NETWORKS

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NETWORKS MARKETS
Macro-level economic sociology emphasizes
interorganizational networks and markets as key
theoretical units of analysis.

• Are organizations markets networked forms of
  social structure?
• How interorgl relations arise? What are its
  benefits liabilities/
• What network properties (centrality, position)
  explain organizational IOR performances?

• Are markets created by producer firms that seek
  optimal niches in a status hierarchy of volume
  and quality? If so, why are consumers demands
  for their goods services irrelevant to
  price-setting?
• Or, are markets better conceived as disembodied
  virtual entities hovering in a symbolic cultural
  space, unconnected to physical social locations?

Next, basic network concepts, then applications
to orgs markets.
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Network Concepts
Any small, closed social system may be treated as
a complete network of social relations among a
set of actors (persons, groups, or orgs)
Small half-dozen to a few hundred actors
Ego-centered network consists of one focal actor
(ego) and its direct ties to a set of others
(alters), plus all the links among those alters
Work team a complete network
Ego net friends of ego
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Network Relational Contents
Diagramming one or more networks in a social
system requires ego actors to report all the
dyadic direct ties (pairwise linkages), of a
specific type, that connect them to all other
alter actors

• A relation is the set of all ties of one specific
  type, measured for every pair of actors (dyad) in
  the network
• A tie is a direct connection or interaction
  between a dyad
• An absent tie of a dyad can be as relevant as a
  present tie
• Multiple relational contents may connect a dyad

Relational content refers to a ties substantive
meaning, the relatively homogeneous linkages
connecting network actors. Varieties of
contents, both positive and negative, are
potentially unlimited friendship, work with,
play with, advise, consult, lend , dislike,
distrust, house-sit, walk the dog for, .
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Varieties of Network Centrality
By interacting, actors come to occupy central
positions in communication and exchange networks.
A more central location reflects egos demand
from others (high prestige as a target of popular
choices ) and greater reach (access to
information, economic, and political resources).

• Degree high volume of direct contacts
  regardless of quality
• Closeness rapid access to influence over
  others
• Betweenness mediation of others ties
  (brokerage, s-holes)

Bureaucratic hierarchies are asymmetric authority
networks (legitimate power) based on command-obey
report-to relations of superiors and
subordinates. Betweenness centrality useful to a
Machiavellian player who can bridge unconnected
others. Workteams are egalitarian networks based
on advice trust relationships to build coworker
solidarity and boost collective performance. As
in dancing and horseshoes, closeness counts.
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Interorganizational Networks
Interorgl interactions involve many
communication exchange relations, creating
various types of interorganizational networks
? Spot market transactions ? Relational
contracting ? Mergers acquisitions ?
Interlocking board directorates ? Joint ventures
IJVs ? Strategic alliances

• Network analysts examine relational contents
  structural forms among interconnected
  organizations. They seek to explain
• Which orgs decide to form interorgl relations
  what types of ties?
• What are the patterns of interorgl communication
  resource exchanges in those networks? What
  density, centralization, etc.?
• How do networks shape orgl behaviors
  performance outcomes?

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Forming Interorgl Relations
At the orgl level of analysis, theories examine
interorganizational relations (IOR). Emergent
properties arise when nonunitary collective
actors interact, exchange, bargain, compete,
collaborate, conflict, ...

• Network theories try to explain origins and
  consequences of IOR ties
• Requires new theoretical concepts (e.g.,
  governance forms)?
• Are IORs simply the aggregation of individuals
  relations?
• Do organizations have motives emotions,
  interests goals? Can orgs trust one another,
  or only people?
• How do persons occupying role of organizational
  agent behave differently than when acting as
  self-interest individuals?
• What cross-level person-organization relations
  are important? Orgs ties to employees,
  shareholders, customers/clients

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Strategic Alliances

• Strategic alliance An agreement among partnering
  firms that
• remain legally independent
• share managerial control over performance of
  assigned tasks
• make resource contributions in strategic areas,
  e.g., inventing technologies, manufacturing, or
  penetrating new markets
• agree on how to distribute any benefits resulting
  from their alliance.

Communication networks can facilitate the flow of
information among potential partners about
alliance opportunities. CEO friendships, board
interlocks, professional ties can all serve as
intelligence-gathering channels. Because trust
among partners is so crucial for success,
communicating with partners-of-partners can help
to verify past performance or misconduct.
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Where Do IOR Come From?
IOR originate in combinations of environmental
constraints and endogenous network structures
that generate new social-economic relations
intended to acquire control of resources
maximize orgl performances (profit, RD
innovation, sales,regulatory autonomy)
Gulati Gargiulos dynamic model with endogenous
feedback loop from present network structure
(past alliances, common 3rd parties, joint
centralities) to transform future alliances
Relational Embeddedness
Structural Embeddedness
Positional Embeddedness
NETWORKFORMATION
Structural Differentiation
Strategic Interdependence
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Optimizing IOR Benefits
Orgs often cooperate as well as compete with the
same orgs. Which network forms optimize an orgs
IOR benefits, such as profits, market share,
growth, legitimacy, political support? Network
closure Closely knit ties among orgl set
facilitates trust, cooperative exchanges,
collective action safeguards against information
asymmetries opportunism (deception
self-interest with guile - Williamson) Network
diversity Sparse ties to orgs not linked to
current partners span structural holes to gain
brokerage benefits, access diverse resources, and
learn innovative ideas
Contingency H Alternative forms of IOR networks
are better suit to achieving different
organizational objectives (1) Close-knit
networks optimize benefits from collaboration
(2) Diverse networks optimize appropriation of
competitive benefits
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An Organizational Field-Net Theory
IOR analyses also focus on explaining relational
structures at the complete network level,
disregarding individual persons or orgs.
Kenis Knoke (2002) combined organizational
field with network properties to develop a
field-net explanation of aggregate change

• Communication ties (info exchanges) are the
  primary IOR, a necessary prerequisite to future
  interfirm collaborations
• Changes in the communication networks formal
  properties (density, centralization) alter
  opportunities for firms to find available
  partners
• Rates of change vary nonlinearly, initially
  accelerating with changes in communication
  network structures, then slowing with saturation
  or ceiling effects
• But, given its heavy longitudinal data demands,
  how testable is this so-called theory?

