- freely available
Systems 2019, 7(2), 27; https://doi.org/10.3390/systems7020027
- Computational Genre:
- This class of DSR research stresses an interdisciplinary approach in developing artifacts such as data representations, algorithms e.g., machine learning algorithms, analytics methods, and human–computer interaction (HCI) innovations.
- Optimization Genre:
- This class of DSR research looks at the creation of IT artifacts that are intended to solve organizational problems such as: maximizing profits, utilities, welfare, etc. Additionally, it falls under the optimization of supply chain activities, internal operations, customer relationship management activities (e.g., the effective use of personalization technologies), and pricing decisions (e.g., price discrimination strategies enabled by analytics).
- Representation Genre:
- This class of DSR research contributes by evaluating and refining existing modeling grammar or methods, the design of new modeling grammar or methods, the development of software artifacts to support or instantiate such work, or the evaluation of these efforts using analytical methods. Such contributions face challenges from philosophy, linguistics, and psychology that unavoidably occur when experimenting representations.
- IS Economics Genre:
- This class of DSR research contributes by developing and refining models and algorithms that focus on the role of IS to solve problems related to the conduct of economic activities and attainment of objectives of an economic system. Additionally, the discovery and characterization of behaviors of economic participants. The instantiation of models and algorithms into software, technology platforms, and other artifacts. Lastly, the evaluation of the validity of causal mechanisms and the utility of solutions. This class mainly focuses on unfolding the relationship between IS and the design of economic systems.
2. Design Science Research
- If the DSR aims to develop design theories, then hypotheses proposed could be tested via experiments, conceptually, or instantiated-oriented;
- In case DSR aims to design an artefact, system, or method, then demonstration is an acceptable evaluation mechanism;
- Design oriented research could utilize lab experiments, pilot testing, simulations, expert reviews, and field experiments;
- Explanatory design, on the other hand, could be evaluated via hypothesis testing and experimental setup;
- Actions design research views design and evaluation as sequential. That is, they look at one process where organizational intervention and evaluation are required.
4. Big Data Analytics
5. Evaluation in the Lens of BDA
- What kind of data [or datasets] about the world are available to a data scientist or researcher?
- How can these data [sets] be represented?
- What rules govern conclusions to be drawn from these datasets?
- How to interpret such a conclusion?
Conflicts of Interest
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