Roles of Digital Innovation in Design Science Research

Abstract

There has been a surge of interest in the design science
research (DSR) paradigm as central to information systems
(IS) studies in the past 20 years. The goal of a DSR
research project is to extend the boundaries of human and
organizational capabilities by designing new and innovative
artifacts represented by constructs, models, methods,
and instantiations (Hevner et al. 2004; Peffers et al. 2007;
Gregor and Hevner 2013). Broadly speaking, DSR aims to
add to knowledge of how things can and should be constructed
or arranged (i.e., designed), usually by human
agency, to achieve a desired set of goals. For example,
design knowledge in the IS discipline includes knowledge
of how to structure and construct a database system, how to
model business processes, how to align IS with organizational
strategy, and how to deliver data analytics for
effective decision making (e.g., Becker et al. 2015). DSR
results in IS have been shown to create significant economic
and societal impact (vom Brocke et al. 2013).
Beyond the IS field, DSR is a central research paradigm in many other domains including engineering, architecture,
business, economics, and other information technologyrelated
disciplines for the creation of novel solutions to
relevant design problems.
With its focus on the design and deployment of innovative
artifacts, DSR is ideally positioned to make both
research and practice contributions to the field of digital
innovation (DI). Digital innovation is the appropriation of
digital technologies in the process of and as the result of
innovation. Digital innovation emphasizes combinations of
digital and physical components to produce novel products
(Yoo et al. 2010). In contrast to process innovation
research, digital innovation research focuses on product
and service innovation using digital technologies. Digital
innovation is rapidly becoming a dominant topic and
research focus in the fields of innovation, entrepreneurship,
strategic management, organizational design, and information
systems. The phenomena of digital innovation
encompasses new digital technologies, information digitization,
digitally-enabled generativity, and innovation
management with a greater range and reach of innovation
across organizational boundaries (Yoo et al. 2010; Fichman
et al. 2014). Surveys show that organizations across a wide
range of disciplines view digital innovation to be of vital
importance (Fielt and Gregor 2016).
However, we observe that there is little understanding
and scarce literature on the relationships and synergies
between DSR and DI. With this special issue, we present a
set of DSR studies that show how DI artifacts are both
produced by and used in DSR projects. In this editorial, we
study the various roles that DI may play in DSR projects.
We propose that the DSR paradigm provides formal and
effective paths for demonstrating measurable impacts of DI
in practice as well as contributing new DI knowledge to the
appropriate discipline knowledge bases. The resulting framework provides a starting point for understanding the
interactions between DI and DSR to the mutual benefit of
both fields of study. Finally, we apply the new framework
to the papers selected for the special issue highlighting the
DI roles in each of the reported DSR projects.

Full text

EDITORIAL
Roles of Digital Innovation in Design Science Research
Alan Hevner •Jan vom Brocke •Alexander Maedche
Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2018
1 Introduction
There has been a surge of interest in the design science
research (DSR) paradigm as central to information systems
(IS) studies in the past 20 years. The goal of a DSR
research project is to extend the boundaries of human and
organizational capabilities by designing new and innova-
tive artifacts represented by constructs, models, methods,
and instantiations (Hevner et al. 2004; Peffers et al. 2007;
Gregor and Hevner 2013). Broadly speaking, DSR aims to
add to knowledge of how things can and should be con-
structed or arranged (i.e., designed), usually by human
agency, to achieve a desired set of goals. For example,
design knowledge in the IS discipline includes knowledge
of how to structure and construct a database system, how to
model business processes, how to align IS with organiza-
tional strategy, and how to deliver data analytics for
effective decision making (e.g., Becker et al. 2015). DSR
results in IS have been shown to create significant eco-
nomic and societal impact (vom Brocke et al. 2013).
Beyond the IS field, DSR is a central research paradigm in
many other domains including engineering, architecture,
business, economics, and other information technology-
related disciplines for the creation of novel solutions to
relevant design problems.
