Advancing our understanding of cultural heterogeneity with unsupervised machine learning

Wolfgang Messner

Journal of International Management, 2022, vol. 28, issue 2

Abstract: National boundaries and country averages are commonly used as delimiters and proxies for culture. By doing so, not enough attention is paid to cultural heterogeneity within and overlays between countries. Deploying a Kohonen self-organizing map (SOM) as an unsupervised machine learning technique on 106,382 individual-level survey data from 66 countries, this article identifies distinct worldwide cultural prototypes, isolates dominantly occurring prototypes within countries, and uses them to calculate cultural core values. It also provides new measures for within-country cultural heterogeneity, between-country cultural differences, and cultural isolation. The results not only show the usefulness of machine learning algorithms in inductive international business research, but also have managerial relevance for international marketing and management.

Keywords: Artificial intelligence (AI); Cultural differences; Cultural heterogeneity; Ethnic fractionalization; Inductive research; Kohonen self-organizing map (SOM); Machine learning (ML); Schwartz Value Inventory (SVI) (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1075425321000648
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intman:v:28:y:2022:i:2:s1075425321000648

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/601266/bibliographic
http://www.elsevier. ... 601266/bibliographic

DOI: 10.1016/j.intman.2021.100885

Access Statistics for this article

Journal of International Management is currently edited by M. Kotabe

More articles in Journal of International Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().