Paper Number
1390
Paper Type
Complete Research Paper
Abstract
In several design science research (DSR) frameworks and methods, the need for generalising problems and solutions has been emphasised. For example, various DSR studies present generalised design principles as nascent theories. Due to the creative and contextual nature of DSR, several scholars report that generalisation can be challenging. The challenge is particularly valid for single qualitative studies because the design of an artefact always reflects the circumstances in the context where it is to be used. Therefore, the purpose of this study is to present guidelines regarding generalisation. The suggested guidelines are: strategically plan the generalisation process, validate the generalised knowledge to augment the reusability and find an appropriate generalisation level. The formulation of the guidelines is based on the analyses of three DSR projects and insights from previous knowledge. Our knowledge contribution consists of prescriptive knowledge (guidelines) as a complement to existing explanative and descriptive knowledge.
Recommended Citation
Cronholm, Stefan; Sjöström, Jonas; Göbel, Hannes; and Juell-Skielse, Gustaf, "Generalisation of Design Science Research" (2024). ECIS 2024 Proceedings. 6.
https://aisel.aisnet.org/ecis2024/track23_designresearch/track23_designresearch/6
Generalisation of Design Science Research
In several design science research (DSR) frameworks and methods, the need for generalising problems and solutions has been emphasised. For example, various DSR studies present generalised design principles as nascent theories. Due to the creative and contextual nature of DSR, several scholars report that generalisation can be challenging. The challenge is particularly valid for single qualitative studies because the design of an artefact always reflects the circumstances in the context where it is to be used. Therefore, the purpose of this study is to present guidelines regarding generalisation. The suggested guidelines are: strategically plan the generalisation process, validate the generalised knowledge to augment the reusability and find an appropriate generalisation level. The formulation of the guidelines is based on the analyses of three DSR projects and insights from previous knowledge. Our knowledge contribution consists of prescriptive knowledge (guidelines) as a complement to existing explanative and descriptive knowledge.
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