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DESIGN SCIENCE IN INFORMATION SYSTEMS RESEARCH (Design-Science Research…
DESIGN SCIENCE IN INFORMATION SYSTEMS RESEARCH
Two paradigms characterize much of the research in the Information Systems discipline:
Behavioral science
seeks to develop and verify theories that explain or predict human or organizational behavior.
Design science
seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts.
The realm of IS research is at the confluence of people, organizations, and technology (Davis and Olson 1985; Lee 1999). IT artifacts are broadly defined as
constructs
vocabulary and symbols
models
abstractions and representations
methods
algorithms and practices
instantiations
implemented and prototype systems
paradigm, an important dichotomy must be faced.
Design is both a process (set of activities) and a product (artifact)óa verb and a noun
(Walls et al. 1992). I
Design processes
(March and Smith, 1995)
Build
Evaluate
Design artifacts produced by design- science research in IS
Constructs
Models
Methods
Instantiations
Design-Science Research Guidelines
Guideline 1: Design as an artifact
Design-science research must produce a viable artifact in the form of a construct, a model, a method, or an instantiation.
artifacts are created and adapted to their changing environments and underlying technologies.
Guideline 2: Problem Relevance
The objective of design-science research is to develop
technology-based solutions
to important and relevant business problems.
Guideline 3: Design Evaluation
The utility, quality, and efficacy of a design artifact must be
rigorously demonstrated
via well-executed evaluation methods.
IT artifacts can be evaluated in terms of functionality, completeness, consistency, accu- racy, performance, reliability, usability, fit with the organization, and other relevant quality attributes.
Given the problem and solution requirements, sufficient degrees of freedom remain to express a variety of forms and functions in the artifact that are aesthetically pleasing to both the designer and the user. Good designers bring an element of style to their work (Norman 1988).
Guideline 4: Research Contributions
Effective design-science research must provide
clear and verifiable contributions
in the areas of the design artifact, design foundations, and/or design methodologies.
ìWhat are the new and interesting contributions?î Design-science research holds the potential for three types of research contri- butions based on the novelty, generality, and significance of the designed artifact. One or more of these contributions must be found in a given research project.
1. The design artifact
the artifact must enable the solution
2. Foundations
The creative development of novel, appropriately evaluated constructs, models, methods, or instantiations that extend and improve the existing foundations in the design-science knowledge base are also important contributions.
3. Methodologies
the creative develop- ment and use of evaluation methods (e.g., experimental, analytical, observational, testing, and descriptive) and new evaluation metrics provide design-science research contributions.
Measures and evaluation metrics in particular are crucial components of design-science research.
Artifacts must accurately represent the business and technology environments used in the research, information systems themselves being models of the business. These artifacts must be ìimplementable,î hence the importance of instan- tiating design science artifacts. Beyond these, however, the research must demonstrate a clear contribution to the business environment, solving an important, previously unsolved problem.
Guideline 5: Research Rigor
Design-science research relies upon the application of
rigorous methods
in both the construction and evaluation of the design artifact.
Design-science research often relies on mathe- matical formalism to describe the specified and constructed artifact. However, the environments in which IT artifacts must perform and the artifacts themselves may defy excessive formalism.
Because design-science artifacts are often the ìmachineî part of the human- machine system constituting an information sys- tem, it is imperative to understand why an artifact works or does not work to enable new artifacts to be constructed that exploit the former and avoid the latter.
Furthermore, designed artifacts are often com- ponents of a human-machine problem-solving system.
Guideline 6: Design as a search process
Design is essentially a search process to discover an effective solution to a problem.
Abstraction and representation of appropriate means, ends, and laws are crucial components of design-science research.These factors are prob- lem and environment dependent and invariably involve creativity and innovation.
Ends represent goals and constraints on the solution. Laws are uncontrollable forces in the environment. Effective design requires knowl- edge of both the application domain (e.g., require- ments and constraints) and the solution domain (e.g., technical and organizational).
One approach is to prove or demonstrate that a heuristic design solution is always within close proximity of an optimal solu- tion. Another is to compare produced solutions with those constructed by expert human designers for the same problem situation.
The search for an effective artifact requires utilizing available means
to reach desired ends while satisfying laws in the problem environment.
Guideline 7: Communication of Research
Design-science research must be presented both to technology-oriented as well as management- oriented audiences
the emphasis must be on the importance of the problem and the novelty and effectiveness of the solution approach realized in the artifact.
it may be necessary to describe the artifact in some detail to enable managers to appreciate its nature and understand its application. Presenting that detail in concise, well-organized appendices, as advised by Zmud, is an appropriate communication mechanism for such an audience.
Design-science research must be presented effectively both to technology-oriented as well as management-oriented audiences
The Design and Implementation of Anonymity in GDSS:
Gavish and Gerdes
Developmental, or design- science, research is called for in the areas of process structures and support and task struc- tures and support. Process structure and support technologies and methods are generic to all GDSS environments and tasks.
Technologies and methods for distributed communications, group memory, decision-making methods, and anonymity are a few of the critical design issues for GDSS process support needed in any task domain.
Task structure and support are specific to the problem domain under consideration by the group (e.g., medical decision making, software development). Task support includes the design of new technologies and methods for managing and analyzing task-related information and using that information to make specific, task-related decisions.
The issue of anonymity has been studied extensively in GDSS environments. Behavioral research studies have shown both positive and negative impacts on group interactions.
On the positive side, GDSS participants can express their views freely without fear of embarrassment or reprisal. However, anonymity can encourage free- riding and antisocial behaviors.
While the pros and cons of anonymity in GDSS are much researched, there has been a noticeable lack of research on the design of techniques for imple- menting anonymity in GDSS environments.
Gavish and Gerdes (1998) address this issue by designing five basic mechanisms to provide GDSS procedural anonymity.
Problem Relevance
Research Rigor
Design as a Search Process
Design as an Artifact
Design Evaluation