Mapping changes over time

A fellow courserian mapped the decline of Monarch butterflies and it had several elements:

1. An external data source (in this case: Flickr) with geocoding
1. Photos are geotagged
2. A time line
1. 2008 to 2013
3. Good visualization 
• a heat map was used
4. A basemap
• Imagery was used I believe

If I'm running a hospital network and I have information such as aggregate patient location, I would be interested in seeing where patients are coming from i.e.

1. An internal data source with geocoding
• patients are located say via postal code
2. A timeline
• last 5 years
3. Good visualization
• a choropleth, or graduated circles
• or a heat map
4. A basemap 
• Either imagery or split by postal code or natural subdistrict

Beyond Model Thinking

 Next steps beyond model thinking

• Figure out entropy 
• Checkout - http://www.complexityexplorer.org/

Networks

Networks

Lectures cover:

• Logic
• what rules or organizations use to form connections?
• how it forms
• Structure
• what are the measures to compare networks?
• measures
• Function
• what properties emerges from the structure?
• what it does

Network Structure

• A set of nodes and edges
• edges can be undirected or directed
• Degree
• how many edges each node has on average
• node
• number of edges attached to a node
• network
• average degree of all nodes
• = 2 x Edges / Nodes
• neighbours of a node
• all other nodes connected by an edge to the node
• Theorem
• The average degree of neighbours of nodes will be at least as large as the average degree of the network
• i.e. Most people's friends are more popular than they are!
• Path Length
• definition
• Minimal number of edges that must be traversed to go from node A to node B
• Average Path Length
• Average path length between all pairs of nodes in a network
• how far it is from each node to another node

• Connectedness
• whether the entire graph is connected to itself
• definition
• A graph is connected if you can get from one node to any other
• Clustering Coefficient
• how tightly clustered are the edges
• definition
• percentage of triples of nodes that have edges between all three nodes
• What each measure tells us
• Degree
• Density of connections
• Social Capital
• A proxy for social capital
• Speed of Diffusion 
• How quickly information spreads
• Path Length
• # Flights Needed
• Social Distance
• Likelihood of information spreading
• unlikely to spread if path length is long
• Connectedness
• Markov Process - an essential precondition
• Terrorist Group Capabilities
• Connected groups are more capable
• Internet/Power Failure
• Information Isolation
• Disconnected people may not learn things
• Clustering Coefficient
• Redundancy/Robustness
• If there is a break, the network still works
• Social Capital
• Innovation adoption (triangles)
• How likely an innovation is likely adopted
• Picture = 1000 words

Network Logic

• Random attachment
• Connection procedure
• N nodes
• P probability two nodes connected
• Contextual Tipping Point
• For large N, the network almost always becomes connected when P > 1/(N-1)
• Small Worlds
• People have some percentage of "local" or "clique" friends and some percentage of random friends
• As people have more random friends, there's less clustering an shorter average path length
• Preferential Attachment
• Connection procedure:
• Node Arrives
• Probability connects to an existing node is proportional to the node's degree
• The degree distribution always results in a long tail
• A lot of nodes only have degree 1
• A handful of nodes with very high degree
• Results
• The exact network we get is path dependent
• The equilibrium degree distribution is not path dependent
• Always a long tail degree distribution

Network Function

• Micro decisions/processes when forming networks aggregates in emergent network properties
• Six Degrees
• Stanley Milgram & Duncan Watts
• Random Clique Network
• Formation Rules: Each person has
• C clique friends
• R random friends
• K-Neighbour
• All nodes that are of path length K to a node but not of any shorter path length
• Strength of weak ties

Path Dependence

Path Dependence

Lectures cover:

• What is Path Dependence?
• Construct Urn Models to understand
• different types of path dependence
• what causes path dependence
• difference between path dependent outcomes and path dependent equilibria
• Examples of Urn Models
• Polya Process, Balancing Process,
• Path dependencies is logically different from increasing returns
• Path dependencies are caused by externalities i.e. interdependencies between choices/decisions
• externalities with negative effects are more likely to be path dependent
• Compare path dependence and Markov Processes, Tipping Points and Chaos
• Key lessons - my own reflection of what this lecture means

