三角测量
语法
实证研究
集合(抽象数据类型)
计算机科学
论证(复杂分析)
基于规则的机器翻译
领域(数学)
认识论
管理科学
语言学
人工智能
数学
经济
生物化学
几何学
化学
程序设计语言
纯数学
哲学
标识
DOI:10.5465/amr.2022.0297
摘要
In management research, theory is commonly viewed as a set of propositional statements backed up by theoretical assumptions. This view is embraced across conceptual and empirical research and effectively binds a particular style of reasoning, as a common grammar, to a specific form that theoretical explanations, as a structured set of propositions, should take. In this paper, I analyze characteristics of the propositional grammar and highlight several significant problems, including its high incidence rate of false positives in empirical research (false hypotheses that are accepted as true) and how it generally limits our explanation of phenomena by casting them as effects to be predicted. Informed by this analysis, I make the case for theoretical triangulation and offer a prescriptive model whereby researchers can strengthen their explanations of phenomena by iterating across multiple theoretical grammars rather than steadfastly using a single grammar. Using examples from prior research, I show how such theoretical triangulation helps mitigate the specific inferential biases and threats to validity of any grammar and leads to better explanations overall. Finally, I spell out the implications of this argument and offer a set of practical recommendations for implementing the practice of theoretical triangulation in the field of management research.
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