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System dynamics applications in performance measurement research

独创性 成熟度(心理) 计算机科学 探索性研究 集合(抽象数据类型) 系统回顾 系统动力学 过程管理 知识管理 管理科学 数据科学 心理学 社会学 业务 定性研究 工程类 社会科学 政治学 法学 程序设计语言 人工智能 发展心理学 梅德林
作者
Olufunke Oladimeji,Heather Keathley-Herring,Jennifer Cross
出处
期刊:International Journal of Productivity and Performance Management [Emerald (MCB UP)]
卷期号:69 (7): 1541-1578 被引量:18
标识
DOI:10.1108/ijppm-12-2018-0453
摘要

Purpose This study investigates system dynamics (SD) applications in performance measurement (PM) research and practice. A bibliometric analysis was conducted to investigate the maturity of this research area and identify opportunities for development. Design/methodology/approach A systematic literature review (SLR) was conducted to provide a comprehensive and rigorous review of the existing literature. The search was conducted on 10 platforms identifying 97 publications, which were evaluated using bibliometric analysis. Findings The analysis revealed that applications of SD are most commonly used in the PM system design phase to model organisational performance. In addition, the bibliometric results showed a highly dispersed author set, with most studies using exploratory methods, suggesting that the research is in a relatively early stage of development. The results also showed that over 50 per cent of the causal models were not validated, emphasizing an important methodological gap in this research area. Research limitations/implications This SLR is limited to indexed publications on 10 platforms, the search strategy was relatively precise and only available papers in English language were used for the literature review. Practical implications PM systems supported by SD can help managers understand and improve organisational behaviours by addressing dynamic complexities and relationship between variables. This study evaluates the maturity of this research area including information about the current development of this area and opportunities to build on existing knowledge. Originality/value This study identifies how SD approaches are applied to PM and highlights areas that require further research consideration. This paper is the first of two publications to result from this study and focuses on evaluating the current state of this research area.

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