Real-world examples:

• QWERTY typewriter keyboard
• increasing returns / virtuous cycle
• the more QWERTYs lead to more QWERTYs
• Technology
• AC vs DC
• Gasoline vs Electric Cars
• Common Law
• Influence of Precedent
• Institutional Choices
• Defined benefits
• Economic Success
• Ann Arbor vs Jackson
• Manifest Destiny of America
• Railroads 

 

Path Dependence

• Path Dependent
• Outcome probabilities depend upon the sequence of path outcomes.
• Doesn't necessarily determine, merely affects the probabilities
• What happens now depends on what happened along the path to get here
• Phat Dependent
• Outcome probabilities depend upon past outcomes outcomes but not their order
• Polya process is Phat

Urn Models

• Basic Urn Model
• Urn contains balls of various colors
• The outcome equals the color of the ball selected
• Bernoulli Model
• Fixed number of balls in the urn
• U = {B blue, R red}     ; U stands for Urn is a set of B blue and R red
• Process: Select ball and return to the urn
• P(red) = R/(B+R)
• Outcomes independent
• Polya Process
• U = {1 Blue, 1 Red}
• Process: 
• Select and return
• Add a new ball that is the same color as the ball selected
• Probabilities will change over time
• Result
• Any probability of red balls is an equilibrium and equally likely
• Any history of B blue and R red balls is equally likely
• Seeing just the set in the outcome doesn't tell you anything about the order (a Phat process) because any order is equally likely
• Example:
• Fashion: People buy leopard prints because there are more leopard prints
• Technology: People buy iPhones because they see iPhones
• Balancing Process
• U = {1 Blue, 1 Red}
• Process:
• Select and return
• Add a new ball that is the opposite color as the ball selected
• Result
• The balancing process converges to equal percentages of the two colors of balls
•  Examples
• Need to keep constituencies happy
• Selection of site for political conventions - northern or southern state
• Selection of site by Olympic committee - Asia, Europe, North America or South America
• Sway Process
•  U = {1 Blue, 1 Red}
• Process
• Select and return 
• In period t, add a ball of the same color as the selected ball and add 2^(t-s) - 2(t-s-1) of color chosen in each period s < t
• As you go back in time,the older events take on exponentially more weight over time
• Early movers have a bigger effect
• Distinguish between:
• Path Dependent Outcomes
• color of ball in a given period depends on the path
• Path Dependent Equilibrium
• percentage of red balls in long run depends on the path
• Outcomes and equilibrium
• Polya process: 
• Path-dependent outcomes
• Path-dependent equilibria
• Balancing process: 
• Path dependent outcomes
• Equilibria independent of path
• Examples of path-independent equilibria
• Manifest Destiny - America will stretch from sea to shining sea
• Railroads - Once railroads were invented, they will build themselves
• Mobile - Once invented, mobiles is the future

Path Dependence and Chaos

• Why is the difference between Path Dependence and Phat Dependence important
• Markov processes
• finite states
• fixed transition probabilities
• can get to any other state
• not simple cycle
• markov converges to a unique stochastic equilibrium
• Chaos
• Extreme Sensitivity to Initial Conditions (ESTIC)
• If initial points x and x' differ by even a tiny amount after many iterations of the outcome function, they differ by arbitraty amounts.
• Tent Map (an example of chaotic)
• x in (0,1)
• F(x) = 2x   if X <0.5,
•         = 2 - 2x if X > 0.5
• Tent Map is not path dependent
• Nothing happens along the way/path will change the end
• is deterministic
• Path dependence means what happens along the way has an impact on the outcome

Types of outcomes

• Independent
• Outcome doesn't depend on starting point or what happens along the way
• Chaotic
• Outcome depends on initial conditions
• Path dependent
• Outcome probabilities depend upon sequence of past outcomes
• Phat dependent 
• Outcome probabilities depend upon past outcomes but not their order

History is path dependent. The future is being written today.

• History/future is not independent i.e. what's happening now is happening regardless of what happened in the past. Independence means no structure.
• History/future is not chaotic i.e. initial conditions matter but it isn't the only thing that matter. Once we write the Constitution, the rest plays out deterministically
• History/future is path dependent not phat dependent because early events have a larger importance.

