Transcript Document 7197382

Innovation networks and
alliance management
The Basic Network Arguments
U. Matzat
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Today
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“It’s not what you, but whom you know!”
Arguments of classical social network theories that
make clear
1. why
2. which network characteristics
3. have what effect?
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What you have learned already the last
time.....what is a network?
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Network
A set of ties among a set of actors (or “nodes”)
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Actors
persons, organizations, business-units,
countries …
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Ties
Any instance of ‘connection of interest’
between the actors
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What you have learned already the last time.....
Example: relations among organizations
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Firms as actors
Buys from, sells to,
outsources to
Owns shares of, is part of
Has a joint venture or
alliance with, has sales
agreements with
Has had quarrels with
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What you have learned already the last time.....
Why networks & innovation?
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Classical innovation studies: characteristics of individuals or
firms
 firm size
However, innovation social in nature
 firms have relations with other firms
networks
 important in explaining innovation
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and innovation changes networks as well
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Today
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Arguments of classical social network theories that
make clear
1. why
2. which network characteristics
3. have what effect?
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Outlooking Example: Innovation Success
Network closure
high
low
trust, safeguard against
opportunism
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Outlooking Example: Innovation Success
Network diversity (of a single company)
high
low
brokerage benefits,
diverse resources, innovative
ideas
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Outlooking Example: Innovation Success
Contingency H: Alternative networks for different objectives:
(1) Close-knit networks optimize benefits from collaboration
(2) Diverse networks optimize competitive benefits
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4 Basic Social Network Arguments
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Mark Granovetter: The strength of weak ties
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James Coleman: Network closure as social capital
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Ron Burt: Structural holes
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J. Coleman/R. Burt: Diffusion of innovation:
cohesion versus structural equivalence
All good theories are portable. Take them to your
problem.
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Argument 1:
Mark Granovetter
The strength of weak ties
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Mark Granovetter: The strength of weak ties
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Dept of Sociology, Harvard, “The strength of weak
ties” (1973)
strong vs. weak ties
- frequency of interaction
- emotional closeness
- duration of contact
interviewed 100 people who had changed jobs in
the Boston area.
More than half found job through personal
contacts (at odds with standard economics).
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M. Granovetter: The strength of weak ties (2)
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Many contacts rather indirect (a “weak tie”)
surprising, “strong ties” usually more willing to
help you out
Granovetter’s conjecture: strong ties are more
likely to contain information you already know
According to Granovetter: you need a network
that is low on transitivity
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M. Granovetter: The strength of weak ties (3)
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weak ties: better access to information
Coser (1975) bridging weak ties: connections to groups
outside own clique (+ cognitive flexibility, cope with
heterogeneity of ties)
Empirical evidence:
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Granovetter (1974)
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Langlois (1977): result depends on kind of job
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28% found job through weak ties
17% found job through strong ties
Blau: added arguments about high status people connecting
to a more diverse set of people than low status people
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Example: acquisition of diverse information
through weak ties
 Assume manager C has to to eliminate some contacts and he
has the opportunity to get rid of T or D
 Whom should he dump?
X X
 Get rid of T and the tie to T!
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Social Networking in plain English
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http://www.youtube.com/watch?v=6a_KF7TYKVc
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Argument 2:
James Coleman
Social Capital and network closure
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Coleman: Social capital in the creation
of human capital
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Social capital vs human capital
Dep. of Sociology,
University of
Chicago, died 1995
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Coleman: Social capital in the creation of
human capital (2) – some (vague) definitions
SEVERAL DEFINITIONS OF SOCIAL CAPITAL:
OF AN ACTOR (person/organisation)
 The resources you can mobilize through others
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The value of social networks that actors can draw
on to solve common problems. The benefits of social
capital flow from the trust, reciprocity, information, and
cooperation associated with social networks.
OF A SOCIETY
 The attitude, spirit and willingness of people to
engage in collective, civic activities: the social
infrastructure

The collective value of all social networks
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Coleman: Social capital in the creation of
human capital (3)
Human capital: the competencies and resources
you have available yourself (e.g., intelligence,
education, experience, …)
Social capital: the resources you can mobilize
through others + the way in which your
connections to others facilitate achieving one’s
goals
Note:
Social capital need not be ‘social’. For instance:
mafia family ties
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Coleman: Social capital in the creation of
human capital (4)
One of Coleman’s social capital examples:
The diamond merchants
Compare …
Diego Gambetta’s 1996 “The sicilian mafia”
( social capital need not be good for society)
Putnam’s “Bowling alone”: Social capital is
declining in the US (and according to him, this has
something do do with privatization and television)
At the same time: new social networking sites
for professionals (LinkedIn..)
