A Three Cycle View of Design Science Research

Abstract

As a commentary to Juhani Iivari's insightful essay, I briefly analyze design science research as an embodiment of three closely related cycles of activities. The Relevance Cycle inputs requirements from the contextual envi- ronment into the research and introduces the research artifacts into environ- mental field testing. The Rigor Cycle provides grounding theories and methods along with domain experience and expertise from the foundations knowledge base into the research and adds the new knowledge generated by the research to the growing knowledge base. The central Design Cycle sup- ports a tighter loop of research activity for the construction and evaluation of design artifacts and processes. The recognition of these three cycles in a research project clearly positions and differentiates design science from other research paradigms. The commentary concludes with a claim to the pragmatic nature of design science.

Full text

© Scandinavian Journal of Information Systems, 2007, 19(2):87-92
A Three Cycle View of Design
Science Research
Alan R. Hevner
Information Systems and Decision Sciences, University of South
Florida, USA
ahevner@coba.usf.edu
Abstract. As a commentary to Juhani Iivari’s insightful essay, I briefly analyze
design science research as an embodiment of three closely related cycles of
activities. The Relevance Cycle inputs requirements from the contextual envi-
ronment into the research and introduces the research artifacts into environ-
mental field testing. The Rigor Cycle provides grounding theories and
methods along with domain experience and expertise from the foundations
knowledge base into the research and adds the new knowledge generated by
the research to the growing knowledge base. The central Design Cycle sup-
ports a tighter loop of research activity for the construction and evaluation of
design artifacts and processes. The recognition of these three cycles in a
research project clearly positions and differentiates design science from other
research paradigms. The commentary concludes with a claim to the pragmatic
nature of design science.
Keywords: design science, relevance cycle, rigor cycle, design cycle.
1 Design Science Research Cycles
Design science research is poised to take its rightful place as an equal compan-
ion to natural science research in the Information Systems (IS) field. As it is
doing so, it is vital that we as a research community provide clear and consist-
ent definitions, ontologies, boundaries, guidelines, and deliverables for the
design and execution of high quality design science research projects. Under-
standing and communicating the design science research process is essential
not only to support acceptance among IS professionals but also to establish the
credibility of IS design science research among the larger body of design sci-

88 • A. R. Hevner
ence researchers in the various engineering fields, architecture, the arts, and
other design-oriented communities.
Juhani Iivari’s essay (Iivari 2007) is an important and insightful contribu-
tion to a clearer understanding of the key properties of the design science
research paradigm—ontology, epistemology, methods, and ethics. I find
myself in basic agreement with the twelve theses that summarize the author’s
analysis of IS as a design science. In this commentary I relate several of the
essay’s theses to the existence of three design science research cycles. The
goal is to enhance our understanding of what it means to do high quality
design science research in IS.
Figure 1 borrows the IS research framework found in (Hevner et al. 2004)
and overlays a focus on three inherent research cycles. The Relevance Cycle
bridges the contextual environment of the research project with the design sci-
ence activities. The Rigor Cycle connects the design science activities with the
knowledge base of scientific foundations, experience, and expertise that
informs the research project. The central Design Cycle iterates between the
core activities of building and evaluating the design artifacts and processes of
the research. I posit that these three cycles must be present and clearly identifi-
able in a design science research project. The following sections briefly
expand on the definitions and meanings of each cycle.
2 The Relevance Cycle
Design science research is motivated by the desire to improve the environment
by the introduction of new and innovative artifacts and the processes for build-
Figure 1. Design Science Research Cycles
Knowledge Base Design Science Research
Build Design
Artifacts &
Processes
Evaluate
Design
C
y
cle
Application Domain
• People
• Organizational
Systems
• Technical
Systems
• Problems
& Opportunities
Relevance Cycle
• Requirements
• Field Testing
Rigor Cycle
• Grounding
• Additions to KB
Foundations
• Scientific Theories
& Methods
• Experience
& Expertise
• Meta-Artifacts
(Design Products &
Design Processes)
Environmen
t

