Self-reporting Limitations in Information Systems Design Science Research
Abstract
Besides increasing transparency and demonstrating awareness of the author, self-reported limitations enable other researchers to effectively learn from, build on, validate, and extend the original work. However, this topic is understudied in information systems design science research (IS DSR). The study has assessed 243 IS DSR papers published in the period 2013–2022 and built a typology of the 19 most relevant limitations, organized into four categories: (1) Input Knowledge and Technology, (2) Research Process, (3) Resulting Artifact, and (4) Design Knowledge. Further, the contribution suggests actions to mitigate each type of limitation throughout the entire IS DSR project lifecycle. The authors have also created guidelines to report the limitations in a useful way for knowledge accumulation. The proposed typology and guidelines enable reviewers and editors to better frame self-reported limitations, assess rigor and relevance more systematically, and provide more precise feedback. Moreover, the contribution may help design researchers identify, mitigate, and effectively communicate the uncertainties inherent to all scientific advances.
- Citation
- BibTeX
Barata, J., Cunha, P. R. & Figueiredo, A. D.,
(2023).
Self-reporting Limitations in Information Systems Design Science Research.
Business & Information Systems Engineering: Vol. 65, No. 2.
Springer.
(S. 143-160).
DOI: 10.1007/s12599-022-00782-8
@article{mci/Barata2023,
author = {Barata, João AND Cunha, Paulo Rupino AND Figueiredo, António Dias},
title = {Self-reporting Limitations in Information Systems Design Science Research},
journal = {Business & Information Systems Engineering},
volume = {65},
number = {2},
year = {2023},
,
pages = { 143-160 } ,
doi = { 10.1007/s12599-022-00782-8 }
}
author = {Barata, João AND Cunha, Paulo Rupino AND Figueiredo, António Dias},
title = {Self-reporting Limitations in Information Systems Design Science Research},
journal = {Business & Information Systems Engineering},
volume = {65},
number = {2},
year = {2023},
,
pages = { 143-160 } ,
doi = { 10.1007/s12599-022-00782-8 }
}
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ISSN: 1867-0202
xmlui.MetaDataDisplay.field.date: 2023
Content Type: Text/Journal Article