Part 1

1

• Part 1 Trust

2
Trust is a Honda Accord

• As opposed to
• "Existentialist trust"
• Reliance on ...

3
Trust

• Working definition handing over the control of
  the situation to someone else, who can in
  principle choose to behave in an opportunistic
  way
• the lubricant of society it is what makes
  interaction run smoothly
• Example
• Robert Putnams
• Bowling alone

4
The Trust Game as the measurement vehicle
5
The Trust Game general format
S lt P lt R lt T
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The Trust Game as the measurement vehicle
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Ego characteristics trustors
Note results differ somewhat depending on
which kind of trust you are interested in.

• Gentle and cooperative individuals
• Blood donors, charity givers, etc
• Non-economists
• Religious people
• Males
• ...
• ? Effects tend to be relatively small, or at
  least not systematic

8
Alter characteristics some are trusted more

• Appearance
• Nationality
• We tend to like individuals from some countries,
  not others.

9
Alter characteristics some are trusted more

• Appearance
• - we form subjective judgments easily...
• - ... but they are not related to actual
  behavior
• - we tend to trust
• pretty faces
• average faces
• faces with characteristics similar to our own

10
Alter characteristics some are trusted more

• Nationality

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Some results on trust between countries

• There are large differences between countries
  some are trusted, some are not
• There is a large degree of consensus within
  countries about the extent to which they trust
  other countries
• Inter-country trust is symmetrical the Dutch do
  not trust Italians much, and the Italians do not
  trust us much

12
Trust has economic value (1)
contract length
trust between NL and other country
13
Trust has economic value (2)
after-sales problems
trust between NL and other country
14
The effect of payoffs on behavior
15
Game theory anyone?

• Started scientifically with Von Neumann en
  Morgenstern
• (1944 Theory of games
• and economic behavior)

• 1950 John Nash (equilibrium concept). Nobel
  prize for his work in 1994, together with
  Harsanyi en Selten.

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Trust Games utility transformations
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Next experiment

• let lots of people play lots of different kinds
  of Trust Games with each other
• (how do you do that?) ? Experimental economics
• figure out what predicts behavior best personal
  characteristics of ego, of alter, or
  game-characteristics

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The effect of payoffs on behavior

• Trustworthy behavior temptation explains
  behavior well
• Trustful behavior risk ((355)/(755)) explains
  behavior well, temptation ((9575)/(955)) does
  not
• People are less good at choosing their behavior
  in interdependent situations such as this one
• Nevertheless strong effects of the payoffs on
  trustful and trustworthy behavior

19
Solving the trust problem

• Norms
• Changing the incentive structure (sanctions /
  "hostages")
• Repetition
• (cf. Robert Axelrod "The evolution of
  cooperation")

20

• Part 2 - Small world networks
• The way in which people are embedded in a
  network of connections might affect, or even
  completely determine, their behavior
• NOTE
• Edge of network theory
• Not fully understood yet
• but interesting findings

21
The network perspective
Two firms in the same market. Which firm performs
better (say, is more innovative) A or B?

• This depends on
• Cost effectiveness
• Organizational structure
• Corporate culture
• Flexibility
• Supply chain management

22
The network perspective
Two firms in the same market. Which firm performs
better (say, more innovative) A or B?
Note Networks are one specific way of dealing
with market imperfection
AND POSITION IN THE NETWORK OF FIRMS
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Example network (source Borgatti)
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Example network a food chain
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Example network terrorists (source Borgatti)
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Kinds of network arguments (from Burt)

• Closure competitive advantage stems from managing
  risk closed networks enhance communication and
  enforcement of sanctions
• Brokerage competitive advantage stems from
  managing information access and control networks
  that span structural holes provide the better
  opportunities
• Contagion information is not a clear guide to
  behavior, so observable behavior of others is
  taken as a signal of proper behavior.
• 1 contagion by cohesion you imitate the
  behavior of those you are connected to
• 2 contagion by equivalence you imitate the
  behavior of those others who are in a
  structurally equivalent position
• Prominence information is not a clear guide to
  behavior, so the prominence of an individual or
  group is taken as a signal of quality

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The small world phenomenon Milgrams (1967)
original study

• Milgram sent packages to a couple hundred people
  in Nebraska and Kansas.
• Aim was get this package to ltaddress of person
  in Bostongt
• Rule only send this package to someone whom you
  know on a first name basis. Try to make the chain
  as short as possible.
• Result average length of chain is only six
• six degrees of separation

28
Milgrams original study (2)

• Is this really true?
• It seems that Milgram used only part of the data,
  actually mainly the ones supporting his claim
• Many packages did not end up at the Boston
  address
• Follow up studies often small scale

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The small world phenomenon (cont.)

• Small world project is (was?) testing this
  assertion as we speak (http//smallworld.columbia.
  edu), you might still be able to participate
• Email to ltaddressgt, otherwise same rules.
  Addresses were American college professor, Indian
  technology consultant, Estonian archival
  inspector,
• Conclusions thusfar
• Low completion rate (around 1.5)
• Succesful chains more often through professional
  ties
• Succesful chains more often through weak ties
  (weak ties mentioned about 10 more often)
• Chain size typically 5, 6 or 7.

