Design Science Research
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Design Science Research
Consolidating existing knowledge in Design Science, this book proposes a new research method to aid the exploration of design and problem solving within business, science and technology. It seeks to overcome a dichotomy that exists in the field between theory and practice to enable researches to find solutions to problems, rather than focusing on the explanation and exploration of the problems themselves. Currently, researches concentrate on to describing, exploring, explaining and predicting phenomena, and little attention is devoted to prescribing solutions. Herbert Simon proposes the need to develop a Science of the Artificial (Design Science), arguing that our reality is much more artificial than natural. However, the research conducted on the Design Science premises has so far been scattered and erratic in different fields of research, such as management, systems information and engineering. This book aims to address this issue by bringing these fields together and emphasising the need for solutions. This book provides a valuable resource to students and researchers of research methods, information systems, management and management science, and production and operations management.
Design Science Research. Cases
Design Science Research is a powerful paradigm enabling researchers to make important contributions to society and industry. Simply stated, the goal of DSR is to generate knowledge on how to find innovative solutions to important problems in the form of models, methods, constructs and instantiations. Over the past 20 years, the design science research (DSR) paradigm has developed into an established paradigm in Information Systems Research and it is of strong uptake in many other disciplines, including Management Science and Computer Science. This book provides a collection of twelve DSR cases, presented by experienced researchers in the field. It offers readers access to real-world DSR studies, together with the authors’ reflections on their research processes. These cases will support researchers who want to engage in DSR, and represent a valuable addition to existing introductions to DSR methods and processes. Readers will learn from the hands-on experiences of respected experts who have conducted extensive DSR in a range of application contexts.
Design Science Methodology for Information Systems and Software Engineering
This book provides guidelines for practicing design science in the fields of information systems and software engineering research. A design process usually iterates over two activities: first designing an artifact that improves something for stakeholders and subsequently empirically investigating the performance of that artifact in its context. This “validation in context” is a key feature of the book - since an artifact is designed for a context, it should also be validated in this context. The book is divided into five parts. Part I discusses the fundamental nature of design science and its artifacts, as well as related design research questions and goals. Part II deals with the design cycle, i.e. the creation, design and validation of artifacts based on requirements and stakeholder goals. To elaborate this further, Part III presents the role of conceptual frameworks and theories in design science. Part IV continues with the empirical cycle to investigate artifacts in context, and presents the different elements of research problem analysis, research setup and data analysis. Finally, Part V deals with the practical application of the empirical cycle by presenting in detail various research methods, including observational case studies, case-based and sample-based experiments and technical action research. These main sections are complemented by two generic checklists, one for the design cycle and one for the empirical cycle. The book is written for students as well as academic and industrial researchers in software engineering or information systems. It provides guidelines on how to effectively structure research goals, how to analyze research problems concerning design goals and knowledge questions, how to validate artifact designs and how to empirically investigate artifacts in context – and finally how to present the results of the design cycle as a whole.