The New Handbookof Organizational Communication

The New HandbookofOrganizational

CommunicationAdvancesinTheory Research,andMethods

FREDRIC M. JABLINLINDA L. PUTNAM.

Editors

Sage Publications, Inc.International Educational and Professional PublisherThousand Oaks 9 London m New Delhi

Emergence ofCommunication Networks

PETER R. MONGEUniversi~ of Southem California

NOSHIR S. CONTRACTORUniversity of Illinois

Communication networks are the patternsof contact between communication part-

ners that are created by transmitting and ex-changing messages through time and space.These networks take many forms in contem-porary organizations, including personal con-tact networks, flows of information withinand between groups, strategic alliances be-tween firms, and global network organiza-tions, to name but a few. This chapter exam-ines the theoretical mechanisms that theorists

and researchers have proposed to explain thecreation, maintenance, and dissolution ofthese diverse and complex intra- and interorg-anizational networks. This focus provides animportant complement to other reviews of theliterature that have been organized o n the ba-sis of antecedents and outcomes (Monge CQEisenberg, 1987) or research themes withinorganizational behavior (Brass Br Krackhardt,in press; Krackhardt & Brass, 1994).

AUTHORS’ NOTE: National Science Foundation Grants ECS-94-27730, SBR-960X&, and IIS-9980Jo9supported preparation of this chapter . We wish to express our apprecia t ion to George Bamett. SteveCorman. Marya Doerfel, Andrew Flanagin, Janet Fulk, Caroline Haythomthwaite, hlaureen Heaid, FredJablin, David Johnson, David Krackhardt, Leigh Moody, Linda Putnam, Heidi Saltenberger, SWIVasserman Rob Whitbred. and Evelien Zeggelink for helpful comments on earlier drafts of this chapter.

&apter begins with a brief overview ofalysis, an examination of the rela-

between formal and emergent net-nd a brief discussion of organiza-

s. The core of the chapter focuseslies of theories and their respective

cal mechanisms that have been used toan, the emergence, maintenance, and dis-on of communication networks in orga-onal research. These are (a) theories ofnterest (social capital theory and transac-

St economics), (b) theories of mutualcrest and collective action, (c) ex-and dependency theories (social ex-

, resource dependency, and network or-onal forms), (d) contagion theoriesinformation processing, social cogni-

institutional theory, structural the-(e) cognitive theories (semantic

reduction and contingency theo-support theories, and (j) evolu-

The chapter concludes with aagenda for future research on

@y emergence and evolution of organizational$frnmunication networks.,_. *at-; ; - ‘ .;pTWORK ANALYSIS.:‘;-”;,. , /.Y:.g-$etwork analysis consists of applying a set-- _-.-.. “..” *.. 3LL “I

- . ihe context of organizational communica-G& .g.;.tion, network analysts often identify the enti-Sties as people who belong to one or more or-

,ganizations and to which are applied one ormore communication relations, such as “pro-%des information to,” “gets information

;:.l’from,” and “communicates with.” It is aho$$T-C’omrnon to use work groups, divisions, andk$%ntire organizations as the set of entities andrz’ to explore a variety of relations such as “coI-5 - laborates::’ wi th ,” “subcontracts with,” and

‘joint ventures with.”

Emergence o f Communicat ion Networks + 44 I

Relations in a World of Attributes

Relations are central to network analysisbecause they define the nature of the commu-nication connections between people, groups,and organizations. This focus stands in sharpcontrast to other areas of the social sciences,which have tended to study attributes, thecharacteristics of people, groups, and organi-zations rather than the relations betweenthem. Relations possess a number of impor-tant properties, including the number of enti-ties involved, strength, symmetry, transitivity,reciprocity, and multiplexity. A large litera-ture exists that describes these properties andother fundamentals of network analysis, in-cluding network concepts, measures, meth-ods, and applications (see, e.g., Haythorn-thwaite, 1996; Marsden, 1990; Monge, 1987;Mange L’ Contractor, 1988; Scott, 1988,1992; Stahl, 1995; Wasserman & Faust, 1994;Wigand, 1988). Since the focus of this chapteris on theory and research results, it is not fea-sible to further explore the details of networkanalysis. However, in addition to the refer-ences cited above, Tables 12.1, 12.2, and 12.3(from Brass, 1995b) summarize major net-

work concepts. These tables describe mra-sures of network ties, measures assigned to in-dividuals, and measures used to describeentire networks.

Network linkages

Network linkages are created when one ormore communication relations are applied toa set of people, groups, or organizations. Forexample, in organizational contexts Farace,Monge, and Russell (1977) identified threedistinct important communication networks interms of production. maintenance, and inno-vation linkages.

Other kinds of communication linkages arepossible. For example, Badaracco (1991) dis-tinguished two types of knowledge, which hecalled migratory and embedded, each associ-ated with a different type of linkage. Migra-

442 + Structure

I

11 4TABLE 12.1 Typical Social Network Measures of Ties : ., ; ;

Measure Definition Example-c

..’4

Indirect links Path between two actors is mediated

by one or the other

Frequency How many times, or how often

the link occurs

A is linked to B. B is linked to C; thus 1.:::

A is indirectly linked to C through B ‘.:;-

A talks to B IO times per week ..i

Stabil i ty

Multiplexity

Extstence of link over time

Extent to which two actors are

linked together by more than one

relationship

A has been friends with B

A and B are friends, they seek out each ‘&

other for advice, and work together-2;

9..?;t,.‘d.::

Strength Amount of time, emotional intensity,

intimacy, or reciprocal services

(frequency or multiplexity often

used as measure of strength of t ie)

Direction Extent to which link is from one

actor to another

S y m m e t r y Extent to which relationship is

bi-directional

A and B are close friends, or spend

much time together

Work flows from A to B. but not from=*ifr

B to A‘8.L”,

:,;

A asks B for advice, and B asks A for

advice

SOURCE: Reprinted from D. J. Brass. “A Social Network Perspective on Human Resources Management.” in G. R. Ferr is2..:TV<,

(Ed.). Research in Personnel and Humon Resources Management, Vol. 13. Copyright 1995. p. 44, with permission from Elsevicr&

tory knowledge is that information that existsin forms that are easily moved from one loca-tion, person, group, or firm to another. Migra-tory knowledge tends to be contained inbooks, designs, machines, blueprints, com-puter programs, and individual minds, all ofwhich encapsulate the knowledge that wentinto its creation. Embedded knowledge ismore difficult to transfer. It “resides primarilyin specialized relationships among individualsand groups and in the particular norms, atti-tudes, information flows, and ways of makingdecisions that shape their dealings with eachother” (Badaracco, 1991, p, 79). Craftsman-ship, unique talents and skills, accumulatedknow-how, and group expertise and synergyare all difficult to transfer from one place to

another and particularly difficult to trat@5across organizational or even divisional boUn-daries.

:bl\j.‘.y. .

The two types of network linkaq.cBadaracco (199 1) identified were the prod62link, associated with migratory knowle&$#and the knowledge link, associated with e$$$bedded knowledge. In the interfirm contex2.?%product link is an arrangement whereby ;a>$$company relies on “an outside ally to ma??‘5..,a”’facture part of its product line or to build c?T$$plex components that the company had Pre??@ously made for itself” (p. 11). Knowld@:$links are alliances Lvhereby companies sfski,g

“to learn or jointly create new knowledge.J ‘$5*“k%#k-.+?

capabilities” (p. 12). These “alliances are&;;XJg$$

ganizational arrangements and operating P”g .‘fLg~

$i$

lnsferboun-

‘<agesoduct

edge,i em-ext, a

by aianu-com-revi-e d g eseek

: and.: or-30%

I..?

TABLE 12.2 Typical Social Network Measures Assigned to Ir.c-,*:Jal Actors

Measure Definition

Degree

In-degree

Out-degree

Range (divers+,

Closeness

Bctweenness

Centrality

Prestige

ROICStar

Liaison

Bridge

Gatekeeps-

Isolate

Number of direct links with other actors

Number of directional links to the actor from other acto- .--rzming links)

Number of directional links from the actor to other ac;oc >-:-:oming links)

Number of links to different others (others are defined as i=e.mt to the extent

that they are not themselves linked to each other, or re;zzy different groups

or statuses)

Extent to which an actor is close to, or can easily reach L :-a &er actors in

the network. Usually measured by averaging the pa-b disc-1:~ (direct and

indirect links) to all others. A direct link is counted as I, ~rt:~ links receive

proporrionately less weight

Extent to which an actor mediates, or falls between any CT*- yedo actors on the

shortest path between those actors. Usually averaged a~- E! possible pairs in

the network

Extent to which an actor is central to a network. Variccs -I-z-res (including

degree, closeness, and betweenness) have been used as 1-.5,c:rrs of centrality.

Some measures of centrality weight an actor’s linb to c-e: Y: centrality of

those others

Based on asymmetric relationships, prestigious actors L-G z-t qect rather than

the source of relations. Measures similar to centrallrf are cr~:ed by

accounting for the direction of the relationship (i.e., in-is-

An actor who is highly central to the network

An actor who has links to two or more groups that wou:c :z-c.-NIse not be

linked, but is not a member of either group

An actor who is a member of two or more groups

An actor who mediates or controls the flow (is the sin+ :.-q zetween one part

of the network and another

An actor who has no links, or relatively few links to othe:

SOURCE: P,e;-,Y-_ f rom D. j. Brass. ‘A Social Network Perspective on Human Rzszur:z “2-a-iement.” in G. R. Ferris(Ed.), Reseor~- - +wnnel and Human Resources Management. Vol. 13. Copyright 1495. : Li -% permission from ElsevierScience.

tics throu$ = hich separate organizations Research on i;:trorganizational linkagessll:lrc admir.i:xtive authority, form social began almost 40 1:~s ago with the work oflinks, and x:tet joint ownership, and in Levine and nhi:: ’ 1961) and Litwak and

\\‘hich looser. <ore open-ended contractual Hylton (1962), xI-,i:Y spawned a quarter cen-;~~~:l[l~emen;: r:glace highly specific, arm’sICngth corm-x:.-(Badaracco, 1991, p. 4).

tury’s worth of iE:?r:st on the exchange ofgoods and ma!%< resources (see, e.g.,

4 4 4 + S t r u c t u r e

TABLE 12.3 Typical Social Network Measures Used to Describe Networks

Measure

Size

Inclusiveness

-Definition

Number of actors in the network

Total number of actors in a network minus the number of isolated actors (not

connected to any other actors). Also measured as the ratio of connected actors

to the total number of actors

Component Largest connected subset of network nodes and l inks. All nodes in the

component are connected (either direct or indirect links) and no nodes have

links to nodes outside the component

Connectivity

(reachability)

Extent to which actors in the network are linked to one another by direct or

indirect ties. Sometimes measured by the maximum, or average, path distance

between any two actors in the network

Connectedness Ratio of pairs of nodes that are mutually reachable to total number of pairs o

nodes

Density Ratio of the number of actual l inks to the number of possible l inks in the

network

Centralization Difference between the centrality scores of the most central actor and those ofall other actors in a network is calculated, and used to form ratio of the actual

sum of the differences to the maximum sum of the differences

Symmetry Ratio of number of symmetric to asymmetric links (or to total number of links)

in a network

Transi t iv i ty Three actors (A, B, C) are transitive if whenever A is linked to B and B is linked

to C, then C is l inked to A. Transit iv i ty is the number of t ransit ive tr iples divided

by the number of potential transitive triples (number of paths of length 2)

SOURCE: Reprinted from D. J. Brass. ‘X Social Network Perspective on Human Resources Management.” in G. R. Ferris(Ed.). Research in Personnel and Human Resources Monogement, Vol. 13. Copyright 1995. p. 44, with permission from Elsevier

Science.

Mitchell, 1973; Warren, 1967). More recentwork has focused on communication, infor-mation, and knowledge linkages (Gulati,

1995). Eisenberg et al. (1985) developed atwo-dimensional typology of interorgani-zational linkages based on linkage contentand linkage level. The content dimension sep-arated material content from symbolic or in-formational content. The level dimension dis-tinguished three forms of exchange.Eisenberg et al. (1985) state:

An irzsrifzctiord linkage occurs when informa-

tion or materials are exchanged between orga-

niza t ions wi thout the involvement of spec i f ic

organiza t ional ro les or personal i t ies (e .g . . rou-

tine data transfers between banks). A represen-tative linkage occurs when a role occupant

who officially represents an organization

nithin the sys tem has contact with a represen-

tative of another organization (e.g., an inter-

agency committee to formulate joint pol icies) .

The emphasis here is on the off icial nature of

the t ransac t ion and the representa t ive capaci.

ties of the individuals. Finally. apcrsorznl link-

age occurs when an individual f rom one Orga-

nization exchanges information or material

wi th an ind iv idua l in ano ther o rgan iza t ion . but

,. ,-.mphasis in the original).

$g$,).),.:~~. -+. . . . Uirtorically, organizational communica-

s have made important theoretical:a1 distinctions between formal and

;i;-i’“.;;,< .-..---L, etworks. Theoretically, the notion$$@@$,-,fl’emergent network” was a designation that?&,$T;;. originally differentiated informal, naturally

from formal, imposed, or

;.c::y --~ :s (Aldrich, 1976), the lat-$$; ter of which represented the legitimate author-

ity of the organization and were typically re-Betted by the organizational chart. Theformal networks were presumed to also repre-sent the channels of communication throughwhich orders were transmitted downward andinformation was transmitted upward (Weber,1947). Early organizational theorists wereaware that the formal organizational structurefailed to capture many of the important as-‘pects of communication in organizations and

pg$i:,i:, &cussed the importance of informal commu-!&@;&-q’Va”““A’- nication and the grapevine (Barnard, 1938;

@.; Follett, 1924). Several scholars developed”&- *“‘ ; ‘ , ways to study the grapevine and informal net-&$:‘:;‘.@;?? j works such as Davis’s (1953) episodic com-:&-.” _Z+ municationggy. .@cco)

in channels of organizationsanalysis, a technique for tracing the

&:$: person-to-person diffusion of rumors or other.‘-’ ;:&g ’ items of information in an organization.t&;.‘.. : Researchers have provided considerable@,$‘: evidence over the years for the coexistence of,Q-:’F*“!:p.:,; the two networks. For example, using a vari-

ant of ECCO analysis, Stevenson and GilIy

i: t

(1991) found that managers tended to forwardproblems to personal contacts rather than toformally designated problem solvers, thus by-Passing the formal network. Similarly, Al-brecht and Ropp (1984) discovered that“workers were more likely to report talkingabout new ideas with those colleagues withwhom they also discussed work and personalmatters, rather than necessarily following pre-scribed channels based upon hierarchical rolerelationships” (p. 3). Stevenson (1990) argued

E m e r g e n c e ofCommunication N e t w o r k s + 4 4 5

that the influence of formal organizationalstructure on the emergent structure could bebest understood on the basis of a status differ-ential model. In a study of a public transitagency, he found evidence that the social dis-tance across the hierarchy reduced the level ofcommunication between higher- and lower-level employees, with middle-level employeesserving as a buffer.

An important rationale for studying emer-gent communication networks has evolvedout of the inconclusive findings relating for-mal organizational structure to organizationalbehavior (Johnson, 1992, 1993; see alsoMcPhee & Poole, Chapter 13, this volume).Jablin’s (1987) review of the empirical re-search on formal organizational structurespointed to the inconclusive nature of studiesinvolving structural variables such as hierar-chy, size, differentiation, and formalization.More recently, a series of meta-analytic stud-ies has concluded that the relationships be-tween formal structure, organizational effec-tiveness (Doty, Glick, & Huber, 1993; Huber,Miller, & Glick, 1990), and technology(Miller, Glick, Wang. 8r Huber, 1991) arelargely an artifact of methodological designs.The fact that formal structural variables havefailed to provide much explanatory poster hasled several scholars to argue that emergentstructures are more important to study thanformal structures because they better contrib-ute to our understanding of organizational be-havior (Bacharach & Lawler, 1980; Krack-hardt & Hanson, 1993; Krikorian, Seibold, RrGoode, 1997; Roberts & O’Reilly, 1978;Roethlisberger & Dickson, 1939).

These problems with formal structures andthe recent priority given to emergent structurehave prompted scholars to develop networkmeasures that capture in emergent networksthe key concepts used to describe formal orga-nizational structure. For example, Krackhardt(1994) has developed four measures of infor-mal structure-connectedness, hierarchy, effi-ciency, and least-upper-boundedness (unity-of-command)-that map onto theories of anorganization’s formal organizational struc-ture.

4 4 6 + S t r u c t u r e

Further, the increased use of new com-

puter-mediated communication systems hasspawned research that uses formal organiza-tional structure as a benchmark against whichto compare communication networks thatemerge in an electronic medium. Several in-teresting, though somewhat conflicting, find-

ings have emerged. In a two-year study ofover 800 members of an R&D organization,Eveland and Bikson (1987) found that elec-tronic mail served to augment, and in somecases complement, formal structures. On theother hand, Bizot, Smith, and Hill (1991)found that electronic communication patternscorresponded closely to the formal organiza-tional structures in a traditionally hierarchicalR&D organization. Lievrouw and Carley(199 1) argued that new communication tech-nologies might usher in a new era of “telesci-ence” by offering alternatives to the tradi-tional organizational structures in universitiesand industry. However, Rice (1994b) foundthat the electronic communication structuresinitially mirrored formal organizational struc-tures, but these similarities diminished o v e rtime. Hinds and Kiesler (1995) explored therelationship between formal and informal net-works in a telecommunications company.They found that communication technologiesu’ere increasingly used as a tool for lateralcommunication across formal organizationalboundaries; this finding was most pronouncedfor technical workers.

The literature comparing face-to-face ormediated emergent communication structureswith formal structures generally demonstratesa “pro-emergent bias.” That is, the theory andempirical evidence focus on the advantages ofinformal communication to individuals andorganizations. However, Kadushin andBrimm (1990) challenged the assumption thatthree types of emergent networks, (a) theshadow networks (the “real” way things getdone), (b) the social interaction networks, and(c) the career networks (the venue forso-called networking) always serve to aug-ment the limitations of the organization’s for-mal network. Instead, they argued that thesethree informal networks frequently work at

promoting the organization’s interests. In 3study of senior executives in a large, interna-:tional high-technology company, they faunathat by saying, “Please network, but don’t yoJdare bypass authority,” organizations creatiwhat Bateson (1972) called a “double bind,‘* ichoice situation where each alternative co,,+flicts with the others. They argued that ll&’important first step is to recognize the incorn;‘,patibilities between emergent network sur&~~!tures and corporate authority structures and $3

fmove this inconsistency from the realm of52double bind to the domain of paradox” (I&-i-$dushin & Brimm, 1990, p. 15). I’?-:. L‘rJ,

Clearly, there is continuing scholarly inter-:?;est in the study of the differences between for-l/2ma1 and emergent networks in organizations.‘.ii$Ironically, however, the distinction between $j,formal and informal structures in organiza- Z@!tions has diminished sienificantlv in recent ..%%

are changes to more team-based forms of or- :@: .F”.:ganizing, the adoption of matrix forms of or-“:.:?,;,z*ganizational structure (Burns & Wholey, $$;1993), and shifts to network forms of organiz- G$#

ing (Miles & Snow, 1986, 1992, 1995; ii;Mange, 1995). At the core of these changes 2has been the explosion of lateral forms of .:communication (Galbraith, 1977, 1995) made ‘:%

possible by new information technologies that +$;:“g

facilitate considerable point-to-point and t$$broadcast communication without regard for :jgtraditional hierarchy. +;g

These developments have eroded the dis- cqtinction between prior structural categories $3used to characterize organizations, specifi- ,Fitally, between formal and informal and/or be- ,‘q,..:7tween formal and emergent. Contrary to tradi- ‘:I:$‘:g ,

tional views, contemporary organizations arey;g$__ <f,a...

increasingly constructed out of emergent ..,$!communication linkages, linkages that are

,>‘-;I‘ .y>,

ephemeral in that they are formed, main- :.“+$i

tained, broken, and reformed with consider--:..+g

.‘I~

able ease (Palmer, Friedland, & Singh, 1986).

