A Decision Support Framework based on FCM for Selecting Key Performance Indicators

Fadwa Oukhay, T. Romdhane
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引用次数: 1

Abstract

One of the main issues that firms encounter in building an effective performance measurement system (PMS) is selecting the most relevant performance indicators, often known as key performance indicators (KPI). These indicators should be chosen according to the company’s objectives, strategies, and key success factors. On the other hand, in a production system, KPIs are not independent and may have inherent interactions with each other. These interactions should be investigated and taken into account in the KPI selection process. The goal of this research is to present a decision support framework based on a Fuzzy Cognitive Map (FCM) for guiding decision-makers in the selection of KPI. The model is based on the idea that KPI may be assessed and chosen based on their impacts on the company’s strategic objectives. In addition, the model allows for the consideration of different causal interdependence between the KPI.
基于FCM的关键绩效指标选择决策支持框架
企业在建立有效的绩效衡量系统(PMS)时遇到的主要问题之一是选择最相关的绩效指标,通常称为关键绩效指标(KPI)。这些指标应该根据公司的目标、战略和关键成功因素来选择。另一方面,在生产系统中,kpi不是独立的,它们之间可能存在固有的交互。在KPI选择过程中应调查并考虑这些相互作用。本研究的目的是提出一个基于模糊认知图(FCM)的决策支持框架,用于指导决策者选择KPI。该模型基于KPI可以根据其对公司战略目标的影响来评估和选择的想法。此外,该模型允许考虑KPI之间的不同因果关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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