Path Dependence and Increasing Returns

• Increasing Returns
• More produces more
• Positive feedback / Virtuous cycles
• The more I have of something, the more I want the same thing 
• The the more other people do something, the more that other people will do it
• Example:
• The more people get QWERTY typewriters, the more people will get QWERTY typewriters
• Is increasing returns equivalent to path dependent equilibrium? No
• Increasing returns without path dependent equilibrium
• Example:
• Gas / Electric
• Always goes to equilibrium at Gas even though there is increasing returns
• Path dependent equilibrium without increasing returns
• Example
• Symbiots

• Path Dependencies comes from a different process - Externalities
• Externalities:
• interdependence between choices can create path dependence
• Decisions create externalities
• Externalities that big projects create path dependence
• Choosing Project A first results in choosing Project C next
• Choosing Project B first results in choosing Project D next
• Yi J's decision to migrate to Australia affects parents & Dai J

Path Dependence or Tipping Point

• Path Dependent Equilibrium
• percentage of red balls in the long run depends on the path
• Tipping points
• direct tips
• Comparison
• Tipping points
• a single instance in time where the long term equilibrium
• a singular event that tips the event abruptly
• diversity index - count of equilibria
• diversity index (uncertainly) is reduced abruptly
• entropy - how much information in the system
• Path Dependent Equilibrium
• accumulative effect of moving along the path
• diversity index reduces gradually
• unlike tipping point where diversity index (uncertainly) is reduced abruptly

Key Lessons

• Externalities are the reason choices we make in the past will affect choices we make in the future
• Pay more attention to choices with externalities e.g.
• Where you choose to live
• What line of work you choose to do
• What language you choose to learn
• Where possible make decisions where externalities are all positive 
• including future externalities
• this will reduce path dependencies i.e. keep your options open
• History matters when it changes transition probabilities
• Make decisions that increase transition probabilities to states you desire - to goal states
• Pay attention to externalities when making decision especially negative externalities
• Keep your options open

The Power of Complements

The Power of Complements

In this week's lecture:

• Examples and definition of complementary products
• The economic definition for complementary products
• Cross-price elasticity of complementary products
• How substitute goods can also be surprising complements
• Interesting strategies in markets with complementary products
• Supporting the supplier of a complementary product
• Produce the complements - Advantages and disadvantages
• Strategies for firms that produce the complements
• Cross subsidize complementary products
• Bundle complementary products
• Increase Lock-In
• How complementarity can help achieve cooperation among firms who might otherwise compete
• Competitors as Complementors
• How Strategic Partnerships foster coordination between firms
• Shared decision making
• Organisation Integration
• Economic Integration

Complementary Products

Examples of complementary products:

• Computers and Software
• Skis & Skiing Sticks
• Smartphones & Apps

 

Economic Definition

The utility increase when the products are used together.

• Two products A and B
• These are complements if B increases users' utility from A, and vice versa
• U(A+B) > U(A) + U(B)

Cross-Price Elasticity

• Two products A and B
• These are complements if the demand for B increases when the price of A drops, and vice versa
• This phenomenon is referred to as negative cross price elasticity
• Cross price elasticity is how the price of one product depend on the price of another products

Surprising Complements

• Substitute good can also have complementary effects
• A price cut of the substitute good decreases market share but increases the size of the market, resulting in a positive net effect
• Example: Cloth shops in the same mall
• Shop A's price cut makes the whole mall more attractive
• Shop B's sales increase due to the additional customers

Supporting the Supplier

• Enable the supplier in ways that increase sales of complement e.g.:
• Better quality of complement
• Higher sales of complement
• Example: Apple
• Gave laptops to students writing software for Mac OS
• More compatible software titles made Apple's laptops more attractive
• Example: Game console manufacturer 3DO
• Problem
• Console manufacturers sold consoles for high prices to make profits
• This attracted a limited number of customers only
• Neither optimal for console manufacturers not for game publishers
• Solution
• Publishers paid a fee of 3 dollars to 3DO for every game copy sold
• 3DO could sell consoles much cheaper and attract more customers
• This way, publishers could sell more copies and increase profits