: :-.g.,

“.&i

As Krackhardt (1994) says,

g$:.F$, inherent principle of the interactive form isg,bat networks of relations span across the en-:2&e 0rganizatiOn. unimpeded by preordained

$iom,d Structures and fluid enough to adapt to$timmediate technological demands. These Aa-p’,Fitions can be multiple and complex. But one$h~aCteristiC they share is that they emerge inghe organization, they are not preplanned. (p.:p-- -$:zl&emphasis in the original).J, Ii,‘,

.+I..,

le networks that emerge by these processesp&d the organizations they create are called.$&work and organizational forms. Both are$$iiewed in the following section.

“i-z. Commumcation network patterns that re-y:” _:;,,-cur in multiple settings are called nehvork12~ @forms. An early theoretical article by Bavelaszfb:;; ,(1948) based on Lewin’s (1936) psychologi-$‘G cal field theory identified a number ofL&32; small-group communication network forms ing.’ organizations, including the chain, circle,!?‘- wheel, and comcon (completely connected),k:,$.:yd theorized about how the different forms$’ processed information. These network forms5:. ._ varied in the degree to which they were cen-:1.$ traIized, with the wheel being the most cen-:,. tralized and the comcon the least centralized.;“.t:i _’ This theoretical article and an imaginative

experimental design created by Leavitt (19.5 1)generated hundreds of published articles oversome 25 years. The primary focus of these ef-forts was the impact of information process-ing via the different network forms on produc-tivity and satisfaction (see Shaw, 1964, for areview of this literature). Two prominent find-ings emerged from this research. First, cen-tralized organizations were more efficient forroutine tasks, while decentralized networkswere more efficient for tasks that required cre-ativity and collaborative problem solving.Second, people in decentralized organizationswere more satisfied with the work processesthan people in centralized organizations, withthe exception in the latter case that the central

anizational Forms

Emergence ofCommunication Networks + 447

person in centralized networks was extremelysatisfied. Unfortunately, little further theoreti-cal development accompanied this plethora ofempirical research. As a result, this line of in-quiry has essentially died; almost no articleshave been published on small-group networkforms in organizations during the past 20years.

Organizational structures, including com-

munication networks, that share common fea-tures or patterns across a large number of or-ganizations are called organizational forms(McKeIvey, 1982). Weber (1947) argued thatbureaucracy was the universal organizationalform. Three principal theoretical mechanismsthat created bureaucracy were rationalization,differentiation, and integration. Rationaliza-tion occurred by specifying legitimating in-structions that produced standard operatingprocedures, thus leaving little opportunity forindividual autonomy. Rationalizing the net-work meant specifying who could say what towhom, often summarized by the injunctionthat commands should flow downward and in-formation upward in the bureaucracy. Differ-entiation was the process of breaking work upinto its various components. This often led tojob specialization particularly as productionprocesses proliferated and increased in sizeand complexity. As work became differenti-ated, the various parts needed to be coordi-nated, and thus processes of integration cameinto operation. Weber argued that bureaucracydifferentiated along vertical organizationallines and primarily integrated that way aswell. Bureaucracy allowed little room for lat-eral, cross-level, or cross-boundary communi-cation networks, that is, informal or emergentnetworks, a feature for which it has been fre-quently criticized (Heckscher, 1994).

Miles and Snow (1986, 1992) identifiedfour major organizational forms that have de-veloped over the past century: (a) the tradi-tional functional form, which emerged duringthe early part of the century; (b) the divisional(or multidivisional) form, which was begunby Alfred P. Sloan at General Motors in the1940s (see Chandler, 1977); (c) the matrixform, which evolved during the 1960s and

4 4 8 4 Structure

1970s; and (d) the network form, which hasemerged over the past decade. Miles andSnow (1992) argue that each of these formscontains its own operating logic, or in terms ofthis chapter, theoretical mechanism. The func-tional form uses a logic of “centrally coordi-nated specialization” (p. 58), which enables itto efficiently produce a limited set of stan-dardized goods or services for a stable, rela-tively unchanging market. The divisionalform operates by a logic of “divisional auton-omy with centrally controlled performanceevaluation and resource allocation” (p. 60).Divisions produce separate products or focuson separate markets but are collectively ac-countable to centralized authority throughtheir communication networks. The ability todevelop new divisions enables the multidi-visional form to pursue new opportunities inchanging markets. The matrix form combinesthe operating logic of functional and multidi-visional forms, using the functional form toproduce standardized goods and services andthe shared resources of the multidivisionalform to explore new opportunities via projectgroups or teams. The network form uses flexi-ble, dynamic communication linkages to con-nect multiple organizations into new entitiesthat can create products or services.

THEORETICAL MECHANISMSTO EXPLAIN THE EMERGENCEOF NETWORKS

Communication network analysis falls with-in the intellectual lineage of structural analy-sis, which has had a long and distinguishedhistory. In sociology, Herbert Spencer (1982)and Smile Durkheim (1895/1964) are oftencredited with introducing structural conceptsinto sociological thinking. In anthropology,Radcliffe-Brown (1952/1959) incorporatedstructural-functionalist ideas into his water-shed analysis of cultures. And in linguistics,structural thinking can be traced to the pio-

neering work of de Saussure (1916/1966).Most structural analyses of organizations andcommunication can be located in one of threetraditions: positional, relational, and cultural.

The posirionaf tradition is rooted in theclassical work of Max Weber (1947), TalcottParsons (1951), and George Homans (19.58).Organizational structure is viewed as a patternof relations among positions. Sets of Organi-

zational roles are associated with positionsand specify designated behaviors and obliga-tory relations incumbent on the people whoassume the positions. The positions and at-tached roles constitute the relatively stableand enduring structure of the organization in-dependent of the people who fulfill the roles.This tradition leads to the view that positionsand roles determine who communicates withwhom, and consequently, the communicationstructure of the organization. White, Boor-man, and Breiger (1976) and Burt (1982) havedeveloped the most significant recent posi-tional theories applicable to organizational *communication under the rubric of structuralequivalence. This theory argues that peoplemaintain attitudes, values, and beliefs consis-tent with their organizational positions irre-spective of the amount of communication thatthey have with others in their organizationalnetworks. The positional tradition has beencriticized for its inability to take into accountthe active part individuals play in creating andshaping organizational structure (Coleman,1973; Nadel, 1957; White et al., 1976).

The relariorraI tradition focuses primarilyon the direct communication that establishesand maintains communication linkages.Taken collectively, these linkages create anemergent communication structure that con-nects different people and groups in the orga-nization irrespective of their formal positionsor roles. Rooted in systems theory (Bateson,1972; Buckley, 1967; Watzla\vick, Beavin, 8:Jackson, 1967), the relational tradition em-phasizes the dynamic, constantly changing,enacted nature of structure created by repeti-tive patterns of person-to-person messageflow. Rogers and Kincaid (195 1) claim that it

1s and at-:IY stablezation in-the roles.positions

:ates withunicationte, B o o r -

J82) haveent posi-iizationalstiU3.rrallt peoples consis-3ns irre-tion thatizationalKS beenaccountting and

‘oleman,

rimarilysblishesnkages.

‘eate anlat con-3e orga-ositionsjateson,avin, &on em-anging,repeti-

lessageI that it

dominant tradition in organizationalF.. WC$junicatiOn.

; The crt[r~crnl tradition examines symbols,. . ’&jeanings, and interpretations of messages

,,t;$nsmitted through communication net-:;:;.,,.,works. As part of the resurgence of interest in

&&‘j&.ganizational culture (Frost, Moore, Louis,$?~~?[&undberg, & Martin, 1985), much of the work@,,~$.nas been based on Giddens’s (1976, 1984)

,,1Y31k<<+itings on structuration, which attempt to ac-$!$~$~-,iia.v%7’y coun t for both the creative and constraining

wjy.:y. p t f‘I.“\ +e-:i-jas ec s 0 social structure. These studies aret$$!;&‘; .;%%~‘? Icharacterized by an explicit concern for the~&,-&,~~~‘~ .(4~L~;~~~.~:.<:<s~.. 1 .‘.continual production and reproduction of;,gj$ <. 3.;; ‘ .

meaning through communication, examiningsimultaneously how meanings emerge frominteraction and how they act to constrain sub-sequent interaction. The cultural tradition hasspawned recent work on semantic networks(Mange & Eisenberg, 1987) described later inthis chapter. These three traditions are dis-cussed in greater detail in Monge andEisenberg (1987).

Although interesting and useful, these net-work traditions focus attention at ametatheoretical level and fail to specify thetheoretical mecfrarukrs that describe howpeople, groups, and organizations forge,maintain, and dissolve linkages. Further,while a number of scholars over the past de-cade have called for greater explication of net-work theory (e.g., Rogers, 1987; Salancik,1995; Wellman, 1988), almost none have pro-vided it. Finally, while several reviewers haveidentified theories that are applicable to net-work research within and between organiza-tions (Brass 8 Krackhardt, in press;Galaskiewicz, 1953; Grandori & Soda, 1995;Mizruchi & Galaskiewicz, 1994; Smith,Carroll, 8 Ashford, 1995), none have system-atically explored the theories and their theo-retical mechanisms.

This chapter addresses these omissions inthe organizational communication networkliterature by focusing on the role of theory andtheoretical mechanisms in explaining theemergence of communication networks. MoreSpecifically, it examines the extant organiza-

Emergence 0fCommunicotion Network5 + 449

tional literature using a network perspectivewith special attention to the mechanisms thathelp explain the emergence of networks. Thisreview will demonstrate that a wide array oftheories is amenable to network formulations.In some cases, different theories, some usingsimilar theoretical mechanisms, offer similarexplanations but at different levels of analysis.The review will also underscore the consider-able variation in the depth of conceptual de-velopment and empirical research across thedifferent theories and theoretical mechanisms.Since the chapter focuses on theoreticalmechanisms, many other interesting networkarticles that have little or no bearing on theseissues have not been included. The theoriesand their theoretical mechanisms are summa-rized in Table 12.4.

i

Theories of Self-Interest

Social theorists have long been fascinatedby self-interest as a motivation for economicand other forms of social action (Coleman,1956). Theories of self-interest postulate thatpeople make what they believe to be rationalchoices in order to acquire personal benefits.The strong form of this theoretical mechanismstipulates that people attempt to maximizetheir gains (or minimize their losses). Theweaker theoretical form says that people“satisfice” rather than maximize, whichmeans that people choose the first good alter-native they find rather than exploring all alter-natives and selecting the best. Two theories ofself-interest that have been used to explorecommunication network issues are examinedin this section: the theory of social capital andtransaction cost economics theory.

Theory of Social Capital

The deployment of social capital (Cole-man, 198s) in networks is best represented inBurt’s (1992) theory of structural holes. Thistheory argues that people accumulate socialresources, or “social capital,” which they in-

TABLE 12.4 Ten Families of Theories and Their Theoretical Mechanisms to Explain the Emergence of Networks

Theories Jheoreticol Mechanisms Refevont Orgonizotionol Variables

I. Theories of self-interest

Theory of Social Capital

Theory of Structural HolesTransaction Cost Economics Theory

2. Theories of mutual self-interest andcol lect ive act ion

Public Goods Theory

Critical Mass Theory

3. Exchange and dependency theories

Social Exchange Theory

Resource Dependency TheoryNetwork Organizations

4. Contagion theories

Social information Processing Theory

Social Learning Theory

Institutional Theory

Structural Theory of Action

5. Cognitive theoriesSemetic and Knowledge Networks

Cognit ive Social StructuresCognitive Consistency theories

Balance TheoryTheory of Cognitive Dissonance

Investments in opportunit ies

Control of information flow

Cost minimization

Joint value maximizat ion

Inducements to contributeNumber of people with resources and interests

Exchange of valued resources (material or information)

Exposure or contact leading to:

Social inf luence

Imitat ion, model ing

Mimetic behavior

Similar positions in structure and roles

Cognit ive mechanisms leading to:Shared interpretations

Similarity in perceptual structures

Drive to restore balanceDrive to reduce dissonance

Employee autonomy, f lexibi l i ty

Employee effectiveness

Employee efficiencyOrganizat ional innovat ion

Coordination by markets and hierarchies

Contr ibut ions to col lect ive good

Mobil ization of resources

A d o p t i o n o f i n n o v a t i o n s

Power, leadership

Trust and ethical behavior

Interorganizational l inkagesCoordination by networks

Virtual organiz ing

General workplace attitudes

Attitudes toward technologies

Behavior through contagion

Interorganizat ional contagion

Shared interpretations on key organizational concepts

Shared atrributions o f o ther ind iv idua ls

Shared perceptions of the social structure

Workplace attitudes such as satisfactionWorkplace behaviors such as turnover

6. Homophily theories

Social Comparison Theory

Social Identity Theory

7. Theories of physical and electronic

proximity

Physical Proximity

Electronic Proximity

8. Uncertainty reduction and contingency

theories

Uncertainty Reduction Theory

Contingency Theory

9. Social support theories

IO. Theories of network evolution

Structuration Theory

Computation and Mathematical

Organizational Theory

Organizational Life Cycle and

Developmental Theories

Choose similar others as basis of comparison

Choose categories to define one’s own group identity

Influence of distance

Influence of accessibility

Choose communrcation links to reduce uncertainty

Choose communication links to gain or mobilize

social resources

Selection and retention

Duality of structure

Nomothetic non-linear generative mechanisms

Evolution of structures as a function of

life-cycle stages

Demographic variables such as age, tenure, gender,

and race

Workplace attitudes

Communication about innovation

Organizational structural characteristics

Introduction of new technologies

Market exchanges

Interorganizational conflict

Buffer social and psychologtcat stress

Coping with stress

General workplace attitudes

Foundings and extinctions

Change in network configurations, role configurations,

appropriation of new structures and media

452 + Structure

vest in social opportunities from which theyexpect to profit. These investments are largelymotivated by self-interest, defined as the re-turn people expect to get on the social capitalthey invest. Network “holes” are those placesin a network where people are unconnected.Consequently, holes provide opportunitieswhere people can invest their social capital.To invest in, fill, or exploit these holes, peoplelink directly to two or more unconnected oth-ers, thus creating indirect ties between thepeople to whom they link. People who linkothers by filling structural holes also enhancetheir own structural autonomy because theycan control the information that flows be-tween others. Consequently, Burt (1992) ar-gues that the diversity of individuals’ net-works is a better predictor of their socialcapital than network size. Researchers haveexamined the relationships between socialcapital and organizational effectiveness, effi-ciency, and innovation. Each area is reviewedbelow.

Social capital and effectiveness. Researchers(Benassi & Gargiulo, 1993; Burt, 1992) haveargued that network linkages enable and con-strain the flexibility, autonomy, and there-fore, the effectiveness of organizationalmembers. Consistent with Burt’s (1992) ar-gument, Papa (1990) found that organizationmembers with diverse networks across de-partments and hierarchical levels were signif-icantly more likely to both increase produc-tivity and hasten the speed with which thischange occurred. Similarly, Burt (1992)found that the occurrence of structural holesin managers’ networks was positively corre-lated with managerial effectiveness. How.ever, he notes that this finding was not sup-ported among female managers and recentrecruits, where effectiveness was correlatedwith strong ties to others, Ibarra and An-drews’s (1993) research showed that individ-uals who were central in the advice andfriendship networks were more likely to per-ceive autonomy in their work. Benassi andGargiulo (1993) found that the flexibility ofmanagers in an Italian subsidiary of a multi-

national computer manufacturer Sign&an*;1affected their likelihood of success in coora-$

nating critical interdependencies. Manage.::+were rated as having high flexibility if titheir commumcation networks were con;strained by a low level of aggregate interdk.-,pendencies and consultations with others id’ptheir network, and (b) their communicatior$network had structural holes among the pet$ple imposing these constraints. More re?{cently, Burt (1997) reports that social capid’is especially valuable for managers with fe$$Jpeers because such managers do not have ~,+$$

-.s&$&guiding frame of reference provided by nu-‘;.;:s$3

L.;,:.?($zmerous competitors, or the legitimacy prG;gg;vided by numerous people doing the same”~~~+~kind of work (p. 356). In addition, Bu&;s(1991) has developed computational mea-,i’$$

-, ‘T.sures of “structural autonomy” to assess the&$level and distribution of constraints affecting.:<$$individuals in a network. .:a!. . .

Walker, Kogut, and Shan (1997) tested :i?$:Burt’s theory of structural holes at the interor- :-:+~ganizational level. Their research showed that

. : ~~;~.~‘~~~- .&,

developing and nurturing social capital in the: I ?$$biotechnology industry was a significant fat-.T .I.;:tor in “network formation and industrygrowth” (p. 109). In the development of en-during relationships, firms choose to increasesocial capital rather than exploit structuralholes. However, they argue that “structuralhole theory may apply more to networks ofmarket transactions than to netivorks ofcooperative relations” (p. 109). In the case of mar-ket transactions, firms are not bound by thestructural constraint to cooperate over timeand may therefore be more inclined to exploitstructural holes.

In related research, Baker (1987) foundthat organizations with low levels of debt im-proved their autonomy in managing transac-tions by establishing communication relation-ships with many, rather than one or a fewIinvestment banks. Kosnik (1987) found thatcompanies who had more outside directors,especially directors from firms that had trans-actions with the focal firm, had less autonomyin engaging in “greenmail,” the private rePur-chase of company stock. In contrast, the

GOs of firms that had more outside directors;ad greater autonomy in negotiating “golden&,&“te” policies for the firms’ top execu-‘ives (Cochran, Wood, & Jones, 1985; Singh

t,P,# Har-ianto, 1989; Wade, O’Reilly, & Chand-&+3t, 1990).gpAs 2,$@?Agbocial capital and efliciency. Granovetter’s$(Igg2) theory 0f the “strength of weak ties”*;;>ykwas also based on the premise that the people

Pk..“t-?,& whom a person has weak ties are less6.J .> :

i.w::l:;, :uely to be connected to one another; that is,h$t~ :;.

@&F&‘+. *;R~,+,,s: the person is embedded in a structural hole.

VP+: Consequently, the information obtained from

dI ;.$&g : : .,~~~Y~.~;;~~ these weak tres is less lrkely to be redundant‘&+$ ,:. and more hkely to be unique, thereby making;iggp&.*~~~~~~,,~~;-..weak ties “information rich.” Burt (1992) ar-&$$:~~~ L gued that being embedded in a structural hole$$gj’~ 11a 0ws actors to be more efficient in obtain-p,G$!,+.&;’ .r-!:--+;.:-~‘.;$p..; . , rng information. Using data from the 1985;&$~~~.~; and 1987 General Social Survey, Carroll and

&$$.$~$;.,-Te0 (1996) found that the members of man-$&$&&<f. g“‘4 a ers’ core discussion networks were less

IFL?x.l.*:j ‘ .v y,?~. ‘.“qJ’piy> : 1 likely to be connected to one another thant;$&& members of nonmanagers’ networks; conse-

@‘ ; quently, nonmanagers’ core discussion net-?;::‘l. works were less efficient in obtaining infor-

#+ ~~;.:;:.,+& $A?,.: ::’ mation. Contrary to conventional wisdom,7if& i .i”“-+*; j~,a,~~~~~;‘i:lt: . .-&+:;i$;:, j_ Granovetter (1982) found that individuals$&K+$$:+. were more likely to find jobs through theirI r,.&$‘$$? weak ties than through strong ties or formalfp&g.+AG$:f.l: listings. However, Lin, Ensel, and Vaughn’s

-%% (1981) research showed that weak ties were?.&~$~;~,p ‘-, , : Ii I,p>~;~‘+h..;’@;;;;$ T’

effective only if they connected individuals

fg+@z; t0 diverse others who could provide nonre-.$$p+j 1.q+ .‘G- dundant information.k’ ..s;,,:,,.:.@$g~:g$$, Social capital arm’ innovation. The diversity

pj&. of information obtained from ties has also

~~$$$~.~~ -,_. I~ .been used to explain the introduction of inno-,. ~~-~~~- 1,c\7,\cauons in organizations. Kogers (IY/I)

noted that innovations were more likely to beintroduced to an organization by cosmopo-lites, that is, people with diverse netvvorks,including several external to the organiza-tion. In a study of the inventory and controlsystems of manufacturing industries, Newelland Clark (1990) reported that British firmswere less innovative than their U.S. counter-


parts in part because they were less central intheir interorganizational communication net-works. More recently, Burns and Wholey(1993) found that hospitals that were cen-trally located in an interorganizational net-work were more likely to be early adopters ofan innovation (the matrix form of manage-ment) than other hospitals in their network.Brass (1995a) suggested that being embed-ded in networks with structural holes can alsoenhance employees’ ability to provide cre-ative solutions to organizational problems.

