能力损耗:研究外部能力获取对组织影响的语言学理论

IF 1.8 4区 管理学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
S. Guercini, C. Lechner
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引用次数: 2

摘要

当获得新能力时,组织中的旧能力会发生什么变化?本文提出了一种胜任力损耗理论来解释获得新胜任力对已获得胜任力的影响。虽然现有能力对获得新能力的假定积极作用一直是广泛研究的主题,但外部能力的获得对现有能力的获得和使用的潜在负面影响尚未得到充分的理论化。我们的目标是通过扩展现有的学习和吸收能力理论来实现这一目标,并结合语言学对能力消耗的见解。具体来说,根据语言习得和流失的平行模式,我们提出了一套关于组织中能力习得和流失的重点命题。最后,我们讨论了我们的理论对现有理论和研究的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Competence Attrition: A linguistic theory of the effects of external competence acquisition for organizations
What happens to old competences in organizations when new competences are acquired? In this paper, we propose a competence attrition theory to explain the effects of acquiring new competences on previously acquired ones. While the presumed positive role of available competences for the acquisition of new competences has been the subject of extensive research, the potentially negative effect of the acquisition of external competences on the availability and use of existing competences has not been sufficiently theorized. We aim to do so by extending existing learning and absorptive capacity theories with insights from linguistics on competence attrition. Specifically, informed by parallel patterns in language acquisition and attrition, we develop a set of focused propositions on competence acquisition and attrition in organizations. We end the paper by discussing the implications of our theorizing for existing theory and research.
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来源期刊
Computational and Mathematical Organization Theory
Computational and Mathematical Organization Theory COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
3.80
自引率
16.70%
发文量
14
审稿时长
>12 weeks
期刊介绍: Computational and Mathematical Organization Theory provides an international forum for interdisciplinary research that combines computation, organizations and society. The goal is to advance the state of science in formal reasoning, analysis, and system building drawing on and encouraging advances in areas at the confluence of social networks, artificial intelligence, complexity, machine learning, sociology, business, political science, economics, and operations research. The papers in this journal will lead to the development of newtheories that explain and predict the behaviour of complex adaptive systems, new computational models and technologies that are responsible to society, business, policy, and law, new methods for integrating data, computational models, analysis and visualization techniques. Various types of papers and underlying research are welcome. Papers presenting, validating, or applying models and/or computational techniques, new algorithms, dynamic metrics for networks and complex systems and papers comparing, contrasting and docking computational models are strongly encouraged. Both applied and theoretical work is strongly encouraged. The editors encourage theoretical research on fundamental principles of social behaviour such as coordination, cooperation, evolution, and destabilization. The editors encourage applied research representing actual organizational or policy problems that can be addressed using computational tools. Work related to fundamental concepts, corporate, military or intelligence issues are welcome.
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