A comparative analysis of methodological adoption, adaptation and implementation of design science research (DSR) across engineering disciplines

Purpose This paper examines how Design Science Research (DSR) frameworks are adopted, adapted and implemented across six engineering disciplines comparing framework selection, artefact types, evaluation methods, success factors, implementation challenges and cross-disciplinary methodological innovations. Design/methodology/approach A systematic literature review covered 406 papers published between 2015 and 2025. Following PRISMA 2020 guidelines, searches across seven databases identified 30 papers representing Software/Computer, Manufacturing/Industrial, Construction/Civil, Biomedical/Healthcare, Environmental/Socio-Environmental, and Mechanical/Aerospace Engineering disciplines. Data extraction used a structured template with dual independent coding across framework adoption patterns, artefact types, evaluation methods, success factors, and implementation challenges. Findings Disciplinary variation reveals an inverse relationship between framework standardisation and domain complexity: software engineering demonstrates highest standardisation through Peffers et al. (2007) DSRM, whilst manufacturing, healthcare and environmental engineering develop custom frameworks addressing distinctive requirements. Five universal success factors are identified: stakeholder engagement, iterative design, mixed evaluation methods, expert validation and clear benchmarks. Boundary conditions for each factor are documented. Cross-disciplinary innovations include echeloned DSR, Design-Develop-Decide, FAIR principles and statistical consensus methods. Originality/value This study provides the first systematic cross-disciplinary comparison of DSR adoption across six engineering disciplines, providing empirical grounding for the inverse relationship between domain complexity and framework standardisation, alongside evidence-based guidance for framework selection, evaluation design and challenge mitigation.

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Publication Details

Journal
International Journal of Industrial Engineering and Operations Management
Published
2026-06-24
DOI
https://doi.org/10.1108/ijieom-01-2026-0015
Primary Topic
Information Systems Theories and Implementation
Type
article
Field-Weighted Citation Impact
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article

A comparative analysis of methodological adoption, adaptation and implementation of design science research (DSR) across engineering disciplines

Mustapha Munir, Alex Mbabu, Ali Saad, Jason Underwood
International Journal of Industrial Engineering and Operations Management
Information Systems Theories and Implementation
article

A comparative analysis of methodological adoption, adaptation and implementation of design science research (DSR) across engineering disciplines

Mustapha Munir, Alex Mbabu, Ali Saad, Jason Underwood
article en

Abstract

Purpose This paper examines how Design Science Research (DSR) frameworks are adopted, adapted and implemented across six engineering disciplines comparing framework selection, artefact types, evaluation methods, success factors, implementation challenges and cross-disciplinary methodological innovations. Design/methodology/approach A systematic literature review covered 406 papers published between 2015 and 2025. Following PRISMA 2020 guidelines, searches across seven databases identified 30 papers representing Software/Computer, Manufacturing/Industrial, Construction/Civil, Biomedical/Healthcare, Environmental/Socio-Environmental, and Mechanical/Aerospace Engineering disciplines. Data extraction used a structured template with dual independent coding across framework adoption patterns, artefact types, evaluation methods, success factors, and implementation challenges. Findings Disciplinary variation reveals an inverse relationship between framework standardisation and domain complexity: software engineering demonstrates highest standardisation through Peffers et al. (2007) DSRM, whilst manufacturing, healthcare and environmental engineering develop custom frameworks addressing distinctive requirements. Five universal success factors are identified: stakeholder engagement, iterative design, mixed evaluation methods, expert validation and clear benchmarks. Boundary conditions for each factor are documented. Cross-disciplinary innovations include echeloned DSR, Design-Develop-Decide, FAIR principles and statistical consensus methods. Originality/value This study provides the first systematic cross-disciplinary comparison of DSR adoption across six engineering disciplines, providing empirical grounding for the inverse relationship between domain complexity and framework standardisation, alongside evidence-based guidance for framework selection, evaluation design and challenge mitigation.

International Journal of Industrial Engineering and Operations Management
University of Salford (GB)
Openalex Percentile: Top 4%
Information Systems Theories and Implementation
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