Practical takeaways

I am trying to develop a coherent line of logic for the most basic courses I teach in the winter semester, namely ‘Microeconomics’ and ‘Management’. This is the hell of an unusual semester. The pandemic makes us pass largely to online teaching, for one. The pandemic itself is fascinating as social phenomenon and I want to include its study into my teaching, for two. Thirdly and finally, over the last 12 months, I developed an acceptably solid hypothesis of collective intelligence in human social structures, together with a method of studying said structures with the use of artificial neural networks.

I teach ‘Microeconomics’ and ‘Management’ to essentially the same group of students, 1st year undergraduate. There might be minor difference between those two subjects as regards the Erasmus students asking to enrol, yet it is really minor. Thus, I decided to combine my teaching in microeconomics and management into one thread, which consists, for my students, in graduating those two courses (i.e. ‘Microeconomics’ and ‘Management’) by preparing business plans as graduation projects. Why do I adopt such a didactic stance? First of all, I have been putting a lot of emphasis on the skill of business planning over the last 5 years or so. I like believing my students have some real takeaways from my classes, i.e. true practical skills, useful in daily life. Being able to put together an acceptably bullet-proof business plan is a skill which is both practical and logically connected to Microeconomics and Management. Yes, management too. In real life, i.e. when a young person starts a corporate career and as soon as he or she stops dreaming about instantly becoming a CEO, they will be climbing the steps of hierarchical ladder in some kind of corporate structure. The first remotely managerial assignment he or she is likely to have will be to manage a project, thus, to build a small team, negotiate a result-based budget, interface with other parts of the organization in a client-supplier manner etc. Once you can prepare a good business plan, you can plan for an intrapreneurial project as well.     

Secondly, when you want to understand how something works, try to build it. Want understand microeconomics? Cool. Build the microeconomics of something: a digital start-up, a food store, a construction business, whatever practical and workable comes to your mind. As soon as you start building up your business concept, you will quickly grasp distinctions such as, for example, that between assets and equity, that between monopolistic pricing and competitive pricing, or, last but not least, your short-term cash-flow, in, respectively, the presence or the absence of amortization. Building a business plan can even help understanding those cherries on the cake of microeconomics, such as the new institutional theory. As soon as you ask yourself the practical question ‘Will it be better for my start up to invest in our own server, or maybe it is more workable to outsource server power?’, you will grasp, lightning fast, the fine niceties of transactional costs.  

Long story short, I combine the teaching of microeconomics with that of management, in the courses I have with 1st year undergraduate students, and I make them graduate both with a project, which, in turn, consists in preparing a business plan. Thus, in the structure of the online course on MS Teams, I give both groups access to the basic course of business planning, on the website of my blog ( ).

From there on, I lead two parallel and concurrent lines of teaching. As regards Microeconomics, I focus on something like a spritzer. What? What is a spritzer? Oh, the youth of today… A sprizter, my dear children, is a drink made of wine, white or rosé, mixed with water and lemon juice, and a zest of ice cubes. Looks innocent, is enormously tempting during the summertime, and, comparatively to its alcohol content, kicks like a mule. My sprizter is made of classics, mostly Adam Smith ( ) and Carl Menger ( ), who come as the gentle and innocent mixture of water and orange juice, combined with wine, in the form of a strong grasp on the present-day crazy ride of digital economy based on cloud computing, the pandemic and the resulting sudden shift towards medical technologies, and all that against the background of a major shift in our energy base, from fossil fuels to renewables as well as towards a possible new generation of nuclear.

I plan to present my teaching of Microeconomics as a combination of quotes from those two big classics, and references to what is happening right now. As for Management, I stick to the spritzer philosophy. The wine is the same, i.e. all the things that are happening around, whilst just one classical name comes as lemon juice and water in one: Nicolo Machiavelli ( ).

So far, when I am writing those words, I have prepared 5 video lectures along the lines I laid out in the preceding paragraphs. In Microeconomics & Management. Opening lecture [ ], I introduce the course of ‘Microeconomics’, as well as that of ‘Principles of Organization and Management’, which I will be holding with the Andrzej Frycz – Modrzewski Krakow University (Krakow, Poland). You can download the corresponding Power Point presentation from:

In ‘Fundamentals of Economics #1’ ( I open up with the first, more or less formalized lecture in the fundamentals of economics. I use five essential readings – Netflix Annual Report 2019, Discovery Annual Report 2019, Adam Smith’s ‘Wealth of Nations’, David Ricardo’s ‘Principles of Political Economy and Taxation’, and Carl Menger’s ‘Principles of Economics’ – in order to show the basis axes of approach to economic sciences. Firstly, it is the special social tension between the diversity of skills and social roles, on the one hand, and the fact of them all summing up to one big body of labour (Smith). Secondly, I introduce the distinction between capital and labour, and the importance of capital resources (Ricardo, example Netflix). Thirdly, and finally, I present the concept of economic good (Carl Menger) and the importance of translating technology into products. Finally, in Fundamentals of Economics #2 The basic theory of markets [], I present the behavioural essence of markets as structure of tacit coordination between humans.

As regards Management, I have shot two video lectures so far. In Fundamentals of Management #1 [  ], I present the main lines of teaching and study in the path of Management. More specifically addressed to my students in the majors of Management and International Relations. The link to power point: . In Fundamentals of Management #2 Team building [  ], I describe the 4 fundamental tools of team building: recruitment, alignment of values and goals, their proper communication, and the assessment of performance. The link to power point:

Neighbourhoods of Cineworld

As I write about cities and their social function, I want to mess around a bit with a business model known as Real Estate Investment Trust, or REIT. You can consult my video on REITs in general, namely the one titled ‘In ‘Urban Economics and City Management #2 Case study of REIT: Urban Edge and Atrium [ ]’. I study there the cases of two REITs, i.e. Real Estate Investment Trusts, namely Urban Edge (U.S.) and Atrium (Central Europe).

I am pursuing the idea of investment as fundamental social activity. I intuitively guess that cities will be developing along the lines of what we will be collectively investing in. By investment I mean a compound process which loops between two specific activities: the accumulation of resources, and the allocation thereof. Since the dawn of human civilization, we have been putting things in reserve. First, it was food. Then, we discovered that putting some of our current resources into building durable architectural structures paid off: warmer in winter, cooler in summer, plenty of room for storing food, some protection against anyone or anything willing to take that food from us etc. Yes, architectural construction is investment. I put my resources – capital, labour, natural resources – into something that will pay me back in the future, over a prolonged period of time.