Extensions to social capital. Since the intro-duction of the “social capital” concept in1988 by Coleman, an impressive body of the-oretical and empirical evidence has demon-strated its relevance. It was developed as aconcept distinct from “human capital,” whichfocuses on the attributes of individuals, suchas seniority, intelligence, and education.Many of the informal means by which indi-viduals accrue social capital rely on theirknowledge of the existing communicationnetworks. However, as the workforce movesfrom being physically co-located to “virtualenvironments,” it is unclear whether elec-tronic forms of communication such asemail, which provide such things as distribu-tion lists and records of messages, make iteasier or more difficult for individuals to as-sess the existing social structure. Hence, asscholars examine the workforce of the 21stcentury, there is a pressing need for researchthat examines the distinctive strategies bywhich individuals can identify structuralholes and thereby accumulate social capitalin virtual organizations.

Trarzsactiorz Cost Economics Theory

From the viewpoint of tradittonal eco-nomic theory, the market was the classical or-ganizational form, where buyers and sellerscommunicated their intentions to each other,and where supply and demand were presumedto determine prices for goods. This is the pur-est form of self-interest theory. By contrast,

r.

j’*

-.

454 0 Structure

neoclassical economics examined the devel-opment of hierarchical and vertically inte-grated forms as a more efficient alternative tomarkets (Coase, 1937), though one that isequally self-interested. However, over the pastdecade important changes in theories andviews of organizational structuring have beenoccurring. A new organizational form, thenetwork organization, is emerging as an alter-native to both markets and vertically inte-grated organizations. This section examinesthese two traditional organizational forms, themarket and hierarchies; the following sectionexplores the development of the new alterna-tive, the network form.

Williamson (1975, 198.5) developed trans-action cost economics to explain the organiza-tion of economic activity. All organizationsrequire raw materials or components to manu-facture their own goods or services. Thus,Williamson argued, organizations face achoice between buying resources from otherfirms or acquiring other firms in order to makethe suppliers’ goods or services at lower coststhan what they could buy them, what is fre-quently called the buy-or-make decision. (It isalso possible to develop internal capabilities,but this is generally seen as a more expensiveoption.) Williamson viewed the first alterna-tive as governed by market mechanisms,where an organization hunts for the bestprices among the alternative supplier firms.“Transaction costs” are the expenses associ-ated with finding information about prices andquality from the available firms and negotiat-ing contracts. He saw the second alternative,vertical integration, as governed by hierarchi-cal forces, the administrative costs, includingcommunication, associated with managingthe internal production of acquired supplierfirms. Economic organizations, Williamsonargued, attempt to minimize transaction costsby making a choice between markets and hier-archies. Vertical integration, he said, is the ef-ficient alternative when the transaction costsfor markets are greater than the administrativecosts of production through hierarchical own-ership (Zajac & Olsen, 1993, p. 133). Clearly,the theoretical mechanism in Williamson’s

.-Interested chorces

the communication, inf0rrn~$~~~~~@$Id decision-making costs rrs - “.q$

,vrthSQQkfJ ~~,~~;,7fmdrng sellers in the market 0r acqu$<;;.~X$+

suppliers. , :.4f?.-?.2It should be clear that this mw:;;;$&nism is centered very much in the d ,I .‘I .-,* * :.;: ‘.rlYnreclsq .5: “+qframework of individual firms. The alterna~-:.~,:~~~~~~~~forms generated by this mechanism d&$~~:,;~+~~~~:::+q

considerably in the nature of their c0mm&&‘~~$$~

Gupta and Govindarajan (199 1) have s::.:,: $;<JJ;tended Williamson’s theory to the arena o;i!‘.‘.~~‘$~multinational corporations. They argued t&.~:.$$$governance in multinational corporations $‘,;,.,;$;‘;5be viewed as a network of transaction cosi&<‘ <$sg$changes. Home offices govern subsidiaries $j~,$$$regulating three critical transaction flows:‘, ~;-<~~~~;capital, product, and knowledge. The fact t&i -,. : ?$subsidiaries are located in different count&$ ‘$:$$creates different strategic contexts and corn:?. ~;.-~~-i>‘&:,, ---munication problems that determine the mag-.J. ” “ir.” “-, :

. , r ,..,_ ‘.,::‘.’ y::c>.

A number of criticisms have been leve~$:~;~:~~‘$$$against transaction cost economics. Gran-;;t’:;;;I$ovetter (1985) observes that analyses 0f h$!~:.i~~~~{!$man and organizational economic behavi&%~~$~$generally cluster at two ends of a continuti~;: ;:;$$.,-t-z.,, :.-.-;;yL~Traditional neoeconomics treats human be- + : ;.+>c-!:;: ;:~$Ihavior and institutional action independent of? --:;$!$.1:: ‘>-I’;..Zyjsocial relations and interpersonal communiti-.2: :..,.+;,:~~tion, a view that Granovetter calls an under-.--. ,?$~$$~,( : ; -I-. L . ,socialized viewpoint. More reformist econo- ::: ;t.?$%mists and sociologists (e.g., piore, 1975) tend,;!, :::;J;?i$. . . . . .j ..;$to see economic action as severely con- .: .; ,:-is?:.-..-:i , , ;’strained by social influences, a position he;; ~~;~;$$calls an oversocialized view. By conks6 ‘:’ ‘.i/.?i;Granovetter argues for a third alternative, that i; ,.. :i:$$economic behavior of both individuals and Or- -:.l. ;,;;$j

- . . . .ganizations occurs within existing cornmum- .:f

‘ . - ; ‘.L,??.-,::,‘p., -,1. ,P, . ‘

cation structures and ongoing social relations, :‘?I,’ ‘., :. :::;ja position he calls the embedded view. ‘“l-he :l-’ -;$‘zembeddedness argument,” he says, “stress@ ’ -‘..instead the role of concrete personand structures (or ‘networks’) oftions” (p. 490). This view was supUzzi’s (1996) study of New York

pare1 firms, which showed that

& is an exchange system with unique$nities relative to markets and that&anized in networks have higher sur-jhances than do firms which maintain

$Ieng~ market relationships” (p. 674).scourse, there are drawbacks to embed-&. Just as theory about the behavior of$.jdual people or organizations can beear undersocialized, so can organizations@erembedded or underembedded. Asit;& (1993) says, “Too little embed-%& may expose networks to an erosion ofi:suppo&ve tissue of social practices andir&ons. Too much embeddedness, how-*.f:may promote a petrifaction of this sup-&e, tissue and, hence, may pervert net-G’into cohesive coalitions against more>A] innovations” (pp. 25-26). Similarly,

I;“”a (1997), recognizing the paradox of~, tidedtress in the New York apparel econ-$5, identified three conditions that turn$&ddedness into a liability: “( 1) There is an&reseeable exit of a core network player,&institutional forces rationalize markets, or!) ‘overembeddedness characterizes the net-grk” (P. 57).@Another criticism developed by Gran-@ter (1985) and Powell (1990) is that theLfhotomy between markets and hierarchies$s not exhaust all of the important organiza-&al forms. Lazerson (1993) claims that “the$e promises of vertical integration haveimulated interest in alternative organiza-

@onal forms that are neither hierarchies nor%arkets” (p. 203). Williamson (19S5, 1991)pi.k$nowledged this possibility in his discus&n of alliances as hybrid forms. These, heg&1.*.Isad, exist between the other two and occur$,hen the transaction costs associated with$$rket exchange are too high but not highienough to justify vertical integration. How-%% a number of scholars, including Powell

@i~~i990), ha ve argued that at least one alterna-!@‘Gve, the network organization, is neither mar-,-$;‘..ket nor hierarchy in form. This issue is dis-PI’:-cussed in a later section of the chapter.I,‘ . ~i‘ Zajac and Olsen (1993) critiqued William-

: -. .,


pointed out that Williamson’s analysis fails toaccount for communication and other pro-cesses encountered in the transaction costsanalysis. Instead, they proposed an alternativethree-stage process that they argue enablesfirms to determine whether they should enterinto the relation. These three are the initial-izing stage, the processing stage, and thereconfiguring stage. During the first stageeach potential partner to the relation deter-mines its own objectives, reviews exchangealternatives, and begins exploratory contactsto examine the feasibility of the relationships.Here, Zajac and Olsen (1993) contend, thefirst rounds of exchange “often take the formof preliminary communication and negotia-tion concerning mutual and individual firm in-terests, and/or feasibility studies and generalinformation exchange” (p. 139). During thesecond stage firms engage in both serial andparallel information processing, “interfirmcommunications . . . occurring between indi-viduals at multiple organizational levels andmultiple functional areas” (p. 140). The thirdstage, reconfiguration, consists of evaluationof the relationship followed by a return to ei-ther of the previous two stages to (a) seek rela-tional changes or (b) reaffnm the status quo.In essence, this stage affirms the informationand communication network linkages onwhich the organizational relations can be es-tablished.

The second problem they identified is thatWilliamson’s view of transaction cost min-imization takes the perspective of only one or-ganization. This is an error, they claimed, be-cause a relationship has two sides, both ofwhich should be included in any comprehen-sive account. Thus, they argued that transac-tion cost minimization from the perspective ofone firm be replace by a “joint value maximi-zation principle” that focuses on the benefitsto both (or multiple) firms. More specifically,they propose that “value estimations ofinterorganizational strategies require that a fo-cal firm consider the value sought by thatfirm’s exchange partner. By taking the part-ner’s perspective, the foca1 firm can better es-

456 + Structure

timate the value and duration of the interor-ganizational strategy, given that value and du-ration are determined interdependently byother firms” (p. 137).

It is worth noting that Zajac and Olsen’scritique transforms the self-interest theoreticalmechanism for creating organizational com-munication networks into one that is jointlyrather than individually self-interested. Fur-ther, it attempts to maximize collective valuerather than minimize individual costs. Thistheoretical mechanism to account for theemergence of communication networks, mu-tual self-interest, is reviewed more fully in thefollowing section.

Theories of Mutual Self-Interestand Collective Action

Collective action is a term that has beenbroadly applied to a wide range of phenomenain the social sciences, including organiza-tional communication (Coleman, 1973). Itsmain focus is on “mutual interests and thepossibility of benefits from coordinated ac-tion” (Marwell & Oliver, 1993, p. 2) ratherthan on individual self-interests. Samuelson(1954) first articulated public goods theory toexplain how people could be induced to con-tribute to collective goods in the public do-main such as bridges, parks, and libraries. Ap-plications of this perspective to the interactivecommunication public goods of connectivityand communality have been made recently byFulk, Flanagin, Kalman, Monge, and Ryan(1996).

The logic of collective action is based onthe assumption that individuals motivated byself-interest will avoid investing resources in ajoint endeavor whenever possible, leavingothers to contribute their share even though allwill benefit (Olson, 1965). This phenomenonis known as “free riding.” Peer pressure is of-ten applied to overcome this tendency to freeride and serves to make individuals complywith the need to contribute their fair share,thus facilitating collective action. Originalformulations treated individuals as if theywere isolated and independent of others mak-

ing similar decisions. Oliver (lgg3), M~~:.:$$(1990), and Marwell and Oliver (1993) h&“‘:r$$criticized this view and emphasized the irn-:,~.:,~~~‘~~portance of the network of relations in which’., ‘;;:if$;people are embedded. Computer simulation ;:’ .:$Jexperiments by Marwell and Oliver (1993)‘: 1:. t:i>showed that the extent to which people arein-.:i ,:::&F7terconnected in communication network in;:i:::,:>:!$<,.?icreases their willingness to support the collec- ::-.:$$tive good. Using a similar research strategy, ;,.:r-~q:: :::.$j

Marwell, Oliver, and Prahl (1988) showed ‘-:..-<s.:Bthat centralization and resource heterogeneity ,:i : $31in the network influenced aggregate contribu-tions to a collective good.

Empirical studies using collective action &an explanatory mechanism fall into two cate-gories: the group’s mobilization as indexed byits level of involvement, and the adoption ofinnovations. Research using a collective ac-tion mechanism has focused on the effect ofthe network on mobilization, as well as morespecifically the adoption of innovations. Eachof these two areas is discussed below.

Collective Actionand Mobilization

In a retrospective study of the insurgencyin the Paris Commune of 1871, Gould (1991)underscored the importance of examiningmultiple, partially overlapping networks inexplaining the insurgents’ solidarity and Corn-mitment. He found that the

importance of neighborhood identity and thepatterns of arrests showed that preexisting so-

cial ties among neighbors and organizationalties formed by the National Guard worked to-

gether to maintain solidarity in the insurgent

ranks.. . , Cross-neighborhood solidarity could

not have emerged in the absence of enlistmentoverlaps that linked each residential area with

Guard units in other areas. (p. 727)

Applied to organizatlonal contexts, Gould’sfindings suggest that collective action is lesslikely to succeed if the informal networks arestructured so as to be either isomorphic with


ac-t ofloreach

?CY91)ing

inm-

:heso-ml:o-:nt:ldTll.th

L’SjS

re-h

iw;ctino formal ties, or if they “completely$ across preexisting networks” (p. 728).$boke (1990, p. 5) examined the determi-Ls 0f member participation and commit-lent among 8,746 respondents from 3.5 “CC&&tive action organizations,” professional&ociations, recreational clubs, and women’s

~+ociations. He discovered that “members’&volvements in their collective action organi-

,$&~ons are enhanced by extensive communi-$&&ion networks that plug them into the thick

,p@,“$~~$.~*~t~~fpolicy discussions, apart from whatever de-ai :;‘g~*$<:;.

$&@$p y9

icZ:;.;gee of interest they may have in particularlit issues” (p. 185). At the interorganiza-

Lt$C~;+Lf~onal level,f$+f;.Laumann, Knoke, and Kim

$$;;(1985) found that health organizations central;I;+:,$ their industry’s communication networks~$‘#vere more involved in mobilizing efforts on

.national policy issues affecting their domain.tionship did not hold up

organizations in the energy industry.aumann et al. (1985) concluded that central-

communication network was more im-ng collective action in in-

dustries that were less institutionalized.:Collective Action and the

Adoption of Imovntions

Theories of collective action have alsobeen used to examine the adoption of new in-teractive communication technologies (Markus,1990; Rafaeli & LaRose, 1993). Valente(1995, 1996) has examined the effect of“threshold” (Granovetter, 1978) on adoptionbehavior. The threshold is defined as the num-ber of other adopters that must be present in aperson’s network before the person decides toadopt. The threshold levels of individuals de-termine whether the group as a whole canachieve the critical mass necessary for rapidand widespread collective action. Rice, Grant,Schmitz, and Torobin (1990) examined therole of critical mass in predicting the adoptionof an electronic mail system at a decentralizedfederal agency. They found that individuals’decisions to adopt the system were contingenton the decisions of others with whom they re-Ported high levels of task interdependence.

Further, individuals’ adoption decisions wereinfluenced by the extent to which they valuedthe potential communication with others whowere likely to be accessible via the new sys-tem. Gurbaxani (1990) used an adoptionmodel based on critical mass theory to predictwith considerable accuracy university adop-tion of the Bitnet computer network. At theinterorganizational level, studies on govern-mental and nonprofit organizations have ex-amined the role of network ties in overcomingobstacles to collective action (Mizruchi &Galaskiewicz, 1993; Rogers & Whetten,1982; Turk, 1977).

Extensions lo CollectiveAction Theory

The interest in examining the emergence ofnetworks from a collective action perspectiveis relatively recent. It has been used persua-sively to address issues of mobilization andthe adoption of innovation. However, unlikesome other mechanisms discussed in thischapter, the theoretical developments in thisarea have not been well complemented by em-pirical evidence. Scholars have proposedmathematical models, and some have carriedout simulations. However, few of these effortshave been empirically validated.

In addition to the need for more empiricalresearch, there are also some conceptual is-sues that continue to be advanced. First, theconceptualization of information technolo-gies, such as discretionary databases, as “pub-lic goods” (Fulk et al., 1996), suggests thatcollective action theories can offer a more so-phisticated explanation of the emergence oforganizational networks, extending their pres-ent use to study the adoption of technologiesin organizations. Discretionary databases arethe message repositories that link knowledgesuppliers and consumers, thereby creatingconnective and communal networks of indi-

. .i’:!:

viduals who share knowledge domains.Second, there is potential for the applica-

tion of network approaches to the conceptual-ization of free riding and its role in collectiveaction. Collective action by groups is based on

458 + Structure

an underlying premise of social control.Homans’s (1974) cohesion-compliance hy-pothesis predicts that group members are ableto enforce social control on one another by ex-changing peer approval for compliance withgroup obligations. Flache and Macy (1996)argue that under some circumstances mem-bers may choose to offer peer approval in ex-change for peer approval rather than compli-ance from others. Using computer simulationsof groups’ networks, they observed that inthese situations groups may reach a high levelof cohesion that is not accompanied by ahigher level of compliance or better groupperformance. Contrary to Homans’s cohe-sion-compliance hypothesis, Flache andMacy (1996) concluded that “peer pressurecan be an effective instrument for blockingcompliance, especially in groups in which thecost of compliance is high relative to the valueof approval” (p. 29). Oliver (1980) describesthis phenomenon, where social control is di-rected toward the maintenance of interper-sonal relationships at the expense of compli-ance with group obligations, as the “second-order free-rider problem.”

Exchange andDependency Theories

Extensive research has been conducted thatseeks to explain the emergence of net\vorksbased on exchange and dependency mecha-nisms. Social exchange theory, originally de-veloped by Homans (1950, 1974) and Blau(1964), seeks to explain human action by acalculus of exchange of material or informa-tion resources. In its original formulation, so-cial exchange theory attempted to explain thelikelihood of a dyadic relationship based onthe supply and demand of resources that eachmember of the dyad had to offer. Emerson(1962, 1972a, 1972b) extended this originalformulation beyond the dyad, arguing that toexamine the potential of exchange andpower-dependence relationships, it was criti-cal to examine the larger network w+thin

which the dyad was embedded. Since then,several scholars have developed this perspec-tive into what is now commonly referred to asnetwork exchange theory (Bienenstock &Bonacich, 1992, 1997; Cook, 1977, 1982;Cook & Whitmeyer, 1992; Cook & Yama-gishi, 1992; Markovsky, Willer, & Patton,1988; Skvoretz & Willer, 1993; Willer &Skvoretz, 1997; Yamagishi, Gillmore, &Cook, 1988).

Network exchange theory posits that indi-viduals’ power to bargain is a function of theextent to which they are vulnerable to exclu-sion from communication and other ex-changes within the network. The argument isthat individuals forge network links on the ba-sis of their analysis of the relative costs andreturns on investments. Likewise, individualsmaintain links based on the frequency, the un-certainty, and the continuing investments tosustain the interaction. Location in the net-work may confer on some people an advan-tage over others in engaging in exchange rela-tionships. Aldrich (1982) notes that thisargument is at the core of several theoriesdealing with social exchange as well as re-source dependency theories. Within organiza-tions, network researchers have proposed asocial exchange mechanism for the study of(a) power, (b) leadership, and (c) trust and eth-ical behavior. At the interorganizational level,researchers have (a) tested resource depend-ency theory, (b) examined the composition ofcorporate elites and interlocking board of di-rectorates, and (c) sought to explain the cre-ation, maintenance, and dissolution of inter-organizational links. Each area is examined ingreater detail below. The section concludeswith proposed extensions to the study of orga-nizational networks from a social exchangeperspective.

