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Martin GargiuloINSEAD

The Two Faces of Control The Two Faces of Control Network Closure and Bonuses among Network Closure and Bonuses among

Investment BankersInvestment Bankers

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Why people cooperate (or not)?

Network research has often assumed that actors are willing to cooperate but may refrain from doing so due to concerns with opportunism

This assumption is grounded on a (naïve?) image of the market: barriers to exchange do exist and may prevent the exchange, but the motivation to cooperate exists

If questionable in a market context, the assumption is truly inadequate in an intra-organizational context

Employees cannot overtly refuse to help colleagues, but the amount of time and energy they actually devote to it can vary widely across colleagues—and so does the quality of the help these colleagues receive

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Network closure and cooperationNetwork closure and cooperation

Information

Reputation

Trust VOLUNTARYCOOPERATION

Reputation(Normative control)

Two-step (Indirect control)

FACILITATINGCooperation

INDUCINGCooperation

Reduce uncertaintyof cooperation

Raise the cost ofnon-cooperative

behavior

INDUCEDCOOPERATION

Repeated games

DRIVERS PROCESSES MECHANISMS OUTCOMES

Catalyzed

Imposed

NETWORKNETWORKCLOSURECLOSURE

Where do Interorganizational networks come from?(Gulati & Gargiulo 1999, AJS)

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-2.64

2.02

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Direct Indirect Both None

Like

liho

od

of

ob

serv

ing

tact

ic (z

-sco

res)

Conflict No Conflict

The two faces of controlThe two faces of controlCONTROL IS GOOD

Direct influence less likelyin conflict dependency

Indirect influence morelikely in conflict dependency

Direct: A builds a tie with B Indirect: A builds a tie with C but not with BBoth: A builds a tie with B and CNone: A does not build a tie with either B or C

B

CA

A

B

Actors embedded in a dense network are less likely to build ties with their new sources of dependence

P (A) < P (B)

Two-Step Leverage(Gargiulo 1993, ASQ)(Bae & Gargiulo 2004, AMJ)

Trapped in Your Own Net(Gargiulo & Benassi 2000, OS)

CONTROL IS BAD

Dependency Cooptation

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Networks, mechanisms, outcomesNetworks, mechanisms, outcomes

EGO

CONTROLConcerns for reputation and dependence enhance ego’s

ability to obtain help from alter

AUTONOMY Disconnected alters less able to impose constraints on how

ego operates

TRUSTCommon third parties

facilitate the emergence of trust between ego and alter

BROKERAGEDisconnected alters more likely

to have different information, creating brokerage opportunities

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Three questions

Are some of these mechanisms more relevant than others in explaining individual outcomes?

Does the effectiveness of these mechanisms vary with the role ego plays towards alter?

How do informal structures interact with formal structures in shaping outcomes?

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Bringing dependence asymmetry back inBringing dependence asymmetry back in

ACQUIREREgo seeks

information from alter

PROVIDERAlter seeks information

from egoEGO

Arrows indicate the direction of the dependence for information

The effects of network structure on ego’s

performance may vary with the role ego plays towards

alter in the relationship

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The contingent effects of controlThe contingent effects of controlConcerns for reputation enhance ego’s ability to obtain help from alter

Communication enhances control but it also

undermines brokerage opportunities

Lack of communication

reduces information redundancy

-

?

+

+

EGO

ACQUIREREgo seeks

information from alter

PROVIDERAlter seeks information

from ego

Communication reduces autonomy and increases

role strain

Reciprocity creates incentives to help but may

restrict the scope of the help

?

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The context: knowledge intensive firms

AS ACQUIRERAccess to high-quality information in a timely and efficient fashion

AS PROVIDERControl on the allocation

of time and energy to the demands of their role

KNOWLEDGE WORKERS AS INFORMATION BROKERSThey acquire, process, and provide information to help define and

address complex problems in the organization

How to secure the attention of colleagues who can provide that

information?

How to maintain freedom to allocate attention to

each of the demands on thier time?

Formal hierarchy Mutual dependence Network closure

Formal hierarchy Uniqueness Structural holes

PREDICAMENTS LEVERSNEEDS

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Networks in a global investment bank

Americas

Asia-PacificEMEASwitzerlandUK

Ties represent strong mutual collaboration

between MDs

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Investment bankers networks

Bonus-eligible officers in the Equities division of a global investment bank identify colleagues with whom they had substantial business interaction in the past year and rate the value these colleagues added to their own work:

“When ranking your colleagues it is important to assign the ranks in terms of usefulness to you and not your perception of their contribution to the bank in general”

Colleague evaluations are consequential for bonus decisions. Holding sex, rank, tenure, and work group constant, a 10 % increase in mean rating is worth 3 % increase in relative bonus (9.08 t-test).

