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Comparing the performance of traditional cluster analysis, self- organizing maps and fuzzy C-means method for strategic grouping

机译:比较传统聚类分析,自组织图和模糊C均值方法进行战略分组的性能

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摘要

Strategic group analysis comprises of clustering of firms within an industry according to their similarities with respect to a set of strategic dimensions and investigating the performance implications of strategic group membership. One of the challenges of strategic group analysis is the selection of the clustering method. In this study, the results of the strategic group analysis of Turkish contractors are presented to compare the performances of traditional cluster analysis techniques, self-organizing maps (SOM) and fuzzy C-means method (FCM) for strategic grouping. Findings reveal that traditional cluster analysis methods cannot disclose the overlapping strategic group structure and position of companies within the same strategic group. It is concluded that SOM and FCM can reveal the typology of the strategic groups better than traditional cluster analysis and they are more likely to provide useful information about the real strategic group structure.
机译:战略组分析包括根据一组战略维度上行业的相似性对行业内的公司进行聚类,并调查战略组成员资格对绩效的影响。战略群体分析的挑战之一是聚类方法的选择。在这项研究中,土耳其承包商的战略集团分析结果被提出来比较传统的聚类分析技术,自组织地图(SOM)和模糊C均值方法(FCM)进行战略分组的性能​​。研究发现,传统的聚类分析方法无法揭示重叠的战略集团结构和公司在同一战略集团中的地位。结论是,与传统的聚类分析相比,SOM和FCM可以更好地揭示战略集团的类型,它们更有可能提供有关实际战略集团结构的有用信息。

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