P o w e r

Social exchange theory has been used toexamine the power that ensues from a struc-tural position. In terms of exchange theory,power is defined as a function of dependence

Esin the network. Location in the com-go,, network is associated with greater:io be extent it offers greater access to{,mateial and informational resources.icdly, people, groups, and organiza-

+ave power to the extent that they have& to alternate sources of a valued re-&, and the extent to which they control&es valued by others in the network&-son, 1962). In a series of experimentalTsimulation studies, Cook and her col-$s (Cook & Emerson, 1978; Cook, Em-

,Zjn; Gillmore, & Yamagishi, 1983) found$aence to support a power-dependence rela-@ship. Carroll and Teo (1996) found that to&ease their resources, organizational man-$s were more motivated than nonmanagers

j’have larger core discussion networks and toEs.: i$reate more communication links outside the@rganization by memberships in clubs and so-pties. In her study of interorganizational so-@al services, AIter (1990) found that the exis-%znce of a centralized, dominant core agency&&

bb,v.reduced the level of conflict and competition‘between service organizations and improved

’ .pthelr level of cooperation. However, Hoffman,%-Stearns, and Shrader (1990) found that orga-

g..nizational centrality;$; in four multiplex&:. interorganizational networks depended on the

trality with different sources of power. Brass(1984) suggested two measures of centralitythat reflect different dimensions of power.Closeness, the extent to which people, groups,and organizations can reach all others in a net-work through a minimum of intermediaries,corresponds to the “access of resources” di-mension of power (Sabidussi, 1966). Be-tweenness, the extent to which a networkmember lies between others not directly con-nected, corresponds to the “control of re-sources” dimension of power (Freeman, 1977,1979). Brass (1954, 1985b) showed that bothmeasures of centrality correlated with repu-tational measures of power. Further, Brass(1983, 1985b) found that employees with highscores on network indicators of power were

Emergence 0fCommunicotion Networks + 459

more likely to be promoted to supervisory po-sitions, and Burkhardt and Brass (1990)discovered that early adopters of a new tech-nology increased their power. Ibarra (1993a)found that centrality in the informal networkwas at least as important as the formal hierar-chical network in predicting power; Krack-hardt (1990) reported similar results for ad-vice and friendship networks. Interestingly,Brass and Burkhardt’s (1992) research re-vealed that measures of centrality at the de-partmental level were more strongly related toseveral indexes of power than measures at thesubunit or the organizational levels.

Leadership

The success of network formulations topredict power has prompted some scholars tosuggest its use in extending theories of lead-ership such as Graen’s (1976) lesder-mem-ber exchange theory (Krackhardt Sr Brass,1994) and attribution theories of leadership(McElroy & Shrader, 1986). Fernandez(1991) found that the effects of informal com-munication netivorks on perceptions of lead-ership were different in three types of organi-zations. Specifically, he found that informalcommunication predicted perceptions of lead-ership most strongly in the participatory orga-nization, a telephone-counseling center; onlyweakly in the professional organization, apublic finance department of a large invest-ment bank; and not at all in the hierarchicalorganization, a metallurgical firm.

Trust ad Ethical Behavior

Researchers have also used socialchange theory to study the developmentutility of trust in organizationalinterorganizational networks. As Burt

ex-andandand

Knez (1996) note, “Trust is committing to anexchange before you know how the other per-son will reciprocate” (p. 69). In a study ofmanagers in a large high-technology firm,they found that the communication networksin which two individuals were embedded pre-

460 4 Structure

dieted the probability of a trust relationshipbetween them. In particular, the trust betweentwo individuals in close contact was high ifother members in the organizations indirectlyconnected the two members to one another.Further, the distrust between two individualswho were not in close contact was further at-tenuated if other members in the organizationindirectly connected them to one another. Thisresearch indicates that indirect communica-tion linkages reinforce trust and distrust rela-tions between people. Labianca, Brass, andGray (1998) also reported a similar amplifica-tion effect. They suggest that the ampliflca-tion effect occurs because the secondhand in-formation transmitted by indirect communica-tion linkages “may be more polarized or exag-gerated (either positively or negatively) thanfirsthand information” (p. 64), as grapevine(rumor) studies have found (e.g., DeFleur BrCronin, 1991; Schachter & Burdick, 19.55).

In a study involving trust as measured viafriendship networks, Krackhardt and Stern(1988) found that a relatively higher propor-tion of interunit (as compared to intraunit)friendship ties was particularly helpful to or-ganizations coping with crisis conditions. Inthis case, the high level of trust was seen as aprerequisite for the increased interunit coordi-nation required during a period of high uncer-tainty and the ensuing potential conflict.Larson’s (1992) study of entrepreneurial firmsindicated that trust as well as shared reciproc-ity norms, close personal relations, and repu-tation determined with whom and how ex-changes occurred.

Researchers examining ethical behavior inorganizations also deploy the exchange mech-anism. Brass, Butterfield, and Skaggs (1995)suggest that networks could also offer an ex-planation for the likelihood of unethical be-havior in a dyad since the connectedness ofpeople is highly related to their observability.Brass et al. (1995) propose that “the strengthof the relationship between two actors will bepositively related to the opportunity to act inan unethical manner, but negatively related tothe motivation to act unethically. Frequencyand trust provide increased opportunity, but

----------1. . ..-

tion” (p. 6).

Resource Dependency Theory andPower in InterorganizationalNetworks --.-;.

I’:<:yIn his now classic article, Benson (1975).

defined interorganizational networks as a p&?Iitical economy. By this he meant that?

change networks were the mechanisms bywhich organizations acquired and dispensedscarce resources, thus creating and perpetuat.ing a system of power relations. Organizationswere viewed as dependent on their positionsin the network, which subsequently influ-enced their ability to control the flow of scarceresources.

Pfeffer and Salancik (1978) drew onBenson’s work on political economy and so-cial exchange mechanisms (Emerson, 1962,1972a, 1972b) to formulate resource depend-ency theory. This theory argues that organiza-tions structure their resource linkages tobuffer themselves from the organization’s en-vironment (Pfeffer & Salancik, 1978). In par-ticular, they identify two mechanisms that or-ganizations can use toward this end. First, bynetwork extension, organizations can seek toincrease the number of exchange alternativesby creating new network links. Second, bynetwork consolidation, they can decrease thenumber of exchange alternatives for others byforming a coalition with other resource pro-viders. These counterbalancing mechanismsprovide an explanation for the stability of ex-change relationships and potential redistribu-tion of power among the individuals. Burt(199 1) developed a measure of equilibrium toassess the likelihood that network membershave the resources to reconfigure their ex-change networks and therebv the distributionof power.

A major tenet of resource dependency the-ory is that organizations tend to avoidinterorganizational linkages that limit theirdecision making and other forms of auton-

@~~Oliver (1991; see also Oliver, 1990)I;i *is assumption across five relational

tpj(Jthat ranged from highest to lowest levels;4dtonomy: personal meetings, resource@&s, board interlocks, joint programs,

Gtten contracts. Surprisingly, she foundYu,.;-,;%&,,dence that linkages that imphed greater&fautonomy led to lower likelihood of es-b’iscng the relationship.

,:substantial body of empirical research__ ;i on a resource dependency framework toidj, the pattern of interorganizational net-

,,,irks These studies examine a wide varietyi$esource relationships, including money,,&terial, information, and messages. How-;.:+.ever, the focus of these relationships is moreig ?: :,epncerned with the pattern of relationshipsbhai; their content; thus, the majority of re-$+e dependency research is conducted,hm a positional perspective. In some of the

gq’&lier studies in this area, Laumann andg;-.:&pappi (1976) and Galaskiewicz (1979) re-@t .’kripotted that organizations that were more cen-%?a1 in their networks had greater reputational;2,y*Wnfluence. In a broad-based study assessing!&he power of the U.S. labor force, Wallace,$$,Griffin, and Rubin (1989) discovered that the2;:. labor force in industries that were more cen-!$btral in the network of interindustry transac->:%ions were more likely to receive higher wages

&?‘:than the labor force in peripheral industries.- ‘~.~~‘.Gerlach’s (1992) study of the Japanese corpo-j!Jfc‘:.:$ate-g; network, including intercorporatep.-.: .-keiretsu groupings, found strong evidence of$$ ‘the centrality of financial institutions in these“ “ ‘ . networks and their resultant ability to control

the capital allocation process (see also Lin-coln, Gerlach, 8;. Takahashi, 1992). However,in a study of health systems, Oliver and Mont-gomery (1996) observed that “the organiza-tion with greatest influence within the system(because of its ability to allocate funds) maynot be the organization that takes the largestrole in terms of coordinating routine contacts”(P. 771), such as client referrals.

Two studies show the impact of resourceexchange on effectiveness. Miner, Amburgey,and Stearns’s (1990) research on 1,011 news-Paper publishers in Finland from 1771 to 1963

Emergence of Communication Networks + 4 6 I

found that publishers with a greater number ofinterorganizational resource linkages, typi-cally to political parties, had a higher overallsuccess rate. Goes and Park (1997) found that“a greater volume of [resource] exchanges be-tween hospitals increases the likelihood thatinnovation will spread between them” (p.771).

Provan and Milward (1995) reported re-search designed to extend resource depend-ency theory by focusing on the effectivenessof the entire interorganizational network (seealso Provan, 1983) rather than the antecedentsand outcomes of individual organizations.Further, they pointed out that how well indi-vidual organizations perform is less importantthan how the interorganizational network as awhole performs. Studying the mental healthcare delivery system in four cities, they foundthat networks with a centralized deci-sion-making agency were more effective thannetworks in which decision making waswidely dispersed across agencies. Their dataalso suggested that the relationship betweennetwork structure and network effectiveness isinfluenced by the existence of a relatively mu-nificent environment and the degree to whichthe overall network is stable.

Corporate Elites and InterlockingBoards of Directors

Corporate elites and networks created bylinkages among people who serve on multiplecorporate boards are areas that have receivedconsiderable research attention in interorga-nizational relations. As Knoke (1993) indi-cated, “‘A power elite is established at the in-tersection of three social formations: a class-conscious upper social class of wealth-hold-ers, interlocked directors of major corpora-tions, and a policy-planning network of foun-dations, research institutes, and nonpartisanorganizations” (p. 26). Useem’s (1984) classicstudy argued that these overlapping networksof friendship, ownership, membership, and di-rectorship produced a core set of individuals,o r “inner circle,” which wields enormouspower. Knoke (1993) explained that “because

462 + Structure

its members simultaneously hold multiple di-rectorships, the core can act politically in theinterests of the class, which transcend theparochial concerns of its individual firms”(p. 26). Consistent with this view, Romo andAnheier (1996) found evidence that a coregroup of elites explained the emergence andinstitutionalization of consortia for private de-velopment organizations in Nigeria and Sene-gal. Studies have also shown that individualswho were more centrally located in the inter-locking board of directors were also morelikely to play a leadership role in cultural,philanthropic, and policy-making organiza-tions (Domhoff, 1983; Mizruchi & Galas-kiewicz, 1993; Ogliastri & Davila, 1987;Ratcliff, Gallagher, &r Ratcliff, 1979; Useem,1980).

Historically, the focus of interlocking di-rectorate research has been on corporate con-trol. However, Minz and Schwartz (1985) ar-gued that “the most compelling interpretationof the overall network created by the collec-tion of individual reasons for and response todirector recruitment is a general communica-tion system” (p. 141). In fact, as Mizruchi(1996) contends, “the emphasis on interlockshas moved increasingly toward their value asa communication mechanism rather than as amechanism of control” (p. 284).

Creation, Maintenance,Dissolution, and Reconstitutionof Inte@irm Links

Studies have also deployed a resource de-pendency framework to explain the creationof links in interorganizational networks.Mizruchi and Stearns (1988) found two gen-eral factors that explained the addition of newfinancial members to an organization’s boardof directors. Under favorable economic condi-tions, when capital demand and supply are in-creasing, organizations initiate links with fi-nancial institutions through their board ofdirectors to co-opt these institutions’ financialand informational resources. However, duringunfavorable economic conditions, including

contractions in the business cycle, lower soI-vency, and lower profitability, it is thefinancial institutions that infiltrate companies’boards of directors to protect their invest-ments. This finding is qualified by Boyd’s(1990) research that showed high-performingfirms responded to resource scarcity and com-petitive uncertainty by decreasing the numberof their directors but increasing the density oftheir linkages with other firms. Mizmchi(1996) argued that a number of other factorsalso affect the creation of interlocking direc-torates. These include creating legitimacy forthe firm, advancing the careers of those whoserve as directors, and fostering the social co-hesion of the corporate upper class.

Palmer et al. (1986) used resource depend-ency theory to hypothesize the conditions un-der which a broken interlock tie between twoorganizations (due to death, retirement, etc.)would be reconstituted. They found that inter-lock ties were likely to be reconstituted if thedeparting member represented an organiza-tion with which the focal organization had (a)formal coordination, such as long-term con-tracts or joint ventures; (b) direct businessties; or (c) headquarters that were physicallyproximate.

Larson (1992) demonstrated that firmstend to enter repeated alliances with eachother; thus, dependencies tend to generate fur-ther dependencies. Gulati’s (1995) researchshowed that the information provided by bothdirect and indirect ties of prior alliances estab-lished the basis for the formation of additionalalliances. However, his research also showedthat as the benefits of linking with specificothers declined over time organizationslooked for new alliances. Of course, as Baumand Oliver (1992) noted, there is a carryingcapacity to alliances in that most organiza-tions can successfully support only a limitednumber of connections, and many firms fearthe overdependence that too many ties mightbring.

Seabright, Levinthal, and Fichman (1992)theorized that reductions in the resource fitbetween organizations would lead to pres-sures to dissolve interorganizational relations

while increases in perSOna and structural at-B&mentS would counter those pressures andlead to continued relations. Their results sup-ported the hypotheses but also showed thatpersonal and structural attachments attenuatedthe firms’ likelihood of dissolving ties underconditions of reduced fit. This finding under-scores the importance of established commu-nication and social attachments in main-taining interorganizational relations beyondthe point where a strict exchange or resourcedependency perspective would predict thatthey would dissolve, even at times when itmight be disadvantageous to maintain them.Overall, however, Mizruchi’s (1996) reviewof the research literature on corporate inter-locks led him to conclude that “although thefindings have been mixed, on balance theysupport the view that interlocks are associatedwith interfirm resource dependence” (p. 274).

The research on interlocking directoratesassumes that each organization is a separateentity tied together at the top by corporateelites. While interest continues in interlockingdirectorates, a new field of research has devel-oped over the past decade that focuses on anemergent organizational form, network orga-nizations. This perspective relaxes these twoassumptions of separate entities and executiveties only. We explore this new area in the nextsection.

Network Organizations

Network organizations are composed of acollection of organizations along with thelinkages that tie them to each other, often or-ganized around a focal organization. Thereare numerous variations on the network orga-nizational form including joint partnerships,strategic alliances, cartels, R&D consortia,and a host of others.

The theoretical mechanisms that generatemost network organizations are exchange anddependency relations. Rather than being orga-nized around market or hierarchical princi-ples, network organizations are created out ofcomplex webs of exchange and dependencyrelations among multiple organizations. In a


sense, the network organization becomes asupraorganization whose primary function islinking many organizations together and coor-dinating their activities. Unlike interlockingdirectorates, the network ties usually occurthroughout the entire organization rather thanonly at the top, and the separate organizationsoften give up some or all of their individualautonomy to become a part of the new net-work organization.

Miles and Snow (1992) observe that net-work organizations differ from their predeces-sors (functional, multidivisional, and matrixforms) in four important ways. First, ratherthan subsume all aspects of production withina single hierarchical organization they attemptto create a set of relations and communicationnetworks among several firms, each of whichcontributes to the value of the product or ser-vice. Second, networks are based on a combi-nation of market mechanisms and informalcommunication relations. As they say, “Thevarious components of the network recognizetheir interdependence and are willing to shareinformation, cooperate with each other, andcustomize their product or service-all tomaintain their position within the net\vork”(p. 55). Third, members of networks are oftenassumed to take a proactive role in improvingthe final product or service, rather than merelyfulfilling contractual obligations. Finally, anumber of industries are beginning to formnetwork organizations along the lines of theJapanese keiretsu, which links together pro-ducers, suppliers, and financial institutionsinto fairly stable patterns of relations

Poole (in press) argues that new organiza-tional forms, including network organiza-tions, are constituted out of six essential quali-ties:

1 .

7A.

3.

The use of information technology to intc-grate across organizational functionsFlexible, modular organizational structuresthat can be readily reconfigured as newprojects, demands, or problems ariseUse of information technology to coordi-nate geographically dispersed units andmembers

464

4 .

5 .

6 .

I n

+ Structure

Team-based work organization, which em-phasizes autonomy and self-managementRelatively flat hierarchies and reliance onhorizontal coordination among units a n dpersonnelUse of intra- and interorganizational m a r -kets to mediate transactions such as the as-signment and hiring of personnel for proj-ects and the formation of interorganiza-tional networks.

today’s world, nearly all organizationsare embedded to some extent in an emergentinterorganizational communication network.For example, most economic institutions arelinked together in “value chains” (Porter,1980) or “value constellations” (Norman &Ramirez, 1993) where each receives a par-tially finished product from an “upstream or-ganization,” adds its contribution, and thendelivers it to the next “downstream organiza-tion” for its contribution. Similarly, educa-tional institutions typically relate to other ed-ucational institutions in a chain frompreschool to postgraduate education. And re-ligious organizations are frequently affiliatedwith coalitions of other like-minded religiousgroups. Of course, all must deal with the tax-ation authorities of federal, state, and localgovernments.

In one sense, network organizations createwhat have come to be called “boundarylessorganizations” (Nohria & Berkley, 1991).Where one organization begins and the otherends is no longer clear. Organizations come toshare knowledge, goals, resources, personnel,and finances, usually with highly sophisti-cated communication technology (Monge 8:Fulk, 1999). To accomplish this they must es-tablish collaborative work arrangements,since that is the only way to transfer embed-ded knowledge.

Ghoshal and Bartlett (1990) argued thatmultinational corporations (MNCs) have tra-ditionally been viewed as an intraorga-nizational network, in many ways not differ-ent from traditional national companies. Eachsatellite, subsidiary, or foreign partner has

been seen as directly connected to the homecorporate oflice, thus tying the MNC into anintegrated hub-and-spoke structural whole.However, they point out that this view of theMNC fails to take into account the extendednetworks in which each of the subsidiaries isembedded. These national, regional, and corn-peting global networks require a reconcep-tualization of MNCs as network organiza-tions.

Limitations of NetworkOrganizations

Several authors have pointed out that net-work organizations have a number of limita-tions. Miles and Snow (1992) observe thatnetwork organizations contain the vestigialweaknesses of their predecessors, the func-tional, multidivisional, and matrix forms. Tothe extent that parts of these prior forms re-main in the network organization, the newform retains their prior limitations. Krack-hardt (1994) identifies four potential con-straints on communication and other net-works. The first he calls the “law ofN-squared,” which simply notes that the num-ber of potential links in a network organiza-tion increases geometrically with the numberof people. In fact, it grows so quickly that thenumber of people to which each person couldbe linked quickly exceeds everyone’s commu-nication capacity. The second constraint is the“law of propinquity.” a rather consistent em-pirical finding that “the probability of twopeople communicating is inversely propor-tional to the distance between them” (p. 213).Though numerous communication technolo-gies have been designed to overcome this phe-nomenon, Krackhardt argues that the ten-dency remains and is difficult for people toovercome. The third constraint he identifies isthe “iron law of oligarchy,” which is the ten-dency for groups and social systems, even fer-vently democratic ones, to end up under thecontrol of a few people. Finally, Krackhardt(1994) notes the potential problem of over-

. ; awdedness. He observes that “people as a--,tier’of habit and preference are likely to,k out their old standbys, the people they

!&gr own to trust, the people they always gog”&d depend on, to deal with new problems,

$&though they may not be the ones best&]e to address these problems” (p. 220)..@$oole (in press) alSO points to several hu-g&, problems that stem from the tightly cou-$d technology but fluid management philos-

jphies on which most network organizationsgn,. .$qe Wt. Foremost among these are maintain-&g a sense of mission, commitment, loyalty,

,&$d trust, and dealing with increased levels of

iir&$rk stress and burnout.

f$@;: ;

@$z.~ Exrensions to Exchangef$.:: and Dependency Theories

22 ated and maintained on the basis of exchange?$! mechanisms. Further, as people and organiza-2:: tions find their exchanges no longer rewarding

or competitive others offer betterbargains in the exchange, linkages begin to

Despite its intellectual roots in the study ofinterpersonal relationships, exchange and de-pendency theories have been more extensivelydeployed in the study of interorganizationalnetworks, often within the context of resourcedependency theory, rather than intraorgan-izational networks. Much of the intraorgani-zational research reviewed above, while pre-mised in a social exchange perspective, doesnot invoke the theory explicitly. Further, in ar-eas such as leadership, trust, and ethical be-havior, the studies so far are more illustrativethen programmatic attempts at applying socialexchange theory. X-Net, a computer simula-tion tool developed by Markovsky (1995)should help researchers explore the emer-gence of networks in terms of different rulesof exchange and varied resources. Re-searchers have also proposed integrating net-

hwgence ofcommunication Networks + 4 6 5

work exchange theory with rational choicetheory (Markovshy, 1997) and identity theory(Burke, 1997), and a general theoreticalmethod called E-state structuralism (SkvoretzBr Fararo, 1996; Skvoretz & Faust, 1996),which integrates research on expectationstates theory (Berger, Cohen, & Zelditch,1966) with network exchange theory. Expec-tation states theory argues that a person’s “be-havior towards social objects depends on pos-tuIated and unobservable states of relationalorientations to objects, E-states for short”(Skvoretz & Fararo, 1996, p. 1370). The so-cial objects toward which individuals orientare the networks of ties among the individu-als. E-state models specify “how the state ofthis network, i.e., the number and nature ofthe ties linking actors, changes over time asindividuals interact” (Skvoretz & Fararo,1996, p. 1370).

