Micro Diginomics Guide: for a Single Digital Good with a focus on business models
Situation
Hypothesis
There is a need for emissions data
Subject: The production and supply of carbon emissions data - and the diginomics thereof
[diginomics is the economics of the production and supply of digital goods.]
Subject: how do we "produce" and "allocate/share/consume" digital good X.
emissions data is digital data
this matters a lot for production and markets for digital stuff
Question: how do we "produce" and "supply/share" carbon emissions data. e.g. carbon emissions "in" this mars bar, for this power station, of this home.
Question 2: What is diginomics and why do we need it (what's wrong with "normal" economics) [NB: this is kind of duplicate of first question subbranch 3 and 4 now ...]
What problems are there in production and supply? Why won't normal markets work here? After all we don't do special analysis about oranges ... - standard economics and practice work fine here.
How is diginomics helpful in understanding and solving them?
Why is diginomics different? [and how is that relevant to everything else in this question tree!]
What problems are there in production?
What problems are there in supply?
How are these related?
Why is digitial/information/data different?
Emissions data is "data" i.e. digital information (information)
Data needs different design/economics from "standard" goods (though note data is becoming the future)
Data is different from "traditional" in one fundamental way: costless copying
We need extrinsic incentives for production/sharing i.e. they won't arise from entirely free market dynamics
Those incentives will have to be predominantly/almost exclusively monetary in form
Physical goods are made of atoms
Purely tech based solutions won't cut it; we need to consider the economics
Data is made of bits
Digital tech means that digital data/info is close to costless to copy aka nonrival in economics terminology
It is different from "physical" goods we are used to
The difference matters as costless copying => that traditional production and exchange models don't work or are very inefficient (and inequitable)
Econ 101 for production and consumption assume X, Y, Z and these assumptions fail for data
Total cost is almost entirely upfront fixed costs (marginal costs of production negligible)
Nonrivalry (antirivalry)
[Obvious for a database but may not be for other stuff]
Essence of X is information
Even if embodied in physical form (e.g. as a CD, a pill, a chairt)
Econ 101 (advanced) tells us that even a toy "free market" economy would only work where production function non-convex, price-takers, complete information (in technical sense).
In many cases demand and supply curves won't intersect at all at any price level in free market (e.g. privacy, competition concerns)
But, tech may have it's place e.g. alleviating privacy concerns
All of these fail here
"Natural" property rights inhere in a physical excludable thing
Without excludability and with nonrivalry real problems of making money as a producer
And ... if we add excludability we have problems of consumption
Traditional goods have X mechanisms for their production and supply
There are X mechanisms for production and supply of "traditional" goods
digital stuff operates differently from oranges, apples, steel and cars. All the stuff we've been used to making (Diginomics is different from "standard" econ you learned in econ 101)
This is evident in terms of issues & different behaviour / approaches than in other areas of the economy e.g. issues in "producing" (enough/quality) data.
We have a decent toolkit for traditional good
How do we produce / supply normal stuff "usually"? (stuff like oranges or cars or ...)
How do we produce it?
How do we supply it?
What incentives are invovled?
What institutions / systems are there in place?
How would this apply to our case of emissions data?
Why is it relevant to emissions data and the climate crisis?
What and why of (normal) economics? [production and supply of "normal" goods e.g. open an econ textbook and it will talk about wool or wine in homage to Ricardo and early 19th c when economics really came into being)
What are normal goods?
Classic profit motive - sell the good
Nationalisation - the state makes them
Grants/subsidies - states or philanthropic actors fund others to make them
What's different about digital goods (data/info goods)?
Why's that a problem?
Why is it a problem for producers?
Why is it a problem for consumers/society?
Complementary good/service models - sell the good cheaply (or even supply it freely) to make profit from complementary goods or services
Atm the tech focus (how do we design and build our database) is as if in trying to understand and develop the apple (fruit?) "economy" we focused on packaging technology or logistics of transport when the basic incentives and institutions for growing and marketing apples weren't working.
"Apples aren't being labelled correctly when in fact apples are just not being grown"
Mandating - the law forces people to make them, and cover the costs themselves
Who would be producers? [producer may even be an odd terminology but useful to start thinking in this way]
Who are the consumers/buyers?
Who consumes/buys it?
What are the (dis)incentives of producers?
What does a market look like?
Why are commons so common?
Why is digital linked to data/info?
What is different?
What is the double life of data/info?
What is nonrivalry / costless copying?
What is a digital "commons"?
What is environmental commons?
What is digital commons and how same / different?
What does this mean for economics? i.e. what is diginomics?
Why are platforms/networks/multi-sided markets so frequent?
What are key assumptions of economics and how do they change for digital (this is kind of a summary of last section)
What does this mean for incentives and institutions?
Why are thinking about incentives and mechanisms more important?
What tools do we have in our toolbox?
What are the building blocks of an incentive mechanism?
What are the different archetypal models?
What are the strengths and weaknesses of the different models?
How can we fit the building blocks together?
How is our use of tools impacted by operating context?
Using a combination of X and Y model and prioritizing X model is the best way to produce and supply emissions data at the scale required.
[Why, What] Production and supply of emissions data (digital goods in general) requires a different set of guiding principles and a richer/alternative set of approaches because digital goods are fundamentally different from "normal" goods [in being ~ costlessly copyable and having active disincentives for production/supply]
Intution pump re data being different: most of us think at least some degree of free access to data/informaiton goods is justifiable/desirable. The same isn't true for physical goods (we don't find it weird to pay for organges, we would find it weird to pay for every individual internet video or article)
[How] There are 6 basic archetypes for production and supply of emissions data (digital goods) and there are these criteria for assessing which are usable in which combination.
[Designing socio-economic systems for digital information/data [Diginomics system design]
builds on these 4 archetypes which can be combined in Z ways.]
This difference matters in X, Y way
Digital goods are different
People have reasons beyond direct cost not to produce/supply them (e.g. competition, reputation concerns)
....
There are these criteria for choosing with this ranking
These subset are especially relevant for digital goods
They're costlessly copyable
Situation here is a,b,c
Hence, combining that with criteria implies use model X and Y
These are these building blocks
Value type(s) to be offered as incentives [invariably money but worth at least mentioning others]
Revenue raising mechanism (/value gathering more broadly)
Revenue/value source
Collection mechanism
Revenue allocation mechanism (/value allocation)
Value assessment mechanism (i.e. how we judge the value of what’s produced)
Entitlements framework (i.e. who’s entitled)
Allocation conditions (i.e. basis for entitlements)
Reuse and value flow
Governance and dispute resolution mechanisms
License type [[Talk here about Open and how this is great/desirable but not necessary for this to work]]
Emissions data is digital data ...
There are these specific options: monopoly rights, remuneration rights, prizes, compulsory, voluntary ⭐⭐
User-specific licensing
Subscription based preemptive licensing
Mandating/Regulation
Public grants and subsidies
Remuneration rights
Data commons models
Complementary goods/services models
Prizes/bounties
Supply (amount and quality)
The overall social welfare (ie. aggregate utility) - crudely no of people get it x benefit they get from it
Ease of implementation (of the model)
Access
Innovation and evolution (note: again one less relevant for "normal" goods
[Simplified] The main options for design of "economy" of emissions data at scale required are monopoly rights or remuneration rights commons (with compulsory supply as an add-on in both cases)
The main options for supply of (digital) goods are: simple exchange (i.e. classic property rights) (does not really work for info), monopoly rights, remuneration rights, pure sharing ...
Situation here is a, b, c
They have these strengths and weaknesses
Hence do X and Y