Investment is an interesting component of our collective intelligence. Our society changes in directions and at paces very much determined by the things we willingly invest in. We organize those things according to the principle of delayed gratification, as controlled today’s deprivation oriented on having some durable outcomes in the future. I deliberately use the term ‘things’, so general and plain. We invest in railroads, and we invest in feeling safe from natural disasters. We invest in businesses, and we invest in the expectation of having the most luxurious car/house/dress/holiday in the entire neighbourhood. We invest in collections of physical things and we invest in ideas.

We have governments and political systems because we have that pattern in our collective intelligence. Governments are in place because and as long as they have legitimation, i.e. because and as long as at least some part of the population accepts being governed, without being coerced into obedience. People give legitimation to governments because they accept sacrificing some of the presently available resources (taxes) and freedoms (compliance with the law) in order to have delayed gratification in the form of security, territorial stability, enforceable contracts etc.

Thus, we go in the direction we invest into. That direction is set by the exact kind of delayed gratification we expect to have in the future, and by the exact type of resources and freedoms we give away today in order to have that delayed thing. Cities evolve exactly according to that pattern. Cities look what they look today because at some point in the past, citizens (yes, the term ‘citizen’ comes from the status of being officially acknowledged and accepted as permanent resident of a city) collectively invested in a given type of urban structures. It is important to understand the way I use words such as ‘collective’ and ‘collectively’. People do things collectively even when they say they completely disagree about doing those things together. This is called ‘tacit coordination’. Let’s consider an example. We disagree, in a city, about the way of organizing a piece of urban space. Some people want to build residential structures there, essentially made for rent. Some others want to see a green space in exactly the same spot, like a park. What you can see emerging out of that disagreement on the long run is a patchwork of residential buildings and green spaces, all over the neighbourhood.

Disagreement is a pattern of tacit coordination, thus a pattern of collective intelligence. We disagree about things which we judge important. Openly expressed disagreement is, in the first place, tacit agreement as for what we really care for (object of disagreement) and who really cares for it (protagonists of disagreement). In my personal experience, if a collective, e.g. a business organization, follows a strategy with unanimous enthusiasm, without any voices of dissent, I am like ‘Ooooh, f**k! That thing is heading towards the edge of the cliff…’.

Good. We invest, i.e. we are collectively intelligent about what kind of present satisfaction we sacrifice for the sake of future delayed gratification. The most important investments we collectively make are subject to disagreement, which is more or less ritualized with legal norms and/or political institutions. Here comes an interesting case, disquietingly connected to real life. Cineworld, a chain of cinema theatres ( has just announced that ‘In response to an increasingly challenging theatrical landscape and sustained key market closures due to the COVID-19 pandemic, Cineworld confirms that it will be temporarily suspending operations at all of its 536 Regal theatres in the US and its 127 Cineworld and Picturehouse theatres in the UK from Thursday, 8 October 2020’ (look up That provokes a question: what will happen to those theatres as physical places? Will the pandemic force a rethinking and reengineering of their functions in the surrounding urban space and of the way they should be managed? Is that closure of cinema theatres a durable, irreversible change or is it just temporary?

You can see the entire map of Cineworld’s cinemas under this link: . A bit of digital zoom, i.e. at, and you can make yourself an opinion about the Cineworld cinemas located in London under the brand of ‘PictureHouse’. Look at the Clapham PictureHouse ( ).  and at its location: 76 Venn St, Clapham Town, London SW4 0AT, United Kingdom. The neighbourhood looks more or less like that:

What can be done there? What will the locals collectively invest in? What will be the key features of that investment which they will be disagreeing about? These are low buildings; the neighbourhood looks like a combination of residential structures and small utility ones. Whatever can that cinema theatre be turned into, that thing will make sense for the immediate neighbourhood, like 5 kilometres around.

I turn that cursory reflection on the closure of Cineworld’s theatres into three pieces of teaching, namely as a case of Urban Development sensu stricte ( ),  for one, then as a case of Economic Policy (, for two, and finally as a case of International Economics (, because as cinemas close, folks are bound to spend more time in front of their private screens, and that means growth in the global market of digital entertainment.

Strangely accommodative of problems

I am returning to the strictly speaking written blogging, after a long break, which I devoted to preparing educational material for the upcoming winter semester 2020/2021. I am outlining a line of research which I can build my teaching around, in the same time. Something looms, and that something is my old obsession: collective intelligence of our human societies and its connection to artificial intelligence. Well, when I say ‘old’, it means ‘slightly seasoned’. I mean, I have been nurturing that obsession for a total of like 4 years, with having it walking around and talking like for the last 18 months or so. It is not truly old, even if ideas were red wine. Anyway, the current shade I paint into that obsession of mine is that human societies have a built-in mechanism of creating new social roles for new humans coming in, in the presence of demographic growth. Cities are very largely factories of social roles, in my view. Close, intense social interactions in a limited space are a mechanism of accelerated collective learning, whence accelerated formation of new skillsets, and those new skillsets, all they need is an opportunity to earn a living with and they turn into social roles.

I have a deep feeling that digital platforms, ranging from the early-hominid-style things like Twitter, all the way up to working and studying via MS Teams or Zoom, have developed as another accelerator of social roles. This accelerator works differently. It is essentially spaceless, although, on the large scale, it is very energy consuming at the level of server power. Still, early cities used to shape new social roles through the skilled labour they required to be built and expanded. A substantial part of whatever we think we know about mathematics and physics comes from geometry, which, in turn, comes from architecture and early machine-building. Similarly, digital platforms make new social roles by stimulating the formation of new skillsets required to develop those platforms, and then to keep them running.