Data consists of a square matrix of 2,000 employees working in 41 groups worldwide (e.g., “Sales Japan”, “Sales Derivatives Europe”). Entries in this matrix are 1 if banker i rated banker j and 0 otherwise

Ties are directional, albeit they are reciprocated in 31% of the cases Controls for sex, age, tenure, work group, and rank

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An example of a banker’s networkAn example of a banker’s network

The Banker’s Background

Sex: Male Age: 31 years

Tenure: 8 years Rank: ED Group Bus. Mgmt.

City: Tokyo Compensation: Top 10%

Banker act as acquirerBanker act as providerBanker engages in reciprocated exchanges

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Types of network structure

Sparse(Density = 0)

Dense(Density = 100)

Centralized(Density = 30)

ProviderRelationships

AcquirerRelationships

AcquirerRelationships

Effect decreases with rank

Effect increases with rank

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Measuring network structureMeasuring network structure

1)0(;)1(

100

jq

i jqi z

NN

zd

Network Density Max (di = 100)Min (di = 0)

In a network with 6 alters j, q there may be up to 30 directed ties between alters, N(N-1)

Network HierarchyThe extent to which one alter concentrates all the connections in ego’s network (Burt 1992)

H

cC N

cC N

N Ni

ij ij

i /

ln/

ln( )

][

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Variable description

Variable Description P E

Sex Male (1), Female (0) C (+)

Age Age of banker, in years C (-)

Seniority (years, ln) Length of service, in years (logged) C (-)

Rank Formal rank (D, ED, MD, AD baseline)) C (+)

Direct reports (#) Number of direct reports C (+)

Knowledge diversity Mean Euclidean distance among contacts C (+)

Quality of providers Mean rating of the providers C (+)

Quality of the banker The banker’s mean rating C (+)

Acquirer network size (ln) Number of people rated by the banker C (+)

Provider network size (ln) Number of people rating the banker C (+)

Reciprocation Proportion of reciprocal exchanges C ?

Network centralization (acquirer) Centralization in acquirer network C (+)

Acquirer-provider density (ln) Ties across people in one role only (%) C ?

Density acquirer role (ln) Ties among people rated by banker the (%) + +

Density provider role (ln) Ties among people rating the banker (%) - -

EGO

AC

QU

IRE

R

PR

OV

IDE

R

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Baseline resultsBaseline results

Variables Effect

Gender (1=male) 0.034 Age (years) -0.002 Seniority (years, ln) -0.045 Director (D) 0.157 Executive Director (ED) 0.398 Managing Director (MD) 0.905 Direct reports (#) 0.012 Knowledge diversity 0.004 Alters' mean evaluation 0.279 Ego's mean evaluation 0.097 Acquirer network size (ln) 0.031 Provider network size (ln) 0.085 Reciprocated ties (prop.) -0.136 Network hierarchy (acquirer) 0.008 Acquirer-provider density (ln) 0.013 Density acquirer role (ln) 0.088 Density provider role (ln) -0.105

The quality of the people providing information and help to the banker increases her bonus

Leverage advantages of supply-demand ties are offset by brokerage losses

Closure among people using information from ego increase her role strain, hurting compensation

Closure among people providing information to ego enhance ego’s ability to obtain their attention and help, increasing performance

Hanging around doesn’t pay. Holding rank constant, tenure has a significant negative effect on bonus

The size of a banker’s network has a strong positive effect Restricted reciprocity may be cozy, but it doesn’t pay Central players can provide indirect leverage on alters

N = 2,000

p < .05; p < .01; p < .001Fixed effects for work unit included

EGO

AC

QU

IRE

R

PR

OV

IDE

R

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Comparing alternativesComparing alternatives

Variables Constraint Density Roles

Constraint (all ties) -0.155 ••• Size (all ties) 0.102 ••• Density (all ties) -0.014 ••• Size acquirer 0.031 •• Size provider 0.085 ••• Density cross-role 0.013 Density acquirer 0.088 •• Density provider -0.105 ••• R-square .769 .774 .778

All three models have similar predictive power

Size matters. Results using the constraint measure are driven fundamentally by network size in these data

When measured as a proportion of existing ties over all of ego’s contacts–that is, without distinguishing role relationships—density does not have a significant effect on bonus (β =-.014, -1.10 t test)

Failing to distinguish between acquirer and provider role relationships may lead to erroneous identification of the mechanisms linking network structures to outcomes

N = 2,000

p < .05; p < .01; p < .001Other controls and fixed effects for work unit included

EGO

AC

QU

IRE

R

PR

OV

IDE

R

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Are these effects the same for everybody?

