Aaron Rockwell – Staff Cultural Advisor
Gerard (Geert) Hofstede developed a system of four elements to try and put a finger on what makes different cultures different. The whole idea was developed through IBM data that Hofstede gathered while working as the head honcho of the personnel research department (he collected over 100,000 surveys). He took time off from IBM to crunch the numbers, and found patterns among different countries that led him to settle on four cultural dimensions, plus another two which were added later: Power Distance Index (PDI), Individualism versus Collectivism (IDV), Masculinity versus Femininity (MAS), Uncertainty Avoidance Index (UAI), Long Term Orientation versus Short Term Normative Orientation (LTO), and Indulgence versus Restraint (IVR). As T-birds, I think these should be common knowledge – so let’s jump into the data! We will be looking at the top 20 countries according to GDP (PPP).
Best Buds (Closet Cultures):
Courtesy: wikipedia.org
Brazil and Turkey: I really enjoy that while Turkey and Brazil are different in location, as well as so many other elements, they are nearly perfect cultural-dimension matches! Turks and Brazilians would probably get along swimmingly.
Australia and the US: Australia and the United States have been strong allies for quite some time (just bad phone buddies recently), and we rotate armed forces and fight in the same wars. This strong link makes sense based on our cultural similarities.
Far Buds (Furthest Cultures):
Australia and Russia: Of the top 20 countries (GDP), the two with the highest degree of cultural difference are Australia and Russia. Russian and Australian relations have been strained for a while. Before Russia invaded the Crimea (2014), a 2013 BBC poll showed that Australian attitudes toward Russia were 29% ‘mainly positive’ and 53% ‘mainly negative’. The top three largest cultural difference countries are Australia, the United States, and the United Kingdom vs. Russia. It’s possible the Cold War was rooted in these deep cultural differences.
| Cultural Degree of Separation | ||
| Australia | 286 | Russia |
| United States | 283 | Russia |
| United Kingdom | 277 | Russia |
Most Unique (Sum of Total Degrees of Separation):
Lower rank means less distance to the sum of all other countries.
China: Compared to the other 20 countries, China is the most unique, which means that the summed variance of every element of their culture, compared to other cultures, was the largest.
| Rank | Total Sums of Distance | Country |
| 1 | 2133 | Turkey |
| 2 | 2153 | Brazil |
| 3 | 2165 | Spain |
| 18 | 3207 | Russia |
| 19 | 3233 | Mexico |
| 20 | 3249 | China |
Top 20 GDPs Average:
As expected, the average of all the scores regress toward 50 (the median), but not completely. I think this is because the nature of surveys that scale between 1-100, or any other number scale. The best way to usefully display data would be to use mean and standard deviations.
-Power Distance Index (PDI): Avg. 62, StDev: 19
-Individualism versus Collectivism (IDV): 50, StDev: 26
-Masculinity versus Femininity (MAS): 55, StDev: 15
-Uncertainty Avoidance Index (UAI): 66, StDev: 20
-Long Term Orientation versus Short Term Normative Orientation (LTO): 53, StDev: 25
-Indulgence versus Restraint (IVR): 48, StDev: 19
Mexico falls outside of two standard deviations in the indulgence/restraint dimension, with a high indulgence score (97), and Japan falls outside of two standard deviations on the masculinity/femininity scale with a high masculinity score (95). Another thing showcased is how the world as a whole really avoids uncertainty; this is probably why China is so unique because they embrace the changing landscape.
Conclusion:
After reading Hofstede’s book, I do believe that he was able to choose smart data and pare it down in an equally intelligent fashion. It can tell a helpful and enlightening story. I think ultimately, machine learning and even bigger data will outpace Hofstede’s work by potentially finding even more subtle, non-survey created ways to parse our societies. But until then, thanks Geert!