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Coleman: Social capital in the creation of
human capital (5)
Social capital (of a society or group) consists of:
1.
2.
3.
Obligations and expectations
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Example: Kahn El Khalili market in Cairo
Channels of information
Norms about what (not) to do
 all kinds of collective action problems can then be
solved (e.g., prevention of deviant behavior in small
cities through gossiping curious neighbours)
For 1. and 3. you need “closure” (dense networks between
actors / connections between your ties)
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Coleman: Social capital in the creation of
human capital (6)
Social capital (of parents) leads to human capital (of children)
Empirical analysis
 To explain: school dropouts
 Network actors: pupils and their parents
 Network ties: “having frequent contact with”
To do well in school, you need
 Financial capital (physical resources)
 Human capital (cognitive environment)
 AND: Social capital
Pupils whose parents spend more time on them, drop out less
often.
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in Catholic schools parents know each other from church
related meetings
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some parents have stayed in the same neighborhood, parents
know each other better
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Example: Social capital for successful
innovation through collaboration
Two collaborating firms anticipate opportunistic behavior of
the partner
e.g.: pooling of resources for collaborating
 Standard solution: contracts
 Disadvantage: costly, sometimes difficult to manage
(e.g., are the best employees given for participation in
collaborative projects?)
 Alternative/additional solution: implementation of
collaboration in an organisational environment with high
network closure
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Example: Social capital for successful
innovation through collaboration (2)
Market 2
with high closure
Market 1
B
A
B
A*
 Assume that manager of company B has to choose between
collaboration in the two markets – which one should he
choose?
 Who would loose more by opportunistic behavior: partner A
or partner A*?
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Example: Social capital for successful
innovation through collaboration (3)
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Opportunities for company B under high network closure:
-damage of reputation of A*
-collective action with other (third) parties if A* violates
basic standards
 A* anticipates these dangers; therefore special interest in
avoidance of anything that could appear as opportunism
 Network closure as safeguard against opportunism
 Network closure facilitates trust
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Argument 3:
Ronald Burt
Structural holes
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Ron Burt:
Structural holes versus network
closure as social capital
Burt’s conclusion:
structural holes beat network closure
when it comes to predicting which actor
performs best
Coleman says closure is good
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Because information goes around fast …
… and it facilitates trust
[fear of a damaged reputation
precludes opportunistic behavior]
University of
Chicago,
Graduate School
of Business
Burt subsequently compares people (managers)
with dense networks with those with networks rich
in “structural holes”
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Ron Burt:
Structural holes versus network closure as
social capital (2)
A
B
1
7
3
2
James
6
Robert
5
4
C
 Robert’s network is rich in structural holes
 James' network has fewer structural holes
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D
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Ron Burt:
Structural holes versus network closure as
social capital (3)
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Robert will do better than James, because of:
 informational benefits
 “tertius gaudens” (entrepreneur)
 autonomy
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Ron Burt:
Structural holes versus network closure as
social capital (4)
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It is not that clear (yet) what precisely constitutes a
structural hole, but Burt does define two kinds of
redundancy in a network:
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Cohesion: two of your contacts have a close connection
Structurally equivalent contacts: contacts who link to the
same third parties
This more or less corresponds to the inverse of structural
holes:
 If two of your contacts are connected, you do not connect
a structural hole
 If two of your contacts lead to the same other, then to
get to that other, you actually would have needed only
one of those contacts
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Structural holes vs network closure
Empirical evidence on
Dependent variable
= early promotion
= large bonus
= outstanding evaluation
Most or all of the evidence seems to favor Burt’s structural
holes
Burt on Coleman:
 Coleman’s dependent variable = “dropping out of school”
 parents in a close network
 smaller probability of school dropout of children
 but: parents may tend to earn less
And about network closure:
Best team performance when groups are cohesive but team
members have diverse external contacts.