Crazy thoughts come to my mind. What if we, humans, are truly able to think ahead, like really ahead, many generations ahead? What if by the mid-20th century we collectively told ourselves: ‘Look, guys. We mean, us. Cities are great, but there is more and more of us around, all that lot needs food, and food needs agricultural land to be grown and bred on. We need to keep the surface of agricultural land intact at the least, or slightly growing at best, whence the necessity to keep the total surface of urban land under control. Still, we need that space of intense social interactions to make new social roles. Tough nut to crack, this one. Cool, so here is the deal: we start by shrinking transistors to a size below the perceptual capacity of human sight, which is going to open up on a whole range of electronic technologies, which, in turn, will make it worthwhile to create a whole new family of languages just for giving them orders, to those electronics. Hopefully, after 2 or 3 human generations, that is going to create a new plane of social interactions, sort of merging with cities and yet sort of supplanting them’.

And so I follow that trail of collective human intelligence configuring itself in the view of making enough social roles for new humans coming. I am looking for parallels with the human brain. I know, I know, this is a bit far-fetched as parallel, still it is better than nothing. Anyway, in the brain, there is the cortex, i.e. the fancy intellectual, then we have the limbic system, i.e. the romantic Lord Byron, and finally there is the hypothalamus, i.e. the primitive stuff in charge of vegetative impulses. Do we have such distinct functional realms in our collective intelligence? I mean, do we have a subsystem that generates elementary energies (i.e. capacities to perform basic types of action), another one which finds complex cognitive bearings in the world, and something in between, which mediates between objective data and fundamental drives, forming something like preferences, proclivities, values etc. ?

Cool. Enough philosophy. Let’s get into science. As I am writing about digital platforms, I can do something useful just as well, i.e. I can do some review of literature and use it both in my own science and in my teaching. Here comes an interesting paper by Beeres et al. (2020[1]) regarding the correlation between the use of social media, and the prevalence of mental health problems among adolescents in Sweden. The results are strangely similar to the correlation between unemployment and criminality, something I know well from my baseline field of science, i.e. economics. It is a strong correlation across space and a weak, if not a non-existent one over time. The intensity of using social media by Swedish adolescents seems to be correlated positively with the incidence of mental disorders, i.e. adolescents with higher a probability of such disorders tend to use social media more heavily than those mentally more robust adolescents. Still, when an adolescent person increases their starting-point intensity of using social media, that change is not correlated longitudinally with an increased incidence of mental disorders. In other words, whoever is solid in the beginning, stays this way, and whoever is f**ked up, stays that way, too.

The method of research presented in that paper looks robust. The sample is made of 3959 willing participants, fished out from among an initial sample of 12 512 people. This is respectable, as social science comes. The gauge of mental health was Strength and Difficulties Questionnaire (SDQ), which is practically 100% standardized (Goodman & Goodman 2009[2]) and allows distinguishing between internalized, emotional and peer problems on the one hand, and those externalized ones, connected to conduct and hyperactivity. If you are interested in the exact way this questionnaire looks, you can go and consult: . The use of social media was self-reported, as answer to the question on the number of hours spent on social media, writing or reading blogs, and chatting online, separately for weekdays and weekends. That answer was standardized, on a scale ranging from 30 minutes a day up to 7 hours a day. Average daily time spent on social media was calculated on the basis of answers given.

The results reported by Beeres et al. (2020) are interesting in a few different ways. Firstly, they seem to discard very largely the common claim that increased use of social media contributes to increased prevalence of mental disorders in adolescents. Intensive use of social media is rather symptomatic of such disorders. That would reverse the whole discourse about this specific phenomenon. Instead of saying ‘Social media make kids go insane’, we should be rather saying ‘Social media facilitate the detection of mental disorders’. Still, one problem remains: if the most intense use of social media among adolescents is observable in those most prone to mental disorders, we have a possible scenario where either the whole culture forming on and through social media, or some specific manifestations thereof, are specifically adapted to people with mental disorders.

Secondly, we have a general case of a digital technology serving a specific social function, i.e. that of mediating social relations of a specific social group (adolescents in developed countries) in a specific context (propensity to mental disorders). Digital technologies are used as surrogate of other social interactions, in people who most likely have hard times going through such interactions.

Another paper, still warm, straight from bakery, by Lin et al. (2020[3]), is entitled ‘Investigating mediated effects of fear of COVID-19 and COVID-19 misunderstanding in the association between problematic social media use, psychological distress, and insomnia’. The first significant phenomena it is informative about is the difficulty to make a simple, catchy title for a scientific paper. Secondly, the authors start from the same hypothesis which Beeres et al. (2020) seem to have discarded, namely that social media use (especially problematic social media use) may give rise to psychological distress. Moreover, Lin et al. (2020) come to the conclusion that it is true. Same science, same hypothesis, different results. I f**king love science. You just need to look into the small print.

The small print here starts with the broad social context. Empirical research by Lin et al. (2020) was conducted in Iran, on participants over 18 years old, whose participation was acquired via Google Forms. The sample consisted of 1506 persons, with an average age of 26 years, and a visible prevalence of women, who made over 58% of the sample. The tool used for detecting mental disorders was the Hospital Anxiety and Depression Scale (HADS). The follow up period was of two weeks, against two years in the case of research by Beeres et al. (2020). Another thing is that whilst Beeres et al. (2020) explicitly the longitudinal within-person variance from the lateral inter-person one, Lin et al. (2020) compute their results without such distinction. Consequently, they come to the conclusion that problematic use of social media is significantly correlated with mental disorders.

I try to connect those two papers to my concept of collective intelligence, and with the use of artificial intelligence. We have an intelligent structure, i.e. humans hanging around together. How do we know we are collectively intelligent? Well, we can make many alternative versions of us being together, each version being like one-mutation neighbour to others, and we can learn new ways of doing things by choosing the best fitting version among those alternatives. On the top of that, we can do the whole stunt whilst staying acceptably cohesive as society. Among many alternative versions of us being together there is a subset, grouping different manners of using social media. Social media are based on artificial intelligence. Each platform runs an algorithm which adapts the content you see to your previously observed online behaviour: the number of times you click on an add, the number of times you share and repost somebody else’s posts, the number of times you publish your own content etc. At the bottom line, the AI in action here adapts so as you max out on the time spent on the platform, and on the clicks you make whilst hanging around there.