Contagion Theories

Contagion theories are based on the as-sumption that communication networks in or-ganizations serve as a mechanism that ex-poses people, groups, and organizations toinformation, attitudinal messages, and the be-havior of others (Burt, 19S0, 19S7; Contractor&r Eisenberg, 1990). This exposure increasesthe likelihood that network members will de-velop beliefs, assumptions, and attitudes thatare similar to those of others in their network(Carley, 1991; Carley &r Kaufer, 1993). Thecontagion approach seeks to explain organiza-tional members’ knowledge, attitudes, and be-havior on the basis of information, attitudes,and behavior of others in the network towhom they are linked. Rogers and Kincaid(198 1) refers to this as the convergence modelof communication.

Theories that are premised on a contagionmodel, at least in part, include social informa-tion processing theory (Fulk, Steinfield,Schmitz, Br Power, 19S7; Salancik & Pfeffer,197S), social influence theory (Fulk, Schmitz,

&i Steinfield, 1990; see also Marsden &r.

4 6 6 + Structure

Friedkin, 1994), structural theory of action(Burt, 1982), symbolic interactionist perspec-tives (Trevino, Lengel, & Daft, 1987), mi-metic processes exemplified by institutionaltheories (DiMaggio & Powell, 1983; Meyer &Rowan, 1977), and social cognitive theory(Bandura, 1986). Fulk (1993) notes that theseconstructivist perspectives “share the coreproposition that social and symbolic pro-cesses produce patterns of shared cognitionsand behaviors that arise from forces well be-yond the demands of the straightforward taskof information processing in organizations”(p. 924). She also points out that the mecha-nisms offered by these theories differ not so

much because of conflicting premises as be-cause the theories focus on different aspectsof the social construction process.

The contagion mechanism has been used toexplain network members’ attitudes as well asbehavior. Erickson (1988) offers a compre-hensive overview of the various theories thataddress the “relational basis of attitudes” (p.99). She describes how various network dy-adic measures such as frequency, multiplexity,strength, and asymmetry can shape the extentto which others influence individuals in theirnetworks. Moving beyond the dyadic level ofnetwork contagion, she also describes cohe-sion and structural equivalence models thatoffer alternative, and in some cases comple-mentary, explanations of the contagion pro-cess. Contagion by cohesion implies that theattitudes and behaviors of the others withwhom they are directly connected influencenetwork members. Contagion by structuralequivalence implies that others who have sim-ilar structural patterns of relationships withinthe network influence people.

An impressive body of empirical researchat both the intraorganizational and interorga-nizational levels is based on the contagionmechanism. At the intraorganizational level,studies have proposed a contagion mechanismto explain (a) general workplace attitudes, (b)attitudes toward technologies, and (c) organi-zational behavior such as turnover and absen-teeism. Researchers have also used contagion

to explain interorganizational behavior. Eatof these topics is reviewed on the followingpages. The section concludes with sUgges-tions for extensions of organizational researchbased on a contagion mechanism.

General Workplace Attitudes

Several studies have examined the extent towhich contagion explains individual attitudesin the workplace. Friedkin’s (1984) early re-search showed that educational policy makerswere more likely to perceive agreement withothers who were either in the same cohesivesocial circle or were structurally equivalent.Walker (1985) discovered that members of acomputer firm who were structurally equiva-lent were more likely to report similarcognitions about means-ends relationships ofproduct development. And Rentsch (1990)found that members of an accounting fin-nwho communicated with one another weremore likely to share similar interpretations oforganizational events.

Goodell, Brown, and Poole (1989) use astructurational argument (Poole & McPhee,1983) to examine the relationship betweencommunication network links and shared per-ceptions of organizational climate. Using fourwaves of observation over a ten-week periodfrom an organizational simulation, they foundthat members’ communication networks weresignificantly associated with shared percep-tions of the organizational climate only at theearly stages of organizing (weeks two andfour). In another study comparing the cohe-sion and structural equivalence mechanismsof contagion, Hartman and Johnson (1989,1990) found that members \vho were cohe-sively linked were more likely to have similarlevels of commitment to the organization.However, those who were structurally equiva-lent were more likely to have similar perceP-tions of role ambiguity in the workplace.Pollock, Whitbred, and Contractor (1996)compared the relative efficacy of three modelsthat seek to explain an individual’s satisfac-tion in the workplace: the job characteristics

(Hackman & Oldham, 1976), the jndi-

d i s p o s i t i o n s mode1 (S,taW & Rqss,and the social rnformatron processmg

Br Pfeffer, 1978). Using datapublic works division of a military

et al. (1996) found thatsatisfaction was significantly pre-

only by the social infom-don process-that is, by the satisfaction of

and communication partners in their

so&l networks, but not by the characteristicsofeeirjobs or their individual dispositions.

Attitudes Toward Techologies

Several researchers have examined the ex-.tent to which contagion explains organiza-Gonal members’ attitudes toward technolo-gies. Drawing on social information pro-cessing theory (Salancik & Pfeffer, 1978) andsocial cognitive theory (Bandura, 1986), Fulkand her colleagues (Fulk, Schmitz, 8r Ryu,1995; Schmitz & Fulk, 1991) found that orga-nizational members’ perceptions and use of anelectronic mail system were significantly in-fluenced by the attitudes and use of the mem-bers’ supervisors and five closest coworkers.Further, Fulk (1993) found that social influ-ence was even more pronounced in more co-hesive groups. The attitudes and use of othermembers in their communication networkssignificantly influenced individuals’ attitudesand use of an electronic mail system. This ef-fect was attenuated, but persisted, even aftershe controlled for the effect of the workgroup’s attitudes and use on each group mem-ber.

Rice and Aydin’s (1991) research showedthat hospital employees who communicatedwith one another or shared supervisory-subor-dinate relationships were more likely to sharesimilar attitudes about a recently introducedinformation technology. Rice et al. (1990)found that individuals’ use of email in a de-centralized federal agency was predicted bythe use of the technology by others in theircommunication network. Further, groups ofindividuals who communicated more strongly

E m e r g e n c e ofcommunicotion N e t w o r k s + 4 6 7

with one another were more likely to sharesimilar distinct email usage patterns.

Using longitudinal data from a federal gov-

ernment agency, Burkhardt (1994) found thatindividuals’ attitudes and use of a recently im-plemented distributed data-processing com-puter network were significantly influencedby the attitudes and use of others in their com-munication network. She found that individu-als’ perceptions of their self-efficacy with (ormastery of) the new technology were signifi-cantly influenced by those with whom theyhad direct communication, which is the theo-retical mechanism of contagion by cohesion.However, individuals’ general attitudes anduse of the technology itself were more influ-enced by the attitudes and behaviors of thosewith whom they shared similar communica-tion patterns, that is, contagion by structuralequivalence. Burkhardt also found that thecontagion effect was higher for individualswho scored higher on a self-monitoring scale.

Extending this line of longitudinal researchon contagion effects, Contractor, Seibold, andHeller (1996) conducted a study comparingthe evolution of the social influence process inface-to-face and computer-augmented groups.They found that group members initial influ-ence on each others’ perceptions of the struc-tures-in-use (i.e., the interaction norms en-acted during the meeting) was high in theface-to-face condition, while group membersusing group decision support systems(GDSSs) started out with low levels of socialinfluence on one another. However, the differ-ence between face-to-face and technologi-cally augmented groups was only transient.By their third meeting, members in all groupsheavily influenced each other’s perceptions ofthe structures-in-use. While the preponder-ance of research has focused on similarity inattitudes based on contagion, Bovasso (1995)reports results from a process he calls“anticontagion.” In a study of managers at alarge, multinational high-tech firm, Bovassofound that “individuals who perceive them-selves as strong leaders are influenced bypeers who do not perceive themselves as

468 + S t ruc tu re

strong leaders” (pp. 1430-1431) and viceversa.

Behavior Through Contagion

Several network studies have used a conta-gion explanation for organizational members’behaviors, including voluntary turnover, ab-senteeism, job-seeking, socialization, and un-ethical behavior. Krackhardt and Porter(1986) found that employees voluntarily quit-ting their jobs were more likely to be structur-ally equivalent to one another than those who

remained. However, they found that employ-ees who were absent were more likely to becohesively connected with one anotherthrough friendship ties. They suggested thatdecisions about turnover were more closelyrelated to individuals’ roles in the organiza-tion and hence, members were more influ-enccd by others in similar roles. On the otherhand, decisions about absenteeism reflectednorms in the organizations that were commu-nicated through cohesive friendship ties. In amore recent study, Feeley and Barnett (1996)examined employee turnover at a supermarketand found that both social influence and struc-tural equivalence networks predicted the like-lihood of employees leaving the organization.Kilduff (1992) studied graduate business stu-dents’ job-seeking behavior and found thatstudents’ decisions to interview with particu-lar organizations were influenced by the opin-ions communicated to them by others in theirfriendship networks. The contagion effect wasmore pronounced for students who reportedbeing high self-monitors. Zey-Ferrell andFerrcll (1982) reported that employees’ self-reported unethical behavior was better pre-dictcd by their perceptions of their peer be-havior than either their own beliefs or those oftop management. Research on organizationalsocialization (Jablin 8: Krone, 1987; Sher-man, Smith, & Mansfield, 1986) has alsoidentified newcomers’ positions in their newcommunication networks as a predictor oftheir assimilation into the organization.

Interorganizational Contagion

The contagion mechanism has also beenused to explain behavior at the interorga-nizational level. Organizations can link toother organizations in many ways. Useem(1984) describes how organizations use direc-tor interlocks as a tool to scan their environ-ment. These linkages are important becausethey provide the opportunity for communica-tion and the exchange of ideas, practices, andvalues. Both the formal activities surroundingthe board meetings and the informal activitiesand acquaintance ties that are created enablepeople to discover how things are done inother organizations. In these and similarinterorganizational studies, the opportunity tocommunicate afforded by the existence oflinkages is viewed as more important thanspecific message content.

Consistent with Useem’s (1984) view,much of the more recent literature examinesthe mechanisms by ivhich organizations usethese linkages to transfer organizational prac-tices and structural forms. Davis (199 1) foundthat Fortune 500 corporations were morelikely to adopt the “poison pill” strategy to de-fend against corporate takeovers if theirboards had directors from organizations thathad already adopted a similar strategy.Haunschild’s (1993) research showed that thenumber and types of corporate acquisitionsundertaken by their interlock partners signifi-cantly influenced the number and type oftakeovers attempted by firms. Likewise, her1994 research demonstrated that “acquisitionpremiums” (p. 406) the price that a firm paysto acquire another firm over the market valueprior to the takeover announcement, are simi-lar to those that their partner firms paid fortheir acquisitions. Other research by Palmer,Jennings, and Zhou (1993) has shown thatfirms are more likely to adopt a multidivi-sional form when they are linked to corpora-tions that have already adopted that form.Similarly, Burns and Wholey (1993) foundthat a hospital’s decision to adopt a matrixmanagement program was significantly pre-

ebw@$edg@q?” by the a(jop tion decision of other local

~i,RIS with high prestige and visibility.~,~~ha.+y---,F&.. and park (1997) found that hospitals that

{structurally tied to other hospitals in a@$~~&ospital system were more likely to

q$&&.; ; <’P*T=L~+flcaopt innovations, and Westphal, Gulati, and

T~DfA,Gqt$$~~ell (19%‘) found that contagion also ex-$$j$$%$&ed the adoption of total quality manage-;;q,+$$&nt ~QM) practices in the organization..‘~-$&$+I&ever,

,i?.::<:+&;,:.r.they observed that early adopters of

~$$$?jQI,j were more likely to use the other early$!$$?~adopters in their medical alliance network to:..- .” c.

~~J$~~;,,:cl~ify their functional understanding of~,,.&:&TQM, The early adopters were therefore more

~:g;;~~..Y;7 ;$Z~;~L~;i;~ fikely to customize the program to their orga-~~~~:,~;.~~i..)~~tlonal needs. In contrast, late adoptersr++j .><ks3;‘.e?. :: were more likely to seek out other adopters in:~:p~$~~~ .; _,~~~:~~,~~~~11~~;‘their alliance network to determine the legiti-,p;‘8: I .-i 1)p>:~;q$:‘cr:;:,~l,~ IVmacy of using TQM. Hence, the late adopters&$$- ;:were more likely to adopt the TQM program$$&;‘~~without any customization. Stearns and::.

l.-Mizruchi (1993) found that the type of financ-. . ing used by a firm, short- versus long-termY debt, was influenced by the types of financialinstitutions to which it was linked by its boardof directors, commercial bankers versus rep-resentatives of insurance companies. How-ever, the embeddedness of an organization’sboard of directors has a somewhat counter-intuitive influence on the selection of its CEO.Khurana (1997) found that Fortrtne 500 com-panies whose boards of directors were wellembedded into the system of interlocking di-rectorates were less likely to choose an out-sider as a CEO because “a high level ofembeddedness is likely to constrain actionsrather than facilitate them” (p. 17).

Interlocking directorates are only one ofseveral possible mechanisms for linking orga-nizations. Organizations are likely to belinked to bankers, attorneys, accountants, sup-pliers, and consultants, all of whom serve asconduits for the flow of information betweenorganizations. Basing their arguments on themimetic processes articulated by institutionaltheory (DiMaggio & Powell, 1983), Galas-kiewicz and Burt (1991), and Galaskiewiczand Wasserman (1989) discovered that contri-bution officers who were structurally equiva-

Emergence ofcommunicotion N e t w o r k + 469

lent in an interorganizational corporate net-work were more likely to give charitable do-nations to the same nonprofit groups thanthose who were cohesively linked. Mizruchi(1989, 1992) found that organizations thatwere structurally equivalent in the interorga-nizational network were more likely to havesimilar patterns of political contributions.Baum and Oliver (1991) showed that in-creased ties to legitimating institutions signifi-cantly reduced the likelihood of failure amongnew organizations. And in a ten-year study,Goes and Park (1997) found that hospitalslinked to their institutional environmentsthrough industry and trade associations weremore likely to adopt innovations in an effort togain legitimacy. This effect was even morepronounced when the hospital industry en-tered a turbulent phase after introduction oftwo regulatory events in 1983. Interestingly,these findings are similar to those obtainedunder predictions from exchange and resourcedependency theories, though obviously gener-ated by a different theoretical mechanism,

Extensions to Contagion Theories

Contagion theories offer by far the mostcommon theoretical mechanisms for studyingthe emergence of networks. The notion of anetwork as labyrinth of conduits for informa-tion flow lends itself to theoretica! mecha-nisms based on contagion. Ho*.sexizr, whilenetwork researchers frequently invoke conta-gion theories, they often fall shoE of a,,iculat-ing specific mechanisms and netl.vorL: modelsby which individuals, groups, and organiza-tions influence each other’s action: and be-haviors (Contractor Rr Eisenberg. 19X1: Mars-den & Friedkin, 1993; Rice, 1993bi. There arefour recent attempts to articulate nlz.:hanismsthat make the contagion process nor? theoret-ically specific and comprehensive frr commu-nication networks.

First, Krackhardt and Brass (1434) notethat the contagion processes dextikd by so-

cial information processing theor\ must overtime lead to an equilibrium wherein. everyone

-

4 7 0 + Structure

in the network will eventually converge intheir attitudes or actions. They note that thisconclusion undermines the very premise ofsocial information processing theory, whichseeks to explain the variation in people’s atti-tudes based on their differential exposure tosocial information. Krackhardt and Brass(1994) suggest that the principle of interuc-tion that is assumed by contagion theoriesneeds to be augmented by a second contagionmechanism, the principle of reflected exclu-sivit)! The principle of interaction states thatgreater interaction leads to greater similarityin attitudes. By contrast, the principle of re-flected exclusivity states that “the degree ofinfluence person j has on person i’s evaluation. . is inversely proportional to the amount oftime person j spends with all others” (Krack-hardt & Brass, 1994, p. 219).

Second, Krassa (1988) advocates the inclu-sion of members’ threshold levels in a socialinfluence model. In its simplest form, thethreshold is the number of others that peoplemust be influenced by before succumbing(Granovetter, 1978). Individuals’ thresholdscould be a function of the intensity of theiropinion and their aversion to the risk of beingsocially isolated. Krassa (1988) uses com-puter simulations of a contagion model todemonstrate the effects of people’s thresholddistributions on their opinions.

Third, Rice (1993b) has argued that a net-work contagion model of social influenceshould also take into consideration the ambi-guity of the situation. Drawing on research byMoscovici (1976), Rice (1993b) argues thatpeople are more vulnerable to social influenceby contagion when confronted with ambigu-ous, or novel, situations. Based on this argu-ment, Contractor and Grant (1996) hypothe-sized that groups using new collaborationtechnologies (a novel situation) would bemore likely to influence each other’s percep-tions of the medium than groups in a tradi-tional face-to-face meeting. However, theyfound that social influence was actuallygreater in face-to-face groups, perhaps be-cause the novelty in this case was associated

with the very medium used to socially influ-ence one another.

Finally, in an attempt to extend the current

debate surrounding the relative efficacy ofcontagion via cohesion versus structuralequivalence, Pattison (1994) argued for acloser examination of automorphic or regularequivalence in addition to mechanisms basedon contagion by cohesion and structuralequivalence. Unlike structural equivalence,which in its strict operationalization is definedas two individuals having identical networklinks to the same others, regular equivalenceis defined as two people having similar pat-terns of relationships, but not necessarily withthe same others (White & Reitz, 1989).Pattison (1993) argues that people who areregularly equivalent are more likely to havesimilar social cognitions because “cognitiveprocesses may directly involve the individ-ual’s perceptions of his or her social locale”(p. 93). In a longitudinal study of students inan undergraduate class, Michaelson and Con-tractor (1992) found that students who wereregularly equivalent were more likely to beperceived as similar by their classmates thanthose who were structurally equivalent.

Cognitive Theories

The contagion mechanisms discussed inthe previous section focused on the extent towhich others who were linked to individualsvia cohesion or structural equivalence influ-enced their attitudes and actions. These stud-ies explain attitudes and behavior based on in-dividuals’ actual interactions. Researchershave employed four concepts to gain insightinto the structure of individuals’ cognitions:semantic networks, knowledge structures,cognitive social structures, and cognitive con-sistency. These areas are discussed in greaterdetail below.

