Design Research in Information Systems

Since the dawn of the digital revolution, information technologies have changed the way we live, work, play, and entertain. Designers of IT-based digital technology products play a critical role in ensuring that their designed artifacts are not just beautiful but provide value to their users. Users are increasingly interacting with a digital world. Designing interactions in this new world is a challenging task. The experiences we have when we browse the web, or visit amazon.com, sell/buy stuff on eBay or play amusing games on our mobile cell phones do have a tremendous impact on how we live our lives. Designing information systems is even more challenging.

Design activities are central to most applied disciplines. Research in design has a long history in many fields including architecture, engineering, education, psychology, and the fine arts (Cross 2001). The computing and information technology (CIT) field since its advent in the late 1940s has appropriated many of the ideas, concepts, and methods of design science that have originated in these other disciplines. However, information systems (IS) as composed of inherently mutable and adaptable hardware, software, and human interfaces provide many unique and challenging design problems that call for new and creative ideas.

Science progresses because of advancement in theories. Dictionary definitions show that the word theory can take on many meanings, including “a mental view” or “contemplation,” “a concept or mental scheme of something to be done, or the method of doing it; a systematic statement of rules or principles to be followed,” a “system of ideas or statements held as an explanation or account of a group of facts or phenomena; a hypothesis that has been confirmed or established by observation or experiment and is propounded or accepted as accounting for the known facts; statements of what are held to be the general laws, principles, or causes of something known or observed,” a “mere hypothesis, speculation, conjecture” (Gregor 2006).

This essay discusses 12 theses for guiding design science research. They are aimed at strengthening the design science orientation of Information Systems, clarifying future discourses on design science research aspects of the discipline, and giving some further guidelines for design science research in Information Systems.

Future complex software-intensive systems (SIS) will be vastly different from the software systems that run today’s world. Revolutionary advances in hardware, networking, information, and human interface technologies will require entirely new ways of thinking about how software-intensive systems are conceptualized, built, and evaluated. As we envision the future of tera¹-computing and even peta²-computing environments, new science of design principles are needed to provide the foundations for managing issues of complexity, composition, quality, cost, and control of software-intensive systems.

Information technology design is by no means simple. Most real-world problems are not simple and they often have no correct solution. The challenges that everyday designers’ face is to handle trade-offs. It is the conscious choice among many alternatives each of which places constraints on utility and resources. As Mitch Kapor suggests above, a designer stands with one foot in the technology and one foot in the domain of human concerns, and these two worlds are not easily commensurable (Winograd 1996).

The design of software has been one of the greatest challenges in the development of information systems. From its fairly primitive beginnings in the form of toggling on/off switches and punching holes in paper tapes, software has come to dominate the cost of all forms of information systems. Yet, instead of gaining increasing mastery over the processes of software design, we continue to be challenged by new software technologies, greater quality expectations, and higher complexities of integrated systems. Thus, software design remains an essentially wicked problem that is typically crafted to each software-intensive system developed.

Evaluation is a key element in the design of IT-based artifacts. A designer finds a suitable and interesting problem to solve. Then they come up with design solutions. That is followed by the actual build phase. After they have built the artifact, the next phase is evaluating for efficiency, utility, or performance.

Evaluation is a crucial component in the design science research process. The designed IT artifact is a socio-technical entity that exists within an environment (business or social) which lays out the requirements for its evaluation. Such evaluation of IT artifacts requires definition of appropriate metrics and possibly the gathering and analysis of appropriate data. IT artifacts can be evaluated in terms of functionality, completeness, consistency, accuracy, performance, reliability, usability, fit with the organization, and other relevant quality attributes (Hevner, March et al. 2004).

In this chapter, it is our goal to help the reader understand the different issues, questions, methods, and techniques that arise when one does evaluation. To present a full detailed analysis of various techniques is beyond the scope of this chapter or the book, but we hope that the reader will learn to ask the right questions, know when to apply which technique and be confident to look at the right places for more answers.

Abraham Maslow once said “The key question isn’t ‘What fosters creativity?’ But it is why in God’s name isn’t everyone creative? Where was the human potential lost? How was it crippled? I think therefore a good question might be not why do people create? But why do people not create or innovate? We have got to abandon that sense of amazement in the face of creativity, as if it were a miracle if anybody created anything.”

Every designer is creative. In the world of software design, we also create artifacts. Where does this creativity come from? What exactly is meant to be creative? In this chapter we explore questions such as these. We also take a brief look at the creativity literature and discuss how information technology tools can help humans become more creative and vice versa.

As with all species, humans spend their life in competition. Unlike other organisms, we carry this competitive drive past mere survival and reproduction into the structures of our social and business life. The structures of our business environment revolve around the ability of an organization to obtain long-term competitiveness through the control of rare and valuable resources that have limited substitutability, mobility, and imitability (Barney, 1991, Peteraf, 1993). Knowledge is precisely such a rare and valuable resource and does add greatly to an organization’s ability to sustain competitiveness (Alavi and Leidner, 2001, Kogut and Zander, 1992, Argote and Ingram, 2000).