With its focus on the design and deployment of inno-
vative artifacts, DSR is ideally positioned to make both
research and practice contributions to the field of digital
innovation (DI). Digital innovation is the appropriation of
digital technologies in the process of and as the result of
innovation. Digital innovation emphasizes combinations of
digital and physical components to produce novel products
(Yoo et al. 2010). In contrast to process innovation
research, digital innovation research focuses on product
and service innovation using digital technologies. Digital
innovation is rapidly becoming a dominant topic and
research focus in the fields of innovation, entrepreneurship,
strategic management, organizational design, and infor-
mation systems. The phenomena of digital innovation
encompasses new digital technologies, information digiti-
zation, digitally-enabled generativity, and innovation
management with a greater range and reach of innovation
across organizational boundaries (Yoo et al. 2010; Fichman
et al. 2014). Surveys show that organizations across a wide
range of disciplines view digital innovation to be of vital
importance (Fielt and Gregor 2016).
However, we observe that there is little understanding
and scarce literature on the relationships and synergies
between DSR and DI. With this special issue, we present a
set of DSR studies that show how DI artifacts are both
produced by and used in DSR projects. In this editorial, we
study the various roles that DI may play in DSR projects.
We propose that the DSR paradigm provides formal and
effective paths for demonstrating measurable impacts of DI
in practice as well as contributing new DI knowledge to the
appropriate discipline knowledge bases. The resulting
A. Hevner
Information Systems and Decision Sciences Department,
University of South Florida, Tampa, FL, USA
e-mail: ahevner@usf.edu
J. vom Brocke
Institute of Information Systems, University of Liechtenstein,
Vaduz, Liechtenstein
e-mail: jan.vom.brocke@uni.li
A. Maedche (&)
Institute of Information Systems and Marketing (IISM),
Karlsruhe Service Research Institute (KSRI), Karlsruhe Institute
of Technology, Karlsruhe, Germany
e-mail: alexander.maedche@kit.edu
123
Bus Inf Syst Eng
https://doi.org/10.1007/s12599-018-0571-z

framework provides a starting point for understanding the
interactions between DI and DSR to the mutual benefit of
both fields of study. Finally, we apply the new framework
to the papers selected for the special issue highlighting the
DI roles in each of the reported DSR projects.
2 DSR Knowledge Consumption and Production Model
Information systems research consumes and produces two
basic types of knowledge: (1) behavioral science-oriented
research activities primarily grow propositional knowledge
or X-knowledge (comprising descriptive and explanatory
knowledge), and, (2) DSR-oriented research activities pri-
marily grow applicable (or prescriptive) knowledge or k-
knowledge (Gregor and Hevner 2013). Contributions to the
kknowledge base typically comprise knowledge about
technological (i.e., digital) innovations that directly affect
individuals, organizations, or society while also enabling
the development of future innovations (Winter and Albani
2013). Contributions to the Xknowledge base enhance our
understanding of the world and the phenomena our tech-
nologies harness (or cause). Research projects may com-
bine both paradigms of inquiry and contribute to both
knowledge bases.
The relationships of design knowledge produced and
consumed in DSR projects and the (design) knowledge
bases are shown in Fig. 1. This figure is adapted and
simplified from (Drechsler and Hevner 2018) and clearly
illustrates paired modes of consuming and producing
knowledge between the DSR project and the Xand k
knowledge bases. The k-knowledge is further divided into
two sub-categories. The Solution Design Entities collect
the prescriptive knowledge as represented in the tangible
artifacts, systems, and processes designed and applied in
the problem solution space. The growth of design theories
around these solutions is captured in the Solution Design
Theories knowledge base (Gregor and Hevner 2013).
Knowledge can be projected from the specific application
solutions into nascent theories around solution technolo-
gies, actions, systems, and design processes based on the
new and interesting knowledge produced in a DSR project.
