Macro-iterativity: A Qualitative Multi-arc Design for Studying Complex Issues and Big Questions

IF 8.9 2区 管理学 Q1 MANAGEMENT Organizational Research Methods Pub Date : 2023-04-17 DOI:10.1177/10944281231166649
Christina Hoon, Alina M. Baluch
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引用次数: 1

Abstract

The impact and relevance of our discipline's research is determined by its ability to engage the big questions of the grand challenges we face today. Our central argument is that we need innovative methods that engage large-scope phenomena, not least because these phenomena benefit from going beyond individual study design. We introduce the concept of macro-iterativity which involves multiple iterations that move between, and link across, a set of research cycles. We offer a multi-arc research design that comprises the discovery arc and extension arc and three extension logics through which scholars can combine these arcs of inquiry in a coherent way. Based on this research design, we develop a roadmap that guides scholars through the four steps of how to engage in multi-arc research along with the main techniques and outputs. We argue that a multi-arc design supports the move toward more generative theorizing that is required for researching problems dealing with the complex issues and big questions of our time.
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宏观迭代性:研究复杂问题和大问题的定性多弧设计
我们学科研究的影响力和相关性取决于它处理我们今天面临的重大挑战中的重大问题的能力。我们的核心论点是,我们需要创新的方法来处理大范围的现象,尤其是因为这些现象受益于超越个人学习设计。我们引入了宏观迭代性的概念,它涉及在一组研究周期之间移动和链接的多次迭代。我们提供了一个多弧研究设计,包括发现弧和扩展弧,以及三个扩展逻辑,通过这些逻辑,学者可以以连贯的方式将这些研究弧结合起来。基于这一研究设计,我们制定了一个路线图,指导学者完成如何进行多弧研究的四个步骤以及主要技术和产出。我们认为,多弧设计支持向更具生成性的理论化迈进,这是研究处理我们这个时代的复杂问题和重大问题所必需的。
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来源期刊
CiteScore
23.20
自引率
3.20%
发文量
17
期刊介绍: Organizational Research Methods (ORM) was founded with the aim of introducing pertinent methodological advancements to researchers in organizational sciences. The objective of ORM is to promote the application of current and emerging methodologies to advance both theory and research practices. Articles are expected to be comprehensible to readers with a background consistent with the methodological and statistical training provided in contemporary organizational sciences doctoral programs. The text should be presented in a manner that facilitates accessibility. For instance, highly technical content should be placed in appendices, and authors are encouraged to include example data and computer code when relevant. Additionally, authors should explicitly outline how their contribution has the potential to advance organizational theory and research practice.
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