On a Quest for Good Process Models: The Cross-Connectivity Metric
On a Quest for Good Process Models: The Cross-Connectivity Metric
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DOI：
10.1007/978-3-540-69534-9_36
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发表时间：
2008-06
期刊：
影响因子：
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通讯作者：
Irene T. P. Vanderfeesten;H. Reijers;J. Mendling;Wil M.P. van der Aalst;J. Cardoso
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文献类型：
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作者：
Irene T. P. Vanderfeesten;H. Reijers;J. Mendling;Wil M.P. van der Aalst;J. Cardoso
业务流程建模是一项重要的企业活动，但是对构成良好流程模型的内容的理解相当有限。在本文中，我们转向认知维度框架，并确定对任何一对模型元素之间的结构关系的理解是一种困难的心理操作。基于最弱链接比喻，我们引入了交叉连接度量，该度量度量流程模型元素之间链接的强度。这个新指标的定义建立在这样一个假设之上，即如果流程模型具有高的交叉连接性，则流程模型更容易理解，并且包含更少的错误。我们进行了彻底的实证评估，以检验这一假设，并提出了我们的发现。这种新度量的良好表现强调了认知研究对推进过程模型测量领域的重要性。
Business process modeling is an important corporate activity, but the understanding of what constitutes good process models is rather limited. In this paper, we turn to the cognitive dimensions framework and identify the understanding of the structural relationship between any pair of model elements as a hard mental operation. Based on the weakest-link metaphor, we introduce the cross-connectivity metric that measures the strength of the links between process model elements. The definition of this new metric builds on the hypothesis that process models are easier understood and contain less errors if they have a high cross-connectivity. We undertake a thorough empirical evaluation to test this hypothesis and present our findings. The good performance of this novel metric underlines the importance of cognitive research for advancing the field of process model measurement.