Related teaching and research materials can be downloaded from my website (esp. course handouts “12brokerage, ”34closure,” and a book chapter “Network Structure

of Advantage”): http://www.chicagobooth.edu/faculty/directory/b/ronald-s-burt.

Social Origins of Your Reputation

the social psychology of competitive

advantage

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Trust and Reputation Can Be Critical: To the extent that a broker is advocating something new, there is no

guarantee that the proposal will work in our market, with our company processes, staffed by our people. The proposal involves uncertainty, so it requires trust; the more uncertain the proposal, the more trust required.

Are you trusted by the people you are trying to bridge?

These are data averaged across a few hundred investment bankers in the mid-1990s sorted by reputation into those with positive (solid dots), average (grey dots), or poor (hollow dots are

bankers in the bottom third of peer evaluations).

Graph is from Figure 2.8 in Burt, "Network Structure of Advantage" (2013 manuscript).

The boutique investment bank, Moelis — "Best Global Independent Investment Bank" in 2010

and "Most Innovative Boutique of the Year" in 2011 — nicely illustrates the competitive

advantage of reputation as an entrée to brokerage opportunities (free Moelis case at

www.sbs.oxford.edu/reputation/cases).

Network Status(eigenvector score / mean score)

Z-Sc

ore

Com

pens

atio

n(to

tal a

nnua

l)

Ban

ker R

eput

atio

n(m

ean

colle

ague

eva

luat

ion)

A. High Status is a Good Signalof Positive Reputation, but LowStatus Is an Ambiguous Signal

Top third

Middle third

Bottom third

B. Regardless of a Banker’s StatusPositive Reputation Is Sufficent

to Get High Returns to Brokerage

BankerReputations:

Network Constraint (C)many ——— Structural Holes ——— few

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Figure 3.1 in Brokerage and Closure (for discussion, see pages 105-111). See Appendix IX on network embedding in the theory of the firm.

Robert Jessica Robert Jessica Robert Jessica

Situation ARobert New Acquaintance

(no embedding)

Situation BRobert Long-Time Colleague

("relational" embedding)

Situation CRobert Co-Member Group

("structural" embedding)

More connections allow more rapid communication, so poor behavior can be more readily detected and punished. Bureaucratic authority was the traditional engine for coordination in organizations (budget, head count). The new engine is reputation (e.g., eBay). In flattened-down organizations, leader roles are often ambiguous, so people need help knowing who to trust, and the boss needs help supervising her direct reports. Multi-point evaluation systems, often discussed as 360° evaluation systems, gather evaluative data from the people who work with an employee. These are "reputational" systems in that evaluations are the same data that define an employee's reputation in the company. In essence, reputation is the governance mechanism in social networks.

Closure Creates a Reputation Cost for Misbehavior,Which Facilitates Trust and Collaboration

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3)"Echo" vs "Bandwidth"

versions of closure argument: more channels of communication create more frequent selective

reinforcement.Third parties do not enhance information and protection so much as they create an echo that makes people feel more certain in their opinion of you.

Bias in selecting third parties (balance mechanism) — Faced with a decision about whether to trust you, the other person (ego) turns to trusted contacts before less close contacts for information on you. Trusted contacts are likely to have views similar to ego’s, so they are likely to report accounts of you consistent with ego’s own view. A preference for trusted third parties means that ego draws a sample of information on you consistent with his or her predisposition toward you.

Bias in what third parties say (etiquette mechanism) — It is polite in conversation to go along with the flow of sentiment being shared. We tend to share in conversations those of our facts consistent with the perceived predispositions of the people with whom we speak, and facts shared with other people are facts more likely to be remembered. The biased sample of facts shared in conversations becomes the population of information on, and so the reality of, the people discussed. For example (Higgans, 1992), an undergraduate subject is given a written description of a hypothetical person (Donald). The subject is asked to describe Donald to a second student who walks into the lab. The second person is a confederate who primes the conversation by leaking his predisposition toward Donald (“kinda likes” or “kinda dislikes” Donald). Subjects distort their descriptions of Donald toward the expressed predisposition. Positive predisposition elicits positive words about Donald’s ambiguous characteristics and neglect of negative concrete characteristics. Negative predisposition elicits negative words about Donald’s ambiguous characteristics and neglect of positive concrete characteristics. In sum, echo has the other person (ego) in vicarious play with you in gossip relayed by third parties. The sample of your behavior to which ego is exposed is biased by etiquette to be consistent with ego’s predisposition toward you. The result is that ego becomes ignorantly certain about you, and so more likely to trust or distrust you (as opposed to remaining undecided between the two extremes). Favorable opinion is amplified into trust. Doubt is amplified into distrust. The trust expected in strong relations is more likely and intense in relations embedded in strong third-party ties. The distrust expected in weak and negative relations is more likely and intense in relations embedded in strong third-party ties.