The papers I have just quoted suggest that artificial intelligence at work in social media is somehow accommodative of people with mental disorders. This is truly interesting, because the great majority of social institutions we have had so far, i.e. since however we started as intelligent hominids, has been actually the opposite. One of the main ways to detect serious mental problems in a person consists in observing their social relations. If they have even a mild issue with mental health, they are bound to have something seriously off either with their emotional bonds to the immediate social environment (family and friends, mostly) or with their social role in the broader environment (work, school etc.).   I made an educational video out of that quick review of literature, and I placed it on You Tube as: Behavioural modelling and content marketing #3 Social media and mental health

[1] Beeres, D. T., Andersson, F., Vossen, H. G., & Galanti, M. R. (2020). Social media and mental health among early adolescents in Sweden: a longitudinal study with 2-year follow-up (KUPOL Study). Journal of Adolescent Health,

[2] Goodman, A., Goodman, R. (2009) Strengths and Difficulties Questionnaire as a Dimensional Measure of Child Mental Health, Journal of the American Academy of Child & Adolescent Psychiatry, Volume 48, Issue 4,

2009, Pages 400-403, ISSN 0890-8567,

[3] Lin, C. Y., Broström, A., Griffiths, M. D., & Pakpour, A. H. (2020). Investigating mediated effects of fear of COVID-19 and COVID-19 misunderstanding in the association between problematic social media use, psychological distress, and insomnia. Internet interventions, 21, 100345,

New, complete course of Business Planning

I have just finished putting together a complete course of Business Planning. You can find the link on the sidebar. In a series of video lectures combined with Power Point presentations, you will go through all the basic skills of business planning: pitching and modelling your business concept, market research and its translation into financials, assessment of the optimal capital base, and thorough reflection on the soft side of the business plan, i.e. your goals, your risks, your people etc.

Click, dive into, dig through and enjoy.

Cautiously bon-vivant

I keep developing on a few topics in parallel, with a special focus on two of them. Lessons in economics and management which I can derive for my students, out of my personal experience as a small investor in the stock market, for one, and a broader, scientific work on the civilizational role of cities and our human collective intelligence, for two.

I like starting with the observation of real life, and I like ending with it as well. What I see around gives me the initial incentive to do research and makes the last pitch for testing my findings and intuitions. In my personal experience as investor, I have simply confirmed an initial intuition that giving a written, consistent and public account thereof helps me nailing down efficient strategies as an investor. As regards cities and collective intelligence, the first part of that topic comes from observing changes in urban life since COVID-19 broke out, and the second part is just a generalized, though mild an intellectual obsession, which I started developing once I observed the way artificial neural networks work.

In this update, I want to develop on two specific points, connected to those two paths of research and writing. As far as my investment is concerned, I am seriously entertaining the idea of broadening my investment portfolio in the sector of renewable energies, more specifically in the photovoltaic. I can notice a rush on the solar business in the U.S. I am thinking about investing in some of those shares. I already have, and have made a nice profit on the stock of First Solar ( ) as well as on that of SMA Solar ( ). Currently, I am observing three other companies: Vivint Solar ( ),  Canadian Solar ( ), and SolarEdge Technologies ( ). Below, I am placing the graphs of stock price over the last year, as regards those solar businesses. There is something like a common trend in those stock prices. March and April 2020 were a moment of brief jump upwards, which subsequently turned into a shy lie-down, and since the beginning of August 2020 another journey into the realm of investors’ keen interest seems to be on the way.

Before you have a look at the graphs, here is a summary table with selected financials, approached as relative gradients of change, or d(x).

 Change from 01/01/2020 to 31/08/2020
Companyd(market cap)d(assets)d(operational cash-flow)
First Solar+23,9%-6%Deeper negative: – $80 million
SMA Solar+27,5%-10%Deeper negative: -€40 million
Vivint Solar+362%+11%Deeper negative: – $9 million
SolarEdge+98%0+ $50 million
Canadian Solar+41%+4%+ $90 million

There are two fundamental traits of business models which I am having a close look at. Firstly, it is the correlation between changes in market capitalization, and changes in assets. I am checking if the solar businesses I want to invest in have their capital base functionally connected to the financial market. Looks a bit wobbly, as for now. Secondly, I look at current operational efficiency, measured with operational cash flow. Here, I can see there is still a lot to do. Here is the link to You Tube video with all that topic developed: Business models in renewable energies #3 Solar business and investment opportunities [Renew BM 3 2020-09-06 09-20-30 ; ].

Those business models seem to be in a phase of slow stabilization. The industry as a whole seems to be slowly figuring out the right way of running that PV show, however the truly efficient scheme is still to be nailed down. Investment in those companies is based on reasonable trust in the growth of their market, and in the positive impact of technological innovation. Question: is it a good move to invest now? Answer: it is risky, but acceptably rational; once those business models become really efficient, the industry will be in or close to the phase of maturity, which, in turn, does not really allow expecting abnormally high return on investment.  

This is a very ‘financial’, hands-off approach to business models. In this case, business models of those photovoltaic businesses matter to me just to the extent of being fundamentally predictable. I don’t want to run a solar business, I just want to have elementary understanding of what’s going on, business-wise, to make my investment better grounded. Looking from inside a business, such an approach is informative about the way that a business model should ‘speak’ to investors.

At the end of the day, I think I am most likely to invest in SolarEdge. It seems to have all the LEGO blocks in place for a good opening. Good cash flow, although a bit sluggish when it comes to real investment.

As regards COVID-19 and cities, I am formulating the following hypothesis: COVID-19 has awakened some deeply rooted cultural patterns, which date back to the times of high epidemic risk, long before vaccines, sanitation and widespread basic healthcare. Those patterns involve less spatial mobility in the population, and social interactions within relatively steady social circles of knowingly healthy people. As a result, the overall frequency of social interactions in cities is likely to decrease, and, as a contingent result, the formation of new social roles is likely to slow down. Then, either digital technologies take over the function of direct social interactions and new social roles will be shaping themselves via your average smartphone, with all the apps it is blessed (haunted?) with, or the formation of new social roles will slow down in general. In that last case, we could have hard times with keeping up our pace of technological change. Here is the link to You Tube video which summarizes what is written below: Urban Economics and City Management #4 COVID and social mobility in cities [ Cities 4 2020-09-06 09-43-06 ;  ].

