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Op-ed - Written by on Monday, December 15, 2008 18:50 - 6 Comments

Naumi Haque
The smaller your home, the cooler your phone

The Wikinomics team recently sat down for lunch with Aaron Kim, Senior Managing Consultant in Emerging Technologies for IBM Global Business Services (blog, Twitter). Among the various meandering discussions, one of the more interesting observations made was Aaron’s notion that population density and average home size has a direct relationship with mobile technology adoption.

It makes sense intuitively; the higher the population density and the tighter the living quarters, the more likely you are to spend time away from home or in “third spaces.” Similarly, if you have a large comfortable home and long distances make travel more infrequent, you will be less likely to need “on-the-go” technology, and more likely to invest in desktop computers and broadband in the home. The proposition that one’s propensity to use mobile tech is directly related to population density is an intriguing one, so I thought I’d do some further investigation. Using population density figures from Wikipedia along with mobile penetration stats from the OECD and wireless penetration rates from RCR Wireless, I compiled a chart showing data from 20 countries.

The trend line isn’t entirely obvious, but mind you, this is very “back-of-the-napkin” type analysis; and of course, other factors such as a population’s affluence, infrastructure availability, domestic cost of technology, and cultural tendencies all factor into adoption rates as well. Still, I think it’s a neat macro way to think about the decision to invest in mobile.

Some clear outliers on the chart are Finland, New Zealand, and Australia, which have low population density, but high mobile adoption rates, as well as Japan and South Korea, which have high population density, but below 80% mobile adoption. Hong Kong and Singapore were purposely left off the chart since their density figures (in the 6,400/square km range) skew the vertical axis, but both have adoption rates close to 100%. Note: All the data used in the chart is from 2005.

Update:

Based on Aaron’s comment below, I thought I’d share this additional graph, from an amazing site www.nationmaster.com (for the curious statistician).  It plots size of house (based on % of homes with five or more rooms) versus mobile phone adoption (per 100 people).  Data is from 2002.



6 Comments

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engineer
Dec 15, 2008 20:57

I hate to be that guy, but I think your plot does more to disprove your hypothesis than it does to prove it.

There doesn’t really seem to be any trend there at all.

Naumi Haque
Dec 15, 2008 23:07

Engineer, thanks for the critical eye – you’re absolutely right, the data could be read either way to prove or disprove the hypothesis. However, there are some compelling examples that do fit the model. Specifically, I think the Americas compared to Europe is an interesting dynamic. Canada, Mexico, and the United States all have low density and low adoption. European countries, by comparison, all have a higher population density and higher mobile penetration as well.

Country………….Pop/km2……….Mobile Index
Netherlands…………………395……………..101
United Kingdom……………246……………..106
Germany……………………..232………………92
Italy…………………………….193………………117
Switzerland………………….176………………90
Czech Republic……………..132………………111
Denmark……………………..127………………98
Portugal………………………114………………109
France…………………………110……………….77
Spain…………………………….89………………..99
Mexico………………………….53………………..45
United States………………..31…………………72
Canada…………………………..3………………….52

Like I said, it’s by no means scientific, just an interesting conversation starter. For a proper comparison, I think you’d also have to look at the percentage of the population that lives in high-density areas versus low-density areas within each country. In the end, perhaps it just comes down to an urban versus rural argument.

Aaron Kim
Dec 19, 2008 14:15

Hey Naumi,

I suspect you would see a slightly better correlation if you can get data on average house sizes. Also, cell phone adoption rates and device sophistication are likely driven also by other factors such as landline infrastructure, network technology, disposable income and demographics. Not sure if you’ve seen the TED Talk video with Malcolm Gladwell talking about spaghetti sauce. There’s an interesting story there about plotting results and trying to find an explanation when dots are all over the place.

Naumi Haque
Dec 19, 2008 23:11

Thanks Aaron. Great video – I think everyone should check it out:
http://www.ted.com/index.php/talks/malcolm_gladwell_on_spaghetti_sauce.html.

Also, I looked for data on home sizes and found this amazing Web site:
http://www.nationmaster.com
and even a ready-made graph for home size vs. mobile:
http://www.nationmaster.com/plot/peo_siz_of_hou/med_mob_pho/flag

Aaron Kim
Dec 23, 2008 12:53

I like the nationmaster site. Humm. Weak correlation eh? At least two possibilities there: my theory is completely wrong, or it needs to be refined. I’m leaning towards the conclusion that all social media and technology adoption patterns need to be assessed within certain boundaries to be meaningful. The reason is that there is a large number of drivers that can determine the adoption outcome, and any single variable will fail to be a good predictor that applies globally. My academic background is in Biology, and I see parallels in trying to explain why, for example, large apes exist in Africa and Asia but not in South America. We may need our own version of Alfred Russel Wallace to examine the geographical patterns for tech adoption :-)

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