Thus, we can describe the interactions of a specific DSR
project with the extant knowledge bases in the following
consuming and producing modes:
•Descriptive (X) Knowledge: X-knowledge (or kernel
knowledge) informs the understanding of a problem, its
context, and the underlying design of a solution entity
(Arrow 1). As results of the research project, the design
and real-world application of solution entities or design
knowledge enhances our descriptive understanding of
how the world works via the testing and building of
new X-knowledge (Arrow 2).
•Prescriptive (k) Solution Design Entities: Existing
solution entities, design processes, or design systems
are re-used to inform novel designs of new entities,
processes, or systems (Arrow 5) (vom Brocke and
Buddendick 2006). Within a DSR project, effective
solution entities, design processes, or design systems
are produced and contributed to new k-knowledge
(Arrow 6).
•Prescriptive (k) Solution Design Theories: Solution
design knowledge, in the form of growing design
theories, informs the design of a solution entity, a
design process or a design system (Arrow 3). Within a
DSR project, effective principles, features, actions, or
effects of a solution entity or a design process or system
are generalized and codified in solution design knowl-
edge (e.g., design theories or technological rules)
(Arrow 4).
Fig. 1 DSR projects and modes
of producing and consuming
design knowledge (adapted
from Drechsler and Hevner
2018)
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A. Hevner et al.: Roles of Digital Innovation, Bus Inf Syst Eng

3 Digital Innovation Roles in DSR
Drawing from our experiences working on DSR projects
involving innovative artifacts and from our knowledge of
the extant DSR literature, we observe multiple roles that
digital innovations may play in DSR projects. However,
nowhere have we found a comprehensive framework that
organizes and describes prevalent DI roles in DSR. In the
following, we propose an initial framework with the
description of six potential DI roles in DSR projects.
A DSR project may include one or more of these DI roles.
We further map the different roles to the DSR paradigm as
shown in Fig. 2.
3.1 Role 0: Understanding of the DI Problem Space
A starting point of all DSR projects is to gain a full
understanding of the relevant problem space and the per-
tinent descriptive theories that may inform the design of
digital innovations in that space. We label this as Role 0
due to its fundamental nature in a DSR project. The
research team draws from the current knowledge base of
‘kernel theories’ that provide the underpinning justificatory
knowledge that informs problem understanding and solu-
tion artifact construction (Walls et al. 1992; Gregor and
Jones 2007). Such descriptive theories are likely based on
the study of previous digital innovations and their appli-
cations in interesting application environments. Thus, the
use of descriptive theory around current DI to inform new
DI supports a Role 0 use to understand the project problem
space.
3.2 Role 1: Design of a DI Technical Artifact
The formative goal of a DSR project is the design of a
novel technical artifact. In the field of information systems,
that artifact will most likely be delivered in the form of
digital innovation. A DI artifact grows through multiple
cycles of build and evaluation activities (Sonnenberg and
vom Brocke 2012) until it is ready to be introduced into the
problem space and its new knowledge added to the k
knowledge base as a technical solution artifact (see Fig. 2).
Depending on the maturity of the problem and solution
environments, the DI contribution to the knowledge base
can be totally new knowledge in the form of an invention,
an advance on existing solution knowledge, or the exap-
tation of known solution knowledge to a new problem
(Gregor and Hevner 2013,2014). The DI artifact contri-
bution in this role corresponds to Simon’s (1996) inner (or,
interior) environment of the artifact. The inner design of
the artifact builds the technical core (e.g., hardware, soft-
ware) that provides the intended behaviors to the world via
well-defined interfaces. Role 1 supports the design and
implementation of a well-defined technical DI artifact and
its introduction into the knowledge base of solution design
entities.
3.3 Role 2: Design of an Artifact for Deployment
and Use of a DI Artifact
Most DSR projects not only produce a novel DI artifact but
also the required processes and procedures for the
deployment and use of that artifact in the problem context.
