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Open AccessConcept Paper

Design Science Research: Evaluation in the Lens of Big Data Analytics

1
Department of Computer Science, Electrical and Space Engineering, Computer and Systems Science, Luleå University of Technology, 97187 Luleå, Sweden
2
Department of Technology, Kristiania University College, 0186 Oslo, Norway
*
Author to whom correspondence should be addressed.
Systems 2019, 7(2), 27; https://doi.org/10.3390/systems7020027
Received: 27 February 2019 / Revised: 7 May 2019 / Accepted: 17 May 2019 / Published: 28 May 2019
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Abstract

Given the different types of artifacts and their various evaluation methods, one of the main challenges faced by researchers in design science research (DSR) is choosing suitable and efficient methods during the artifact evaluation phase. With the emergence of big data analytics, data scientists conducting DSR are also challenged with identifying suitable evaluation mechanisms for their data products. Hence, this conceptual research paper is set out to address the following questions. Does big data analytics impact how evaluation in DSR is conducted? If so, does it lead to a new type of evaluation or a new genre of DSR? We conclude by arguing that big data analytics should influence how evaluation is conducted, but it does not lead to the creation of a new genre of design research. View Full-Text
Keywords: DSR; big data analytics; evaluation DSR; big data analytics; evaluation
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Elragal, A.; Haddara, M. Design Science Research: Evaluation in the Lens of Big Data Analytics. Systems 2019, 7, 27.

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