What we know: Networks matter more as your job is more unique (Burt 1997 in ASQ)

An alternative viewThe type of network that matters depends on the role you play

in the informal structure and your rank in the formal hierarchy

Control effects should be more apparent as we move down in the hierarchy, as lower ranks lack alternative mechanism to induce others’ cooperation

Autonomy (lack of control) effects should be more apparent as we move up in the hierarchy, as higher ranks do jobs that are more ambiguous and require more freedom to recombine resources

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Density effects vary by role and rankDensity effects vary by role and rank

VARIABLES Acquirer Provider - Baseline (AD) 0.137 ••• - Director -0.076 ••• - Executive Director -0.085 • - Managing Director -0.146 - Baseline (AD) 0.004 - Director -0.098 ••• - Executive Director -0.170 ••• - Managing Director -0.481 •••

N = 2,000

p < .05; p < .01; p < .001Other controls and fixed effects for work unit included

The positive effect of density in the information supply network weakens as we move up in the formal hierarchy and reverts to negative for managing directors

The negative effect of density in the information demand network is negligible for associate directors and becomes stronger as we move up in the hierarchy

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Density effects by network and rankDensity effects by network and rank

N = 2,000 – Log-log specificationControls and fixed effects for work unit included

0.0

0.5

1.0

1.5

2.0

2.5

-1.5 -1.3 -1.0 -0.8 -0.5 -0.2 0.0 0.3 0.5 0.8 1.0 1.3 1.5

Re

lativ

e b

on

us

(log

)

Acquirer density (deviations from mean, log)

Figure 2aAcquirer Role Relationships

`

ManagingDirectors

ExecutiveDirectors

Directors

Associates

0.0

0.5

1.0

1.5

2.0

2.5

-1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Rela

tive

bonu

s (lo

g)

Provider density (deviations from mean, log)

Figure 2bProvider Role Relationships

ManagingDirectors

Executive Directors

Directors

Associates

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Closure, norms, and survival

Years of service is negatively associated with bonus when rank is held constant

… But old-timers with a dense network do better than those with sparse networks do

Two implicationsThe mechanism through which dense acquirer networks affect

bonuses seems more consistent with normative control than with the acceleration of trust

Dense networks help foster cooperative norms, but they may also allow poor performers to survive

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The two faces of control

The normative control associated with dense networks is good to get other people to do things for you and you lack other means to induce their help

Yet, this same normative control takes away your freedom to decide which people and projects to allocate time and energy

The trade-off is not the same for everybody in the organization: the more formal authority you have, the more you need a sparse provider network, and the less you benefit from a close acquirer network

Closure is the strength of the weak

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APPENDIX

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Types of network structure

Sparse(Brokerage)

Dense(Closure)

Centralized

Network Density Max (di = 0)Max (di = 100)

NETWORK DENSITYThe density of a network is the proportion of possible ties that are presentIf you have 6 people in your network, they can have a maximum of 15 ties Possible ties = N(N-1)/2, where N is the # of people in the (symmetric) network

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4

6

8

10

12

14

16

18

20

0 20 40 60 80 100Acquirer network density

Info

rmat

ion

div

ersi

ty in

dex

Below Mean Density Above Mean Density

y = 20.96 +.001(Size) -.131(D) [-0.19] [-10.45]

y = 17.01 +.014(Size) -.046(D) [11.17] [-3.49]

Mean = 37.54

Footnote # 1:Information diversity and network density

Information diversity measured as the mean Euclidian distance among all alters in the demand network.

It assumes that diversity increase with the difference in communication patterns between actors

Information diversity increases with network size and decreases with network density

The effect of size is stronger and significant below mean density

The negative effect of density on information diversity is almost three times stronger above mean density than below the mean

Conclusive evidence would come from data in which knowledge diversity and networks are directly measured

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Footnote #2:Centralization can substitute for density

y = -0.05x + 6.32

0

2

4

6

8

10

12

14

0 10 20 30 40 50 60 70 80 90 100

Acquirer Network Density

Cen

tral

izat

ion

(H

iera

rch

y)

There are a number of bankers with sparse but centralized (hierarchical) networks. These bankers

can have leverage on their alters through the central players in their

networks, despite having a relatively sparse acquirer network