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Application of the Self-Organizing Map (SOM) to Analyze the Multiple Perspectives on Cross-National Culture
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- Chuang Li-Ming
- The Department of International Business, Chang Jung Christian University
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- Lee Yu-Po
- The Ph.D. Program in Business and Operations Management, College of Management, Chang Jung Christian University
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- Chao Shu-Tsung
- Graduate School of Business and operation Management, Chang Jung Christian University
Description
Organizational behavior in different countries and cultures has been the focus of studies in recent years. Following a literature review, we find that there are many different perspectives and features in the related cross-cultural studies. However, whether the analysis methods of these different cultural dimensions can fit into the increasingly complex and diverse topics of cross-cultural studies have not been determined, which is also a topic of great interest to scholars. Therefore, 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.
Journal
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- Proceedings of International Conference on Artificial Life and Robotics
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Proceedings of International Conference on Artificial Life and Robotics 26 421-424, 2021-01-21
ALife Robotics Corporation Ltd.
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Details 詳細情報について
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- CRID
- 1390851175704165248
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- ISSN
- 21887829
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
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- Abstract License Flag
- Disallowed