III. Network Closure as the Source: Echo Story

(vs good behavior or closure bandwidth)

Third parties selectively repeat information and

enforcement,and so

amplify relationsto extremes of trust and

distrust.

See Section 4.1 inBrokerage and Closure,

Appendix IV onsusceptibility to gossip,

Dunbar (1996) Grooming, Gossip, and the Evolution of

Language.

Quidnunc (KWID-nunk, from Latin "what now", to English in 1709) - a person who seeks to know all the latest news or

gossip. Example: I lowered my voice when I noticed that Nancy, the office quidnunc, was standing right next to my cubicle hoping to

overhear what I was saying.

LovegetyFrom Wikipedia, the free encyclopedia

Lovegety is a wireless-enabled, spontaneous matchmaking service that originated in Japan in 1998. Mr.Takeya Takafuji and his friends created Lovegety.

Users enter their profile of interests into the device and when the device, with a limited wireless communications range, discovers a user with a “matching” profile, LoveGety notifies the user that their matched partner is nearby. Notification is done via device vibration. LoveGety was the inspiration for countless bluetooth-enabled matchmaking services for mobile phones, see Bluedating.

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4)Detail on Gossip Creating Ignorant Certainty. Expect extreme opinions amplifiedbygossipinclosednetworks(regardlessofthebandwidthfocusonpositiveversusnegativeindirect connectionsthrough mutual contacts).

For discussion, read the footnotes on pages 98-99 and 106 of Brokerage and Closure. For selected illustration from a team of employees driven into ignorant certainty, see Levy, "The Nut Island Effect" (2001, HBR). Several examples are briefly described in Chapter 4 of Brokerage and Closure.

E

EEEEEEEEEEEEEEEEEE

EEEEEEEEE

EEEEEEEE

EEEEEEEE

J

J

JJ

1 2 3 4 5 . . .

E Stories they know

J Stories they shareExtremePositive

Ego’sInitial

ExtremeNegative

Ego’s sequence of conversations in which business leader is discussed

Distribution of the stories knownDistribution of the stories ego hears

Opi

nion

of B

usin

ess

Lead

er

GOSSIP(data filtered by etiquette)

CREATESIGNORANT CERTAINTY

Confidence intervalaround ego’s opinion

is the average datum,plus and minus the

standard error, which is .

Variance S2 is severely underestimatedby the stories shared with ego.

The number of observations N is increasing as ego hears more stories.

So the confidence interval around ego’s opinionbecomes tight, making ego feel certain,

but only because etiquette has filtered outdata inconsistent with ego’s opinion.

S √N

Figure 2.11 Closure Essential to Reputation

Graph A plots analyst and banker reputations this year versus next. Squares are analysts (r = .55, t = 9.78), and circles are bankers (r = .61, t = 13.16). Graph B describes for the bankers subsample correlations between positive (above average)

and negative (below average) reputations this year and next year. Adapted from Burt (2010:162, 166).

Mean Number of Third PartiesConnecting Banker with

Colleagues This Year

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B. Disappears Without ClosureR

eput

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ear

(ave

rage

eva

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by c

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ague

s)

Reputation This Year(average evaluation by colleagues)

Bold line through white dots describes aboveaverage reputations (8.1 routine t-test). Dashedline through black dots describes reputationsaverage and below (6.1 routine t-test).

banker banker

1

2

3

4

1 2 3 4

1

2

3

4

1 2 3 4

A. Stability from Year to Year

AnalystsBankers

10 ormore

From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research)

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Implications for Managing Reputation

Table 2.4 in Burt, "Network Structure of Advantage" (2013 manuscript)

Questions:

When Closure Creates Bandwidth (e.g., Amazon, eBay)

When Closure Creates Echo (most social networks)

1. What makes your reputation persist?

Your consistent behavior, on which others are informed. The bandwidth provided by a closed network enhances information distribution and consistency.

Consistent stories circulating among them about your behavior. The echo produced by etiquette enhances story distribution and consistency in a closed network.

2. Therefore, who owns your reputation?

You do. It is defined directly and indirectly by your behavior.

They do. It is defined by people gossiping about you. Reputation quickly decays in open networks.

