On Culture

Introduction

As someone who works in the field of consumer behaviour, and  has been living as an expat in the past 5 years, I have been keenly interested in the topic of culture.
From a professional perspective, understanding how background affects the decisions of a certain cohort of customers, has an obvious implications for the marketing strategies a company employs in managing its B2C relationships. And on a more personal level - knowing how culture affects the decisions of your foreigner friend, can help you in better empathizing with that friend, and thus make you a better person.
Accounting for the differences between cultures could be a Sisyphean task, though, as there are numerous factors that will vary in importance depending on the context. Hence, a popular approach among researchers on the topic is to create a framework with a limited number of cultural dimensions for a given context of use. A well known framework of this kind is Hofstede's Cultural Dimensions Theory. While it has its fair share of criticism, it is generally considered as one of the most comprehensive models by those studying culture for business applications.

Hofstede's website has a good tool for comparing two countries and I give it additional points for using my favourite Highcharts library. Nevertheless, one thing that lacks, and would be interesting for overall comparison purposes, would be to visualize each of the 6 dimensions on the world map.
So, below I will briefly summarize what each dimension is about and I will post a visualization each one spreads on the world map. At the end I will provide the code I used to generate it.

One important note - if your mobile device does not support Java, the graphs below won't load.

Power Distance

The Power Distance dimension expresses the degree to which the members of a society accept the unequal distribution of power. People in countries with low power distance (light green) would be aiming at equalizing the distribution of power and demanding justification for inequalities. Whereas individuals in countries with high power distance (dark green) will be more likely to be accepting of hierarchical order and would be less likely to require justification.
Here's how countries look like on this dimension.

Individualism

The definition of this dimension is rather straight forward - in more individualistic societies (dark green) members are expected to take care of themselves and their immediate families, while personal achievements and individual rights are essential. On the other hand, in more collective societies (light green) individuals would usually have a large extended family, and would act as a part of a larger group.

Masculinity

Masculine societies (dark green) value assertiveness, competitiveness, ambition to power and the difference between gender roles will be more pronounced. In contrast, feminine societies will value modesty and cooperation.

Uncertainty Avoidance

As the name clearly suggests, this dimension measures to what extend a society is willing to tolerate uncertainty. Countries with high uncertainty avoidance index (dark green) will strive to minimize the anxiety from uncertainty by maintaining a governing code and by not tolerating unconventional behaviours. Societies with lower uncertainty avoidance tend to be more pragmatic and accepting of the changing nature of life. They tend to have fewer rules and encourage individuals do discover their own truth.

Long-term Orientation

Again, as the name clearly suggest, societies scoring high on this dimension (dark green) will encourage future orientation that will manifest itself in behaviours related to persistence, saving, and educating oneself to prepare for the future. Countries with more short-term orientation promote values related to the past and the present -  honouring traditions, fulfilling one's social obligations, reciprocation and so on.

Restraint  vs. Indulgence

The final dimension of Hofstede's framework measures whether a society is accepting of gratification coming from the exercise of natural human drives or if the society tries to abolish gratification of needs through strict social norms. In more restrained societies (light green) individuals will expect material rewards for a job well done and will pay attention to status items. In contrast, societies with high indulgence index (dark green) would not be so easily motivated by material rewards and items need to fulfil a purpose rather serve as a status symbol.

Code

I scraped the data from various sources, and I used Hofstede's website to manually filled in some of values I was missing. So, I can't provide you with the source of my data, but if you want to play around with it - you can easily scrape it from the java charts above.

I generated the charts with Google vis library in R. Here's my code

# First, load your data

hofs.db<-read.csv("C://Type-a-path-here//HofstedeDimensions.csv", sep=";")

hofs.db$ctr<-as.character(hofs.db$ctr)
hofs.db$country<-as.character(hofs.db$country)



# Rename country names that are not recognized by the googleVis library


hofs.db[2][hofs.db[2]=='Bosnia']<-'Bosnia i Hercegovina'
hofs.db[2][hofs.db[2]=='Czech Rep']<-'Czech Republic'
hofs.db[2][hofs.db[2]=='Dominican Rep']<-'Dominican Republic'
hofs.db[2][hofs.db[2]=='Great Britain']<-'United Kingdom'
hofs.db[2][hofs.db[2]=='Korea South']<-'South Korea'
hofs.db[2][hofs.db[2]=='Kyrgyz Rep']<-'Kyrgyzstan'
hofs.db[2][hofs.db[2]=='Macedonia Rep']<-'Macedonia'
hofs.db[2][hofs.db[2]=='U.S.A.']<-'United States'


# Give the columns a nice  name

colnames(hofs.db)[3]<-"Power Distance"
colnames(hofs.db)[4]<-"Individualism"
colnames(hofs.db)[5]<-"Masculinity"
colnames(hofs.db)[6]<-"Uncertainty Avoidance"
colnames(hofs.db)[7]<-"Long-Term Orientation"
colnames(hofs.db)[8]<-"RestraintRestraint vs Indulgence"


#Create the plot. To create one per each dimension you'd need to manually change the numvar below

library(googleVis)

G1 <- gvisGeoMap(hofs.db,locationvar='country', numvar='Power Distance'
                 #, hovervar='Power Distance'
                 ,options=list(dataMode='regions'
                               ,width=1012
                               ,height=649
                               ,showZoomOut=TRUE
                               #,colors=c('0x80FF51',0xFF5151)
                 )
)

# Remove caption
G1$html$caption<-''
#REmove the footer
G1$html$footer <-""

print(G1, 'chart')