Academic journal article Electronic Journal of Business Research Methods

Design Science Research: The Case of the IT Capability Maturity Framework (IT CMF)

Academic journal article Electronic Journal of Business Research Methods

Design Science Research: The Case of the IT Capability Maturity Framework (IT CMF)

Article excerpt

1. Introduction

"What is design? Its where you stand with a foot in two worlds - the world of technology and the world of people and human purposes - and you try to bring the two together" (Kapor (1990) in Hevner and Chatterjee, 2010).

Design Science research is centered on building and evaluating artifacts in order to solve organisational problems. Much has been written about the research paradigm in other disciplines - its roots lie in engineering and the "sciences of the artificial" (Simon, 1996). Since the early 1990's, DS has been recognised as important in the Information Systems (IS) field in increasing an IT artifact's utility and effectiveness for solving complex business problems (Hevner and Chatterjee, 2010; Peffers et al, 2007). Over the past 15 years, IS DS research has been at best sporadic (Peffers et al, 2007; Walls et al, 2004) and publication in IS journals remains problematic (March and Storey, 2008). Despite this, Hevner and Chatterjee (2010) state that the IS field has witnessed a "flurry of recent activity" on the use of DS research.

This paper adds to the body of DS research in the IS field. It aims to establish the value of using a DS approach in the development of an IT Capability Maturity Framework (IT CMF) that seeks to help organisations to better manage and deliver value from their IT investments. The IT CMF focuses on four integrated strategies and 32 associated critical processes against which the IT organisation's level of maturity can be assessed according to five levels. The project has followed the DS research paradigm; this paper discusses its development in terms of key DS principles and concludes with a discussion of how this research approach has been of benefit.

The structure of this paper is as follows: Section two discusses the need for DS research in IS to complement the currently predominant behavioral science paradigm, so that the type of organisational problems that demand innovative and creative solutions can be addressed. Section Three summarises key principles drawn from seminal DS articles that underpin DS research projects. Section four provides an overview of the IT CMF project and discusses the DS approach to its content development in terms of Hevner's (2007) three DS cycles. Section five discusses the challenges and benefits associated with DS and draws conclusions to the research.

2. The need for design science research in IS

Both behavioural science and design science research paradigms are foundational to the IS discipline, which is positioned "at the confluence of people, organisations and technology" (Hevner et al, 2004). However, the prevalent research paradigm in the IS field to date has been behavioral science research (Hevner and Chatterjee, 2010). The objective of the behavioral science paradigm, which has its roots in natural science research methods, is problem understanding through developing and verifying theories on human and/or organisational phenomena that explain what happened, why it happened, and perhaps what will happen in a given context (March and Smith, 1995; March and Storey, 2008; Pries-Heje and Baskerville, 2008). March and Storey (2008) suggest that a typical question in this stream of IS research is "Why do investments in IT artifacts often not result in an increase in firm's value?" Its two key activities are regarded as discovery (i.e. generating new scientific claims such as theories or laws) and justification (i.e. testing such claims for validity) (March and Smith, 1995); the research output in such studies is often explanatory in nature (Peffers et al, 2007). March and Smith (1995) provide the following explanation:

"Natural scientists develop sets of concepts, or specialized language, with which to characterize phenomena. These are used in higher order constructions - laws, models, and theories - that make claims about the nature of reality. Theories - deep, principled explanations of phenomena - are the crowning achievements of natural science research. …

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