I want to gain some insight into the epidemiological angle of that claim, and I am passing in review some recent literature. I start with: Gatto, M., Bertuzzo, E., Mari, L., Miccoli, S., Carraro, L., Casagrandi, R., & Rinaldo, A. (2020). Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures. Proceedings of the National Academy of Sciences, 117(19), 10484-10491 ( ). As it is usually the case, my internal curious ape starts paying attention to details which could come as secondary for other people, and my internal happy bulldog follows along and bites deep into those details. The little detail in this specific paper is a parameter: the number of people quarantined as a percentage of those positively diagnosed with Sars-Cov-2. In the model developed by Gatto et al., that parameter is kept constant at 40%, which is, apparently, the average level empirically observed in Italy during the Spring 2020 outbreak. Quarantine is strict isolation between carriers and (supposedly) non-carriers of the virus. Quarantine can be placed on the same scale as basic social distancing. It is just stricter, and, in quantitative terms, it drives much lower the likelihood of infectious social interaction. Gatto el al. insist that testing effort and quarantining are essential components of collective defence against the epidemic. I generalize: testing and quarantine are patterns of collective behaviour. I check whether people around me are carriers or not, and then I split them into two categories: those whom I strongly suspect to host and transmit Sars-Cov-2, and all the rest. I define two patterns of social interaction with those two groups: very restrictive with the former, and cautiously bon vivant with the others (still, no hugging). As the technologies of testing will be inevitably diffusing across the social landscape, that structured pattern is likely to spread as well.    

Now, I pay a short intellectual visit to Jiang, P., Fu, X., Van Fan, Y., Klemeš, J. J., Chen, P., Ma, S., & Zhang, W. (2020). Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour. Journal of Cleaner Production, 123673 . Their methodology is based on correlating spatial mobility of cars in residential areas of Singapore with the risk of infection with COVID-19. A 44,3% ÷ 55,4% decrease in the spatial mobility of cars is correlated with a 72% decrease in the risk of social transmission of the virus. I intuitively translate it into geometrical patterns. Lower mobility in cars means a shorter average radius of travel by the means of available urban transportation. In the presence of epidemic risk, people move across a smaller average territory.

In another paper (or rather in a commented dataset), namely in Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C., & Tizzoni, M. (2020). COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown. Scientific data, 7(1), 1-7. , I find an enlarged catalogue of metrics pertinent to spatial mobility. That paper, in turn, lead me to the functionality run by Google: . I went through all of it a bit cursorily, and I noticed two things. First of all, countries are strongly idiosyncratic in their social response to the pandemic. Still, and second of all, there are common denominators across idiosyncrasies and the most visible one is cyclicality. Each society seems to have been experimenting with the spatial mobility they can afford and sustain in the presence of epidemic risk. There is a cycle experimentation, around 3 – 4 weeks. Experimentation means learning and learning usually leads to durable behavioural change. In other words, we (I mean, homo sapiens) are currently learning, with the pandemic, new ways of being together, and those ways are likely to incrust themselves into our social structures.    

The article by Kraemer, M. U., Yang, C. H., Gutierrez, B., Wu, C. H., Klein, B., Pigott, D. M., … & Brownstein, J. S. (2020). The effect of human mobility and control measures on the COVID-19 epidemic in China. Science, 368(6490), 493-497 ( ) shows that without any restrictions in place, the spatial distribution of COVID-19 cases is strongly correlated with spatial mobility of people. With restrictions in place, that correlation can be curbed, however it is impossible to drive down to zero. In plain human, it means that even as stringent lockdowns as we could see in China cannot reduce spatial mobility to a level which would completely prevent the spread of the virus. 

By the way, in Gao, S., Rao, J., Kang, Y., Liang, Y., & Kruse, J. (2020). Mapping county-level mobility pattern changes in the United States in response to COVID-19. SIGSPATIAL Special, 12(1), 16-26 ( ), I read that the whole idea of tracking spatial mobility with people’s personal smartphones largely backfired because the GDS transponders, installed in the average phone, have around 20 metres of horizontal error, on average, and are easily blurred when people gather in one place. Still, whilst the idea went down the drain as regards individual tracking of mobility, smartphone data seems to provide reliable data for observing entire clusters of people, and the way those clusters flow across space. You can consult Jia, J. S., Lu, X., Yuan, Y., Xu, G., Jia, J., & Christakis, N. A. (2020). Population flow drives spatio-temporal distribution of COVID-19 in China. Nature, 1-5.  ( .

Bonaccorsi, G., Pierri, F., Cinelli, M., Flori, A., Galeazzi, A., Porcelli, F., … & Pammolli, F. (2020). Economic and social consequences of human mobility restrictions under COVID-19. Proceedings of the National Academy of Sciences, 117(27), 15530-15535 ( ) show an interesting economic aspect of the pandemic. Restrictions in mobility give the strongest economic blow to the poorest people and to local communities marked by relatively the greatest economic inequalities. Restrictions imposed by governments are one thing, and self-imposed limitations in spatial mobility are another. If my intuition is correct, namely that we will be spontaneously modifying and generally limiting our social interactions, in order to protect ourselves from COVID-19, those changes are likely to be the fastest and the deepest in high-income, low-inequality communities. As income decreases and inequality rises, those adaptive behavioural modifications are likely to weaken.

As I am drawing a provisional bottom line under that handful of scientific papers, my initial hypothesis seems to hold. We do modify, as a species, our social patterns, towards more encapsulated social circles. There is a process of learning taking place, and there is no mistake about it. That process of learning involves a downwards recalibration in the average territory of activity, and smart selection of people whom we hang out with, based on what we know about the epidemic risk they convey. This is a process of learning by trial and error, and it is locally idiosyncratic. Idiosyncrasies seem to be somehow correlated with differences in wealth. Income and accumulated capital visibly give local communities an additional edge in the adaptive learning. On the long run, economic resilience seems to be a key factor in successful adaptation to epidemic risk.

Just to end up with, here you have an educational piece as regards Business models in the Media Industry #4 The gaming business[ Media BM 4 2020-09-02 10-42-44;]. I study the case of CD Projekt ( ), a Polish gaming company, known mostly for ‘The Witcher’ game and currently working on the next one, Cyberpunk, with Keanu Reeves giving his face to the hero. I discover a strange business model, which obviously has hard times to connect with the creative process at the operational level. As strange as it might seem, the main investment activity, for the moment, consists in terminating and initiating cash bank deposits (!), and one of the most important operational activities is to push further in time the moment of officially charging customers with some economically due receivables. On the top of all that, those revenues deferred into the future are officially written in the balance sheet as short-term liabilities, which CD Projekt owes to…whom exactly?   

