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Network Economics - lectures
Network economics (Radboud Universiteit Nijmegen)
StudeerSnel wordt niet gesponsord of ondersteund door een hogeschool of universiteit
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Network Economics –
lectures
Lecture 1 – welcome and introduction to the
course
1.
2.
3.
4.
Intro
Measuring networks
Determinants of networks
Consequences of networks
One lab for every topic
Assignment over the last two topics
Networks comes from the field of sociology and made its way into physics and later into economics
6 degrees of separation (Milgram):
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Need to know by first name
Write down your name when you hand over the letter
On average there where 6 letter handovers until it came to its destination.
Nodes: actors. Lines: ties, links, lanes or edges.  network is a collection of both.
On Facebook there is three and a half degrees of separation  it keeps shrinking
Epidemiology and neuroscience benefit a lot from networks. Especially the financial sector after 2008 
risk can spread like a virus.
Why study networks:
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Trade: what alliances to entre and what conflicts to undertake depend on what alliances other
countries have. Will only have a conflict with a country that will not affect your own alliances.
Voting: informational and social messages have a direct effect. Social message had a stronger
effect, actions of your social connections have an effect on yourself.
Smoking: big influence of your surroundings on your decision to start smoking,
Relational thinking
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Who is ‘connected’ with/to whom?
Who are the actors (nodes)?
What is the connection (links)?
Networks at play:
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Can sometimes have direction in your network  f.e. who do you go to for advice
Trust network  who trusts who?  no direction because they trust each other.
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Each network can show a very different picture.
Need to get different views
Network concepts:
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The dyad: two nodes that are connected
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o
The triad: three nodes that may or may not be connected
o
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 When there is a triad, social norms start to emerge
 In an open triad, if you are B, you are in a position of power.
Simmelian tie: like a closed triad
Structural hole: like an open triad.
Position within a network can influence your behaviour
In data: 0 = no relationship, 1 = relationship.
Attributes: information about the nodes.
Lecture 2 – measuring and characterising
networks + overview of IOR
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Used network economics to find Saddam Hussein and to build his network  based on informal
aspects.
Popularity:
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Look at incoming ties  in-degree centrality
o Can mean that a lot of people reach out to you
o About how people react to you
o Could mean a position of power
o How many connections are incoming, doesn’t matter whether or not they are connected
with each other too.
o Can see it as trade links
o How do you define the link?  type of connections matter
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o
Number of outgoing ties  out-degree centrality
o How many ties are going out?
o Doesn’t have to be equal
o
Position in a network:
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Determines opportunities and constraints
Central position might become even more central over time
Does a high and rising number of friends have consequences
Are there disadvantages?
In friendship a high outdegree may not have a high indegree  so think they have a lot of friends
but are actually not very popular
Advice network:
o Sign of knowledge, tenure and power  with many requests for advice.
o A high outdegree signals the opposite  need a lot of help from others.
Betweenness centrality  connect more people to each other. Bridging networks.
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Identifies the gatekeepers within the network
Have more paths running through them, allowing them to pass (or restrict) information to others
in the network
They are sometimes in the position to benefit from privileged access to multiple sources of
information
A higher betweenness centrality
o Connect different groups and are sometimes the only link between them
o Have control over communication flows in the network
o May act as intermediaries
A = 0  don’t need to go through A to get everywhere
For C: G  B, G  A, F  B etc.  8
Can also look at speed/distances
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Diane has the highest central
Fernando and Garth have a higher between centrality  they are at a shorter distance. Easiest
for them to reach any part of the network.
Betweenness centrality = heather. Ike and Jane would be excluded without her.
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Both have the same degree centrality but they are not equally important. B is connected to
actors that have a higher degree centrality and that is why B is more important.
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Eigenvector  centrality of a node as a function of the centralities of its neighbours  it matters who
you are connected to. (don’t need to learn the formula)
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Capital is the connection between the Dutch and the French part of Belgium
2 separated communities so little interconnectedness
Community:
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Group of nodes that have a higher likelihood of connecting to each other than to nodes from
other communities
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Miscommunication and disagreements caused part of the club to support one person
and the rest the other.