IS research has been criticized for having little influence on practice. One approach to achieving more relevance is to conduct research using appropriate research methods that balance the interests of both researchers and practitioners. This chapter examines the similarities between two methods that address this mandate by adopting a proactive stance to investigating information systems in organizations. These two approaches, action research and design research, both directly intervene in “real-world” domains and effect changes in these domains. We investigate these similarities by examining exemplars of each type of research according to the criteria of the other. Our analysis reveals interesting parallels and similarities between the two suggesting that the two approaches have much to learn from each other. Based on our analysis, we propose ways to facilitate integration of the two approaches that we believe will be useful for both and for IS research in general.

Design science and natural science are complementary research paradigms in the management disciplines. Fundamentally the task of management is to develop, articulate, and achieve organizational goals and purposes. Design science research addresses that task by creating novel and effective artifacts that are demonstrated to improve managers’ capability to change “existing situations into preferred ones” (Simon (1996), p. 130). Natural science research addresses it by developing theories that provide deep, principled explanations of phenomena, justified by rigorous empirical evidence that managers can use to guide their actions. Designed artifacts have no special dispensation from the laws of nature; however, business organizations and the environments in which they operate are social constructions (Searle, J. R. (2006) Social ontology: some basic principles, Anthropological Theory 6 (1), pp. 12–29). They are themselves artifacts designed to achieve human goals, purposes, and intentions, influenced by and operating within the context of emergent and intentional human behavior. Furthermore, natural science explanations of how or why an artifact works or does not work may lag years behind the application of the artifact. If academic research is to make significant contributions to management practice it must utilize the results from each paradigm to guide the other. There is evidence that this integration is beginning to take place in several management disciplines including information systems and organizational science. This paper summarizes and assesses this emerging work.

Information systems (IS) research has serious utilization and relevance problems. To increase IS research utilization and relevance, scholars argue that the dominating behavioral IS research paradigm should be complemented with IS design science research. The most influential IS design science research schools have a strong focus on the IT artifact, in most cases an exclusive focus on the IT artifact. The schools have very little discussions and clarifications regarding underpinning philosophies, but most seem to be based on positivism, traditional realism, or pragmatism. This chapter presents, as a complement to the most influential design science research schools, an alternative approach for IS design science research. The approach builds on the premise that one of the most critical aims of IS design science research is to develop practical knowledge for the design and realization of different classes of IS initiatives, where IS are viewed as socio-technical systems and not just IT artifacts. The underpinning philosophy of the approach is critical realism which has been developed as an alternative to positivism and traditional realism as well as to constructivism (relativism). The developed practical IS design knowledge can be represented in different forms, for example, as heuristic design propositions, design exemplars and patterns, models or frameworks, and stories or narratives. The IS design knowledge can be developed using different methods and techniques. The chapter presents how practical IS design knowledge can be developed as well as the nature of the developed knowledge.

There has been a gigantic shift from a product-based economy to one based on services, specifically digital services. From every indication it is likely to be more than a passing fad and the changes these emerging digital services represent will continue to transform commerce and have yet to reach market saturation. Digital services are being designed for and offered to users, yet very little is known about the design process that goes behind these developments. Is there a science behind designing digital services? By examining 13 leading digital services, we have developed a design taxonomy to be able to classify and contrast digital services. What emerged in the taxonomy were two broad dimensions: a set of fundamental design objectives and a set of fundamental service provider objectives. This chapter concludes with an application of the proposed taxonomy to three leading digital services. We hope that the proposed taxonomy will be useful in understanding the science behind the design of digital services.

As you near the completion of a design science research project, your thoughts are now diverted to what to do next? Every researcher wants to publish their finding to the scientific community and in particular to their peer group. While academic publishing is certainly a preferred outcome of DSR, we would also like to mention that another possible (and lucrative) outcome of DSR is entrepreneurial activity for those who have the mindset. If you have built it, let them come.

As experienced researchers, and editors in the field, we share with the readers the challenges and issues of writing papers for leading conference and journals. In that context, we also briefly discuss getting funds from foundation to support your research. We also discuss the necessary first steps toward commercializing DSR by building a start-up company around the project artifact.

The previous chapters have taken you through the fundamentals of design science research, the problems, solutions space, design process, frameworks, outputs and artifacts, theories and dissemination of the research results. The design science research paradigm is highly relevant to information systems (IS) research because it directly addresses two of the key issues of the discipline: the central, albeit controversial, role of the IT artifact in IS research (Weber 1987; Orlikowski and Iacono 2001; Benbasat and Zmud 2003) and the lack of professional relevance of IS research (Benbasat and Zmud 1999; Hirschheim and Klein 2003). Design science, as conceptualized by Simon (1996), supports a pragmatic research paradigm that calls for the creation of innovative artifacts to solve real-world problems. Thus, design science research combines a focus on the IT artifact with a high priority on relevance in the application domain.