Healthily dosed meanness

I am connecting the dots, progressively. People tend to, by the way. Essentially, all that stuff called ‘civilisation’ consists in people figuring s**t out, progressively.

I am connecting two paths of my educational content, i.e. the account of my investment experience in the stock market, and urban economics, on the one hand, with a third one, namely the philosophy of science and especially the concept of truth, on the other hand.

My so-far adventure with the philosophy of science allows me to approach truth under different angles. One of the most down-to-earth tests for truth is the capacity to recognize when someone is lying to me. From the perspective of Pierre Simon, marquis de Laplace[1], I can recognize a lie when the things which someone tells me are endowed with very low probability of happening, given the knowledge I already have about the phenomena concerned. Gotcha’, f**ker! You went too far into and under the tail of the curve which sets my distribution of probability. Here, a bit accidentally, Pierre Simon, marquis de Laplace, sort of agrees with Sir George Maynard Keynes, when he wasn’t even a Sir yet, as for the theory of probability[2]. Agreement is reached as regards the claim that in practical life choices, the kind of probability that matters to us is the probability of claims we make about reality, whilst the strictly speaking probability of single phenomena happening in a given place and time is nice to know, yet of little utility in daily life.

If, alternatively, I follow the hermeneutic take by Hans Georg Gadamer[3], and you, my friend tell me things which are ugly, in the first place, and do not match at all the patterns of my historically grounded culture, you are probably telling me lies. If I take still another turn, and follow the recently formulated Interface Theory of Perception (Hoffman et al. 2015[4]; Fields et al. 2018[5]), lies are claims which contradict my empirically grounded knowledge about the way I can have the best possible payoffs from interactions with my environment.

The truth is that truth is complex and requires experience, judgment and healthily dosed meanness. That being said, let’s tackle the two problems at hand: my investment in the stock market, and the civilizational role of cities as demographic anomalies. As regards the former, here is the deal. My next instalment of investment comes. Every month, I invest in the stock market the rent which I collect from an apartment in town (i.e. in Krakow, Poland), roughly $670. Every month, I reconsider my investment portfolio and I decide what to buy, and what to sell. I am going to use the theories of truth which I tentatively outlined in the preceding paragraphs, in order to approach my next investment decision in strict scientific terms. Theories of truth will serve me to assess the well-founded of my decisions. Roughly speaking, when I choose between a limited number of alternative options, I can claim, about each of them, that this specific way to do things is the best one. If that claim is true, I can assume that it is truly the best option. Theories of truth are used here to assess the veracity of situation-specific claims. As I think about it, things are going to turn really funny if I come to the conclusion that I can label more than one option as truthfully the best. We’ll live, we’ll see. Anyway, here comes the video content: Invest 5 2020-09-02 07-55-26 ; .

As I have been doing my research on the civilizational role of cities, I have kept repeating and I still maintain that cities are demographic anomalies with a purpose. I am going to use those theories of truth as an intellectual toolbox for nailing down precisely the phenomenon of demographic anomaly. In other words, I want to determine which specific spatial distribution of human population can be truthfully labelled as anomalous, and, on the top of that, I want to assess, just as truthfully, what is the most likely scenario of change in urban life, urban economics and city management under the impact of COVID-19. In this case, theories of truth serve me to assess the veracity of general, theoretical claims. Here is the video on You Tube: Cities 3 2020-09-02 08-38-47 ;  .

I am using theories of truth in two different contexts, namely one situationally specific, and another one theoretically general, and, in my next step, I take on describing those contexts more abundantly. The context of investment decision comes with an important trait, as the philosophy of science comes, i.e. with an apparently clear, yet a bit blurry a distinction between assumptions and hypotheses.

[1] Laplace, Pierre Simon, marquis de, 1795 – 1902, A Philosophical Essay on Probabilities, Project Gutenberg EBook, #58881

[2] Keynes, John Maynard, 1921, A Treatise On Probability, McMillan and Co., Project Gutenberg Ebook #32625

[3] Gadamer, Hans Georg, 2004, Truth And Method, 2nd, revised edition, Continuum Books, ISBN 08264 7697X

[4] Hoffman, D. D., Singh, M., & Prakash, C. (2015). The interface theory of perception. Psychonomic bulletin & review, 22(6), 1480-1506.

[5] Fields, C., Hoffman, D. D., Prakash, C., & Singh, M. (2018). Conscious agent networks: Formal analysis and application to cognition. Cognitive Systems Research, 47, 186-213.

Fire and ice. A real-life business case.

I keep going along the frontier between my scientific research, my small investment business, and my teaching. In this update, I bring you two typically educational pieces of content, one sort of astride educational and practical investment decisions of my own, and finally I give slightly educational an account of a current business decision I am taking.  

In the video entitled ‘My investment experience, my teaching and my science #3  BMW, Daimler and Volkswagen’ [ Invest 3 2020-08-26 14-02-22 ;  ], I discuss those three investment positions in my portfolio. Three German automotive companies. Same industry, same country, same macroeconomic environment, and yet three different performances in terms of return on investment. In this video, you can see me developing on the distinction between long term-trends and short-term variations, as well as trying to connect technical analysis of price trends with fundamental analysis of their half-annual reports.

I have place on You Tube two pieces of content in the stream of teaching designated as ‘Urban Economics and City Management’. ‘Urban Economics and City Management #1 Lockdowns in pandemic and the role of cities’ [ Cities 1 2020-08-27 08-57-15;  ] recounts and restates my starting point in this path of research. I browse through the main threads of connection between the pandemic of COVID-19 and the civilisational role of cities. The virus, which just loves densely populated places, makes us question the patterns of urban life, and makes us ask question as for the future of cities.

In ‘Urban Economics and City Management #2 Case study of REIT: Urban Edge and Atrium [Cities 2 2020-08-27 11-00-52 ; ], I study the cases of two REITs, i.e. Real Estate Investment Trusts, namely Urban Edge (U.S.) and Atrium (Central Europe), with two assumptions. Firstly, cities can grow and evolve, when the local humans master the craft of agglomerating in one, relatively tiny place, the technologies of construction, sanitation, transportation, energy supply etc., and to parcel those technologies into marketable goods. Secondly, rental and lease of real estate are parcelled, marketable urban technologies.