3. So, what are the implications for effectively building reputation?

Behave well and get the word out. Put a premium on projects, products, and services likely to be talked about.

4. How many reputations do you have? (Does the relevant network distribute or filter information?)

One reputation, defined by your behavior. Variation can exist from imperfect information distribution or conflicting interests, but variation is resolved by finding the true, authentic you.

Multiple, depending on gossip. You have as many reputations as there are groups in which you are discussed. The reputations can be similar, but they are generated and maintained separately.

Appendix Materials

Figure 2.3 Brokerage for Detecting and Developing Opportunities

Graph A shows idea quality increasing with more access to structural holes. Circles are average scores on the vertical axis for a five-point interval of network constraint among supply-chain managers in a large electronics firm (Burt, 2004:382, 2005:92). Bold line is the vertical

axis predicted by the natural logarithm of network constraint. Graph B shows performance increasing with more access to structural holes. Circles are average scores on the vertical axis for a five-point interval of network constraint within each of six populations (analysts, bankers,

and managers in Asia, Europe, and North America; Burt, 2010:26, cf. Burt, 2005:56).

Network Constraintmany ——— Structural Holes ——— few

Aver

age

Z-Sc

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Idea

Val

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Z-Sc

ore

Res

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form

ance

(eva

luat

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com

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n, p

rom

otio

n)

B. Yielding Performance Scores Higher than Peers(r = -.58, t = -6.78, n = 85)

A. Brokers Are More Likely to Detect & Articulate Good Ideas

(r = -.80, t = -9.67, n = 54)

Figure 2.4Network Brokers Tend To Be Recognized Leaders

Constraint and status are computed from work discussion networks around twelve hundred managers in four organizations.

A. In the formalorganization

B. And in the informal organization

Most Senior Job Ranks(29.5 mean network constraint)

Next-Lower,Middle Ranks(56.4 mean constraint)

Next-Lower,Senior Ranks(41.9 mean constraint)

r2 = .61

Net

wor

k St

atus

(S)

(Si =

Σj z

ji Sj,

divi

ded

by m

ean

so a

vera

ge is

1.0

)

Perc

ent o

f Peo

ple

with

in E

ach

Leve

l of J

ob R

anks

18%

1%

Network Constraintmany ——— Structural Holes ——— few

Network Constraintmany ——— Structural Holes ——— few

From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research)

Figure 2.9 Diagnostic Contingency in Three Organizations

Z-Sc

ore

Rel

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ompe

nsat

ion

Z-Sc

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Rel

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ompe

nsat

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Z-Sc

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Rel

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Z-Sc

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A. Leader DevelopmentAll But One Division of Firmr = -.36, t = -5.66, P < .001

The One Other Divisionr = .09, t = 1.05, P = .30

Early

Pro

mot

ion

(in y

ears

)

B. Merger & Acquisition C. Diversity

Acquiring Managementr = -.40, t = -4.92, P < .001

Acquired Managementr = .11, t = 1.06, P = .29

Women and Junior Menr = .30

t = 3.38P < .01

Senior Menr = -.40

t = -5.56P < .001

Network ConstraintNetwork Constraint Network Constraint Network Constraint

Early

Pro

mot

ion

(in y

ears

)

From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research)

Figure 2.13 Essential Closure Is Around Contacts, Maintaining the Reputations of Brokers and People in Closed Networks

Vertical axis is same as in Figure 2.11B. Horizontal axis is average number of third party connections in the networks around banker's contacts (rounded to nearest whole number). Brokers are bankers with below-median network constraint this year. Regression lines in graph go through averages. Regression equations estimated from 894 year-to-year banker transitions. Test statistics are adjusted down for correlation between repeated observations of the same bankers using the "cluster" option in Stata.

Mea

n C

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rB

anke

r’s R

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om th

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1

2

3

4

1 2 3 4

1

2

3

4

1 2 3 4

Mean Number of Third PartiesConnecting People in the Networksaround Banker’s Contacts this Year

banker banker

10 ormore

Brokers (8): Y = .248 + .202 log(X), n = 894, t = 13.0

Other (J): Y = -.047 + .274 log(X), n = 897, t = 15.1

From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research)

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Who Talks To WhomLines indicate frequent and substantive work contact (.15 ≤ connect ≤ 1.00)

270

61

384

540

33

39

190

252

760848

804

455613747

443

868

292

766

406

44

Program ParticipantSenior Executive Team (not invited to survey)Respondent (reports to participant)Nonrespondent