Producing Complements

• It may make sense to produce the complement yourself
• Example
• Sony produces game console and video games
• Hewlett Packard manufactures printers and printing ink
• Contra
• Market for complements may simply be unattractive
• Complement may require competencies the firm lacks (production, R&D, management, ...)
• Prospective customers might be put off by a firm's dominant position
• Pro
• Better tailoring of complement to own product
• Quality control for complement
• Internalization of the positive effects (externalities) of the complement on own product
• Cross-Subsidies
• Bundling
• Increasing Lock-in

Cross Subsidies

• Idea
• Product A is sold at small margins (even loss) to increase sales of Product B (high margins)
• Advantage
• Increase profits through intelligent pricing
• Risks
• Consumers do not buy product B at all
• Consumers buy product B from another manufacturer
• Examples: 
• Razors and razor blades
• Printers and printer cartridges
• Mobile phones & operator contracts

Bundling

• Idea
• Firm sells product A and complement B combined as a package
• Advantage
• Little or no competition in market for A
• Decreased competition in market for B
• Risks
• Potential buyers of "A only" or "B only" are lost
• Bundling becomes standard and advantages of unbundling are overlooked
• e.g. How to differentiate and how to set prices
• Examples
• Game console and games 
• e.g. Wii bundle with console, game, steering wheel
• Operating system and web browser
• Flight and baggage handling

Increasing Lock-In

• Idea
• Users have switching costs when switching from A to a substitute
• The more complements (B, C, ...) to A they buy, the higher the switching cost
• Advantage
• Higher switching costs imply a higher value of the customer to the firm
• You can charge customers higher prices
• Examples
• Microsoft Office and MS Windows
• Games and video consoles

Competitors as Competitors

• In certain situations, firms may be
• Competitors in one part of the market
• Complementors in another part of the market
• In such a constellation, they may not compete that harshly
• Example: Music Players & Music Content
• Sony and Apple
• Competitors
• Both sell portable music players
• Complementors
• Sony Music provides music content for Apple's iPod / iPhone
• Apple's iTunes store is important sales platform for Sony's music content
• Example: Mobile Phone Calls
• Vodafone and T-Mobile
• Competitors
• Both sell mobile phone contracts
• Complementors
• Their networks are interlinked
• Customers join Vodafone because they know that they can also call T-Mobile customers , and vice versa.
• Parts of Vodafone's / T-Mobile's revenues come from these cross-network calls

Strategic Partnerships

• Drivers of Strategic Partnerships
• Producers of complementary goods depend on each other
• Helping each other and coordinating each other's behaviour maximizes the positive effects of complementarity
• In many cases, integration into one single company not feasible or not desired by involved firms
• Forming a strategic partnership is a powerful way of institutionalizing coordination and formalising interests
• Definition of Strategic Partnerships
• Relationships between firms
• Typical characteristics
• Shared decision making
• Organizational linkages & coordination mechanisms(organisational integration)
• Joint equity ownership (economic integration)
• Organisational Integration
• Teams across firms
• Established reporting and decision routines across firms
• Heavy exchange of information
• Economic Integration
• Direct cross ownership of equity
• Firm A holds X% of Firm B's assets and vice versa
• Setting up a new legal entity (joint venture)
• Benefits
• Alignment of interests
• Retention of control and exclusivity
• Feasibility of inter-organisational coordination
• Complementarity and Strategic Partnerships
• If firms produce complementary products, already high incentives to work together cooperatively
• Less need for economic integration to align interests

Beyond Creative Programming Course

Next steps after Creative Programming Course:

1. Develop Mandelbrot Surfer
2. Read the Nature of Code
3. Develop Shoot the Apple Game
4. Develop a site like http://funprogramming.org/ (they key being graduated exercises)
5. Checkout Processing.js on Windows 8

Social Sharing Programmatically

Sharing on Social media

• Tumblr: http://stackoverflow.com/questions/6169603/tumblr-sharer-url-override

A good source of information on Tumblr

• http://www.cherrybam.com/tumblr-tutorials.php