A structured conceptualization method, concept mapping, is applied to visualize the conceptual domain of explicit and tacit quality linkages in a complex, causally ambiguous production system of a premium automotive OEM. Experts, intimately familiar with all facets of the conceptual domain, defined sources of quality problems and rated their impact on product quality. These inputs, formative measures for a latent construct, were used to create concept maps and clusters for the sources of quality problems. Differences and disagreements between subgroups were highlighted by pattern matching. The concept map and the preferred cluster solution, based on user-defined measures, served as inputs in the development of a causal loop diagram and an action plan for better resource allocation to specific improvement activities. The approach, using formative rather than the more commonly used reflective indicators, uses key informants and explanation building processes of high internal validity. In the spirit of the “proximal similarity model,” the presented methodology is also highly transferable to similar settings of other automotive OEMs and beyond.

一种结构化的概念化方法，即概念映射，用于在高级汽车OEM的复杂，因果关系不明确的生产系统中可视化显性和默认质量链接的概念域。与概念领域的各个方面都非常熟悉的专家定义了质量问题的根源，并评估了它们对产品质量的影响。这些输入（用于潜在构造的形成性度量）用于创建概念图和质量问题根源的群集。模式匹配突出显示了亚组之间的差异和分歧。基于用户定义的度量的概念图和首选的群集解决方案，在制定因果循环图和行动计划的过程中用作输入，以更好地为特定的改进活动分配资源。该方法，使用形成性指标而不是更常用的反思性指标，而是使用关键的线人和具有较高内部有效性的解释构建过程。本着“近邻相似性模型”的精神，所提出的方法也可以高度移植到其他汽车OEM以及以后的相似环境中。