A. R. Hevner • 89
ing these artifacts (Simon 1996). An application domain consists of the peo-
ple, organizational systems, and technical systems that interact to work toward
a goal. Good design science research often begins by identifying and repre-
senting opportunities and problems in an actual application environment. In
his essay, Juhani points out that some design science research is about potenti-
ality; the identification of new opportunities to improve practice before any
problem is recognized.
Thus, the relevance cycle initiates design science research with an applica-
tion context that not only provides the requirements for the research (e.g., the
opportunity/problem to be addressed) as inputs but also defines acceptance
criteria for the ultimate evaluation of the research results. Does the design arti-
fact improve the environment and how can this improvement be measured?
The output from the design science research must be returned into the environ-
ment for study and evaluation in the application domain. The field study of the
artifact can be executed by means of appropriate technology transfer methods
such as action research (Cole et al. 2005; Jarvinen 2007).
The results of the field testing will determine whether additional iterations
of the relevance cycle are needed in this design science research project. The
new artifact may have deficiencies in functionality or in its inherent qualities
(e.g., performance, usability) that may limit its utility in practice. Another
result of field testing may be that the requirements input to the design science
research were incorrect or incomplete with the resulting artifact satisfying the
requirements but still inadequate to the opportunity or problem presented.
Another iteration of the relevance cycle will commence with feedback from
the environment from field testing and a restatement of the research require-
ments as discovered from actual experience.
3 The Rigor Cycle
Design science draws from a vast knowledge base of scientific theories and
engineering methods that provides the foundations for rigorous design science
research. As importantly, the knowledge base also contains two types of addi-
tional knowledge:
• The experiences and expertise that define the state-of-the-art in the
application domain of the research.
• The existing artifacts and processes (or meta-artifacts as put forth by
Juhani in Thesis 5) found in the application domain.

90 • A. R. Hevner
The rigor cycle provides past knowledge to the research project to ensure its
innovation. It is contingent on the researchers to thoroughly research and ref-
erence the knowledge base in order to guarantee that the designs produced are
research contributions and not routine designs based upon the application of
well-known processes (Hevner et al. 2004). As Juhani notes, “It is the rigor of
constructing IT artifacts that distinguishes Information Systems as design sci-
ence from the practice of building IT artifacts.”
Research rigor in design science is predicated on the researcher’s skilled
selection and application of the appropriate theories and methods for con-
structing and evaluating the artifact. A key question that Juhani addresses is
whether a ’design theory’ is an essential aspect of design science rigor. My
opinion aligns with Juhani’s contention that it is often a stretch to find kernel
theories for the creative activities of design research. While theories can serve
as sources of creative ideas, to insist that all design research must be grounded
on descriptive theories is unrealistic and even harmful to the field when good
design science papers are rejected in top journals due to lack of a grounding
theory. I much prefer the direction of identifying several different sources of
ideas for the grounding of design science research to include rich opportuni-
ties/problems (from the relevance cycle), existing artifacts, analogies/meta-
phors, and theories (Juhani 2007). I would expand this list of design
inspiration to include additional sources of creative insights (Csikszentmihalyi
1996).
Additions to the knowledge base as results of design science research will
include any extensions to the original theories and methods made during the
research, the new meta-artifacts (design products and processes), and all expe-
riences gained from performing the research and field testing the artifact in the
application environment. Research contributions to the knowledge base are
key to selling the research to the academic audience just as useful contribu-
tions to the environment are the key selling points to the practitioner audience.
4 The Design Cycle
The internal design cycle is the heart of any design science research project.
This cycle of research activities iterates more rapidly between the construction
of an artifact, its evaluation, and subsequent feedback to refine the design fur-
ther. Simon (1996) describes the nature of this cycle as generating design
alternatives and evaluating the alternatives against requirements until a satis-
factory design is achieved. As discussed above, the requirements are input
from the relevance cycle and the design and evaluation theories and methods

