外文翻译
原文
Design Science in Information Systems Research
Material Source: Publication in MIS Quarterly
Author: Alan R．Hevner、Salvatore T．March、Jinsoo Park、Sudha Ram
1. INTRODUCTl0N
Information systems are implemented within an organization for the purpose of improving the effectiveness and efficiency of that organization. Capabilities of the information system and characteristics of the organization, its work systems, its people, and its development and implementation methodologies together determine the extent to which that purpose is achieved (Silver et al. 1995). It is incumbent upon researchers in the Information Systems (IS) discipline to “further knowledge that aids in the productive application of information technology to human organizations and their management” (ISR 2002, inside front cover) and to develop and communicate “knowledge concerning both the management of information technology and the use of information technology for
managerial and organizational purposes” (Z mud 1997).
We argue that acquiring such knowledge involves two complementary but distinct paradigms, behavioral science and design science (March and Smith 1995). The behavioral-science paradigm has its roots in natural science research methods. It seeks to develop and justify theories (i. e. , principles and laws)that explain or predict organizational and human phenomena surrounding the analysis, design, implementation, management, and use of information systems. Such theories ultimately inform researchers and practitioners of the interactions among people, technology, and organizations that must be managed if an information system is to achieve its stated purpose, namely improving the effectiveness and efficiency of an organization. These theories impact and are impacted by design decisions made with respect to the system development methodology used and the functional capabilities, information contents, and human interfaces implemented within the information system.
The design-science paradigm has its roots in engineering and the sciences of the artificial (Simon 1996). It is fundamentally a problem-solving paradigm. It seeks to create innovations that define the ideas, practices, technical capabilities, and products through which the analysis, design, implementation, and use of information systems can be effectively and efficiently accomplished (Tsic
hritzis 1997; Denning 1997). Such artifacts are not exempt from natural laws or behavioral theories. To the contrary their creation relies on existing “kernel theories”that are applied, tested, modified, and extended through the experience, creativity, intuition, and problem solving capabilities of the researcher(Walls et al.1992; Markus et al. 2002).
design翻译The importance of design is well recognized in the IS literature (Glass 1999; Winograd 1996; Winograd 1997). Benbasat and Zmud(1999, P. 5)argue that the relevance of IS research is directly related to its applicability in design, stating that the implications of empirical IS research should be “implement table…synthesize an existing body of research…[or] stimulate critical thinking” among IS practitioners. However, designing useful artifacts is complex due to the need for creative advances in domain areas in which existing theory is often insufficient. “As technical knowledge grows, IT is applied to new application areas that were not previously believed to be amenable to IT support” (Markus et al. 2002, P. 180). The resultant IT artifacts extend the boundaries of human problem solving and organizational capabilities by providing intellectual as well as computational tools. Theories regarding their application and impact will follow their development and Use.
Here, we argue, is an opportunity for IS research to make significant contributions by engaging the complementary research cycle between design-science and behavioral-science to address fundame
ntal problems faced in the productive application of information technology. Technology and behavior are not dichotomous in an information system. They are inseparable (Lee 2000). They are similarly inseparable in IS research. Philosophically these arguments draw from the pragmatists (Aboulafia 1991) who argue that truth (justified theory) and utility (artifacts that are effective) are two sides of the same coin and that scientific research should be evaluated in light of its practical implications.
The realm of IS research is at the confluence of people, organizations, and technology (Lee 1999; Davis and Olson 1985). IT artifacts are broadly defined as constructs (vocabulary and symbols), models (abstractions and representations), methods (algorithms and practices), and instantiations (implemented and prototype systems). These are concrete prescriptions that enable IT researchers and
practitioners to understand and address the problems inherent in developing and successfully implementing information systems within organizations (March and Smithl995; Nunamaker et al. 1991a). As illustrations, Walls et al. (1992) and Markus et al. (2002) present design-science research aimed at developing executive information systems (EISs) and systems to support emerging knowledge processes (EKPs), respectively, within the context of ”IS design theories. “Such”theories “prescribe”effective development practices”(methods) and ”a type of system solution”(instantiation) fo
r ”a particular class of user requirements”(models) (Markus et al. 2002, P 180). Such prescriptive theories must be evaluated with respect to the utility provided for the class of problems addressed.
An IT artifact, implemented in an organizational context, is often the object of study in IS behavioral-science research. Theories seek to predict or explain phenomena that occur with respect to the artifact’s use (intention to use), perceived usefulness, and impact on individuals and organizations (net benefits) depending on system, service, and information quality (DeLone and McLean 1992; Seddon 1997; DeLone and McLean 2003). Much of this behavioral research has focused on one class of artifact, the instantiation (system), although other research efforts have also focused on the evaluation of constructs (e. g. , Batra et al. 1990; Kim and March 1995; Bodart et al. 2001; Geerts and McCarthy 2002)and methods(e. g. , Marakas and Elam 1998; Sinha and Vessey 1999). Relatively little behavioral research has focused on evaluating models, a major focus of research in the management science literature.
