-------- Forwarded Message --------
Design science is a diverse research area that extends the
boundaries and
capabilities of individuals and organizations by designing,
building, and
evaluating new constructs, models, algorithms, methods, and
systems to
solve practical problems. It includes computational design
science,
optimization design science, representation design science, and
economics
design science, among others (Rai, 2017). While the different
streams of
design science paradigms have their different focal topics and
writing
styles, they together make significant contributions to the world
and
change the practice.
In particular, we witnessed the emergence (advance) of several
technologies
in recent years, such as artificial intelligence (AI), augmented
reality
(AR)/metaverse, blockchain/nft/distributed computing, cloud/edge
computing,
Internet of Things (IoTs), and cyber-physical system (CPS), which
has
afforded new possibilities as well as new concerns (e.g.,
fairness,
security, and privacy) for design science in various application
domains.
This calls for more grounded design science research that leads
and directs
the design, implementation, and evolution of contemporary IT
artifacts,
which would solve problems and improve the environment in which
they are
instantiated.
We thereby welcome a diversity of submissions that can produce
novel
theoretical knowledge, practical insights, and methodological
basis on
novel design science topics. The track seeks to synthesize broader
understandings in the diversity of all types of design science
studies, as
specified by Rai (2017).
Reference:
Arun Rai. 2017. “Editor’s Comments: Diversity of Design Science
Research,”
MIS Quarterly, (41: 1) pp.iii-xviii.
Potential Topics include (but are not limited to):
- Design theories and principles for emerging digital technologies
- Conceptual modeling, including big data modeling
- Innovate design of information systems
- Design of novel algorithms or models
- Design for innovative applications, such as AI, AR, IoT, etc.
- Modeling and optimization of IS design
- IT-enabled mechanism design
- Design for platforms and collaborative applications
- Design science research to solve IT use and user experience
issues
- Impact of design on individuals, organizations, and society
- Ethics in design science research
- Fairness, security, and privacy issues in design science
research
- AI behavior and human-computer interaction design
- Emerging methods for design science research
*Track Co-Chairs:*
- Xin Li (City University of Hong Kong),
Xin.Li@cityu.edu.hk
- Yidong Chai (Hefei University of Technology),
chaiyd@hfut.edu.cn
- Mohammad Jabbari (Université Laval),
mohammad.jabbari@fsa.ulaval.ca
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