A. R. Hevner • 91
are drawn from the rigor cycle. However, the design cycle is where the hard
work of design science research is done. I believe that it is important to under-
stand the dependencies of the design cycle on the other two cycles while
appreciating its relative independence during the actual execution of the
research.
During the performance of the design cycle it is important to maintain a
balance between the efforts spent in constructing and evaluating the evolving
design artifact. Both activities must be convincingly based in relevance and
rigor. Having a strong grounded argument for the construction of the artifact,
as discussed above, is insufficient if the subsequent evaluation is weak. As
Juhani states in his essay, ”The essence of Information Systems as design sci-
ence lies in the scientific evaluation of artifacts.” Along with Juhani, I agree
that artifacts must be rigorously and thoroughly tested in laboratory and exper-
imental situations before releasing the artifact into field testing along the rele-
vance cycle. This calls for multiple iterations of the design cycle in design
science research before contributions are output into the relevance cycle and
the rigor cycle.
5 Design as a Pragmatic Science
Let me conclude this brief commentary with a claim for the pragmatic nature
of design science. Juhani states that prior research papers (Hevner et al. 2004;
March and Smith 1995) associate design science with a pragmatic philosophy.
Pragmatism is a school of thought that considers practical consequences or
real effects to be vital components of both meaning and truth. Along these
lines I contend that design science research is essentially pragmatic in nature
due to its emphasis on relevance; making a clear contribution into the applica-
tion environment. However, practical utility alone does not define good design
science research. It is the synergy between relevance and rigor and the contri-
butions along both the relevance cycle and the rigor cycle that define good
design science research.
In my current assignment at the U.S. National Science Foundation (NSF) I
work with research proposals in the directorate of Computer and Information
Science and Engineering. A majority of these research projects use a design
science research paradigm. Since its beginnings in 1953, the NSF has strug-
gled with distinctions between basic science and applied science in its award-
ing of research funds1 to academic researchers. Does the practical utility of a
result necessarily make the research project applied science? Can a research
project effectively balance goals of fundamental scientific understanding with

92 • A. R. Hevner
considerations of the usefulness of the resulting artifacts? These are impor-
tance issues for us in Information Systems to address as we strive to better
understand how to perform rigorous and relevant design science research and
how to attract external funding to our research.
Notes
1. I highly recommend Stokes (1997) for an in-depth discussion of the history
and current implications of the debates over the funding of basic and applied
research at NSF and in the U.S. government.
References
Csikszentmihalyi, M., Creativity: Flow and Psychology of Discovery and
Invention, HarperCollins, New York, 1996.
Cole, R., Purao, S., Rossi, M. and Sein, M.K., “Being Proactive: Where
Action Research Meets Design Research,” Proceedings of the Twenty-
Sixth International Conference on Information Systems, Las Vegas,
2005, pp. 325-336.
Hevner, A.R., March, S.T., Park, J. and Ram, S., “Design Science in Informa-
tion Systems Research, MIS Quarterly, 28(1), 2004, pp. 75-105.
Iivari, J., “A Paradigmatic Analysis of Information Systems as a Design Sci-
ence, Scandinavian Journal of Information Systems, 19(2), 2007.
Jarvinen, P., “Action Research is Similar to Design Science, Quality & Quan-
tity, 41, Springer, 2007, pp. 37-54.
March, S.T. and Smith, G.F., “Design and Natural Science Research on
Information Technology, Decision Support Systems, 15, 1995, pp. 251-
266.
Simon, H., The Sciences of Artificial, 3rd Edition, MIT Press, Cambridge, MA,
1996.
Stokes, D., Pasteur’s Quadrant: Basic Science and Technological Innovation,
Brookings Institution Press, Washington D.C., 1997.