Agent-based modelling of individual absorptive capacity for effective knowledge transfer

3区 计算机科学 Q1 Computer Science
Thomas Dolmark, Osama Sohaib, Ghassan Beydoun, Firouzeh Taghikhah
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引用次数: 0

Abstract

The importance of knowledge for organizational success is widely recognized, leading managers to leverage knowledge actively. Within knowledge transfer, the Absorptive Capacity (ACAP) of Knowledge Recipients (KR) emerges as an unresolved barrier. ACAP is the dynamic capability to absorb knowledge and surpass the aggregation of individual ACAP within an organization. However, more research is needed on individual-level ACAP and its implications for bridging the gap between individual and organizational knowledge transfer. To address this gap, this study employs Agent-Based Modeling (ABM) as a simulation method to replicate individual ACAP within an organization, facilitating the examination of knowledge transfer dynamics. ABM allows for the detailed analysis of interactions between individual KRs and the organizational environment, revealing how uninterrupted time and other factors influence knowledge absorption. The implications of the study are that ABM provides specific insights into how individual ACAP affects organizational learning and performance, emphasizing the importance of uninterrupted time for KR to achieve optimal knowledge exploitation and highlighting the need for organizational practices and policies that foster environments conducive to knowledge absorption.

Abstract Image

基于代理的个人吸收能力模型,促进有效的知识转移
知识对组织成功的重要性已得到广泛认可,这促使管理者积极利用知识。在知识转移过程中,知识接受者(KR)的吸收能力(ACAP)成为一个尚未解决的障碍。ACAP 是吸收知识的动态能力,它超越了组织内个体 ACAP 的集合。然而,还需要对个人层面的 ACAP 及其对缩小个人与组织知识转移之间差距的影响进行更多研究。为了弥补这一差距,本研究采用了代理建模(ABM)作为一种模拟方法,在组织内复制个体的 ACAP,从而促进对知识转移动态的研究。ABM 可以详细分析个体知识资源与组织环境之间的相互作用,揭示不间断的时间和其他因素是如何影响知识吸收的。该研究的意义在于,ABM 提供了关于个体 ACAP 如何影响组织学习和绩效的具体见解,强调了不间断时间对于知识共享者实现最佳知识利用的重要性,并突出了营造有利于知识吸收的环境的组织实践和政策的必要性。
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来源期刊
Journal of Ambient Intelligence and Humanized Computing
Journal of Ambient Intelligence and Humanized Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
9.60
自引率
0.00%
发文量
854
期刊介绍: The purpose of JAIHC is to provide a high profile, leading edge forum for academics, industrial professionals, educators and policy makers involved in the field to contribute, to disseminate the most innovative researches and developments of all aspects of ambient intelligence and humanized computing, such as intelligent/smart objects, environments/spaces, and systems. The journal discusses various technical, safety, personal, social, physical, political, artistic and economic issues. The research topics covered by the journal are (but not limited to): Pervasive/Ubiquitous Computing and Applications Cognitive wireless sensor network Embedded Systems and Software Mobile Computing and Wireless Communications Next Generation Multimedia Systems Security, Privacy and Trust Service and Semantic Computing Advanced Networking Architectures Dependable, Reliable and Autonomic Computing Embedded Smart Agents Context awareness, social sensing and inference Multi modal interaction design Ergonomics and product prototyping Intelligent and self-organizing transportation networks & services Healthcare Systems Virtual Humans & Virtual Worlds Wearables sensors and actuators
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