1、 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 efficie
2、ncy 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 rese
3、archers 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 informati
4、on 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 it
5、s 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
6、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 decisio
7、ns 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 funda
8、mentally 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 (Tsichritzis 1997; Denning 199
9、7). 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
10、al.1992; Markus et al. 2002). 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 empiric
11、al IS research should be “implement tablesynthesize an existing body of researchor 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
12、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 computa
13、tional 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 fundamental p
14、roblems 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
15、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; Dav
16、is 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 practiti
17、oners 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
18、 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) for ”a particular class of
19、 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. Th
20、eories seek to predict or explain phenomena that occur with respect to the artifacts 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
21、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. ,
22、 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 ide
23、ntified 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, includin
24、g 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 p
25、eople, 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,
26、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 res
27、earchers 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 c
28、onducting 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
29、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 cha
30、llenges 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
31、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 essen
32、tial 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-organiza
33、tional 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
34、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 emergin
35、g 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 discuss
36、ion 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 Hevne
37、r、 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” ，(ISR 2002，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” (Zmud 1997)。 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
38、科学 (March and Smith 1995)。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 (Simon 1996)。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
39、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:Denning 1997)。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 (Glass 1999;Winograd 1996;Winograd 1997)。 Benbasat and Zmud(1999,p.5)辩称信息系统相关的研究，直接关系到其在设计的适用性，指出实验式的暗示是
40、信息系统研究的“执行表综合现有的研究机构的影响 或 在实践中刺激批判性思维。然而，设计中有用的物品复杂的原因是由于在现有的理论有域区创造性的进展需 要往往是不够的。“随着技术知识的增长， IT 将被应用到以前没有认为是适合的 IT 支持的领域了” (Markus et al.2002,p.180)。 由此产生的科技产物延伸到人类解决问题的边界和计算机工具一样用过提高智力的组织能力。就其理论的应用和影响将遵循其发展和使用。 在这里，我们认为，通过研究与设计进行科学和行为科学，以解决在信息技术的生产应用所面临的根本问题的补充研究周期的重大贡献是一个机会。技术和行为在信息系统是不可分割的。他们是不可
41、分割的 (Lee 2000)。在研究工作中他们同样是密不可分的。在哲学上这些论点吸取实用主义者 (阿布拉菲亚1991)谁认为真理 (合理的理论 )和公用事业 (工件是有效的 )是同一问题两面，而科学研究应当在其实际影响来加以评价。 该信息系统研究的领域是人民，组织和技术的汇合 (Lee 1999;Davis and Olson 1985)科技产品大致定义为构造 (词汇和符号 )，模型 (抽象和表现 )，方法 (算法和做法 )，和 (执行和原型系统 )实例。这些都是具体的方案，使 IT 研究人员和从业人员在制定和成功实施信息系统内部组织时了解和解决的问题(March and Smithl995;
42、Nunamaker et a1.1991a)作为插图， Walls et al.(1992)和 Markus et a1.(2002)现时的设计，在科学发展的执行信息系统 (EIS 系统 )和系统的目的是支持新兴的知识流程 (EKPs)，分别研究范围内的“信息系统设计理论。”这种“理论”规定“有效的发展做法” (方法 )和“系统类型的解决方案”(实例 )的“用户要求的某一类” (模型 )(Markus et a1.2002,p.180)。这种规范必须评估理论方面的问题处理的类提供的实用工具。 一 个 IT 工件，在组织范围内实施，往往是在信息系统行为科学调查研究的对象。寻求理论预测或解释发生在
43、工件的使用 (打算使用 )，被认为是有用的，冲击个人和组织依赖系统，服务的影响，以及信息质量 (网络利益 )的净效益的现象 (DeLone and McLean 1992; Seddon 1997;DeLone and McLean 2003)。这种研究的行为大部分集中在一个工件类，实例 (系统 )，尽管其他研究成果也集中对重点结构的评价 (e.g., Batra et a1.1990;Kim and March 1995;Bodart et al.2001;Geerts and McCarthy 2002)和方法 (e.g., Marakas and Elam 1998；Sinha and
44、Vessev 1999)。相对小的行为研究侧重于评估模型，主要焦点在管理科学文献的研究。 设计科学，作为是信息系统研究周期的另一端，创建和评估科技产品旨在解决查明组织的问题。这类产品代表在结构化的形式可能的不同软件，形式逻辑和严格的数学非正式自然语言描述。一种数学基础的设计，允许多种类型的定量评价一个 IT 工件，包括优化的证据，分析仿真，并与其他设 计定量比较。一个新的工件在一个特定的组织范围内进一步的评估提供了申请经验和定性的方法的机会。这样一种从交互的人，组织和可能需要定性评估的技术中显现出来，为 理论 的发展 或者 解决 的问题 有充 分的 认识得 现象 (Klein and Meye
45、rs1999)。作为研究领域，使行为科学的研究，在上下文中了解组织的现象，建设进程和行使创新的 IT 产品，使设计科学的研究人员通过产品和解决问题的可行性来弄懂解决问题的根源 (Nunamaker et al.1991a)。 本文的主要目的是通告信息系统研究人员和从业者如何进行评估，和现在的 科研设计工作。为此，我们通过描述概念上的架构来了解信息系统的研究 (第2)，通过开发一系列行为的和评价进行科学的研究 (第 3)准则的概念框架，设计科学的学科界限。我们主要侧重于技术为基础的设计，虽然我们饶有兴趣地注意到，组织，政策，目前的勘探，设计和构件的工作模式 (Boland 2002)。继克莱因和
46、迈尔斯 (1999 年 )的在信息系统方面的行为和解释性研究论文的评价是，我们使用拟议的准则，以评估最近发表在信息系统文献上用来说明这样的作者，评论和编辑可以贯彻采用 (第 4 节 )。我们得出结论 (第 5)，对高品质表演的挑战的 分析的设计科学研究和行为之间的科学和设计科学和行为科学之间促进效率的的呼吁。 2一个信息系统研究的框架 信息系统和对此支持的组织，是复杂的，人为的，特意设计的。他们又人，结构，技术和工作系统组成 (Bunge 1985;Simon 1996;Alter 2003)。大部分是由行业工作者和一般管理人员进行的工作 (Boland 2002)，涉及设计资源目标明确的组织
47、来实现的目标。图 1 说明了企业与信息技术战略和组织结构和信息系统基础设施 (Henderson and Venkatraman 1993)的基本路线。基 础设施有效地策略转变需要对数字双方广泛的设计活动 -组织设计和有效的信息系统基础设施进行广泛的设计行为动作。 这些都是在 IS 纪律设计活动相互依存的核心。因此， IS 研究必须解决相互之间的影响：经营战略， IT 战略，组织的基础设施和 IS 基础设施。这种相互作用作为企业战略和组织基础设施变得越来越关键 (Kalakota and Robinson 2001;Orlikowski and Barley 2001)。可利用的和显现出来的 IT 能力是在管理一个组织中决定一项战略中重要的因素。最先进的信息系统，允许组织机构能够参与 的新形式和新的结构 ,以改变它们的“做生意” (Drucker 1988;Drucker 1991;Orlikowski 2000)。我们的设计科学随后进行的讨论将仅限于建设 IS 企业组织内的基础设施的活动。战略调整 的 问题，组织基础设施设计不属于本文的讨论范围。