Semantic Nehvorks

With an eye toward a more systematictreatment of message content, semantic net-

were introduced into the organizationalliterature by Monge and

1987; see also Carley, 1986;network analysis;

Fiol’s [ 19891

& Kincaid’s [ 198 l]of networks; Woelfel &

Galileo system). The essential

perspective was a focus on thethat people have for message

those messages that com-of an organization’s

such as corporate goals, slogans,Monge and Eisenberg

#$::$1987) argued that asking people to provide$8: . . their interpretations of one Or more significant&.&;+.kjY:lc communication messages, events, or artifacts

&@ ;,.icould create semantic networks. Content anal-; ysis of members’ responses provides catego-

-:ries of interpretation. Linkages can then becreated between people who share similar in-terpretations. The resultant network articula-tion provides a picture of the groups of peoplewho share common understandings, thosewho have idiosyncratic meanings such as iso-lates, and those who serve as liaisons andboundary spanners between the variousgroups.

With respect to empirical studies of seman-tic networks Lievrouw, Rogers, Lowe, andNadel (1987) used four methods to identifythe invisible research colleges among biomed-ical scientists: (a) co-citation analysis, (b)coward occurrence, (c) interpretive thematicanalysis, and (d) network analysis. They con-cluded that their focus on the content of thenetworks helped clarify the structure of the in-visible colleges. On the basis of communica-tion network patterns alone, all the scientistswould have been clustered into one invisiblecollege. However, a closer examination ofcontent helped them identify several invisiblecolleges, “each of which represents a distinctand identifiable line of research” (p. 246).

In a study of a high-technology firm, a li-brary, and a hospital, Contractor, Eisenberg,and Monge (1996) examined the semanticnetworks representing the extent to which em-

E m e r g e n c e 0fCommun~cotion Ne tworks + 4 7 I

ployees shared interpretations of their orgam-zations’ missions. In addition to their actualagreement, employees were also asked to re-port their perceived agreement, that is, the ex-tent to which they believed others shared theirinterpretations in the organization. Theyfound that employees at higher levels in thehierarchy were more likely to perceive agree-ment, even in cases when there was no agree-ment. However, employees with more tenurein the organization were more likely to haveactual agreement, even though they did notperceive that others shared their interpreta-tions of the mission. Contrary to the acceptedview that communication builds shared mean-ing, employees cohesively connected in thecommunication network were not more likelyto agree with their colleagues’ interpretationsof the organizational mission, even thoughthey perceived agreement. However, employ-ees who were structurally equivalent weremore likely to share actual agreement, eventhough they were not as likely to perceiveagreement.

Krackhardt and Kilduff (1990) applied thenotion of semantic networks to examine indi-viduals’ attributions about others in the net-work. They asked individuals in an organiza-tion to make cultural attributions on sevendimensions about the behaviors of each othermember in the organization. They found thatindividuals who were friends were morelikely than nonfriends to make similar attribu-tions about other members in the organiza-tion. Rice and Danowski (1993) applied thenotion of semantic net\vorks to examine indi-viduals’ attributions of the appropriation of avoice mail system. They found that individu-als who used the system for “voice process-ing” (i.e., routing and structuring the flow ofmessages among individuals) characterizedtheir use of the technology in terms that weresystematically distinct from those who usedthe voice mail technolosy as a substitute fortraditional answering machines.

‘‘:,

Two studies have used semantic networksto examine variations in national cultures.Jang and Barnett (1991) analyzed the chief ,

4 7 2 + Structure

operatmg officer’s letter that 17 Japanese and1 S U.S. organizations published in the organi-zation’s annual report to stockholders. Theyfound that the co-occurrence of words in thesemessages resulted in two distinct clusters forthe Japanese and U.S. companies. Further, thewords co-occurring in the Japanese annual re-ports focused on concepts related to organiza-tional operations, while the U.S. documentsfocused on concepts related to organizationalstructure. In a study of 12 managers from fiveEuropean countries, Stohl (1993) examinedthe cultural variations associated with manag-ers’ interpretation of a key communicativeprocess, worker participation. She found thatthe semantic network based on shared inter-pretations of the concept reflected greaterconnectedness within countries than betweencountries. Further, similarities in interpreta-tions about worker participation were system-atically associated with three of Hofstede’s(1984) dimensions of cultural variabilityacross countries. These were (a) the powerdistance index, the extent to which less pow-erful people accept inequality in power; (b)the uncertainty avoidance index, the extent towhich people avoid uncertainty by relying onstrict codes of behavior; and (c) individual-ism, the extent to which citizens place primaryimportance on the needs of the individualrather than the collective.

Estetuions to senmztic networks. The theo-retical mechanisms of contagion have alsobeen used to explain the co-evolution of com-munication and semantic networks. Contrac-tor and Grant (1996) developed a computersimulation of the effects of social contagionin communication and semantic networksthat contained varying levels of initial net-work density and heterogeneity. They foundthat the time required for semantic conver-gence within groups was positively related tothe density of the communication and seman-tic networks, inversely related to the hetero-geneity of the communication network, andinversely related to the individual’s inertiaagainst being influenced socially. Signifi-cantly, the initial heterogeneity in the seman-

tic network, an indicator of initial variation ininterpretations, was not a Significant predic-tor of the time required for semantic conver-gence.

In a similar endeavor, Carley (1991) of-fered a “constructural” theory of group stabil-ity, modeling the parallel cultural and socialevolution of a group. SO&l structure was de-fined as the distribution of interaction proba-bilities, and culture was defined as the distri-bution of distinct facts. Carley’s (1991) modeldescribed a cycle of three events for eachgroup member: “ ( 1) action-exchange infor-mation with their partners; (2) adapta-tion-acquire the communicated informationand update the probabilities of interaction;and then (3) motivation-choose new interac-tion partners on the basis of their new proba-bilities of interaction” (p. 336). Results ofcomputer simulations showed that thesegroups did not evolve monotonically towardgreater homogeneity. Instead they often oscil-lated through cycles of greater and lesser co-hesiveness. Her simulations also indicatedthat groups with “simpler” cultures (i.e.,fewer facts to be learned by group members)tended to stabilize more quickly. Further,those in less homogeneous groups (i.e., wherefacts were not equally distributed) were lesslikely to stabilize, since they could form en-during subcultures. One corollary of construc-tural theory is that the probabilities for two in-dividuals to interact are not symmetric(Carley &r Krackhardt, 1996).

