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

Budayan C., Dikmen I., BİRGÖNÜL M. T.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.36, sa.9, ss.11772-11781, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 9
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.eswa.2009.04.022
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.11772-11781
  • Anahtar Kelimeler: Strategic groups, Traditional cluster analysis techniques, Self-organizing map, Fuzzy C-means, NEURAL-NETWORK, VALIDITY, SEGMENTATION, MANAGEMENT, ALGORITHMS
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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. (C) 2009 Elsevier Ltd. All rights reserved.