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Design science in information systems research

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TLDR
The objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research.
Abstract
Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact Three recent exemplars in the research literature are used to demonstrate the application of these guidelines We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community

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Journal ArticleDOI

A Design Science Research Methodology for Information Systems Research

TL;DR: The designed methodology effectively satisfies the three objectives of design science research methodology and has the potential to help aid the acceptance of DS research in the IS discipline.
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Business intelligence and analytics: from big data to big impact

TL;DR: This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A, and introduces and characterized the six articles that comprise this special issue in terms of the proposed BI &A research framework.
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The nature of theory in information systems

TL;DR: The essay addresses issues of causality, explanation, prediction, and generalization that underlie an understanding of theory, and suggests that the type of theory under development can influence the choice of an epistemological approach.
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Positioning and presenting design science research for maximum impact

TL;DR: This essay aims to help researchers appreciate the levels of artifact abstractions that may be DSR contributions, identify appropriate ways of consuming and producing knowledge when they are preparing journal articles or other scholarly works, and understand and position the knowledge contributions of their research projects.
References
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Book

The Structure of Scientific Revolutions

TL;DR: The Structure of Scientific Revolutions as discussed by the authors is a seminal work in the history of science and philosophy of science, and it has been widely cited as a major source of inspiration for the present generation of scientists.
Book

The Sciences of the Artificial

TL;DR: A new edition of Simon's classic work on artificial intelligence as mentioned in this paper adds a chapter that sorts out the current themes and tools for analyzing complexity and complex systems, taking into account important advances in cognitive psychology and the science of design while confirming and extending Simon's basic thesis that a physical symbol system has the necessary and sufficient means for intelligent action.
Journal ArticleDOI

Information Systems Success: The Quest for the Dependent Variable

TL;DR: A large number of studies have been conducted during the last decade and a half attempting to identify those factors that contribute to information systems success, but the dependent variable in these studies-I/S success-has been an elusive one to define.
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