These processes are novel ‘use artifacts’ that describe
effective methods to make the best use of the DI artifact for
problem solutions (see Fig. 2). Thus, the role of the DI
artifact is as a pre-defined entity with the DSR goal being
one of designing methods of its application to important
problems. This role corresponds to Simon’s (1996) outer
(or, exterior) environment of the artifact. The DI artifact
interfaces provide the exigent opportunities for its appli-
cation. We note that a single DSR project may iterate
between the DI artifact in its Role 1 (internal technical
design) and Role 2 (external use design) as it attempts to
Fig. 2 Roles of DI in DSR
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satisfy project goals. The new processes and procedures for
use of the DI artifact are added to the knowledge base of
solution design entities.
3.4 Role 3: Design of a Socio-Technical DI System
Role 3 of a DI artifact is in its composition (perhaps with
other DI artifacts) into a larger, more complex socio-
technical system (Demetis and Lee 2016). The DSR project
builds and evaluates the integration of the multiple DI
artifacts into a new system to address different and, likely,
more challenging problem contexts. The integrated system
itself becomes a novel DI artifact that is added to the k
knowledge base as a solution design entity (see Fig. 2).
Research issues of artifact compatibilities, interfaces, and
integration become paramount in this type of DSR project.
Thus, the DI artifact in its Role 3 plays a component role
for the design of a more complex, integrated Role 1 DI
artifact.
3.5 Role 4: Development of Design Theories
Surrounding a DI Artifact
An essential research activity in a DSR project is the
reflection, learning, and design theorizing around the
development of DI artifacts. The project captures pre-
scriptive design knowledge from the DSR design cycles
and from the introduction of the DI artifact into the prob-
lem space of the project. These solution design theories can
be represented in multiple formats as knowledge for tech-
nology, action, integration, or process (see Fig. 2)
(Drechsler and Hevner 2018). The goal of design theories
in the form of nascent or mid-range theories is to grow
understanding of the DI artifact for generalizing its tacit
knowledge for future improvements and adaptations to new
problem contexts (Gregor and Hevner 2013). Thus, Role 4
of a DI artifact in DSR provides a rigorous base for cap-
turing solution knowledge in the form of solution design
theories as a prescriptive research contribution. We would
expect the use of a DI artifact in Role 4 to be combined in a
DSR project with its use in preceding Roles 1, 2, or 3.
3.6 Role 5: Use of a DI Artifact as a Creativity Tool
in the DSR Solution Process
Innovative artifacts are often used as creativity tools in a
DSR project to provide new ways of thinking and doing in
the design of novel artifacts. For example, the ideation
activity in a DSR project can be supported with novel
visualization tools (e.g., mind mapping tools) as digital
innovations. Furthermore, specialized tools such as
MyDesignProcess have been suggested recently to support
entire DSR processes executed by (distributed) design
teams (Morana et al. 2018). This DI role is termed an
operant innovation resource by Nambisan (2013). In Role
5, a DI artifact acts on other resources to build and evaluate
new designs. The DSR project would retrieve this existing
DI artifact from the prescriptive knowledge base and use it
in the DSR process of creating a new DI artifact (see
Fig. 2).
4 Special Issue Papers
The five DSR projects presented in this special issue pro-
vide an interesting variety of how DI artifacts participate in
different research roles. Here we briefly describe each of
the following papers and highlight the roles of DI artifacts
in each of the DSR projects.
1. Service-Dominant Business Model Design for Digital
Innovation in Smart Mobility
The authors claim that many digital innovations that
exhibit smart mobility features require business-modeling
support in order to achieve broader impacts in large-scale
systems, such as smart city applications (e.g., Role 3). To
this end, the Service-Dominant Business Model Radar
(SDBM-R) is designed as a business-engineering frame-
work. The goal is to better support the design of new
business models for the incorporation of digital innovations
for collaborative transport of people and goods. Thus, the
design of SDBM-R itself is a Role 1 application of DI in
the project, while the use of SDBM-R in the design of new
business models is a Role 5 application.
