The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
On theory development in design science research: anatomy of a research project
Abstract
The common understanding of design science research in information systems (DSRIS) continues to evolve. Only in the broadest terms has there been consensus: that DSRIS involves, in some way, learning through the act of building. However, what is to be built – the definition of the DSRIS artifact – and how it is to be built – the methodology of DSRIS – has drawn increasing discussion in recent years. The relationship of DSRIS to theory continues to make up a significant part of the discussion: how theory should inform DSRIS and whether or not DSRIS can or should be instrumental in developing and refining theory. In this paper, we present the exegesis of a DSRIS research project in which creating a (prescriptive) design theory through the process of developing and testing an information systems artifact is inextricably bound to the testing and refinement of its kernel theory.
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Citations
Cites
The Framing of Decisions and the Psychology of Choice
Tversky, A., & Kahneman, D. (1981) · Science · doi:10.1126/science.7455683 · Cited by 18,497
Design Science in Information Systems Research1
Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004) · MIS Quarterly · doi:10.2307/25148625 · Cited by 10,707
Design science in information systems research
(2004) · Journal of the Association for Information Systems · doi:10.5555/2017212.2017217 · Cited by 8,254
The Nature of Theory in Information Systems1
Gregor, S. (2006) · MIS Quarterly · doi:10.2307/25148742 · Cited by 3,306
Cited by
Design science research contributions: Finding a balance between artifact and theory
Georgia State University, Baskerville, R., Baiyere, A., University of Turku, F., Gergor, S., Australian National University, Hevner, A., University of South Florida, Rossi, M., & Aalto University (2018) · Journal of the Association for Information Systems · doi:10.17705/1jais.00495 · Cited by 437
Designing a feature selection method based on explainable artificial intelligence
Zacharias, J., von Zahn, M., Chen, J., & Hinz, O. (2022) · Electronic Markets · doi:10.1007/s12525-022-00608-1 · Cited by 109
University of Sydney, Seymour, M., Riemer, K., University of Sydney, Kay, J., & University of Sydney (2018) · Journal of the Association for Information Systems · doi:10.17705/1jais.00515 · Cited by 77
Lins, S., Schneider, S., Szefer, J., Ibraheem, S., & Ali, A. (2019) · Communications of the Association for Information Systems · doi:10.17705/1cais.04425 · Cited by 26
Monson, M. (2023) · European Journal of Information Systems · doi:10.1080/0960085x.2021.1946442 · Cited by 21
Metadata
- Authors
- Kuechler, B., & Vaishnavi, V.
- Venue
- European Journal of Information Systems
- Publisher
- Informa UK Limited
- Published
- 2008-10
- Volume
- 17
- Issue
- 5
- Pages
- 489-504
- ISSN
- 0960-085X (ISSN-L)
- 1476-9344
- OpenAlex
- W2012594940
- Cited by
- 631
- References
- 4
- FWCI
- 81.31
- Type
- journal article
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