Nehvork Orga?zitatiomas Knowledge Sttxctwes

A complementary view of semantic net-works as meaning structures is provided byKogut, Shan, and Walker (1993), who arguedthat it is interesting to view interorganiza-tional networks as structures of knowledge.Organizations seek out other organizationsbecause they want to establish some form ofrelationship. But to do so, they must first findat least some of the other organizations thatare also interested in entering into the rela-tionship with them and choose among the al-

~~~~,~:;~:,~~L;.; camp are it with information from other orga-@$$I:~;~., GzaGons. Often, in searching for partners, or-~y;.;+J~L”...m. . . ,;,.;l .,,“,*(y;y;,,;.. :, gmizations begin close to home or on the ba-r.;,; !:>. :;+.*;?A( .r.. , . j- . , , ’*‘> ::>,,;y*. ,.. sis of recommendations from others with.+:e;\<..A~-‘.- -::,::‘4;.~,.y’.~~&x~~~;~?~p~

whom they are already linked. Over time, this@#&.. : p.,.‘;i, :G.!j:~’ : smching process builds up a knobvledge base

@$&’ .about the skills, competencies, trustworthi-

I.Once organizations choose partners, how-

ever, they tend to spend less time seekingother partners. AS Kogut et al. (1993) say,“Because information is determined by previ-ous relations and in turn influences the subse-quent propensity to do more relations, thestructure of the network tends to replicate it-self over time. The early history of coopera-tion tends to lock in subsequent cooperation”(p. 70). Further. they observe:

The replication of the network is a statement ofthe tendency of learning to decline with time.

. The structure of the network is a limiting con-straint on how much new learning can beachieved. . . But when viewed from the per-spective of the evolution of networks, there is atendency for old lessons to be retaught. (p. 71)

Powell, Koput, and Smith-Doerr (1996)argue that learning networks are particularlyimportant in industries where there is rapidtechnological development, knowledge iscomplex, and expertise is distributed aroundmany organizations. Using data collected on225 firms over four years, they found strongevidence for increasing levels of interor-ganizational communication and collabora-tion in the biotechnology industry, includingincreases in ties and network density. In astudy of two new biotechnology firms(NBFs), Liebeskind, Oliver, Zucker, andBrewer (1996, p. 428) documented how theyused social networks to “source their mostcritical input-scientific knowledge.” Theyfound that “almost none of the individ-ual-level exchanges of knowledge throughresearch collaboration involved organiza-

Emergence ofCommunrcotfon Networks + 473

tions with which either NBF had a marketagreement” (p. 439). The lack of market-based contractual arrangements increasedtheir flexibility to create and dissolve net-works as well as adapt strategically to evolv-ing research interests.

Bovasso (1992) used four network mea-sures of an organization’s structure-density,range, prominence, and elitism-to examinethe changes that resulted when three high-technology, knowledge-intensive firms onthree continents were merged by the parentcorporation to create a single networked orga-nization. In the newly formed networked or-ganization, Bovasso found support for theemergence of a structural convergence, withgeographic divisions and hierarchical levelshaving a smaller impact on members’ involve-ment in the influence of ideas and control ofresources. More specifically, geographicaland hierarchical differences in prominence,elitism, and density scores between middleand upper management in the three firms werereduced.

Cognitive Social Stmctwes

Several researchers (Corman P; Scott,1994; Krackhardt, 1987) have sought to dis-tinguish people’s cognitions of social struc-tures from their actual, observed communica-tion networks. This line of research wasprecipitated by a series of studies in the early1980s questioning the ability of informants toaccurately report their own communicationnetwork patterns (Bernard, Kill\vorth, &Sailer, 1980, 1982; Bernard, Kill\vorth, &Cronenfeld, 19S4; Freeman, Romney, s( Free-man, 1987). Their results underscored theproblematic nature of collecting self-reportmeasures of communication net\sork data ifthe underlying theory being tested v,.as basedon the assumption that individuals’ attitudesand behavior were shaped by their actualcommunication networks. However, as Rich-ards (1985) argued, the differences betweenself-reported and observed network data areproblematic only if the underlying theoreticalconstruct being measured was actual commu-

474 + Structure

nication behavior (see also Marsden, 1990). Infact, Richards (1985) notes, many social andpsychological theories are based on individu-als’ perceptions-an assertion well capturedby W. I. Thomas’s observation that “percep-tions are real in their consequences even ifthey do not map one-to-one onto observed be-haviors” (Krackhardt, 1987, p. 128; Pattison,1994). For researchers drawing on such socialand psychological theories, a discrepancy be-tween observed and self-reported measureswould suggest a measurement error in usingdata about observed communication.

Krackhardt (1987) developed the conceptof cognitive social structures to characterizeindividuals’ perceptions of the social net-works. Cognitive social structures assume thestatus of socially shared, structural “taken-for-granted facts” (Barley, 1990, p. 67) by indi-viduals about the predictable and recurrent in-teractions among individuals in the network,even if these cognitions are at variance withthe actual communication. Krackhardt (1987)aggregated individuals’ cognitive social struc-tures to estimate a “consensual” cognitive so-cial structure, in which a link existed betweentwo individuals if others in the network per-ceived this tie, irrespective of whether it wasacknowledged by either of the people in thedyad. As such, a link in the “consensual” cog-nitive social structure indexed a common ad-age: It is not who you know, but who othersthink you know.

Several empirical studies have demon-strated the explanatory power of the cognitivesocial structure concept. Krackhardt (1987)found that managers in a high-technology en-trepreneurial firm who were deemed as highlycentral (betkveenness) in the consensual cog-nitive social structure were significantly morelikely to be able to reconstruct the “actual” ad-vice network reported by the people involved.Krackhardt (1990) also found that the per-ceived influence of organizational memberswas significantly associated with their abilityto accurately estimate the consensual cogni-tive social structure in terms of advice rela-tionships. Krackhardt’s (1992) researchchronicled how a union’s inability to accu-

rately assess the organization’s social she-ture led to its failure in organizing employees.Further, Kilduff and Krackhardt (1994) dem-onstrated that individuals’ reputations in theO r g a n i z a t i o n W e r e more closely associated

with their centrality in the consensual cogni-tive structure than in the “actual” communica-tion network based on the self-reports of thepeople involved. Finally, Heald, Contractor,Koehly, and Wasserman (1996) found that in-dividuals of the same gender, in the same de-partment, and in a supervisor-subordinate re-lationship were more likely to share similarcognitive social structures. Those individualswho were linked in acquaintance and commu-nication networks were also more likely toshare similar cognitive social structures.

ExfeFlsioFls to cognititte social strrictnres. Theconceptual and empirical work on cognitivesocial structures has moved the initial debateabout differences between actual and per-ceived communication from the methodolog.ical and measurement domain to a substan-tive exploration of the ~vays in which actualand perceived communication enable andconstrain each other. Corman and Scott(1994) deployed Giddens’s (1984) structur-ation theory to argue that three modalities ex-plain the recursive relationships between ob-servable communication and cognitive socialstructures: reticulation, activation, and enact-ment. Reticulation denotes the duality inwhich perceived communication relation-ships are produced and reproduced in observ-able communication behavior. Activationrepresents the duality of activity foci in thestructural domain with joint activity in the in-teraction domain. Enactment relates codingconventions in the structural domain to trig-gering events in the interaction domain(Corman, 1997, p. 69). They refer to this per-spective as the latent netivork of perceivedcommunication relationships.

Research on cognitive social structures hastaken on additional currency with the adventof virtual organizations, supported by infor-mation and communication technologies. Intraditional organizations, individuals who are

~~pfpiCtily Gu-I... . - --.---a

,,,,,..z>& to observe face-to-face interactions, and

structures. The pervasiveness ofmedia in virtual or-

~~,.~.‘.;:‘;p:~‘~j_‘. ~!~,~~~~:~;...sequently, organizational members have sig-$@&y;$i;: nificant problems accurately determining~~~~~~~~.,,,.‘~h~ knows who?” and “Who knows who.,.. _‘,.” ‘I, .:fq.$,;~~ : 1ii:. knows who?” Information technologies that&*kjl:‘L;.w,:;,~~~~~~~~~~.~aieresponsibIe for triggering this problem canp&.,,;yy ‘i.,$7-J?,..,‘:-: 2., c--also be used to overcome these obstacles. Be-~$$$~~~~!$~. ‘&use information transacted over electronic‘.LL..&..,... I*&..+..x;“-. L:I;. ., i+c+&$;.z, :ix<media such as the Web can be stored in digital$!&$$f>~~.~‘~? form, a new generation of software calledz’!,s: $.,‘,$ , -;%fi$@~~-i* “collaborative filters” has emerged (Contrac-c+JJ?&~:’ I.,.<. .s??’ i2J$,“p ,../, ,.._“-Q$.“‘~ tar, 1997; Contractor, O’Keefe, &r Jones,>5’*c;:~&:r+ >:,j; $$;~;:, . .;:r7&.>&z!: , . 1997; Contractor, Zink, Sr Chart, 1998; Kautz,~~.~~~~~~~r’::;,.Selman, & Shah, 1997; Nishida, Takeda,. , .c. I-r, ::

Iwazume, Maeda, & Takaai, 1998). These fil-ters can be used to make visible the organiza-tion’s virtual social and knowledge structures.Collaborative filters process individuals’ in-terests, relationships, and the structure andcontent of their electronically stored informa-tion (such as Web pages). They can assist indi-viduals in searching the organization’s data-bases to automatically answer questions aboutthe organization’s knowledge network, that is,“Who knows what?” as well as questionsabout the organization’s cognitive knowledgenetworks, that is, ‘Who knows who knowswhat?’ within the organization. The use ofthese kinds of tools is likely to have a levelingeffect on the organization’s cognitive socialstructure, because they can potentially under-mine the perceived centrality of those individ-uals in the organization who are viewed as im-portant resources about the organization’ssocial and knowledge networks.

Like the semantic networks and cognitiveSocial structures discussed above, consistencytheories focus on members’ cognitions. How-ever, in this case the explanatory mechanism

underscores individuals’ aspirations for con-sistency in their cognitions. When applied toorganizational communication networks, con-sistency theories seek to explain the extent towhich a drive for consistency is manifest inpeople’s networks and attitudes. That is,members’ attitudes are viewed as a function ofthe balance in their networks rather than alter-native mechanisms such as contagion. Heid-er’s (1958) balance theory posited that if twoindividuals were friends, they should havesimilar evaluations of an object. This modelwas extended and mathematically formulatedby Harary, Norman, and Cartwright (1965),and later by Davis and Leinhardt (1972), andHolland and Leinhardt (1975), who arguedthat the object could be a third person in acommunication net\vork. If the two individu-als did not consistently evaluate the third per-son, they would experience a state of discom-fort and would strive to reduce this cognitiveinconsistency by altering their evaluations ofeither the third person or their own friendship.They extended this line of argument to all pos-sible triads in a network. Researchers have ex-amined the effects of cognitive consistency onboth attitudes and behavior.

The effect of cognitive consisterq on ntti-tudes. Consistency theories have played animportant role in clarifying an earlier debateabout the relationship between involvementin communication networks and work atti-tudes such as job satisfaction and organiza-tional commitment. Early studies (e.g.,Brass, 1981; Eisenberg, Monge, & hliller,1984; Roberts &r O’Reilly, 1979) reportedcontradictory and inconsistent findings aboutthe extent to which individuals who werewell connected, integrated, or central in theircommunication networks were more likely tobe satisfied and committed to their organiza-tions. Consistency theories suggest that it isnot the centrality or number of links in indi-viduals’ networks but the perceived balancewithin the network that influences level ofsatisfaction and commitment. Krackhardtand Kilduff (1990) found that individuals’job satisfaction scores were predicted by the

476 4 Structure

extent to which they agreed with their friendson cultural attributions about other membersin the network. Kilduff and Krackhardt(1993) found that individuals who werehighly central in the friendship network wereless satisfied than others who were less cen-tral; however, those who saw their friendshipnetworks in balance (they call it “schemaconsistent”) were more likely to be satisfiedand committed. In a study of three organiza-tions (described earlier in the Semantic Net-works section), Contractor, Eisenberg, andMonge (1996) also found that the extent towhich employees shared common interpreta-tions of their organization’s mission had nodirect bearing on their level of satisfaction ororganizational commitment. However, thosewho perceived greater agreement with oth-ers’ interpretations were more likely to besatisfied and committed. Barnett and Jang(1991), while not explicitly invoking consis-tency theories, found that members of a po-lice organization who were central and con-nected in their communication networkswere more likely to perceive their views ofsalient organizational concepts as being con.sistent with those of others. Researchers haveused network concepts of transitivity tooperationalize the effect of balance in thenetwork.

The effect of cogrutrve consistency on behav-ior. Consistency theories have also been re-lated to the behavior of organizational mem-bers. Krackhardt and Porter (1985) foundthat friends of those who voluntarily left anorganization were no longer exposed to theirformer coworkers’ unhappiness and weretherefore able to restore their previous per-ceived balance; as a result they reportedgreater le\‘els of satisfaction following thedeparture of these friends from the organiza-tion. Brass et al. (1995) argued that the needfor balance among three people can also in-fluence the likelihood of unethical behavior.“The addition of the third party with strongties tp both other actors will act as a majorconstraint on unethical behavior when thetwo actors are only weakly connected” (p. 7).Further, they proposed that the likelihood of

unethical behavior 1s least likely to occurwhen a l l t h ree peop le a re Connected bystrong ties (i.e.. a Simmelian triad; Krack,hardt, 1992).

Extensions to cognitive consistency t}leories.The deployment of consistency theories toexplain organizational phenomena is rela-tively recent. Conceptually and analytically,it challenges network researchers to movefrom the dyad to the triad as the smallest unitof analysis. As the examples above indicate,it has the potential of resolving many of theinconsistent results in network studies thatuse the dyad as the primary unit of analysis,

Like the other cognitive theories discussedm the previous section, consistency theorieshave also been used to address the ongoingdebate about differences between actual andperceived communication. Freeman (1992)suggested that consistency theories offer asystematic explanation for differences be-tween actual and self-report data on commu-nication. He argued that individuals’ needs toperceive balance in observed communicationnetworks help explain some of the errors theymake in recalling communication patterns.Using experimental data collected by De Soto(1960), Freeman found that a large proportionof the errors in subjects’ recall of networkscould be attributed to their propensity to “cor-rect” intransitivity, a network indicator of im-balance, in the observed network.

Theories of Homophily

Several researchers have attempted to ex-plain communication networks on the basis ofhomophily, that is, the selection of others whoare similar. Brass (1995b) notes that “similar-ity is thought to ease communication, increasepredictability of behavior, and foster trust andreciprocity” (p. 51). Homophily has beenstudied on the basis of similarity in age, gen-der, education, prestige, social class, tenure,and occupation (Carley, 199 1; Coleman,1957; Ibarra, 1993b, 1995; Laumann, 1966;Marsden, 1988; McPherson & Smith-LovinY1987).

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Several lines of reasoning support thehomophily hypothesis. These fall into twogeneral categories: the sitnilarity-attractionhypothesis (Byrne, 1971) and the theory ofself-categorization (Turner, 1987). The simi-larity-attraction hypothesis is exemplified inthe work of Heider (1958), who posited thathomophily reduces the psychological discom-fort that may arise from cognitive or emo-tional inconsistency. Similarly, Sherif (1958)suggested that individuals were more likely toselect similar others because by doing so theyreduce the potential areas of conflict in the re-lationship. The theory of self-categorization(Turner & Oakes, 1986) suggests that individ-uals define their social identity through a pro-cess of self-categorization during which theyclassify themselves and others using catego-ries such as age, race, gender. Schachter(1959) argued that similarity provided indi-viduals with a basis for legitimizing their ownsocial identity. The manner in which individu-als categorize themselves influences the ex-tent to which they associate with others whoare seen as falling into the same category.

A substantial body of organizational de-mography research is premised on a ho-mophily mechanism. In addition, several stud-ies have focused specifically on gender ho-mophily. Each area is reviewed below.

Gerreral Demographic Homophily

The increased workforce diversity in con-temporary organizations has seen a rise in thecreation of heterogeneous work groups thatcomplicate individuals’ desires for homoph-ily. Several studies have examined the extentto which individuals’ predilection for ho-mophily structures organizational networks.Zenger and Lawrence (1989) found that tech-nical communication among researchers in ahigh-technology firm was related to their ageand tenure distribution. Studies by O’Reillyand colleagues (Tsui, Egan, & O’Reilly, 1992;Tsui & O’Reilly, 1989; Wagner, Pfeffer, 8:O’Reilly, 1984) found that differences in ageamong employees hindered communicationand social integration and resulted in lower

E m e r g e n c e 0fCommunicotion N e t w o r k s + 4 7 7

commitment and greater turnover among em-ployees.

Basing their arguments on the principle ofhomophily, Liedka (1991) studied the age andeducation distribution of members recruitedto join voluntary organizations such as youthgroups, farm organizations, and sports clubs.Using data collected in the 198.5 and 1936General Social Survey, he found results at theaggregate level, suggesting that members ofvoluntary organizations were more likely topersuade others similar to their age and educa-tion to join the organization. He also foundthat when people in the same age groups Lveremore densely connected, they were morelikely to be represented in voluntary organiza-tions. At the interorganizational level! Galas-kiewicz (1979) and Schermerhorn (1977)found that interorganizational links weremore likely to occur among individuals nhoperceived similarity in religion, age, ethniciry,and professional affiliations.

Gerder HonrophilJ

Considerable research has examined theeffect of gender homophily on organizationalnetworks. Lincoln and Miller (1979) foundthat similarities in sex and race of organiza-tional employees were significant predictorsof their ties in a friendship network. Brass’s(1985a) research indicated that communica-tion networks in an organization ivere largelyclustered by gender.

Several studies have examined the effectsof gender homophily on friendship. For in-stance, Leenders (1996) discovered that gen-der wras a more influential predictor of endur-ing friendship ties than proximity. In a studyof 36 female and 45 male senior managers intwo New York state government bureaucra-cies, Moore (1992) found that “half of the ad-vice cliques and nearly that proportion ofcliques in the friendship network contain menonly” (p. 53). Ibarra’s (1992) research of anadvertising agency revealed that even thoughwomen reported task-related, communication,advice influence ties with men. they weremore likely to select other women in their SO-

cial support and friendship netivorks. Men, on

478 + Structure

the other hand, were more likely to have in-strumental as well as noninstrumental tieswith other men. She pointed out that the con-straints of social exchange (see earlier sec-tion) and the resulting need to be connectedwith the organization’s predominantly male

power base often force women to forgo theirpropensity for homophily in terms of their in-strumental relationships.

Some aspects of culture bear on the pre-ceding results. For example, contrary to other

findings, research by Crombie and Birley(1992) showed that the network of contactsamong female entrepreneurs in Ireland wasnot different from that of men in terms of size,diversity, density, and effectiveness. Perhapsthe reason for this result is that the people inthis study were entrepreneurs. However, thewomen tended to be younger, owners ofsmaller businesses that had been establishedfor shorter periods of time, and less involvedin traditional exterior activities such as be-longing to civic organizations. Women alsotended to rely on men and women for advicewhile men consulted largely with other men.In similar fashion, Ethington, Johnson, Mar-shall, Meyer, and Chang (1996) studied twoorganizations with different gender ratios.They found that men and women were equallyintegrated into and prominent in each other’snetworks in an organization that had an equalratio of men and women and an equal genderdistribution in the power hierarchy. However,in an organization that had a 75%-25% fe-male-to-male ratio, the networks were moresegregated and women were more prominent

Estensiom to Theoriesof Homophily

Communication scholars have maintainedan enduring interest in the principle ofhomophily as a theoretical mechanism to ex-plain the emergence of networks. In responseto the ongoing focus on workforce diversity,they have invoked this mechanism in the studyof gender and race issues. The principle of

homophily has also been suggested as a net-work mechanism that is relevant to research-ers interested in the social comparison pro-cesses used by individuals to make assess-ments, for instance, about their perceptions ofequity in the workplace. According to equitytheory (Adams, 1965), individuals’ motiva-tions are a direct function of the extent towhich their input (i.e., efforts) to output (i.e.,rewards) ratios are commensurate with thoseof “relevant” others. Social comparison the-ory (Festinger, 1954) suggests that these rele-vant others are selected on the basis of beingsimilar, or homophilous, in salient respects.Likewise, social identity theory (Turner &Oakes, 1989) proposes that these relevant oth-ers are those who are seen as sharing the same“social identity” as the focal person. Krack-hardt and Brass (1994) suggest that the selec-tion of relevant others is constrained and en-abled by the networks in which individualsare embedded. Individuals could select as rel-evant others those with whom they have closecommunication ties (i.e., a cohesion mecha-nism) or with others who they see as havingsimilar roles (i.e., a structurally equivalentmechanism).

Several scholars have urged that similarityof personality characteristics be used to ex-plain involvement in communication net-works (Brass, 1995b; Tosi, 1992). McPheeand Corman (1995) adopted a similar per-spective in an article that drew on Feld’s(1981) focus theory to argue that interaction ismore likely to occur among individuals whoshare similar foci, including being involved inthe same activities. They found limited sup-port for their hypotheses in a study of churchmembers, suggesting the need for further re-search.

Tlzeories of Physical aridElectronic Proximity

A number of researchers have sought to ex-plain communication networks on the basis ofphysical or electronic propinquity (Corman,1990; Johnson, 1992; Rice, 1993a). Proximity

that individuals will

(Festinger, Schachter, &r1950; K o r z e n n y & Bauer, 1981;

Rothman, E isenberg , Mi l le r , &If these interactions were to oc-

allow individuals the opportu-the extent to which they have

and shared beliefs (Ho-research in organizationalthat the frequency of

communication drops pre-75-100 feet (Allen,

cent research also demonstrated that increasedphysical distance between offices, chain ofcommand, and status led to decreased proba-bility of communication. Likewise, Van denBulte and Moenaert (1997) found that com-munication among R&D teams was enhancedafter they were co-located. Therefore, individ-uals who are not proximate are deprived of theopportunity to explore these common inter-ests and are hence less likely to initiate com-munication links. As such, physical or elec-tronic proximity is a necessary but not suf-ficient condition for enabling network links.Dramatic evidence of the influence of physi-cal proximity involves the physical disloca-tion of 817 employees of the Olivetti factoryin Naples following the 1983-1984 earth-quakes. Bland et al. (1997) report that em-ployees who were permanently relocatedrather than evacuated only temporarily re-

ported the highest distress levels due to thedisruption in their social networks. Rice(1993b) notes that physical proximity mayalso facilitate contagion (see section above)by exposing spatially co-located individualsto the same ambient stimuli. Rice and Aydin(1991) found modest evidence of the roleplayed by physical proximity on employees’attitudes toward a new information system. Atthe interorganizational level, Palmer et al.(1986) found that interlock ties were morelikely to be reconstituted if departing mem-bers represented organizations whose head-quarters were physically proximate to that offocal organizations.

Emergence of Communication Networks 6 479

The effects of new communication tech-nologies on the creation and modification ofsocial networks are well documented (Barnett& Salisbury, in press; Rice, 1994a; Wellmanet al., 1996). Less intuitive, but just as evident,are the effects of new technologies in preserv-ing old communication structures. In a studyof three sectors of the UK publishing industry(the book trade, magazine and newspapertrade, and the newsprint suppliers), Spinardi,Graham, and Williams (1996) found that theintroduction of electronic data interchangeconsolidated and further embedded existinginterorganizational relationships, thereby pre-venting business process reengineering.

Extensions to Theoriesof Proximity

The proliferation of information technolo-gies in the workplace capable of transcendinggeographical obstacles has renewed interest inthe effects of physical and electronic proxim-ity and their interaction on communicationpatterns (Kraut, Egido, & Galegher, 1990;Steinfield & Fulk, 1990). Fulk and Boyd(199 1) underscored the potential of networkanalysis “to test the situational moderating ef-fect of geographic distance on media choice”(p. 433). Corman (1996) suggested that cellu-lar automata models are particularly appropri-ate for studying the effects of physical prox-imity on communication networks. Cellularautomata models can be used to study the col-lective and dynamic effects of proximity onthe overall communication network when in-dividuals in the network apply theoreticallyderived rules about creating, maintaining, ordissolving links with their “local.” that is,proximate, network neighbors.

Uncerrainty Reduction andContingency Theories

Uncertainty about individual and organiza-tional environments has played an importantrole in explaining organizational processes.Two theories have incorporated communica-

480 + Structure

tion network concepts to explain how peoplereduce this uncertainty. Uncertainty reductiontheory (URT) and contingency theory are re-viewled in this section.

Uncertainty Reduction Theory

URT (Berger, 1987; Berger & Bradac,1982) suggests that people communicate toreduce uncertainty thereby making their envi-ronments more predictable (Weick, 1979).Researchers have examined how communica-tion networks help manage and reduce the or-ganization’s uncertainty (Leblebici & Salan-cik, 1981; Miller & Monge, 1985). However,

as Albrecht and Hall (1991) note, “innovation,and especially talk about innovation, is inher-ently an uncertainty-producing process” (p.537). As a result, Albrecht and Ropp (1984)

found that communication about innovation ismost likely to occur among individuals who

have strong multiplex ties (i.e., both work andsocial ties) that guarantee them a level of rela-

tional certainty and thereby greater perceivedcontrol in a potentially uncertain situation.Albrecht and Hall (1991) found evidence thatthe need to reduce uncertainty also explainedthe creation of dominant elites and coalitionsin innovation networks. Burkhardt and Brass(1990) chronicled the changes in the commu-nication network following the introduction ofa new technology. They found that the uncer-tainty resulting from the introduction of thetechnology motivated employees to seek outnew contacts and hence change their commu-nication networks. Kramer (1996) found thatthe employees who had experienced job trans-

fers were more likely to have positive atti-tudes about the adjustment if their reconsti-tuted network offered the quality of com-munication that reduced their uncertainty.

At the interorganizational level, Gran-ovetter (1985) argued that organizational de-

cision makers use social networks to reduceuncertainty associated with market ex-

changes, thereby reducing their transactioncosts (see earlier discussion). Picot (1993)suggested that network organizations were su-

perior to markets and hierarchies when taskuncertainty was high and task specificity waslow. In a study of relationships between fn-rnsand their investment banks, Baker (1987) re-ported that the firms’ financial officers oftendrew on their informal networks to reduce “n-certainty surrounding the creation of a markettie. The reduction of uncertainty due to strongties was also useful to explain the reduction of

interorganizational conflict. Using data fromintergroup networks in 20 organizations, Nel-son (1989) found that organizations withstrong ties between their groups were lesslikely to report high levels of conflict thanthose organizations that had groups that wereconnected by weak ties.

Contingency Theory

In the early 196Os, organizational scholarsbegan to focus their attention on the environ-

ment and ways to reduce the uncertainty itcreated. Emery and Trist (1960) developedsociotechnical systems theory in which theyargued that the nature of an organization’s en-vironment significantly influences its struc-ture and operations (Emery 6: Trist, 1965). Acontingency theory approach to formal orga-nizational structures is based on the premisethat an organization should structure itself in amanner that maximizes its ability to reducethe uncertainty in its environment. For exam-ple, Burns and Stalker (1961) contrasted “or-ganic” with bureaucratic organizations, whichthey labeled “mechanistic.” The defining fea-ture of organic organizations was that theirstructures were internally adaptable to chang-

ing features of the environment Lvhile mecha-nistic organizations were not. Lawrence andLorsch’s (1967) contingency theory formal-ized this view and argued that all internal rela-tions and structures were contingent on exter-