2. Scenario-based Design Theorizing – The Case of a
Digital Idea Screening Cockpit
This paper studies the ideation process within organi-
zations. A thorough survey of the literature on DI idea
generation (Role 0), provides a set of criteria for idea
screening. The authors design a Digital Idea Screening
Cockpit (DISC) to organize and track ideas in organiza-
tions (Role 1). In addition, a new ideation process of
generating, assessing, selecting, and tracking of how ideas
become digital innovations is built around the use of the
DISC tool (Role 2). Finally, the authors perform design
theorizing around the DISC artifact to support its adapta-
tion to the specific needs of an organization (Role 4).
3. Towards Digital Transformation in Fashion Retailing:
A Study of Automated Checkout Systems
This paper presents a cyber-physical system enabling
automated checkout in fashion retail stores. Automated
checkout systems have the potential to reduce costs and in
parallel improve customer experience. Building on differ-
ent innovative digital technologies the paper follows Role 1
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and designs an IT artifact that leverages hardware and
software components to automatically detect purchases.
The design of the artifact takes various constraints such as
privacy and reliability under consideration. The evaluation
of the artifact in a laboratory environment shows that
shopping baskets can be detected in an efficient and reli-
able way.
4. Engineering of Augmented Reality-Based Information
Systems: Design and Implementation for Intralogistics
Services
This article focusses on digital innovation facilitated by
augmented reality glasses, and, following Role 1, it pro-
vides several artifacts to support the development of aug-
mented reality-based systems. The authors first take a
domain specific lens investigating 36 use cases for aug-
mented reality in the logistics service domain, so that their
work also incorporates Role 0 providing a detailed DI
problem understanding in a specific domain, which they
operationalize by means of meta-requirements. They derive
design principles as well as an architecture for augmented
reality-based system design in the logistics services
domain, which outline principles of form and function and,
thus, according to Role 4, mark important contributions
towards the development of DI design theories. Applying
concurrent evaluation, the authors develop a number of
prototypes and, based on their observations from these
projects, derive a more general framework for the aug-
mented reality glasses implementations, which following
Role 1 serves as a technical DI artifact. They discuss their
findings and outline future research opportunities.
5. Design Principles for Systematic Search Systems:
Synthesis of a Rigorous Multi-Cycle DSR Journey
This article investigates how to design innovative arti-
facts to facilitate systematic searches on research literature.
Existing systematic literature search systems (SLSS) are
studied to build a set of meta-requirements for an improved
artifact (Role 0). A prototype SLSS, LitSonar, is built and
evaluated via several controlled experiments (Role 1).
Finally, a set of design principles for effective SLSS is
proposed to guide the development of innovative search
systems in different application contexts (Role 4).
5 Conclusions
In this editorial, we have discussed the many roles DI plays
in DSR, and we have shown that, in turn, DSR is ideally
positioned to make both research and practice contributions
to the field of digital innovation. Based on the DSR
knowledge consumption and production model, we have
derived six specific roles of DI in DSR: Understanding of
the DI Problem Space (Role 0), Design of a DI Technical
Artifact (Role 1), Design of an Artifact for Deployment and
Use of a DI Artifact (Role 2), Design of a Socio-Technical
DI System (Role 3), Development of Design Theories
Surrounding a DI Artifact (Role 4), Use of a DI Artifact as
a Creativity Tool in the DSR Solution Process (Role 5). We
have used these roles to characterize the five articles on DI
in DSR presented in this paper, and the papers, in turn,
illustrate the six roles we have introduced.
We very much invite fellow researchers to contribute to
the exciting research fields in the intersection between DI
and DSR, and we very much hope that this special issue
will give many examples of the manifold research
opportunities.
Acknowledgements We would like to cordially thank all colleagues
who have supported this special issue in roles of reviewers and edi-
tors. We highly appreciate the strong support of our community in
making this special issue happen.
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