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Heuristic Theorizing: Proactively Generating Design Theories

机译:启发式理论化:主动生成设计理论

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Design theories provide explicit prescriptions, such as principles of form and function, for constructing an artifact that is designed to meet a set of defined requirements and solve a problem. Design theory generation is increasing in importance because of the increasing number and diversity of problems that require the participation and proactive involvement of academic researchers to build and test artifact-based solutions. However, we have little understanding of how design theories are generated. Drawing on key contributions by Herbert A. Simon, including the ideas of satisfice and bounded rationality and reviewing a large body of information systems and problem-solving literature, we develop a normative framework for proactive design theorizing based on the notion of heuristic theorizing. Heuristics are rules of thumb that provide a plausible aid in structuring the problem at hand or in searching for a satisficing artifact design. An example of a problem-structuring heuristic is problem decomposition and an example of an artifact design heuristic is analogical design. We define heuristic theorizing as the process of proactively generating design theory for prescriptive purposes from problem-solving experiences and prior theory by constantly iterating between the search for a satisficing problem solution, i.e., heuristic search, and the synthesis of new information that is generated during heuristic search, i.e., heuristic synthesis. Heuristic search involves alternating between structuring the problem at hand and generating new artifact design components, whereas heuristic synthesis involves different ways of thinking, including reflection and learning and forms of reasoning, that complement the use of heuristics for theorizing purposes. We illustrate the effectiveness of our heuristic theorizing framework through a detailed example of a multiyear design science research program in which we proactively generated a design theory for solving problems in the area of intelligent information management and so-called big data in the finance domain. We propose that heuristic theorizing is a useful alternative to established theorizing approaches, i.e., reasoning-based approaches. Heuristic theorizing is particularly relevant for proactive design theorizing, which emphasizes problem solving as being highly intertwined with theorizing, involves a greater variety of ways of thinking than other theorizing approaches, and assumes an engaged relationship between academics and practitioners.
机译:设计理论提供了明确的处方,例如形式和功能原理,用于构建旨在满足一组已定义要求并解决问题的工件。设计理论的产生越来越重要,因为问题的数量和多样性不断增加,需要学术研究人员的参与和积极参与才能构建和测试基于工件的解决方案。但是,我们对设计理论的生成方式了解甚少。利用Herbert A. Simon的主要贡献,包括满足和有限理性的思想,并回顾大量的信息系统和解决问题的文献,我们开发了一个基于启发式理论的主动设计理论规范框架。启发式算法是一种经验法则,在构造当前问题或寻找令人满意的工件设计时提供了合理的帮助。问题分解试探法的一个示例是问题分解,而工件设计试探法的一个示例是类比设计。我们将启发式理论定义为:通过不断地在寻找令人满意的问题解决方案(即启发式搜索)与在搜索过程中生成的新信息的合成之间进行迭代,从解决问题的经验和先验理论中主动生成用于说明目的的设计理论的过程。启发式搜索,即启发式综合。启发式搜索涉及在解决当前问题和生成新的工件设计组件之间进行交替,而启发式综合则涉及不同的思维方式,包括反思和学习以及推理形式,这些补充了启发式方法在理论上的使用。我们通过多年设计科学研究计划的详细示例来说明启发式理论框架的有效性,在该计划中,我们主动生成了一种设计理论,用于解决智​​能信息管理和金融领域所谓的大数据领域的问题。我们建议启发式理论化是已建立的理论化方法(即基于推理的方法)的有用替代方法。启发式理论与主动设计理论特别相关,后者强调解决问题与理论高度交织,比其他理论方法涉及更多的思维方式,并且假定学者与实践者之间存在着紧密的联系。

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