This is a graduate-level text on design science research with a focus on information and communications technologies (ICT). It grew out of a doctoral research course on design research methodology and was shaped by the insights gained from the design science doctoral dissertations completed at the senior author’s university.
Just as the goal of any academic research is to develop and disseminate new knowledge about a phenomenon, the central aim in design research is the acquisition and dissemination of new knowledge through the building of artifacts. In design science research, the acquisition of new knowledge is structured around a design science research (DSR) cycle, and new knowledge is expressed as constructs, models, and frameworks in order to build theories. The focus on building theory shifts the center of attention from the artifact itself to structuring new knowledge into theory that explains the underlying phenomenon and/or predicts effects or behavior. For example, in the development of constructive cost models (COCOMO) models, statistical artifacts were designed to mine data on past projects in order to discover relationships between project size and project efforts or project duration. The knowledge gained was configured as a set of effort and duration calculation models. Extensive evaluation of these models resulted in COCOMO models for estimating effort, duration, and cost based on anticipated size of new projects. Barry Boehm’s work on COCOMO models is an example of design science research theory, which is called design-relevant explanatory/predictive theory (DREPT) in the text. Thus, unlike other empirical research methodologies in information systems research, design science research not only contributes new understanding and knowledge about a phenomenon, but also helps people fulfill specific needs through their use of design science theories.
The first part of the book introduces design science research methodology, the second part focuses on a wide array of design science research techniques that are captured as best practices patterns, and the third part unpacks exemplar design science research projects using the design science vocabulary and concepts introduced in Parts 1 and 2.
A unique contribution of this book is that it presents the procedural knowledge to perform design science academic research as a set of best practices patterns. These patterns are structured in six chapters: “Creativity Patterns,” “Problem Selection and Development Patterns,” “Literature Search Patterns,” “Suggestion and Development Patterns,” “Evaluation and Validation Patterns,” and “Publishing Patterns.” Since creativity, problem selection and development, literature search, and publishing patterns are relevant and integral parts of all academic research, this book is useful to anyone engaged in it.
My own past research would have benefited greatly if the patterns discussed in the book were part of my knowledge base of how effective academic research is conducted. In my opinion, this book is an ideal text for a design science research course and an excellent reference book for anyone engaged in academic research.
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