Detecting communities, clusters and components in large networks
Understanding how different network structures reflect different group/node characteristics
How behaviours diffuse within and across communities
Notion of group only allows for binary membership status, while network consideres varied
levels of embeddedness and commitment
A group appears as a cohesive whole, while a network allows for multiple memberships and
interests (whether in agreement or conflict)
o
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Bottom-up approach:
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Subcultures build up from dyads and triads to more extended dense clusters
Cliques, members all know each other:
o
Generalizes the triangle
Larger cliques are rare, triangles frequently appear
Requiring a community to be a complete subgraph may be too restrictive, missing many
other legitimate communities
N-cliques
o
o
o
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o
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N-clans
o Members of n-cliques are connected by actors who are not members of the clique 
difficult to interpret
o One may add the restriction that all ties among members of an n-clique must occur by
way of other members of the n-clique
o N-clan rule
o Alternative to the stricter clique definition
o Reachability: important social processes
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o
o
Except for 1 there is a distance of two for everyone
N-clan rule: only 2,3,4,5,6  6 is not a member of the clique
Top down approach:
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Sub-structures as areas of the graph that are locally dense, but separated form the rest to some
degree
Components: sub-graphs that are connected within, but disconnected between sub-graphs
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Forms of interorganisational networks:
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Need to look into this. They are separated and need to match the right ones
Read the paper that is connected to this
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Lecture 3 – network determinants
Who are the organisations?
o
o
Types of organisations and collaborations that will be discussed
What defines the tie?
In a network equation
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Portfolio view (focal firm)
o Look at the number of ties per node
Dyad view: pair of two nodes, want to extract every pair that you have in the network and
determine the number of ties within the dyad (can be 0). Are there any ties between a pair of
nodes?
Key terms:
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Organisational boundaries: boundaries separating specialised sub-units/organisations from each
other and from external areas
Boundary spanner: actors who understand the coding schemes from the different sides of the
boundary
Reasons:
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Acquire resources
Reduce uncertainty
Enhance legitimacy
Attain collective goals
From reasons to conditions that facilitate the creation of inter-organisational networks
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Determinants:
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Learning
Trust
Norms and monitoring
Equity
Trust
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A priori trust  how to determine which one is the most trustworthy  indegree centrality, look
at closeness centrality
Interpersonal trust
Inter-organisational trust
Deterrence
Calculative
Institutional
Relational
Norms and monitoring
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Reciprocity  you do something for me, I do something for you. Put in the same effort that the
other is.
Rules of behaviour  measured with closeness centrality. What is expected from you?
Network identities  develop in a form of somebody that is behaving according to the norm
Equity
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Power  market share, customer base,
Status
Relative  relative power and status difference, if somebody is much better or lower you are
less likely to collaborate.
Lecture 4 – network determinants (part 2)
Goal:
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Strategic alliances can help alleviate environmental uncertainty, but entering alliances in its own
poses’ uncertainty
The setting:
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Organisations create stable, preferential relationships thereby reducing moral hazard problems
Over time, these embedded relationships accumulate into a network that becomes a growing
repository of loads of information on prospective partners
Allowing organisations to search the network for future alliance decisions.
Why is there a need for information?
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Strategic alliances can help alleviate environmental uncertainty, but entering alliances in its own
poses’ uncertainty
Competencies and needs of partners
o Organisations needs are multifaceted, ambiguous and not publicly available
o In which settings could this be even worse?
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 Cultural differences, privately owned, distance
Reliability of potential partners
o Moral hazard
o In which settings could this be even worse?
 Large investments (in-balance), different cultures/laws,
Possible explanations
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Interdependence: encompass accessing capabilities and resources, share the costs and risks of
technology development, enter new markets, pursue resource specialisation strategies
o The probability of a new alliance between two organizations increase with the level of
interdependence between those organisations
Interorganisational embeddedness: relying on information provided by existing
interorganisational networks. E.g. board interlocks, trade associations, research and
development ventures
o Relational embeddedness: previous direct alliances
o Structural embeddedness: indirect alliances ties through third parties
 Know the needs of the partner, and if the other partner is able to offer some of
the need of the partner you know what they have to offer.
o Positional embeddedness: reputation resulting form the potential partner’s position in
the network of pre-existing alliances
Prior ties/relational embeddedness
o Provide channels through which each partner can learn about the competencies and the
reliability of the other
o Amplify trust and diminishes the uncertainty associated with future partnerships
o The probability of a new alliance between two organisations increases with the number
of prior direct alliances between those organisations
Structural embeddedness:
o Frame of reference shifts form the dyad to the triad
o Indirect channels for information and reputation effects
o Sharing common ties
 May indicate that both are regarded as suitable and trustworthy by the same
organisations
 May signal that the partner can cooperate with the same kind of organisations
 Can create a reputational lock-in whereby good behaviour is ensured through a
concern of local reputation.