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Networks Change Alliances
Changes in the formal properties of an
organizational fields communication network
generate nonlinear rates of change in
interorganizational tie-formation rates (e.g.,
strategic alliances)
DENSITY
RECIPROCITY
TIE CONFIRMATION
CONNECTIVTY
RATE OF STRATEGIC ALLIANCE FORMATION
CENTRALIZATION
MULTIPLEXITY
SUBGROUP COHESION
HIERARCHY
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Markets from Networks
Harrison White developed a sociological model of
markets based on producer networks, not
neoclassical exchange theory.
In Michael Spences (1973) signaling game, market
actors seek signs of quality in goods and
services on offer. In distinguishing good used
cars from lemons, a dealer with an expensive
showroom sends a much stronger signal of her
dependability than an owner selling via want-ad.
White assumed that firms in a production market
will constantly look for signals clues on what
their rivals are doing. Then, one chooses its
volume of production to fill market niche y(n) in
the quality distribution. Handfuls of large
producers socially construct industries,
interlinked by the upstream and downstream flows
of goods services. The result is a production
economy with networks of intermediate products
and services that routinely generate net
profits for all.
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W(y) a Duck?
In Whites W(y) model, firms play all three
market roles in those streams supplier,
producer, purchaser with uncertainty about
future flows making decisions about commitments
of production facilities problematic.
The many 19th c. Minneapolis flour millers
consolidated into todays few huge global
corporate giants (General Mills, Pillsbury) that
pay close attention to one anothers strategies
for producing cereal, packaged baked goods,
bread, related product lines.
Whites math (and dense writing) on the market
schedule mechanism W(y) is difficult, but the
next figure may be more easy to grasp. W(y)
revenue-against-volume profile signals all peer
firms about their industrys stable, socially
constructed, status-ranked, quality order. Each
firm fits into one of the profiles niches,
enabling production commitments and stable
profits Firms shelter themselves within the
rivalry of a production market.
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Where are Lexus, Chevy, Kia, ?
Y (volume shipped)
Revenue-against-volume profile is a quality
ordering among competitive producer firms, where
y volume of production W(y) total revenue
received (worth). This pecking order, bundling
together structurally equivalent firms
products, is taken for granted by each firm in
making its production commitments. The quality
array also signals the products prestige to
aggregate buyers. Existing network ties become
folded into and supplanted by relations with a
quality ordering, which comes to be perceived in
terms of prestige that combines quality for
consumption with competitive relations of
rivalry.
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Slicing the Market Space
The neoclassical exchange market sets equilibrium
prices at intersection of the producers supply
and consumers demand for goods or services.
But, Whites producers do not know how consumers
view their products only what items sell, in
what volumes, at what prices. Their industry
competitors matter most Markets are tangible
cliques of producers watching each other.
Pressure from the buyer side creates a mirror in
which the producers see themselves, not
consumers.
Using a varying product substitutability
parameter (?), Whites next figure shows the
product market space differentiated into five
dynamic types Paradox, Ordinary (Grind),
Crowded, and Explosive. Ordinary producers of
high-quality goods spend increasingly more in
production costs to make a given volume of goods.
As more firms crowd into a market, producers
move into an explosive-feedback region. Every
producer keeps raising its volume, which the
market price sustains until these lemmings
plunge over the cliff!
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What Are Examples of Each Market Type?
Volume dependencies a/c
contribution/cost Quality variations b/d
desirability/expense
ORDINARY
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Sociology of Financial Markets
Karin Knorr Cetina rejected Whites orgl
approach as too narrow for fully understanding
markets in the new knowledge economy.
She examined the global microstructures of
currency traders, a 24-hour financial market.
Their main action is speculation, aimed at
profiting from the buy-sell price differentials
in spot market exchanges. Global financial
markets are decoupled from networks and exhibit
an architecture based on reflexive mechanisms of
observation and projection that project market
reality and enable it to flow. (Knorr Cetina
20058-9)
Drawing from sociology of science, Knorr Cetina
used ethnographic methods to expose the Schutzian
phenomenology of currency traders video screens.
She disputes claims that markets (and orgs) are
networked forms rather, they must be seen as
disembodied systems generated entirely in a
symbolic space an icon of contemporary global
high-technology culture (p. 38). What theories
could you construct to connect such global
reflexive systems (GRSs) to the nonvirtual
economics of production and consumption embedded
within geographical and social spaces?
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References
Gulati, Ranjay and Martin Gargiulo. 1999. Where
Do Networks Come From? American Journal of
Sociology 1041439-1493. Kenis, Patrick and David
Knoke. 2002. How Organizational Field Networks
Shape Interorganizational Tie-Formation Rates.
Academy of Management Review 27275-293.. Knorr
Cetina, Karin. 2005. How Are Global Markets
Global? The Architecture of a Flow World. Pp.
38-61 in The Sociology of Financial Markets,
edited by Karin Knorr Cetina and Alex Preda.
Oxford, UK Oxford University Press. Spence,
Michael. 1973. Job Market Signaling. Quarterly
Journal of Economics 87355-374. White, Harrison
C. 2002. Markets from Networks Socioeconomic
Models of Production, Princeton, NJ Princeton
University Press.