Multi-stage clustering with complementary structural analysis of 2-mode networks

Emanuela Todeva, David Knoke, Donka Keskinova

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper offers a synthesis of a new analytical procedure based on the complementary use of a large number of methods and techniques for categorisation of objects, pattern recognition and for structural analysis. It represents an example of a functional clustering [1] and an extension to the ‘posteriori methods’ for clusterisation [2]. We call this approach MultiStage Clustering (MSC), as it applies cluster analysis methods at three distinctive stages. We present the MSC and demonstrate its application to a business dataset of 275 multinational corporations (MNCs), aiming to address the inherent weaknesses of existing industrial classification tools designed to capture diversification of firms. We evaluate the outcomes from the MSC using a combination of complementary methods for structural analysis and data visualisation, such as multi-dimensional scaling (MDS), network mapping (NM) and multiple correspondence analysis (MCA). The MSC is designed for the analysis of diversification patterns of MNCs, which can enable the measurement of group competitiveness and performance across these patterns, known as industry segments, or strategic industry groups (SIGs).

Original languageEnglish (US)
Title of host publicationProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
EditorsFrancesca Spezzano, Wei Chen, Xiaokui Xiao
PublisherAssociation for Computing Machinery, Inc
Pages771-778
Number of pages8
ISBN (Electronic)9781450368681
DOIs
StatePublished - Aug 27 2019
Event11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019 - Vancouver, Canada
Duration: Aug 27 2019Aug 30 2019

Publication series

NameProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019

Conference

Conference11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
Country/TerritoryCanada
CityVancouver
Period8/27/198/30/19

Bibliographical note

Publisher Copyright:
© 2019 Copyright is held by the owner/author(s).

Keywords

  • Data categorization
  • Industry classification
  • Multidimensional scaling
  • Multiple correspondence analysis
  • Multistage cluster analysis
  • Network analysis
  • Pattern recognition

Fingerprint

Dive into the research topics of 'Multi-stage clustering with complementary structural analysis of 2-mode networks'. Together they form a unique fingerprint.

Cite this