Towards Multiple Perspectives of Cross-National Culture Using Self-Organizing Map (SOM)

Abstract

This study integrates the previous cross-cultural literature and aims to construct an analysis model of cross-national culture with multiple dimensions from three important cultural dimension theoretical models commonly used in cross-cultural studies: Hofstede, Global Leadership and Organizational Effectiveness (GLOBE) and World Values Survey (WVS). Traditional statistical analysis seems to be unable to solve the problem of the integration of relevant scales and units in different dimensions of cultural analysis. Therefore, this study uses a self-organizing map (SOM) as an analysis method to integrate 17 cultural variables from this multicultural dimension for cluster analysis and explains the cultural types in 26 countries based on the results. This study explores the differences and similarities of different countries in different cultural dimension analyses and provides a comparative model of multicultural analysis. This study takes samples from three cross-cultural analysis databases as data sources and employs the self-organizing map for analysis based on a neural network algorithm that can be used for type discrimination, map analysis, process monitoring, and error analysis. The results identify the cross-cultural groups of 26 countries and reveal their key cultural similarities and differences. We also elaborate upon the findings of these cultural characteristics and multi-cultural dimensions. The signification of this study is presented as a reference for subsequent studies of transnational and cross-cultural analysis and its applications.