Paper Number
ICIS2025-2590
Paper Type
Short
Abstract
Iivari, Hansen, and Haj-Bolouri’s 2018 framework for the reusability of design principles was a significant step toward defining a dependent variable specific to design science research. While the framework has been adopted in various studies as a basis for qualitative evaluations, validation tests reveal that it requires further refinement to serve as a valid scale for evaluating the reusability of DPs. This paper presents the results of statistical validity tests on the framework used as a post-treatment survey. This analysis shows many overlapping constructs and potential Kelley’s Jingle and Jangle fallacies. We propose a questionnaire adopted from this framework to be used as a scale for reusability. Also, we added knowledge alignment and impact, and one extra layer for accessibility to enhance the framework’s predictive power for reusability of design principles.
Recommended Citation
Nabavian, Sanaz; Parsons, Jeffrey; and Ogunseye, Shawn, "Scale development for measuring design principle Reusability" (2025). ICIS 2025 Proceedings. 17.
https://aisel.aisnet.org/icis2025/isdesign/isdesign/17
Scale development for measuring design principle Reusability
Iivari, Hansen, and Haj-Bolouri’s 2018 framework for the reusability of design principles was a significant step toward defining a dependent variable specific to design science research. While the framework has been adopted in various studies as a basis for qualitative evaluations, validation tests reveal that it requires further refinement to serve as a valid scale for evaluating the reusability of DPs. This paper presents the results of statistical validity tests on the framework used as a post-treatment survey. This analysis shows many overlapping constructs and potential Kelley’s Jingle and Jangle fallacies. We propose a questionnaire adopted from this framework to be used as a scale for reusability. Also, we added knowledge alignment and impact, and one extra layer for accessibility to enhance the framework’s predictive power for reusability of design principles.
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