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Structural holes vs network closure (2)
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Coleman:
closure can overcome trust and cooperation problems
(empirical evidence from data on school dropouts)
Burt:
Structural holes give entrepreneurial possibilities
(empirical evidence from data on US managers)
Perhaps this is not so much a controversy after all …?
There is a problem though, when it comes to innovation. For
successful innovation one needs both to overcome trust and
cooperation problems and entrepreneurial possibilities.
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Argument 4:
James Coleman vs Ronald Burt
The diffusion of innovation:
Cohesion vs. structural equivalence
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J. Coleman/R. Burt: Diffusion of Innovations
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What happens with innovations?
a) How and when do they spread (adoption)?
b) How and when are they used?
2 theories (network theories of social influence)
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A: Coleman: Diffusion by cohesion
B: Burt: Diffusion by structural equivalence
Both theories predict which individuals of a social system are
similar with regard to behavior, evaluation of some
phenomena, and attitudes.
Both theories make predictions about who adopts an
innovation.
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Diffusion via social networks
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effects of individual differences in receptivity (k)
dy/dt = k*(1-y)*t
•effects of social contagion (influences via social
networks): The ‘Snowball Effect’
dy/dt = k*y*(1-y)*t
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Which situations?
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social influences of cost-benefit evaluation do not always
take place
important for social influences:
uncertainty of results of actions (often when actors are
confronted with innovations)
no scarcity of information, sometimes even information
overload
problem: finding trustworthy information
individuals rely on others
both models (cohesion, structural equivalence) argue that
the decisions of actors are influenced by "other actors" in the
social network
they make different predictions about who these "others" are
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J. Coleman: Diffusion of Innovation by
cohesion
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two actors share same understanding of costs and benefits
(shared attitudes) of an innovation when they socialize with
each other
shared understanding of costs and benefits (shared
attitudes) leads to similar behavior
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if alter adopts the innovation then ego will follow soon
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who are the relevant alters?
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the less indirect and the stronger the relationship between
ego and alter the more likely that social influences take
place
the stronger the relationship with alter the more likely that
the adoption of alter will trigger the adoption of ego
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J. Coleman: Diffusion of Innovation by
cohesion (2)
A
B
1
7
Peter
3
2
James
Robert
6
C
Tom
5
4
assume Peter adopts the innovation
who would be the next to adopt?
who would follow thereafter
who would never adopt?
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R. Burt: Diffusion by structural equivalence
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What is structural equivalence? - An example
1
2
3
4
3 classes of equivalent actors:
 class A: 1 & 2
 class B: 3 & 4
 class C: 5
5
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R. Burt: Diffusion by structural equivalence (2)
 two actors in structurally equivalent positions act in the
same way because their positions imply that they act under
the same structural conditions
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individuals take others as a frame of reference for judging
whether their decisions are correct
theory offers a different answer to the question "Who are the
relevant others that are taken as a frame of reference?"
structural equivalence emphasizes the competitive character
of many situations that lead to social comparisons
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R. Burt: Diffusion by structural equivalence (3)
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the more similar the relationships of ego and alter
are to other (third) individuals the more likely that
ego takes alter as a frame of reference for social
comparisons
hypothesis: the higher the degree of structural
equivalence between ego and alter the more likely
that alter's adoption will trigger ego's adoption of
an innovation
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Structural Equivalence versus Cohesion:
3 typical Cases
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A: Identical predictions of both models: social influence
between ego & alter
ego
Person 1
person 2
alter
B: cohesion: social influence between ego & alter
structural equivalence: no influence
ego
Person 3
Person 4
alter
C: structural equivalence: social influence between ego & alter
cohesion: no influence
ego
Person 3
Person 4
alter
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Today


“It’s not what you, but whom you know!”
Arguments of classical social network theories that
make clear
1. why
2. which network characteristics
3. have what effect?
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To Do:
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Read the following articles
Granovetter, M. S., "The Strength of Weak Ties,"
American Journal of Sociology 78 (6): 1360-1380
(1973).
Coleman, J.S. "Social Capital in the creation of human
capital" American Journal of Sociology 94: 95-120
(1988).
Burt, R. (2001) "Structural Holes versus Network
Closure as Social Capital", in: Social Capital. Theory
and Research, ed. by Lin, N., Cook, K. & Burt, R.
Read these papers with in the back of your head the
idea that you will have to be able to apply similar
network arguments to problems of alliance
management and innovation science.
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