In the video ‘My investment experience, my teaching and my science #4 The Copernic project’, [ Invest 4 Copernic 2020-08-30 08-57-54 ;  ], I am developing on a topic exactly at the intersection of those three: the Copernic project. Honestly, this is complex stuff. I hesitated to choose this topic as educational material, yet I have that little intuition that good teachers teach useful skills. I want to be a good teacher, and the s**t I teach, I want it to be useful for my students. Life is complex and brutal, business is complex and brutal, and, as a matter of fact, each of us, humans, is complex and brutal. Fake simplicity is for pussies.

Thus, whoever among my students reads this update and watches the accompanying video material, is going to deal with real stuff, far beyond textbooks. This is a business which I am thinking about engaging in, and I am just starting to comprehend its patterns. This update is a living proof and test how good I am, or how I suck, at grasping business models of the digital economy.

In educational terms, I am locating the content relative to Copernic project in the path of teaching which I labelled ‘My investment experience, my teaching and my science’, as I am entertaining the idea of investing in the Copernic project. The subject cuts comprehensively across and into many aspects of economics and management. It can be considered as useful material for any educational path in these major fields.

It started when I reacted to a piece of advertising on Facebook. Yes, many interesting stories start like that, nowadays. It was an ad for the Copernic project itself. Here you have a link to Copernic’s website – – but keep in mind that it is only Polish version, at least for the moment. I will do my best to describe the project in English.

Copernic is both the name of the project, and the name of an LLP (Limited Liability Partnership), incorporated under Polish law, in Krakow, Poland. The commonly used Polish acronym for an LLP is ‘sp. Z o.o.’, however, as I write in English, I will keep using the name ‘Copernic LLP’. I checked this company in the Judicial Register (of incorporated entities) run by the Ministry of Justice of the Republic of Poland, under the link . A business story emerges. On December 6th, 2019, Copernic LLP is founded, under the register #817764, in Gdansk, Poland, technically by two partners: a physical person and another LLP, i.e. TTC Trade LLP (register #788023). Yet, after scratching the surface, the surface being the Judicial Register, I discovered that TTC Trade LLP is wholly owned by the same physical person who was its partner in Copernic LLP. Anyway, the physical person apported 1000 PLN and took 1 partner share, whilst her LLP paid in 4000 PLN in exchange of 4 partner shares. By the way, PLN stands for Polish zloty and it comes like PLN 1 = $0,27.

On May 6th, 2020, the physical person who founded Copernic LLP steps out of the partnership, and her own LLP, TTC Trade, sells two of its two partner shares in Copernic LLP, to Sapiency LLP (, register #789717) incorporated in Krakow, Poland, at their face value of 2000 PLN. On the same day, the partnership contract is being reformulated entirely and signed anew, including a change of headquarters, which move from Gdansk to Krakow, Poland. By the same occasion, another corporate partner steps in, namely Reset Sun Energy LLP (Konin, Poland, register #802147) and takes 2 partner shares in Copernic LLP, for a price of 2000 PLN. By the same means, the total partners’ equity in Copernic LLP moves from 5000 PLN to 6000 PLN.

On July 20th, 2020, TTC Trade LLP and Reset Sun Energy LLP both sell their partner shares in Copernic LLP to Sapiency LLP, at face value, i.e. 6000 PLN. We have an interesting legal structure, when one Limited Liability Partnership (Copernic) is wholly owned by another Limited Liability Partnership (Sapiency), which, in turn, is 50/50 owned by two gentlemen, one of whom I had the honour to meet in person. Cool guy. Fire and ice in one. A bit like me.   

Sapiency is mostly active in cryptocurrencies. They make Blockchain-based tokens for whoever asks, and I think their main technological platform is Ethereum ( The marketing model is membership-based, thus oriented on long-term relations with customers. The business model of Copernic LLP is logically connected to that of Sapiency LLP. Copernic builds solar farms in Poland, and markets Blockchain-based tokens labelled Copernic1, at a face value of 4 PLN apiece. Each such token corresponds to a share in the future leasing of solar farms, and those farms, by now, are under actual or planned construction. Later on, i.e. after the solar farms become operational, those lease-connected Copernic1 tokens are supposed to give their holders a claim on secondary tokens CopernicKWH, which, in turn, correspond to claims on electricity generated in those solar farms. The first attribution of CopernicKWH tokens to the holders of Copernic1 tokens is supposed to take place within 14 days after the first photovoltaic farm becomes operational with Copernic LLP, with a standing power of at least 1 MW. That day of operational capacity can be a movable feast, and thus the official statute of those tokens stipulates that the first attribution of CopernicKWH will take place not later than January 1st 2021. After the first attribution of  CopernicKWH, subsequent attributions to the holders of Copernic1 are supposed to take place at least once a week.

The CopernicKWH tokens can be used as means of payment at the Kanga Exchange ( ), which looks cool, on the whole, with one exception. According to Kanga’s own statement, ‘Kanga Exchange is operated by Good Investments Ltd, registered in accordance with the International Business Companies Act of the Republic of Seychelles, Company Number 192185’ ( ). Just for your information: I can incorporate a business in Seychelles without getting up from my desk, 100% online, for the modest sum of 399 British Pounds ( I am fully aware how bloody hard it is to set up any business structure connected to cryptocurrencies in the European legal environment, however… Seychelles? Seriously?

The average price of electricity in Poland, when I am writing those words, is around 0,617 PLN per 1 kWh. One Copernic1 token, with its current price of 4 PLN, corresponds to 4/0,617 = 6,48 kWh of energy. Assuming that every week, starting from the day 0 of operations at the solar farm, Copernic LLP attributes me 1 CopernicKWH token for each Copernic1 token in my possession, I break even after 7 weeks, and each consecutive week brings me a net profit.

I do my maths according to the logic of the capital balance sheet. First of all, I want to compute the book value of assets that corresponds to the planned solar farm of 1 megawatt in standing power. In a report published by the International Renewable Energy Agency (IRENA ), entitled ‘Renewable Power Generation Costs in 2019’ ( ), I can read that the average investment needed for 1 watt of power in a photovoltaic installation can be cautiously estimated at $0,38, thus PLN 1,40.

