At The Culture Factor Group, we believe in unlocking culture with data. Our research advances the understanding of how culture shapes decisions, organisations, and societies. By analysing large-scale data, we refine existing models, challenge assumptions, and provide insights that drive better leadership, HR policies, and global strategies. This forthcoming dataset will allow researchers to explore how gender differences in cognition and behavioural preferences are shaped by cultural and socio-economic contexts, building a stronger evidence base for applied cultural analysis worldwide.
This ongoing research is conducted by Michael Schachner, Head of Research at The Culture Factor Group Oy, Antonio Espin, behavioral economist at the University of Granada, Hester van Herk, Professor of Marketing at Vrije Universiteit Amsterdam, Michael Minkov, Professor of Cross-Cultural Studies at Varna University of Management, and Pablo Brañas, Professor of Behavioral Economics at Loyola Andalucia University.
Why This Research Matters
This dataset will be valuable to:
- Researchers studying cross-cultural psychology, behavioural economics, or gender studies
- Educators teaching cultural frameworks and decision-making theory
- Policymakers developing strategies to promote equality and inclusion
- Consultants and trainers applying cultural insights to leadership and organisational change
The research addresses a timely question: How do cultural values and socio-economic factors influence gender differences in cognition and behaviour?
By combining country-level cultural indicators with individual-level behavioural data, it will provide a clearer picture of whether these differences widen or narrow under different cultural conditions.
Purpose of the Research
The main aim is to determine whether gender differences in cognition-related and behavioural preference measures vary according to country-level cultural and socio-economic indicators.
The study specifically asks:
- Are gender differences in the dependent variables larger or smaller in countries with higher gender equality?
- How do these differences relate to dimensions such as power distance, Schwartz’s cultural values, and Minkov’s cultural dimensions?
The dataset covers 21 countries across all continents, selected to represent global diversity without significant deviation from worldwide averages on more than 20 key indicators. The included countries are: Australia, Brazil, Bulgaria, China, Colombia, Germany, India, Indonesia, Italy, Japan, Mexico, Philippines, Poland, Romania, Saudi Arabia, South Africa, Spain, Sweden, Turkey, United States, Vietnam.
Anticipated Findings or Key Areas of Focus
While detailed findings will be presented in forthcoming papers, the dataset is designed to answer:
Whether cultural values moderate gender differences in:
- Cognitive reflection
- Distributional preferences (envy, compassion, self-interest, egalitarianism, social efficiency, altruism)
- Loss aversion and risk aversion
- Time preferences (short- and long-term)
- Taste for competition (self- and other-referenced)
- Overconfidence (overestimation and overplacement)
- Math ability
Whether patterns observed in individual countries align with global-level correlations between gender differences and cultural or socio-economic indicators.
Potential Implications
For researchers: Enables robust cross-country comparisons of gender differences in cognition and preferences. Supports testing of cultural frameworks (e.g. Hofstede, Schwartz, Minkov) against behavioural data.
For educators:
Offers a large-scale, representative dataset for teaching statistical methods, cultural analysis, and behavioural science.
For consultants and trainers:
Provides empirical grounding for cultural diagnostics and gender-inclusion strategies.
For policymakers:
Informs evidence-based policies on education, equality, and behavioural change by linking cultural indicators to observed behavioural differences.
Methodology
- Sample: Minimum 4,200 participants, with at least 100 women and 100 men per country.
- Design: Cross-country dataset, 21 countries selected using power calculations and representativeness testing against 127-country benchmarks.
- Dependent variables: Measured via standardised decision-making tasks with real monetary incentives (1% chance of payment based on performance).
- Country-level indicators: Gender equality, power distance, Schwartz’s values, Minkov’s dimensions, GDP per capita.
Analytical Approach
Analytical approach:
- Multilevel regressions with gender and country-level indicators as explanatory variables.
- Cross-level interactions to assess moderation effects.
- Two-stage individual participant meta-analysis to combine results and assess heterogeneity.
Research Limitations & Implications
Results are not yet available and will be published in subsequent papers.
Project Details
- Title: TBA
- Partners: Michael Schachner, Head of Research at The Culture Factor Group Oy, Antonio Espin, behavioral economist at the University of Granada, Hester van Herk, Professor of Marketing at Vrije Universiteit Amsterdam, Michael Minkov, Professor of Cross-Cultural Studies at Varna University of Management, and Pablo Brañas, Professor of Behavioral Economics at Loyola Andalucia University.
- Timeline: Ongoing