nal conditions. Galbraith (1977) argued thatorganizations needed to develop slack re-sources and flexible, internal lateral commu-

nication networks to cope with environmentaluncertainty. Thus, the theoretical mechanismin contingency theory that accounted for the

formation, maintenance, and eventual dissolu-tion of communication networks was the levelof uncertainty m the organization’s environ-ment. Stable environments led organizationsto create long-standing, entrenched networks,while turbulent environments led organiza-tions to create flexible, changing networks.

In an empirical study of Burns andStalker’s distinction between mechanistic andorganic organizations, Tichy and Fombrun(1979) found that the differences between theformal and informal communication networkswere more pronounced in mechanistic organi-zations than they were in organic organiza-tions. Barney’s (1985) inductive blockmodel-ing, clustering, and scaling techniques identi-fied the dimensions of informal communica.tion structure in interaction data collected byColeman (1961) from the entire student population of ten Midwestern high schools. Onedimension identified was “analogous to Burnsand Stalker’s (1961) organic-mechanistic di-mension of formal structure” (Barney, 1985,p. 35), which proved to be consistent withcontingency theory’s proposed relationshipbetween environmental diversity and formalorganizational structure (Miles, 1980).

Shrader, Lincoln, and Hoffman (1989)tested Bums and Stalker’s argument that or-ganic forms of organizational structure wouldresult in informal organizational communica-tion networks that were denser, more highlyconnected, and more multiplex than thosefound in mechanistic organizations. Theyfound that organic “smaller organizationsmade up of educated staff applying nonrou-tine technologies have denser, more cohesive,and less-segmented networks consistinglargely of symmetric or reciprocated ties” (p.63). By contrast, vertically and horizontallydifferentiated, as well as formalized, mecha-nistic organizations were less densely con-nected, more segmented, and less likely tohave symmetric and reciprocated communica-tion ties.

Contingency theory’s proposed relation-ship between technology and the organiza-tion’s structure was examined in a study by

Emergence of Communication Networks + 48 I

Brass (1985b). Using network techniques tomeasure pooled, sequential, and reciprocal in-terdependencies in an organization’s work-flow, Brass (1985b) found that the relation-ship between interpersonal communicationand performance was contingent on the extentof horizontal differentiation in the organiza-tion’s structure and the coordination require-ments of the task.

Extensions to UncertaintyReduction cud ContingencyTheories

The review above suggests that the deploy-ment of uncertainty reduction theory wasmore prevalent in the 19SOs and has been onthe decline lately. This decline corresponds,not coincidentally, with the increasing critiqueof the scope and operationalization of the “un-certainty” concept (Huber & Daft, 19S7). Fu-ture network research from an uncertainty re-duction perspective should respond to callsfor a conceptual delineation bethveen uncer-tainty reduction and equivocality reduction(Weick, 1979). The relative efficacy of net-works to help reduce uncertainty andequivocality is a potentially useful but as yetuntapped area of inquiry. Further, past net-work research based on uncertainty reductiontheory has not distinguished bet\veen uncer-tainty reduction and uncertainty avoidance(March & Weissinger-Baylon, 1956). The useof communication networks to reduce uncer-tainty implies the presence or creation oflinks, while the avoidance of uncertainty mayimply the absence or dissolution of links.

Although the research literature testing thevalidity of the contingency mechanism issparse, it tends to support the importance ofinternal adaptability to external constraints. Infact, most theorists today accept the contin-gency thesis without significant empiricalsupport because the enormous increase in therates of environmental change in the contem-porary world makes it seem intuitively obvi-ous. No subsequent theory has argued againstthe contingency mechanism, and Galbraith’s

482 + Structure

(1977) extensive analysis of the developmentof slack resources and deployment of lateralcommunication linkages remains the cleareststatement of how to develop communicationnetworks to cope with rapidly changing envi-ronmental uncertainty.

Social Support Theories

Interest in social support networks canbe traced back to Durkheim’s (1897/1977)groundbreaking work on the impact of soli-darity and social integration on mental health.A social support explanation focuses on theways in which communication networks helporganizational members to cope with stress.Wellman (1992) and others have adopted thisframework in their study of social support net-works. Their research is largely based on thepremise that social networks play a “buffer-ing” role in the effects of stress on mentalwell-being (Berkman & Syme, 1979; Hall &Wellman, 1985).

Two general mechanisms exist by whichsocial networks buffer the effects of stress.First, an individual in a dense social supportnetwork is offered increased social support inthe form of resources and sociability. Lin andEnsel’s (19S9) research produced evidencethat strong ties in the support network pro-vided social resources that helped buffer bothsocial and psychological stress. Second,Kadushin (1983) argued that social supportcan also be provided by less dense social cir-cles. Social circles (Simmel, 1955) are net-works in which membership is based on com-mon characteristics or interests. Membershipin a social circle can help provide social sup-port “by (1) conveying immunity throughleading the members to a better understandingof their problems, (2) being a resource forhelp, or (3) mobilizing resources” (Kadushin,1983, p. 191).

A substantial amount of research exists onthe role of networks in providing social sup-port in varying organizational contexts, suchas families, communities, and neighborhoods(for reviews, see O’Reilly, 1985; Walker,

Wasserman, & Wellman, 1994). In a classiclongitudinal study of residents in a northernCalifornia county, Berkman and Syme (1979)found that respondents “who lacked socialand community ties were more likely to die inthe follow-up period than those with more ex-tensive contacts” (p. 186). Berkman (1985)found that individuals with fewer social support contacts via marriage, friends, relatives,church memberships. and associations had ahigher mortality rate.

Researchers (Barrera & Ainlay, 1983;Cu t rona & Russe l l , 1990 ; Wellman &Wortley, 1989, 1990) have identified four di-mensions of social support, including emo-tional aid, material aid (goods, money, andservices), information, and companionship.Considerable empirical evidence demon-strates that individuals cannot rely on a singlenetwork link, except to their parents or chil-dren, to provide all four dimensions of socialsupport. Studies by Wellman and Wortley(1989, 1990) of a community in southern On-tario, Canada, found that individuals’ specificnetwork ties provided either emotional aid ormaterial aid, but not both. Additionally, stud-ies have found that women are more likely tooffer emotional aid than men (Campbell &

Lee, 1990).Remarkably few srudies have examined

networks of social support in organizationalcontexts even though several scholars haveunderscored the need for research in this area(Bass 8r Stein, 1997). For example, Langford,Bowsher, Maloney, and Lillis (1997) proposethe examination of networks to study socialsupport in nursing environments such as hos-pitals and nursing homes. A comparison of sixhospital units by Albrecht and Ropp (1982)found that the volume and tone of interactionin the medical surgical unit’s communicationnetwork improved their ability to cope withchronic pressures and stress. In one of the fewstudies of social support networks in organi-zations, Cummings (1997) found that individ-uals who reported receiving greater socialsupport from their network were more likelyto generate radical (i.e.. “frame-breaking”) in-novation.

F..’

@&+,c);urlbert ( 1991) used ego-centric network

@Y*& for a sample of respondents from the@j9s General Social Survey (the first national

. .@f&ple contalnlng network data) to examine$i$$:.effect of kin and coworker networks on$@++s, as measured by individuals’ job satis-

&$~aac~on. She argued that individuals’ networks$$$.~ay (a) provide resources to decrease the$$$&e,+=l ofstress created by job conditions, or(b)

*Ye &de support thereby helping the individualg&p

~~@yOp” with job stress. She found that member-

$&&.;~ship in a coworker social circle was positively~$$$$$ .associated with job satisfaction, even after

.&&&:~ controlling for other social and demographic$%$~$$&,>.i variables. The effect on job satisfaction was$+t*,%6,:>c&+@~,~&.$$$ !.‘; even higher if the coworkers were highly edu-

r$$@~,:.cated, suggestin,0 that they were able to offer

,. :-’@$$&,J,~ additional instrumental resources. However,@$$$:,, Hurlbert (1991) also found that for individuals..y;:> , %~&$$~;.. . ..<.r A. who were in blue-collar jobs or those with low.:

security, “kin-centered networks may exacer-bate, rather than ameliorate, negative job con-ditions” (p. 426). Consistent with this latterfinding, Ray (1991) and Ray and Miller(1990) found that individuals who werehighly involved in networks offering socialsupport to friends and coworkers were morelikely to report high levels of emotional ex-haustion. The negative effects of the networkon individuals were also reported in a Iongitu-dinal study of relatively well-functioningolder men and women. Seeman, Bruce, andMcAvay (1996) found that men who hadlarger instrumental support networks weremore likely to report the onset of activities ofdaily living disability. They speculated thatthese results may reflect “the consequences ofgreater reliance on others, a behavior patternwhich may, over time, erode the recipient’sconfidence in their [sic] ability to do things in-dependently” (pp. S197-S198).

At the interorganizational level, Eisenbergand Suanson (1996) noted that Connecticut’sHealthy Start program served an important so-cial support role for pregnant women by serv-ing as referral to hospitals and agencies.Zinger, Blanco, Znnibbi, and Mount (1996)reported that Canadian small businesses reliedmore heavily on an informal support network

than government programs. Paterniti, Chel-lini, Sacchetti, and Tognelli (1996) describedhow an Italian rehabilitation center for schizo-phrenic patients successfully created networklinks with other organizations to reflect “thesocial network that surrounds the patient andfrom which he [sic] has come” (p. 86).

Extensions to SocialSupport Theories

The amount of research on social supportnetworks has increased substantially in thepast few years. Some of these changes are per-haps motivated by changes in the organiza-tional landscape, such as the increase inoutsourcing, telecommuting, job retrainingfor displaced workers (Davies, 1996), andsmall business start-ups (Zinger et al., 1996).All of these activities often serve to isolate theindividual worker from the institutional sup-port structures of traditional organizations.Hence, there is greater salience today for im-proving our understanding of the role of socialsupport mechanisms in the emergence of net-Lvorks.

Early research on the role of networks inproviding social support focused on structuralcharacteristics of the networks, such as tiestrength, frequency, reciprocity of the links,the size, and the density of the networks.Walker et al. (1994) noted that recent networkresearch has abandoned the notion of socialsupport as a unitary construct as well as theassumption that the presence of a tie can beequated with the provision of social support.Instead, they model social support as “a com-plex flow of resources among a wide range ofactors rather than as just a transaction betweentwo individuals” (p. 54). Indeed, in a study oflow-income, immigrant women Vega, Kolody,Valle, and Wei r (1991) found tha t t hewomen’s overall frequency of interaction withfriends and family was not correlated withlevels of depression. However, the quality ofsocial support, measured as the frequency ofspecific social support messages, was the bestpredictor of low depression scores among thewomen.

484 + Structure

Theories of Network Evolution:Emergent Versus Emergence

In a special issue of the Journal of Mathe-matical Sociology, “The Evolution of Net-works,” Stokman and Doreian (1996) exam-ined the distinction between the terms net-work dynamics and nehsork evolution. Theyargued that the study of network dynamicsprovides a quantitative or qualitative temporalcharacterization of change, stability, simulta-neity, sequentiality, synchronicity, cyclicality,or randomness in the phenomena being ob-served (Monge B: Kalman, 1996). The focusis on providing sophisticated descriptions ofthe manifest change in networks. In contrast,Stokman and Doreian define the study of net-work evolution to contain an important addi-tional goal: an explicit, theoretically derivedunderstanding of the mechanisms that deter-mine the temporal changes in the phenomenabeing observed. While most of the longitudi-nal network studies reviewed in this chaptercontain theoretical mechanisms to explainchanges over time, many of them could bemore explicit about this connection and movemore in the direction of fully developed theo-ries of network evolution.

In an early example, Fombrun (1986) theo-rized about evolution in terms of infrastruc-tures, sociostructures, and superstructures thatinteracted dynamically with each other acrossorganizational, population, and communitylevels. He identified two dynamically oppos-ing forces that led both to conflict and to even-tual resolution: processes of convergence andprocesses of contradiction. In a more recentexample, Salancik (1995) critiqued the intel-lectual contributions of Burt’s (1992) struc-tural theory of holes. He noted that it was im-portant to acknowledge Burt’s finding that aperson occupying a structural hole will gainpolitical advantage, but he also asserted that‘<a more telling analysis might explain whythe hole exists or vvhy it Lvas not filled before”(Salancik, 1995, p. 349). Salancik challengednetwork researchers to invest efforts in creat-ing a more specific network theory. Such atheory does not take a network as given. In-

stead, it seeks to uncover the mechanisms thatcreate network evolution.

Two of the more comprehensive reviews ofnetwork studies have called for greater atten-tion to the evolution of networks (Brass,1995b; Monge & Eisenberg, 1987). Whileboth were organized around antecedents andoutcomes of networks, they acknowledgedthat such distinctions are often nonexistentand potentially misleading. Monge and Eisen-berg (1987, p. 3 10) offered a hypothetical see-nario to illustrate the ongoing evolution of anetwork, a concept they term reorganizing.Brass (1995b) underscored the importance ofarticulating the dynamic nature of the rela-tionships between networks, their anteced-ents, and outcomes.

Four lines of research emphasize the im-portance of this perspective. The first articu-lated a recursive model of communicationnetworks and media (Contractor & Eisenberg,1990). Drawing on structuration theory(Giddens, 1983) and the theory of structuralaction (Burt, 1982), they proposed that whilenetworks influence individuals’ adoptions,perceptions, and use of new media, this usehas the potential for altering the very net-works that precipitated their use in the firstplace. In some instances, this altered networkhas the potential of subverting individuals’continued use of the media. Hence, the CO-

evolution of communication networks and theactivities they shape are inextricably linkedand must be examined as a duality.

Similarly, Barley (1990) and Haines(1988) have argued for the use of network an-alytic techniques to articulate and extendstructuration theory. Barley (1990) used net-work analytic tools to describe the situatedways in which relatively small role differ-ences in initial conditions reverberatedthrough seemingly similar social systems, re-sulting over time in widely different social

structures. Barley (1990) rejected contingencytheories because they offer static predictionsof a match between technologies and socialstructures. Instead, he argued for using net-works as a way of making explicit the theoryof negotiated order (Fine & Kleinman, 1983).

d&&$.-,~~~~~~~:~~utes of a CT scanner recently adopted in&+~~:.~ two$&.?.

radiology departments affected the~~~~~~~~i~-nonrelational elements of employees’ work.‘T _..__ -\, c;:...g:;;i~<~: _roles, including their skills and tasks; this, in$%$~&’ ‘hm,~~~~~i, - :: : affected their immediate communication;F~~.>“->sr ,x~~~e~:-~;:re]ationships and precipitated more wide-+; .*- -2 ,,$ ,y.i:. . . :.- spread changes in the department’s social net-

work. Significantly, his analysis explains whythe technology was appropriated differently inthe two radiology departments. Barley’s em-pirical work exemplifies several symbolicinteractionists who argue for the importanceof understanding the emergence of social or-der as a process of social construction (Berger&Luckmann, 1966; Giddens, 1976,1984).

From Barley’s (1990) standpoint, networktechniques offer an opportunity to illustratethe ideographic and idiosyncratic nature of or-ganizational phenomena. The ideographic as-sumption reflects an ontological viewpointthat rejects the nomothetic goal of seekinggeneralizable regularities in explaining orga-nizational phenomena. Instead, the goal of theresearcher with an ideographic viewpoint is tounderstand the processes that unfold in the

particular organization being studied. Zackand McKenney (1995) offer a more recent ex-ample of work in this tradition. They exam-ined the appropriation of the same group-authoring and -messaging computer systemby the managing editorial groups of twomorning newspapers owned by the same par-ent corporation. Drawing on Poole and De-Sanctis’ (1990) theory of adaptive structur-ation, they discovered that the two groups’ ap-propriation of the technology, as indexed bytheir communication networks, differed in ac-

cordance with the different contexts at the two


locations. Further, they found evidence thatthe groups’ performance outcomes for similartasks were mediated by these interaction pat-

terns.

to this theory, structures are

such as structuration or negotiated order A second line of research embraces thecentral precept of focusing attention on evolu-tion of networks, but seeks nomothetic, that is,lawful and generalizable, underlying theoreti-cal mechanisms to explain the appearance ofseemingly ideographic, nongeneralizable,surface phenomena (Stokman & Doreian,1996). These authors argue for the develop-ment of computational models that incorpo-rate network mechanisms that both influenceand are influenced by people in the social net-work. This line of research extends recentwork in object-oriented modeling, cellular au-tomata (CA), and neural networks to capturethe ongoing, recursive, and nonlinear mecha-nisms by which organizational networksevolve over time (Abrahamson Sr Rosenkopf,1997; Banks & Carley, 1996; Corman, 1996;McKelvey, 1997; Stokman & Zeggelink,1996; Woelfel, 1993). Banks and Carley(1996) compared three mathematical modelsof network evolution based on social compari-son theory (Heider, 195S), exchange theory(Blau, 1964), and constructuralism (Carley,1990, 1991). They noted that the pattern ofnetwork evolution associated with the threemodels were not always distinct, therebymaking it difficult to empirically validate onemodel over the other. They offer statisticaltests that, at the very least, allow for the falsi-fication of a particular model.

Corman (1996) suggested that multidimen-sional CA models offer insights into the unan-ticipated consequences of collective commu-nication behavior. His computer simulationsof a simplified CA model based, in part, onGiddens’s structuration theory, suggested thatintegrationist strategies by individuals were,unintentionally and perversely, most responsi-ble for segregation in communication -strut-tures.

Zeggelink, Stokman, and Van de Bunt(1996) modeled the likelihood of various con-figurations of friendship networks that mayemerge among an initial set of mutual strang-

486 + Structure

ers. Their stochastic model deployed networkmechanisms of selection and contagion to ex-plain the creation, maintenance, and dissolu-tion of friendship ties among the individuals.The complex specifications of such modelsmake it impossible to mentally construe thelong-term dynamics implied by the models.Further, given the nonlinearities implied bythe mechanisms, these models are often ana-lytically intractable. Hence, researchers usecomputer simulations to help assess thelong-term evolutionary implications of theproposed network mechanisms. For instance,Stokman and Zeggelink (1996) developedsimulations and then empirically tested thenetwork configuration of policy makerscharged with determining the fate of a largefarming cooperative in the Netherlands. Thisresearch (see also Robinson, 1996) is basedon the assumption that ideographic differ-ences in the dynamics of friendship networkscan be adequately explained and stochastic-ally predicted by nomothetic underlying net-work mechanisms.

The use of computer simulations to studythe evolution of networks requires consider-able programming knowledge by researchers.To make these efforts more accessible to alarger community of researchers, Hyatt,Contractor, and Jones (1997) have developedan object-oriented simulation environment,called Blanche (available online at http://www.tec.spcomm.uiuc.edu/blanche.html).Blanche provides an easy user-interface tosupport the specification of mathematicalmodels, execution simulations, and the dy-namic analysis of the network evolution.

A third line of research examines the evo-lution of organizational networks as a func-tion of the stage in an organization’s life cy-cle. Monge and Eisenberg (1987) suggestedthat at early stages organizations are likely tohave structures that are less stable and formal.Building on this suggestion, Brass (1995b)noted that structuration theory would suggestthat these patterns would become more stableand formalized as organizations mature.

A fourth line of research focuses on theemergence of network organizations, such as

strategic alliances, partnerships, and researchconsortia, in lieu of discrete market transac-tions or internal hierarchical arrangements.

Ring and Van de Ven (1992,1994) focused at-tention on the developmental processes ofinterorganizational relations: emergence, eve-lution, and dissolution. They proposed, as aframework for this process, “repetitive se-quences of negotiation, commitment, and exe-cutions stages, each of which is assessed interms of efficiency and equity” (p. 97). Draw-ing on much of the same literature, Larson andStarr (1993) proposed a model to explain theemergence of entrepreneurial organizations.Finally, Topper and Carley (1997) describedthe evolution of a multiorganization networkorganization in a hyperturbulent environment:the integrated crisis management unit networkthat responded to the Exxon Vulde: disaster.

The four streams of research reviewed inthis section share an intellectual commitmentto a better understanding of the situationalevolution of organizational networks. Futureresearch that combines this commitment tosituated evolution with the theoretical mecha-nisms reviewed in this chapter has the poten-tial to significantly extend our knowledge oforganizational communication networks andthe explanatory power of our models and the-ories.

CONCLUSION

This chapter has focused on emergence Ofcommunication networks-their creation,maintenance, and dissolution-within andamong organizations. Ten major families oftheories were reviewed to explore the theo-retical mechanisms that have been used bynetwork scholars to examine these evolution.ary processes in organizational communica-tion networks. Six conclusions seem warranted from this review.

First, the literature reviewed in this chapterfocuses much more on the creation of net-works than their maintenance or dissolution.This imbalance reflects a serious shortcoming

$, current theoretical perspectives and empiri-cal research. Theories that describe conditionsunder which the likelihood of creating net-work links is lower rather than higher must be,xamined more carefully to see if these condi-tions also predict the dissolution of networklinks. The Seabright et al. (1992) research, re-viewed earlier, offers a notable example ofsuch an attempt. Their study found evidencethat reductions in the resource fit between or-ganizations would lead to pressures to dis-solve interorganizational network links.

Second, considerable additional work is re-quired to reduce or eliminate the extensive re-dundancy that exists among the different theo-retical perspectives. For example, as dis-cussed earlier, the theoretical mechanisms inexchange theory and social support theoryshare a great deal in common with each other.Likewise, homophily, which is defined assimilarity of individual characteristics, can beviewed as conceptually overlapping withproximity, which can be viewed as similarityof location. Other examples abound in this re-view. Some of this redundancy stems fromconceptual vagueness, as was mentioned ear-lier with the notion of uncertainty. Other as-pects of redundancy are attributable to the factthat the theories were developed in differentcontexts, as is the case for network organiza-tional forms, which clearly use exchangemechanisms though they emerged out of in-terests in economic markets and transactioncosts. Still another source of overlap is thatdifferent theories were developed in differentdisciplinary traditions, including communica-tion, economics, political science, socialwork, and sociology, to name but a sample.

The third conclusion is that the time mayhave come to explore a mote eclectic, multi-theoretical approach to network theory inwhich several theories are used simulta-neously to predict communication networkbehavior and outcomes. While elimination ofconceptual and theoretical redundancy will bebeneficial, it seems unlikely to produce a gen-eral, integrated theory (and there are thosewho argue in principle that such a feat is im-possible). None of the theories reviewed in

E m e r g e n c e ofCommunication N e t w o r k s + 4 8 7

this chapter, by themselves, seem sufficientlypowerful to explain large portions of the vari-ance in network emergence. Nor do they indi-vidually seem capable of predicting the emer-gence, maintenance, and dissolution of com-munication networks with anything near areasonable level of precision. Consequently,an integrative, multitheoretical alternative ap-pears worth exploring. A multitheoretical ap-proach would use different theories to accountfor different aspects of network phenomena orto account for the same aspects at differentpoints in the evolutionary process. There issome precedence for this strategy in the publicgoods literature, which examines one set ofmechanisms for the creation of public goodsbut an alternative set for their maintenance(Mange et al., 199s).

A fourth conclusion is that it is importantto focus attention on uniquely network formsof communication network theory. This re-view has highlighted the fact that most theo-retical explanations for communication net-works, though not all, stem from nonnetworktheories applied to network phenomena. Moretheoretical effort is required like the work thathelped to develop network exchange theories,structural holes theory, and network evolutiontheories. Wasserman and Pattison (1996) haverecently made important contributions in thisdirection with the development of “p*” mod-els, which explore how the various endoge-nous characteristics of a matrix of network re-lations, together with other exogenous explan-atory variables, shape the outcomes of the net-work.

Fifth, much work needs to be done to de-velop network theories that bridge the expan-sive analytic levels covered by network analy-sis. In one sense, the fact that networks spansuch diverse phenomena and operate on somany levels underscores their importance ineveryday life. On the other hand, these expan-sive and multilevel qualities make theoreticalintegration a very challenging task. Theoriesthat range from internal cognitive social struc-tures to global network organizations makeformidable intellectual leaps that need carefulexamination and theoretical development.

4 8 8 4 S t r u c t u r e

Finding commonalities as well as disjuncturesacross levels will be an important part ofbuilding a more integrated theory of commu-nication networks.

Finally, as the literature reviewed heredemonstrates, the study of emergence in com-munication networks continues to be over-whelmingly influenced by structural perspec-tives. Of the three network traditionsemployed throughout this chapter, the posi-tional and relational traditions continue todominate, while the cultural tradition hasstruggled to bridge the gap between structureand the content of communication networks.The theoretical mechanisms used in networkresearch invest greater currency in the struc-tural relationships among people than on thetypes of network linkages (e.g., material vs.symbolic, product vs. knowledge; see the ear-lier discussion in this chapter) or the contentof the messages within these networks.Wellman (1988) notes that the genesis for thisbias goes back to Georg Simmel’s influenceon the pioneers of network research (e.g.,Simmel, 1955). In fact, Wellman (1988) char-acterizes the early work of an influential mi-nority of formalists (e.g., Fararo, 1973; Hol-land Rr Leinhardt, 1979; Lorrain & White,1971) by asserting that in “concentrating onthe form of network patterns rather than theircontent. . they have shared a Simmelian sen-sibility that similar patterns of ties may havesimilar behavioral consequences no matterwhat the substantive context” (p. 25). Eventhe network studies based on the cultural tra-dition (e.g., semantic networks) are largely fo-cused on structural explanations for the emer-gence of these networks, despite the fact that

they are based on network linkages represent-ing common interpretations. They seek to ex-plain variation in the structure of the semanticnetworks rather than variation in the content(e.g., types of linkages or messages) within

these networks. Missing from the network lit-erature is any systematic theoretical or empiri-cal work aimed at examining the relationshipbetween the structure of networks and thecontent of messages, symbols, and interpreta-

tions that produce and reproduce them.Consequently, we know very little about themanner in which different network configura-tions (e.g., centralized networks, dense net-works) are likely to facilitate the creation ofcertain types of messages (e.g., Sllppofiive

critical). Conversely, little is known abou;how the production and reproduction of cer-tain types of messages or symbols are likely toinfluence the structural emergence of commu-nication networks.

The field of organizational network analy-sis has grown exponentially since the originalchapter on emergent communication net-works was published in the Handbook of Or-ganizational Communication more than a de-cade ago (Monge & Eisenberg, 1987). Thediversity of scholars from various intellectualbackgrounds who are currently developingtheories of communication and other net-works in organizations is truly impressive, asis the high quality of their work. Even moreimportant, as this review has demonstrated, isthe development and application of theoriesand theoretical mechanisms in what once wasa very atheoretical field. There is, of course, agreat deal remaining to be done. But contin-ued work in these theoretical areas, with spe-cial attention to network evolution, promisesto make the years ahead a very exciting timefor organizational communication networkscholars.

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