o The probability of a new alliance between two organisations increases with the number
of prior indirect alliances between those organisations
Positional embeddedness:
o Having a particular position in the network of alliances give informational benefits about
potential partners
o Central actors have a more accurate representation of the existing network
o Overall central actors lower their level of uncertainty about partnerships
o Central actors are also more attractive partners
o The probability of a new alliance between two organisations increases with the
combined alliance-network centrality of those organisations
 The higher the centrality the better
o The probability of a new alliance between two organisations increases with the similarity
in alliance network centrality between those organisations.
 About similar centralities
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Empirics
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Dependent variable: 0 or 1 if they have a tie or not.
Operationalisation:
o Interdependence: the extent to which organisations may need each other to access
critical resources and capabilities. Firms that belong to the same sector will be more
complementary
o Relational embeddedness: the extent to which a pair of organisations had direct contact
with each other in the past
o Structural embeddedness: the extent to which a given pair of organisations shared
common partners from past ties

o Positional embeddedness: the extent to which the organisations in a dyad occupy similar
or different network positions
Lecture 5 – consequences of networks and
relations at the organisational level  study this
with the powerpoint
Consequences of interorganisational networks:
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Imitation
o Information transmission leads to imitation
o Diffusion: adoption of practices through awareness  information on costs and benefits
of adoption at a greater level of detail and persuasiveness
o
o
o
o
o
Simulate how the diffusion of practices would happen
Assume that everything you learn from each other is beneficial 5/3 most beneficial. ½
uncertain.
Managers are unlikely to change the strategy even if things go bad  everyone else is
wrong but they are correct
Systematic biases  perceptual distortions
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o Rely on social networks to get advice.  but they might all have the same views/ideas
o
Innovation
o Firms in close proximity to each other gain knowledge spill overs
o Networks shape innovation input  R&D investment
o Market signal: new product awards in technically intensive industries
o
Firm survival
o Liability of newness  lack of stable exchange relations and a lack of access to resources
make new firms particularly prone to fail
o Network ties with legitimated symbols in an organisational field also affect survival
o SSA  site sharing arrangements: operate in space leased from or provided by
community based, educational and social service oriented organisations including
community centres, public schools and churches  day cares with more ties to
community organisations and government agencies have much lower death rates
Performance
o Strength of ties
 Increases sales growth for new businesses
 Balance of strong and weak ties most effective
 A main effect can still be obtained when visible network ties are interpreted as a
signal of quality that confers status on a firm, and thus increases the price of its
products and services
o Centralised or decentralised networks
 Centralisation decreased effectiveness as perceived by providers but increased
effectiveness as perceived by users
 Network centralisation:
 Refers to the power and control structure of the network, or whether
network links and activities are organised around any particular one or
small group of organisations
 Core agency centrality: whether the core agency, often a community
mental health centre, is central in the flow of services
 Concentration of influence: whether influence over decisions related to
clients was concentrated in a single organisation.
 It may be that decentralised networks are superior when they are organised
according to small world principles
 Local clustering into dense subnetworks, short paths between actors
and relatively few ties.  bridges span dense clusters and connect
different parts so that resources go from cluster to cluster
 Improve  rewire so that there are short custs between clusters that minimize
the average path distance
Network perspective: whole network vs ego network
Whole/complete network
Focus on the whole group  global structure
Ego/personal network
Focus on individual ego networks: local structure
Patterns of interaction used to explain:
- Concentration of power
- Flow of information or resources
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- Status structures
Cases are complete networks  generalised to
other networks
Cases are individual ego networks  generalised
to other ego networks
Whole networks:
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Mapping the whole set of ties to fa particulat type of a particular group, setting or population
Not focussed on one particular person or entity
Network boundaries must be well-defined
Personal networks:
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Social environment
The whole set of contacts of one person or entity
Usually includes attributes of alters and ties between them
Usually collected for a sample of egos
Graphically represented with ego at its centre
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Size: number of nodes (alters) that the ego is directly connected to
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Number of directed ties  number of connections among all the nodes in the ego network
Number of ordered pairs  number of possible ties in each ego network
Density  number of ties divided by the number of pairs
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Effective size: the number of alters – the average degree of alters within the ego network, not
counting ties to the ego
o
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Efficiency: the effective size / number of alters
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Constraint: measure of the extent to which ego is invested in people who are invested in other of
ego’s alters
o Individual constraint and aggregate constraints
o
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Hierarchy: extent to which constraint on ego is concentrated in a single alter
o
Which perspective to use?
