My individual square of land, 9 meters on 9

My editorial

And so I am building something with a strategy. Last year, 365 days ago, I was just beginning to play with scientific blogging. Now, I have pretty clear a vision of how I want to grow over the next 365 days. My internal bulldog is sniffing around two juicy bones: putting up a method of and pitching a product, relevant to the teaching of social sciences by participation in the actual doing of research, and, on the other hand, putting together an investment project in the domain of smart cities. In this update, I start developing more specifically on that second one, and I focus on two things. Firstly, I perceive smart cities as both technological and social a change, which develops through diffusion of innovation. Very nearly axiomatically, the phenomenon of diffusion in innovations is represented as a process tending towards saturation. I want to find a method, and, hopefully, the metrics relevant to measuring the compound size of the market in the phenomenon called ‘Smart Cities’, mostly in Europe. In the same time, I want to test the tending-towards-saturation approach in forecasting the size of this market.

The emergence of smart cities, as both an urban concept and a business model, is made of smaller parts. There is investment in the remodelling and rebuilding of infrastructure. On the other hand, there is the issue of energy, both in terms of efficiency in its use, and in terms of its renewable sourcing. Finally, there is the huge field of digital technologies, and, looming somehow at the horizon, the issue of Fintech: the use of digital technologies to create local, flexible monetary systems. I am collecting data, step by step, to acquire a really sharp view of the situation, and so my internal curious ape comes by that report ‘The State of European Cities’ , as well as by that article ‘Smart Cities in Europe’ , and finally it swings to that interesting website: ‘Organicity’ . There seem to be two common denominators to all the reports and websites on this topic: experimentation and teaming up. Cities build their smart cities in consortiums rather than single-handedly. Each project is an experiment, to the extent that ‘established technologies’ are essentially the opposite of what business people expect to invest in when they invest in a smart city.

When I teach my students the fundamentals of business planning, I ask them frequently to look at the business concept from two sides: that of the enthusiastic founder, and that of a conservative investor. The balance sheet of the new business is likely to take shape at the intersection of those two approaches. I am adopting the same approach with my business concept. If I were a truly conservative an investor, I would ask, among other questions, what type of business am I supposed to put capital into, and what is the workable business model. The main types of business that come to my mind, regarding smart cities, are: development of real estate, construction, and technical services. However smart a city is becoming, it is made of architectural structures: buildings, roads, rails etc. Someone owns them before the smart city starts burgeoning, and someone owns them when the smart city is already running. Question: are the someones who own those structures afterwards the same someones who owned them beforehand, or are they different someones? What does the transfer of property in real estate look like in those smart cities? Another thing that I teach my students is ‘When you know nearly nothing about a market or a business, look at the prices and the demographics in the first place. Is the market conflating with people, is it stationary, or is it deflating? Are there any prices, which you can qualify as equilibrium prices, i.e. prices virtually exogenous to the bargaining power of individual market players, and clearly sensitive to other economic variables? If you can spot such prices, what trends do they display?’. Right, so now, I am applying my wisdom for sale to my own plans, and I try to figure out those things for selected cases of smart cities, just to make my hand.

I have recently read a lot about a project of smart city, namely the ‘Confluence’ project in Lyon, France. The place is dear to my heart, as I spent quite a chunk of my youth in Lyon, and I am glad to return there, whenever I can. The Confluence Project is located in the 2nd district of Lyon, at what the locals call ‘Presqu’Ile’, i.e. ‘Nearly an Island’, and the confluence of two rivers: Rhone and Saone. From the bird’s view, it is like an irregular, triangular wedge, with its top pointing South at the exact confluence of the two rivers, and its base resting, more or less, on the Perrache rail station. I am having a look at the local prices of real estate. As I visit the website ‘Meilleurs Agents’  , I can see an almost uninterrupted growth in the price per 1 m2, since 1994. Surprisingly, even the burst of the housing bubble in 2007 – 2009 didn’t curb much that trend. Over the last 10 years, it means almost 31% more in the average price of square meter. I focus on the prices of flats. Right now, the average price in Lyon is 3 690 € per square meter, and that average is expected in a general span from 2 767 € to 5 535 €. Against this general background, I take a few snapshots at different addresses. First, I have a glance at a long street – Cours Charlemagne – which almost makes the longitudinal backbone of the Confluence wedge. The average price per 1 m2 is 3 783 €, in a range from 2 664 € to 5 040 €. That average is slightly higher than the whole city, but the range of prices has slightly lower extremities.

Cours Charlemagne connects the posh neighbourhood of Perrache, in the North, to really industrial a place, at the Southern junction of the two rivers. Thus, I take a closer focus, and I target those different environments. Angle of Quai Rambaud and Rue Suchet, a truly posh place in the Northern part of Confluence, displays an average price of 4 725 € per 1 m2, in a range from 3 186 € to 6 207 €. Yes, baby, it just rockets up. Now, I take a little stroll to the South, apparently advancing towards lower prices, and I call by Rue Paul Montrochet. It should be cheaper than up North, and yet it is not: the average price is 5 144 € per square meter, in a range from 3 461 € to 6 483 €.

As usually, observing reality has been of some value. Provisional hypothesis, based on the case of Lyon-Confluence: smart cities grow where the prices of real estate grow. Now, a bit of a bow to reverend Malthus: I check the demographics, with The World Population Review , and I show those numbers in Table 1, below. There has been, and there still is, quite a consistent demographic growth. Basically, if you calculate the annual average growth rates in, respectively, the price of 1 m2 in residential space, and the local population, those two rates look almost like twins: around 3% a year. My provisional hypothesis puts on some ornamentation: smart cities grow where the prices of real estate grow, and where population grows.

