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Fuzzy cognitive map-based approach to evaluate EDI performance: a test of causal model

机译:基于模糊认知图的EDI性能评估方法:因果模型检验

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This paper proposes the usage of fuzzy cognitive map (FCM) for the evaluation of electronic data interchange (EDI) performance. Although there has been a stream of research on the performance of EDI systems during the last decades, possible interrelationships among those individual factors of EDI performance have been largely ignored and thereby were not adequately examined. The main task of evaluation of EDI performance demands consideration of the complex causal relationship among EDI performance factors. It is difficult even for experts in organizational behavior to cognitively predict the causal effect of one factor on the others. A FCM is used to describe the inference process for the evaluation of EDI performance. Initially, structural equation models are used for identifying relevant relationships among the factors and indicating their direction and strength. This study collected data from the 202 companies, which already experienced EDI systems implementation. The derived five factors include reduction of processing time, improved information quality, decreased processing cost, improved operational efficiency, competitive advantage. Findings indicate that a causal model of EDI performance adequately capture each of the proposed variables. The cognitive map provides preliminary insights into the causal model of EDI performance.
机译:本文提出了使用模糊认知图(FCM)评估电子数据交换(EDI)性能的方法。尽管在过去的几十年中对EDI系统的性能进行了大量研究,但是EDI性能的各个因素之间可能存在的相互关系已被大大忽略,因此没有得到充分研究。 EDI绩效评估的主要任务是考虑EDI绩效因素之间的复杂因果关系。即使是组织行为专家也很难从认知上预测一个因素对其他因素的因果关系。 FCM用于描述推论EDI性能评估的推理过程。最初,结构方程模型用于识别因素之间的相关关系,并指示其方向和强度。这项研究从202家已经实施EDI系统的公司收集了数据。得出的五个因素包括处理时间的减少,信息质量的提高,处理成本的降低,运营效率的提高以及竞争优势。结果表明,EDI性能的因果模型足以捕获每个建议的变量。认知图提供了对EDI绩效因果模型的初步见解。

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