Design science, as the other side of the IS research cycle, creates and evaluates IT artifacts intended to solve identified organizational problems. Such artifacts are represented in a structured form that may vary from software, formal logic and rigorous mathematics to informal natural language descriptions. A mathematical basis for design allows many types of quantitative evaluations
of an IT artifact, including optimization proofs, analytical simulation, and quantitative comparisons with alternative designs. The further evaluation of a new artifact in a given organizational context affords the opportunity to apply empirical and qualitative methods. The rich phenomena that emerge from the interaction of people, organizations, and technology may need to be qualitatively assessed to yield an understanding of the phenomena adequate for theory development or problem solving (Klein and Meyers 1999). As field studies enable behavioral-science researchers to understand organizational phenomena in context, the process of
constructing and exercising innovative IT artifacts enable design-science researchers to understand the problem addressed by the artifact and the feasibility of their approach to its solution (Nunamaker et al. 1991a).
The primary goal of this paper is to inform the community of IS researchers and practitioners of how to conduct, evaluate, and present design-science research。We do so by describing the boundaries of design science within the IS discipline via
a conceptual framework for understanding information systems research(Section
2)and by developing a set of guidelines for conducting and evaluating good design-science research(
Section 3). We focus primarily on technology-based design although we note with interest the current exploration of organizations, policies, and work practices as designed artifacts (Boland 2002). Following Klein and Myers (1999) treatise on the conduct and evaluation of interpretive research in IS, we use the proposed guidelines to assess recent exemplar papers published in the IS literature in order to illustrate how authors, reviewers, and editors can apply them consistently (Section 4). We conclude (Section 5)with an analysis of the challenges of performing high-quality design-science research and a call for synergistic efforts between behavioral-science and design-science researchers.
2. A FRAMEWORK FOR IS RESEARCH
Information systems and the organizations they support are complex, artificial, and purposefully designed. They are composed of people, structures, technologies, and work systems (Bunge 1985; Simon 1996; Alter, 2003). Much of the work performed by IS practitioners, and managers in general (Boland 2002), deals with design-the purposeful organization of resources to accomplish a goal. Figure 1 illustrates the essential alignments between business and information technology strategies and between organizational and information systems infrastructures (Henderson and Venkatraman 1993). The effective transition of strategy into infrastructure requires extensive design activity on both
sides of the figure-organizational design to create an effective organizational infrastructure and information systems design to create an effective information system infrastructure.
These are interdependent design activities that are central to the IS discipline. Hence, IS research must address the interplay among: business strategy, IT strategy, organizational infrastructure, and IS infrastructure. This interplay is becoming more crucial as information technologies are seen as enablers of business strategy and organizational infrastructure (Kalakota and Robinson 2001; Orlikowski and Barley 2001). Available and emerging IT capabilities are a significant factor in determining
the strategies that guide an organization. Cutting-edge information systems allow organizations to engage new forms and new structures-to change the ways they ”do business”(Drucker 1988; Drucker 1991; Orlikowski 2000). Our subsequent discussion of design science will be limited to the activities of building the IS infrastructure within the business organization. Issues of strategy, alignment, and organizational infrastructure design are outside the scope of this paper.
译文
设计科学的信息系统研究
资料来源: Publication in MIS Quarterly
作者：Alan R．Hevner、Salvatore T．March、Jinsoo Park、Sudha Ram 1．引言
信息系统是在一个组织内部为提高效率和有效性而实现的一个组织。信息系统组织的能力和特点，它的工作系统，它的发展和执行方法共同确定在某种程度上可以实现这一目的(Silver et a1.1995)。在信息系统学科的研究中有义务“进一步的认识，在信息技术的生产应用在艾滋病到人类的组织及其管理”，(ISR2002，封面内页)，并发展和交流“知识管理问题在信息技术管理和使用信息技术为管理和组织的目的”(Zmud1997)。
我们认为，掌握了这些知识包括两个相辅相成的，但不同的模式，行为科学和设计科学(March and Smith1995)。行为科学范式在自然科学研究方法有它的根源。它谋求发展和辩护的理论(即，原则和法律)，解释或预测和周围组织，分析，设计，实施，管理人类现象，以及使用信息系统。这种理论最终告诉研究人员和从业者之间的互动，如果一个信息系统是实现其既定目标，即提高效率和组织效率，那么技术和组织必须进行管理。这些理论影响，并被有关系统开发使用的方法和功能的能力，信息内容进行设计决策的影响，使信息系统实施人性化界面。
设计科学模式在工程和人工科学有它的根源(Simon1996)。这是从根本上解决问题的范例。它旨在建立创新，定义观念，做法，技术能力，并通过这些分析，设计，实施和使用信息系统能够有效地和高
效率地完成产品(Tsichritzis 1997:Denning1997)。这种物品是不能免除的自然法则或行为理论。相反，其创作依赖于现有的研究，“核心理论”的应用，测试，修改，并通过经验，创造力，直觉，和研究者解决问题的能力(Walls et a1.1992;Markus et al.2002)。
设计重要的是对信息系统的一个很好的认知(Glass1999;Winograd

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