Table 1 The population of Lyon, France (urban area)

Year  Population Growth Rate (%) Growth
2030  1 814 000 3,72%  65 000
2025  1 749 000 3,98%  67 000
2020  1 682 000 2,81%  46 000
2017  1 636 000 1,68%  27 000
2015  1 609 000 3,74%  58 000
2010  1 551 000 3,68%  55 000
2005  1 496 000 3,67%  53 000
2000  1 443 000 2,78%  39 000
1995  1 404 000 2,48%  34 000
1990  1 370 000 2,54%  34 000
1985  1 336 000 4,54%  58 000
1980  1 278 000 8,49%  100 000
1975  1 178 000 5,56%  62 000
1970  1 116 000 8,67%  89 000
1965  1 027 000 13,61%  123 000
1960  904 17,71%  136 000
1955  768 5,06%  37 000
1950  731 0,00%  –

source: , last accessed January 11th 2018

The decision makers of the Lyon-Confluence project claim they are in some sort of agreement with two other initiatives: Vienna and Munich. I quickly perform the same check for Vienna as I did for Lyon. In this case, the initiative of smart city seems to be city-wide, and not confined to just one district. As for the prices of apartments, I start with the Global Property Guide . Apparently, the last six years brought a sharp rise in prices (plus 39%), still those prices started curbing down a bit, recently. A quick glance at Numbeo shows an average price of 7 017,18 € per 1 m2 in the city centre, in a range from 4 800 € to 10 000 €, and further out of the centre it makes like 3 613,40 € per square meter on average, comprised between 3 000 € and 5 000 €. On the whole, Vienna looks a shade more expensive than Lyon. Let’s check the demographics, once again with The World Population Review (Table 2, below). Quite similar to Lyon, maybe with a bit more bumps on the way. Interestingly, both initiatives of smart cities started to take shape around 2015, when both cities started to flirt with more or less 1,5 million people in the urban area. Looks like some sort of critical mass, at least for now.

Table 2 The population of Vienna, Austria (urban area)

Year Population Growth Rate (%) Growth
2030 1 548 000 0,98% 15 000
2025 1 533 000 2,06% 31 000
2020 1 502 000 2,32% 34 000
2017 1 468 000 2,09% 30 000
2015 1 438 000 6,28% 85 000
2010 1 353 000 7,89% 99 000
2005 1 254 000 4,33% 52 000
2000 1 202 000 -3,14% (39 000)
1995 1 241 000 1,89% 23 000
1990 1 218 000 -3,87% (49 000)
1985 1 267 000 -2,46% (32 000)
1980 1 299 000 0,23% 3 000
1975 1 296 000 0,15% 2 000
1970 1 294 000 10,13% 119 000
1965 1 175 000 10,85% 115 000
1960 1 060 000 13,25% 124 000
1955 936 12,64% 105 000
1950 831 0,00%

source: , last accessed January 11th, 2018

Good. As my internal curious ape turns and returns those coconuts, ideas start taking shape. At least one type of socio-economic environment, where that curious new species called ‘smart cities’ seem to dwell, is an environment where them growth rates in housing prices, and in population, are like 3% or more. One million and a half people living in a more or less continuous urban area seem to make like a decent size, in terms of feeding grounds for a smart city. Prices of residential real estate, associated with the emergence of smart cities in Europe, seem hitting like 4 500 € or more. This is probably just one type of environment, but one is already better than saying ‘any environment’. The longer I do social sciences, the more I am persuaded that we, humans, are very simple and schematic in our social structures. Theoretically, with the individual flexibility we are capable of, the science we have, and with Twitter, we could form an indefinitely diverse catalogue of social structures. Yet, it is more like in a chess game: there are just a few structures that work, and others just don’t, and we don’t even full comprehend the reasons for them not working at all. When we talk business and investment, there are some contexts that allow the deployment of a business model, whilst it just doesn’t work in other contexts. Same thing here: the type of environment I am casually sketching is the one where smart cities work in terms of business and investment.

My business plan for investing in smart cities has certainly one cornerstone, namely that of gains in the market value of real estate involved. One cornerstone is not bad at all, and now I am thinking about putting some stones under the remaining three corners. In that report which I mentioned earlier, namely report ‘The State of European Cities’ , I have already spotted two interesting pieces of information. Firstly, the sustainable density of population for a smart city is generally the same as for sustainable public transport: 3000 people per km2 or more. Secondly, the dominant trend in the European urbanisation is the growth of suburbs and towns, rather than cities strictly spoken. It pertains to my home country, Poland, as well. Thus, what we have as market, is a network of urban units moderate in size, but big in connections with other similar units. Two classes of business prospects emerge, then, regarding the investment in smart cities. Following my maths classes at school, I call those prospects, respectively, the necessary context, and the favourable context. The necessary is based on the density of population: the more we are per square kilometre, the more fun we are having, and the special kind of fun we can have in a smart city requires at least 3000 people per km2, or, in other words, each individual person having for their personal use no more than a square of 18 meters on 18. The favourable is made of real estate prices, and demographic growth, the former hitting above 4 500 € per 1 m2, and growing at 3% per annum, on average; the latter needs to make the same 3% a year.

By the way, I made a quick calculation for my family and our house. We live in a terraced house, located on a plot of land of 250 m2. We are three, which makes 83,6 m2 per capita, which, in turn, means that each capita has an individual square of land the size of 9,14 meters on 9,14. We are double the density of population required for a smart city. There is no other way: I have to go for it.

6 thoughts on “My individual square of land, 9 meters on 9

Leave a Reply