results can be overtaken by technology before they even appear in the research literature.
        • How much research was published on the Year 2000 problem before it became a non-event?
      • Rigorous evaluation methods are extremely difficult to apply in design-science research (Tichy 1998; Zelkowitz and Wallace 1998).
        • For example, the use of a design artifact on a single project may not generalize to different environments (Markus et al. 2002).
    • We believe that design science will play an increasingly important role in the IS profession.
      • IS managers in particular are actively engaged in design activities – the creation, deployment, evaluation, and improvement of purposeful IT artifacts that enable organizations to achieve their goals.
      • The challenge for design-science researchers in IS is to inform managers of the capabilities and impacts of new IT artifacts.
    • Much of the research published in MIS Quarterly employs the behavioral-science paradigm.
      • It is passive with respect to technology, often ignoring or "under-theorizing" the artifact itself (Orlikowski and Iacono 2001).
      • Its focus is on describing the implications of "technology" – its impact on individuals, groups, and organizations.
      • It regularly includes studies that examine how people employ a technology, report on the benefits and difficulties encountered when a technology is implemented within an organization, or discuss how managers might facilitate the use of a technology.
      • Orman (2002) argues that many of the equivocal results in IS behavioral-science studies can be explained by a failure to differentiate the capabilities and purposes of the studied technology.
    • Design science is active with respect to technology, engaging in the creation of technological artifacts that impact people and organizations.
      • Its focus is on problem solving but often takes a simplistic view of the people and the organizational contexts in which designed artifacts must function.
      • As stated earlier, the design of an artifact, its formal specification, and an assessment of its utility, often by comparison with competing artifacts, are integral to design-science research.
      • These must be combined with behavioral and organizational theories to develop an understanding of business problems, contexts, solutions, and evaluation approaches adequate to servicing the IS research and practitioner communities.
      • The effective presentation of design-science research in major IS journals, such as MIS Quarterly, will be an important step toward integrating the design-science and behavioral-science communities in IS.