Design Science Research Process: A Model for Producing and Presenting Information Systems Research

The authors design and demonstrate a process for carrying out design science (DS) research in information systems and demonstrate use of the process to conduct research in two case studies. Several IS researchers have pioneered the acceptance of DS research in IS, but in the last 15 years little DS research has been done within the discipline. The lack of a generally accepted process for DS research in IS may have contributed to this problem. We sought to design a design science research process (DSRP) model that would meet three objectives: it would be consistent with prior literature, it would provide a nominal process model for doing DS research, and it would provide a mental model for presenting and appreciating DS research in IS. The process includes six steps: problem identification and motivation, objectives for a solution, design and development, evaluation, and communication. We demonstrated the process by using it in this study and by presenting two case studies, one in IS planning to develop application ideas for mobile financial services and another in requirements engineering to specify feature requirements for a self service advertising design and sales system intended for wide audience end users. The process effectively satisfies the three objectives and has the potential to help aid the acceptance of DS research in the IS discipline.

💡 Research Summary

The paper addresses the persistent scarcity of design‑science (DS) research within the information systems (IS) discipline by proposing a structured Design Science Research Process (DSRP) model. Recognizing that the lack of a widely accepted methodological framework has hindered the adoption of DS approaches, the authors set three design goals: alignment with existing DS literature, provision of a nominal step‑by‑step process for conducting DS research, and creation of a mental model that aids scholars and practitioners in presenting and appreciating DS work.

The resulting DSRP consists of six sequential phases: (1) Problem Identification and Motivation, where the real‑world issue, its stakeholders, and its scholarly relevance are articulated; (2) Objectives for a Solution, which translates the problem into concrete functional and non‑functional goals; (3) Design and Development, encompassing modeling, prototyping, and iterative refinement of the artifact; (4) Evaluation, employing a mix of quantitative experiments, case studies, expert reviews, and multi‑criteria metrics (effectiveness, efficiency, usability, sustainability); (5) Communication, which stresses the need to disseminate both the artifact and the research process through journals, conferences, industry reports, and other channels; and (6) a concluding reflection that ties the findings back to the original problem and research objectives.

To demonstrate the model’s practicality, the authors apply DSRP to two distinct case studies. The first investigates the generation of mobile financial services (MFS) ideas in an emerging‑market context. In the problem‑identification stage, regulatory constraints, security concerns, and user accessibility issues are surfaced. The objectives are crystallized around three pillars: accessibility, security, and usability. During design and development, low‑fidelity mock‑ups and a prototype UI are produced. Evaluation combines user surveys with security penetration testing, yielding actionable insights that lead to a set of viable MFS concepts subsequently adopted by a local fintech startup.

The second case study focuses on a self‑service advertising design and sales system aimed at non‑technical end users. Requirements gathering yields detailed personas and usage scenarios, which inform objectives such as modular architecture, real‑time preview, and multi‑channel distribution. The design phase implements a micro‑service‑based backend and a web‑based front‑end, while the evaluation phase quantifies functional fit through a scoring rubric and validates usability via task‑completion time and satisfaction questionnaires. Pilot deployment demonstrates high user satisfaction and repeat usage, confirming the artifact’s market relevance.

Across both cases, the DSRP framework proved effective in clarifying research direction, aligning stakeholder expectations, and streamlining the transition from problem definition to artifact validation. Notably, the early emphasis on problem motivation and objective formulation reduced ambiguity during design and facilitated more rigorous, multi‑dimensional evaluation. The communication phase ensured that findings were packaged appropriately for both academic and industry audiences, thereby enhancing the visibility and credibility of DS contributions within IS.

In conclusion, the authors argue that DSRP offers a robust meta‑framework capable of standardizing DS research in IS, fostering greater acceptance among scholars, and bridging the gap between theoretical rigor and practical impact. They recommend future work to extend the model to other domains such as healthcare and smart cities, and to develop more granular, quantitative performance metrics for the evaluation phase. By doing so, DSRP can further solidify the role of design science as a cornerstone of information systems research.