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The Kevin Bacon experiment Tjaden (/-1996)

• Actors actors
• Ties has played in a movie with
• Small world networks
• short average distance between pairs
• but relatively high cliquishness

31
The Kevin Bacon game

• Can be played at
• http//oracleofbacon.org
• Kevin Bacon
• number
• Jack Nicholson 1 (A few good men)
• Robert de Niro 1 (Sleepers)
• Rutger Hauer (NL) 2 Jackie Burroughs
• Famke Janssen (NL) 2 Donna Goodhand
• Bruce Willis 2 David Hayman
• Kl.M. Brandauer (AU) 2 Robert Redford
• Arn. Schwarzenegger 2 Kevin Pollak

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Connecting the improbable
3
2
33
Bacon / Hauer / Connery
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The top 20 centers in the IMDB (2004?)

1. Steiger, Rod (2.67)
2. Lee, Christopher (2.68)
3. Hopper, Dennis (2.69)
4. Sutherland, Donald (2.70)
5. Keitel, Harvey (2.70)
6. Pleasence, Donald (2.70)
7. von Sydow, Max (2.70)
8. Caine, Michael (I) (2.72)
9. Sheen, Martin (2.72)
10. Quinn, Anthony (2.72)
11. Heston, Charlton (2.72)
12. Hackman, Gene (2.72)
13. Connery, Sean (2.73)
14. Stanton, Harry Dean (2.73)
15. Welles, Orson (2.74)
16. Mitchum, Robert (2.74)
17. Gould, Elliott (2.74)
18. Plummer, Christopher (2.74)
19. Coburn, James (2.74)

NB Bacon is at place 1049
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Elvis has left the building
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Strogatz and Watts

• 6 billion nodes on a circle
• Each connected to 1,000 neighbors
• Start rewiring links randomly
• Calculate average path length and clustering
  as the network starts to change
• Network changes from structured to random
• APL starts at 3 million, decreases to 4 (!)
• Clustering probability that two nodes linked to
  a common node will be linked to each other
  (degree of overlap)
• Clustering starts at 0.75, decreases to 1 in 6
  million
• Strogatz and Wats asked what happens along the
  way?

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Strogatz and Watts (2)
We move in tight circles yet we are all bound
together by remarkably short chains (Strogatz,
2003)
? Implications for, for instance, AIDS research.
38
We find small world networks in all kinds of
places

• Caenorhabditis Elegans
• 959 cells
• Genome sequenced 1998
• Nervous system mapped
• ? small world network
• Power grid network of Western States
• 5,000 power plants with high-voltage lines
• ? small world network

39
Small world networks so what?

• You see it a lot around us for instance in road
  maps, food chains, electric power grids,
  metabolite processing networks, neural networks,
  telephone call graphs and social influence
  networks ? may be useful to study them
• We (can try to) create them
• see Hyves, openBC, etc
• They seem to be useful for a lot
• of things, or at least pop up often,
• but how do they emerge?

40
Combining game theory and networks Axelrod
(1980), Watts Strogatz (1998?)

1. Consider a given network.
2. All connected actors play the repeated Prisoners
   Dilemma for some rounds
3. After a given number of rounds, the strategies
   reproduce in the sense that the proportion of
   the more succesful strategies increases in the
   network, whereas the less succesful strategies
   decrease or die
4. Repeat 2 and 3 until a stable state is reached.
5. Conclusion to sustain cooperation, you need a
   short average distance, and cliquishness (small
   worlds)

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How do these networks arise?

• Perhaps through preferential attachment
• lt show NetLogo simulation heregt
• Observed networks tend to follow a power-law.
  They have a scale-free architecture.

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The tipping point (Watts)

• Consider a network in which each node determines
  whether or not to adopt (for instance the latest
  fashion), based on what his direct connections
  do.
• Nodes have different thresholds to adopt
• (random networks)
• Question when do you get cascades of adoption?
• Answer two phase transitions or tipping points
• in sparse networks no cascades
• as networks get more dense, a sudden jump in the
  likelihood of cascades
• as networks get more dense, the likelihood of
  cascades decreases and suddenly goes to zero

Watts, D.J. (2002) A simple model of global
cascades on random networks. Proceedings of the
National Academy of Sciences USA 99, 5766-5771
43
Open problems and related issues ...

• Decentralized computing
• Imagine a ring of 1,000 lightbulbs
• Each is on or off
• Each bulb looks at three neighbors left and
  right...
• ... and decides somehow whether or not to switch
  to on or off.
• Question how can we design a rule so that the
  network can solve a given task, for instance
  whether most of the lightbulbs were initially on
  or off.
• - As yet unsolved. Best rule gives 82 correct.
• - But on small-world networks, a simple
  majority rule gets
• 88 correct.
• How can local knowledge be used to solve global
  problems?

44
Open problems and related issues (2)

• Applications to
• Spread of diseases (AIDS, foot-and-mouth disease,
  computer viruses)
• Spread of fashions
• Spread of knowledge
• Small-world networks are
• Robust to random problems/mistakes
• Vulnerable to selectively targeted attacks

45
Application to trust

• People (have to or want to) trust each other.
• Whether or not this will work out, is dependent
  on the context in which the interaction occurs ?
  this can be given a more concrete meaning it is
  dependent on in which kind of network the Trust
  Game is being played!
• Dealing with overcoming opportunistic behavior is
  difficult, given that people are relatively poor
  at using the other parties incentives to predict
  their behavior. Perhaps it is better to make sure
  that the network you are in, deters opportunistic
  behavior.

cf. eBay reputation
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Possible assignment

• For the programmers have a look at the
  literature on "games in networks".
• Run a simulation where people are playing Trust
  Games on a network. Try to determine, for
  instance, how network characteristics affect
  behavior in Trust Games.
• Take one other "soft topics" such as trust
  (regret? envy? guilt?). Scan the literature for
  implementations of that particular topic in terms
  of abstract games. Explain and summarize the
  findings.