Design Science Research In Information Systems Research Articles

A set of ethical principles for design science research in information systems

Over the past decade, design science research (DSR) has re-emerged as an important research paradigm in the field of information systems. However, the approaches currently recommended for conducting design science research do not include an ethical component. Thus, the objective of this paper is to initiate a debate about the need for ethical principles for DSR in Information Systems (IS). To launch this debate, we suggest that a set of ethical principles for DSR in IS must be created. Although the interpretation and application of these principles might not always be straightforward, our argument is that all DSR practitioners in IS should devote at least some time to consider ethical principles.

Application Strategies for Neuroscience in Information Systems Design Science Research

Design science has evolved as a major research paradigm in the information systems (IS) discipline, which aims to design innovative and useful IT artifacts, such as conceptual models and software systems. Despite the increasing attention paid to the cognitive and emotional mechanisms that underlie the perception of such artifacts, research that explores the neurobiological determinants of these mechanisms has only recently begun to emerge. The primary argument for the use of neurobiological approaches in IS design science research is that IT artifact design — and, ultimately, human-computer interaction in general — may significantly benefit from neuroscience theories, concepts, methods, and data. In particular, the consideration of neuroscience may improve IT artifacts' alignment with users' perceptual and information processing mechanisms, particularly the brain. Against this background, this article presents a taxonomy of application strategies for neuroscience in IS design science research. It describes three major areas of application and explains that conducting research in an area comes with a specific set of requirements (e.g., applicability, costs, accessibility, and knowledge relevant to planning and conducting a research project). Therefore, if an IS design science scholar decides to draw upon neuroscience, the taxonomy transparently explains possible working areas and corresponding requirements. The taxonomy is described based on example studies published in the IS literature and on contributions that appeared in outlets pertaining to related disciplines, such as affective computing and neuroergonomics. The article concludes that, if neuroscience is considered a valuable complement to the more traditional approaches, it has the potential to become a major reference discipline for IS design science research.

A Framework for Theory Development in Design Science Research: Multiple Perspectives

One point of convergence in the many recent discussions on design science research in information systems (DSRIS) has been the desirability of a directive design theory (ISDT) as one of the outputs from a DSRIS project. However, the literature on theory development in DSRIS is very sparse. In this paper, we develop a framework to support theory development in DSRIS and explore its potential from multiple perspectives. The framework positions ISDT in a hierarchy of theories in IS design that includes a type of theory for describing how and why the design functions: Design-relevant explanatory/predictive theory (DREPT). DREPT formally captures the translation of general theory constructs from outside IS to the design realm. We introduce the framework from a knowledge representation perspective and then provide typological and epistemological perspectives. We begin by motivating the desirability of both directive-prescriptive theory (ISDT) and explanatory-predictive theory (DREPT) for IS design science research and practice. Since ISDT and DREPT are both, by definition, mid-range theories, we examine the notion of mid-range theory in other fields and then in the specific context of DSRIS. We position both types of theory in Gregor’s (2006) taxonomy of IS theory in our typological view of the framework. We then discuss design theory semantics from an epistemological view of the framework, relating it to an idealized design science research cycle. To demonstrate the potential of the framework for DSRIS, we use it to derive ISDT and DREPT from two published examples of DSRIS.

Design Science in Information Systems Research

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.