Building a solar farm of 1 MW, thus of a million watts in terms of electric power, means an investment of at least PLN 1,40 * 106 = PLN 1 400 000. To that, you need to add the price of acquiring land. At the end of the day, I would tentatively put a PLN 2 million capital tag on the project. Supposing that capital for the project comes from the sales of Copernic1 tokens, Copernic LLP needs to sell at least 2 000 000 PLN/ 4 PLN = 500 000 of them Copernic1.

Looks like a lot, especially for a Limited Liability Partnership with partner equity at 6000 PLN. Assets worth PLN 2 000 000 minus PLN 6000 in partner equity means PLN 1 994 000 = $ 538 919  in capital which is not clear at all where it is supposed to come from. The sole partner in Copernic LLP, namely Sapiency LLP could pay in additional equity. Happens all the time. Still, Sapiency LLP as a partner equity of PLN 5000. See what I mean? Another option is a massive loan, and, finally, the whole balance sheet could rely mostly on those Copernic1 tokens. Only those tokens are supposed to embody claims on the lease of the solar farm. Now, legally, a lease is a contract which gives to the lessee (the one who physically exploits), the right to exploit things or rights owned by the lessor (the one who graciously allows others to exploit). In exchange, the lessee pays a rent to the lessor.

There are two things about that lease of solar farms. A lease is not really divisible, as it is the right to exploit something. If you divide that something into smaller somethings, you split the initial lease into as many separate leases. If I buy one Copernic1 token and that token embodies claims derived from a lease contract, what specifically is the object of leasing? There is another thing. If I buy Copernic1 tokens, it gives me claims on the future CopernicKWH tokens. In other words, Copernic will pay me in the future. If they pay me, on the basis of a lease contract, it is as if they were paying me a rent, i.e. as if they were leasing that solar farm from me. Only I don’t have that solar farm. They will have it. Yes, indeed, WTF? This is the moment to ask that rhetorical question.

A few paragraphs ago, I wrote that I am entertaining the idea of investing in those Copernic1 tokens. I think the idea has become much less attractive, business-wise, whilst becoming much more entertaining. There is an important question, though. Isn’t it ethically advisable to invest in renewable energies, even if the legal scheme is a bit sketchy, just to push forward those renewables? I can give an answer in two parts to that question. Firstly, renewables grow like hell, both in terms of power supplied, and in terms of attractiveness in financial markets. They really don’t need any exceptional push. They walk, and even run on their own legs. Secondly, I worked through my own ideas for implementing new technologies in the field of renewable energies, and, notably, I worked a lot with a tool called ‘Project Navigator’, run by the same International Renewable Energy Agency which I quoted earlier. The link is here: . There is one sure takeaway I have from working with that tool: a good project needs a solid, transparent, 100% by-the-book institutional base. Wobbly contracts translate into wobbly financing, and that, in turn, means grim prospects for the project in question.     

Another doubt arises in my mind, as I do flows instead of balances. A solar farm needs to earn money, i.e. to make profit, in order to assure a return on investment. The only asset which can earn value over time is land in itself. In practical terms, as long as we want that solar farm to work, it needs to generate a positive operational cash flow. Photovoltaic equipment ages inexorably, by physical wear and tear as well as by relative moral obsolescence. That aging can assure substantial amortization, yet you need some kind of revenue which you can write that amortization off from. If all or a substantial part of energy produced in the solar farm is tokenized and attributed to the holders of Copernic1, lease-based tokens, there could be hardly any energy left for sale, hence not much of a revenue. In other words, the system of initial financing with tokens can jeopardize economic payoff from the project, and that’s another thing I learnt with the Project Navigator: you need a solid economic base, and there is no way around it.

The hopefully crazy semester

Another handful of educational material, for the apparently (hopefully) crazy semester at the university. Crazy because of the virus, stands to reason. Things are never crazy because we make them so, stands to reason, once again.

I am making a big, fat bottom line at my investment portfolio in the stock market, and I am using this opportunity to make some educational material. The point of using my experience in education. It is personal experience, important to enrich theory. It is a story of personal limitations in business decisions, and understanding those limitations is important for understanding microeconomics as the substance of decisions, macroeconomics as their context, and management as their execution.

I have successful experience, together with hindsight on the mistakes I made. I can utilize it as valuable material to share and to build some teaching on. Since January 2020, I have invested  $7 924,76 in the stock market, and today (August 25th, 2020), my investment portfolio is worth  $11 719,91. I have 47,89% of return on the cash invested, over a period of 7 months. Not bad for a theoretician, isn’t it? I am deeply convinced that personal experience is impossible to bypass in any true teaching. Whatever kind of story I am telling on the moment, I always tell the story of my own existence. I can make it genuine and truthful just as well. Here is the link to the first, introductory video in this path: ‘My investment experience, my teaching and my science #1’  [Invest 1 2020-08-25 11-54-58 ; ]

In the second video of the same series [Invest 2 2020-08-26 07-37-08; ], I focus on the presentation of my investment portfolio. I stress two points. Firstly, the portfolio which I hold now is the cumulative outcome of past trials and errors. Secondly, my portfolio shows many alternative scenarios of what could possibly have happened to my money, had I invested in just one among the 27 positions, thus if I had not diversified. I could have made +313% or -49%, instead of the 48% I had made as of August 25th 2020. I study more fundamentally the case of General Electric, which is one of my financial failures as for now. Turns out they have stakes in aviation, and that sucks in the times of pandemic.

In the third video of the series ‘Business Models in the Media Industry’ [Media BM 3 2020-08-26 08-24-42; ] I focus more in depth on studying the case of Netflix. You can have a glimpse of their transition from a streamer of externally made content to a business based on in-house made content. You can also see how strongly their business model is grounded in the assumption of constant growth in size.

In my second video devoted to Political Systems [PolitSys 2 2020-08-26 09-02-47; ] I use two cases, i.e. the constitutions of France and Finland, to give my readers, followers and students a first glimpse on forms of political power. You can see that general concept in the context of distinction between a presidential system (France) vs a Parliamentary one (Finland).