Cultural Differences in an Artificial Representation of the Human Emotional Brain System: A Deep Learning Study

Abstract

Cultural differences between countries are customarily calculated by comparing mean scores on a number of dimensions, thereby ignoring heterogeneity within societies. This article proposes a fundamentally new way of measuring cultural differences by evaluating the functioning of the emotional brain, that is, by comparing how people think, rather than what they think. Deep learning as a supervised machine learning technique is used to mathematically represent the emotional brain of the Volksgeist with a complex system of non-linear combinations of value priorities, opinions, and other factors with subjective feelings of well-being. Cross-validating how well one Volksgeist’s artificial brain fits another country provides a novel measure for emotional cultural differences, which also considers heterogeneity within a society. This measure is conceptually and statistically totally unrelated to the Kogut-Singh index calculated from mean scores on cultural dimensions. But it shows good face validity and supports international marketing and business theory as a negative and highly significant predictor for bilateral trade flows within Europe, using a classic gravity model.

Managing artificial intelligence in international business: Toward a research agenda on sustainable production and consumption

“…In this case, IB studies demonstrate that managers can deploy AI to learn about cultural heterogeneity within nations, focusing on individuals to draw on country-level differences (Messner, 2022c). As an example, AI models can learn to trace cultural distance by crunching data on individuals' values embodying societal and cultural beliefs and behaviors, even emotional brain systems (Messner, 2022a(Messner, , 2022b. Such learning enables managers to identify similar cultural subgroups across counties and isolate nations with notable cultural similarities.…”