The Past, Present, and Future of Research on Organizational Routines

The Past, Present, and Future of Research on Organizational Routines
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组织惯例研究的过去、现在和未来

DOI:
10.11207/taaos.10.2_49
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发表时间:
2021
期刊:
Transactions of the Academic Association for Organizational Science
影响因子:
--
通讯作者:
吉野直人
吉野直人
中科院分区:
--
文献类型:
--
作者:
Yoshiki Shinohara;Lailani Laynesa Alcantara;井上裕珠・沼崎誠;井上裕珠・沼崎誠;吉野 直人;吉野直人

文献摘要

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本文的目的是质疑从批判现实主义的角度对组织惯例进行研究的意义。组织惯例已经被概念化,使用了各种定义作为分析单位,供研究人员解释商业公司的行为。然而,自2000年以来,它们被定义为受结构化理论影响的模式和动作的二元性,并发展了对常规动力学的研究,以捕捉实践中常规的稳定性和变化。目前,研究人员被称为“叙事网络”的分析框架所吸引,该框架基于社会学叙事方法论和平面本体论来描述这些动态。因此,虽然组织例程已作为描述性模型加以阐述,但描述例程的理由并不一定得到澄清。为了弥合文献中的这一差距,在本文中,我基于批判现实主义对这一问题进行了讨论,并认为通过描述例程,研究人员可以对象化构成例行化的倾向,并批判性地分析这些倾向,以及创造新的实践和惯例。这表明,叙事方法具有作为一种实用方法的潜力,而不仅仅是一种描述性的模式。
The aim of this paper is to question the significance of conducting research on organizational routines from the perspective of critical realism. Organizational routines have been conceptualized using a variety of definitions as analytical units for researchers to explain the behavior of business firms. However, since 2000, they have been defined as a duality of patterns and actions influenced by structuration theory, and research on routine dynamics has been developed to capture the stability and change of routines in practice. Presently, researchers are drawn to the analytical framework called “narrative networks,” which describes these dynamics based on sociological narrative methodology and flat ontology. Thus, while organizational routines have been elaborated as a descriptive model, the reasons for describing the routines have not necessarily been clarified. To bridge this gap in the literature, in this paper, I discuss this issue based on critical realism and argue that by describing the routines, researchers can objectify the tendencies that constitute the routineness of routines, and analyze those tendencies critically as well as create new practices and routines. This suggests that the narrative approach has potential as a pragmatic methodology and not just as a descriptive model.