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Depends on the research question
What aspects/characteristics of networks might matter?
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Network structure
Position in a network
Network composition  not just about how strong or how many, also matters to whom you are
connected  the same kind of companies or not. How homogenous or not your network is.
Lecture 6 – consequences of networks and
relations at the organisational level (part 2)
What network structures can lead to better innovation.
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Closure
Intense communication
Trust
Social sanctions
Social capital consists of closed structures:
- Ties among parents, teachers and other
adults ensure child does homework and
succeeds in life
Structural holes
Control of information
Opportunities  strength of weak ties
Power
Autonomy
More non-redundant information
- Managers higher compensation,
performance evaluations, promotions,
good ideas
Innovation – the role of network structure
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Q: is information collection more efficiently done in networks with closure or in networks with
structural holes
Two studies done in the same year, one in Canada and one in the chemical industry. (see slides)
o Found very different outcomes about which structure is better
o Start-ups need more openness to gain more access to more information.
Strong or weak ties?
o Strong ties: trust and fine-grained information exchanges between partners
o Weak ties: novel information, access to divergent regions of the network
o Usually have a mix of both, most beneficial depends on the context, and which ties do
you have more of
o Cohesive/intensive ties involve substantial investments while weaker linkages are
usually about marketing and licensing agreements/standards and training arrangements.
Exploitation  refinement and extension of existing competencies, technologies, paradigms,
using existing information to improve efficiency and returns from present strategies etc.
Exploration  experimention with new, uncertain alternatives; searching and experimenting to
find emerging innovations that will produce future profits
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o
Depends on environmental conditions  level of uncertainty
Vasudeva, G., Zaheer, A., & Hernandez, E. (2013). The embeddedness of networks: Institutions, structural
holes, and innovativeness in the fuel cell industry. Organization Science,24(3), 645-663.
Embeddedness of networks
Institutional context  laws/rules you have to follow/more about the environment and how you need to
operate in that environment
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Corporatism: characterize the nature of collaboration, participation and exchange among actors
within a society in the process of achieving collective goals.
High:
o Hierarchically structured and functionally differentiated groups
o Relationships often cemented through business confederations, industry associations
etc.
o Japan, Germany
Low
o Industry groups tend to arise to address narrow issues of mutual interest, dissolving
once those issues are less salient to members
o Individualism and competitiveness
o US/UK
Approach innovation in unique ways
Structural holes and innovativeness:
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Value of structural holes: ability of an actor to obtain and meld together diverse, nonredundant
information from partners not directly connected to each other
Innovation  recombination of existing knowledge for new applications.
Conditions:
o Partners to which the broker is tied should each possess nonredundant knowledge
o Broker must be capable of managing a diverse array of partners and drawing out,
absorbing and recombining the knowledge obtained from its partners in creative ways
o Knowledge flows occur from the partner to the broker
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Don’t need to memorise the formula but need to explain how it works. About understanding
About understanding the concepts
o
o
o
o
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Measures closed networks, the higher the closer the higher the constraint
It means more connections between alters the higher the constraint measure
The more alters, the lower the constraint
Is the network more closed or open?  more or fewer structural holes.
If it is normalised it is between 0 and 1.
Broker corporatism:
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Collaborative norms present in the corporatist home country of the broker enable it to better
manage the knowledge integration process so crucial for structural holes to deliver innovation
Structural holes put the broker in a position in which it must manage diversity
Collaborative norms and capabilities particularly useful when the firm spans structural holes
because it finds itself in a position in which it encounters a similar imperative to manage diverse
interests
Corporatism facilitates absorptive capacity
Have the effect of structural holes on innovative companies, use interaction effect. Positive relationship.
(see slides)
Patent = innovative performance
Alliance partner = alter
Assignment about the consequences of network  innovation (increase in innovation)
Motivate better why we excluded all the other companies  also with the hypothesis. The size would
make sense. Analysis would be restricted to a few observations which would need to be addressed.
Final lecture
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