Description

This Master Prompt establishes a comprehensive framework for strengthening the governance, transparency, ethical integrity, stakeholder participation, implementation quality and reproducibility of Design Science Research investigations. It examines the relationships among research governance, methodological accountability, artifact development decisions, stakeholder involvement, research ethics, data management, technological responsibility and scientific credibility. Particular emphasis is placed on ensuring that Design Science Research processes remain transparent, traceable, ethically defensible and reproducible throughout problem identification, requirements analysis, artifact conceptualization, design development, demonstration, evaluation and research communication. The framework integrates research transparency principles, responsible innovation, participatory design, stakeholder co-creation, design ethics, project governance, risk management, data protection, cybersecurity governance, quality assurance and research reporting standards. Researchers are guided in developing governance frameworks, documenting design decisions, establishing stakeholder responsibilities, designing ethical evaluation protocols, managing research risks, recording artifact development iterations and implementing procedures for methodological verification. The Master Prompt addresses informed consent, privacy protection, fairness, accessibility, algorithmic accountability, stakeholder conflicts, research integrity, intellectual property, implementation risk, data provenance and the responsible use of Artificial Intelligence. It also examines the relationships among artifact documentation, design rationale, evaluation transparency, replication materials, methodological consistency and independent verification of research findings. Researchers are guided in developing governance matrices, stakeholder engagement frameworks, risk assessment tables, ethical decision models, artifact traceability diagrams, reproducibility checklists and research quality assurance frameworks. Particular attention is given to distinguishing documented design decisions from retrospective explanations, ensuring that reported evaluation outcomes correspond to authentic research evidence, and preventing unsupported claims regarding artifact effectiveness, generalizability or scientific novelty. The framework supports the development of trustworthy Design Science Research practices that preserve scientific rigor while enabling responsible technological innovation and stakeholder-centered problem solving.