Networking
Guanxi[1]
Barry Wellman, with Wenhong Chen and Dong Weizhen
March
13, 2001
wellman/wenchen/wdong@chass.utoronto.ca www.chass.utoronto.ca/~wellman
Concluding Chapter in:
Social Networks in China:
Institutions, Culture, and the Changing Nature of Guanxi
Edited by Thomas Gold, Douglas Guthrie and David Wank
Cambridge University Press 2001 guanxi3a.doc
The Social
Network Approach
From Metaphor
to Toolkit
The end of every journey is the beginning of the next
adventure. As my tired eyes rest from reading the chapters in this book and my
exhilarated soul reflects, I think back on the wonders I have encountered and
think ahead about what to do next. As I basked in the pleasure of learning
about guanxi, I started thinking
about how some of the tools of my trade – social network analysis – might help
me and others to delve deeper into guanxi's mysteries.
Yet there is a danger sign along the road, a bit old fashioned
but still worth pondering: The Economist (2000:
7) warns that outsiders may find guanxi an unfathomable “mystical concept”. With the
ironic tone of a jaded old China hand, the magazine asserts: “If you don’t have
the patience to learn about guanxi old
boy, you might as well pack your bags and go home.”
Thrilled by what I’ve learned about guanxi, the last thing I want to do is to go home, warned off by a
claim that newbies can neither understand guanxi nor provide useful advice about studying it.
Reading this book has been a wonderful journey, and I do not want to pack my
intellectual bags just yet.
My intention is to show how some of the toolkit of my
specialty, social network analysis, could lead to new understandings of guanxi, both as a phenomenon in itself
and in relation to other aspects of Chinese societies. This is not just the
case of using an available hammer to fit all nails: The fit between network
analysis and guanxi is tight (see also
Lin forthcoming). Although scholars of guanxi
often talk about “the social network” as a useful, organizing metaphor,
social network analysis – like guanxi
analysis – has developed beyond the metaphor. I deliberately enter what Kipnis
calls “the trap of making guanxi
either `an orientalist gloss for networking’ or an acultural, universal
necessity.”[2] Where area specialists
argue for the particularity of their field, paradigm mongers such as me argue
for the generality of their approach. I join with many of this book’s authors
in belunivieving that social network analysis can provide useful ways to study
both dyadic, two-person guanxi ties, and multi-person guanxi networks.[3] Social network analysis can
help identify more precisely different aspects of guanxi and provide techniques for studying it. Its approach can
help develop the analysis of guanxi
and place it in the perspective of interpersonal relations and exchanges
elsewhere in the world (see the articles in Wellman 1999b). Although China is
different from Western countries, we should be able to use the same tools to
address similar intellectual challenges
Analyzing
Guanxi
This book does both an eloquent job of describing guanxi and raising further questions
about it. The chapters provide much evidence that guanxi is more than the bribery and corruption on which Yang’s
(1994) pathbreaking book and others have focused.[4] Guanxi relationships can reduce uncertainty, lower search and other
transaction costs, provide usable resources, and increase interpersonal
pleasure and a sense of connectedness. They provide informal ways to reduce
environmental uncertainty and opportunistic behavior(Standifird and Marshall
2000). Guanxi networks are flexible, efficient, available, and custom
tailored sources of social capital that are low in financial cost.
Guanxi is a
fundamental web of interpersonal relations permeating Chinese societies that
should not be facilely dichotomized into “bad” bribery relations and “good”
friendship ties. Guanxi forms
multidimensional continua of interpersonal behavior rather than a bad/good
dichotomy. Instead of sniffing at guanxi as a corrupter of rational
bureaucratic procedures or celebrating it as a liberation of human initiative,
analysts can concentrate on its characteristics and contexts. Back doors are
not the only entry points for guanxi.
This book presents a broad view of guanxi by:
1)
Demonstrating that guanxi is prevalent. Until recently, this has
been somewhat a Yes/No debate. As almost always, once you look for something,
you usually find them. The question remains, as Guthrie notes, as to how
prevalent guanxi is and how much it
has changed since the coming of Communism and through the various stages of the
Communist regime. For example, Sik and Wellman (1999) show the persistence of guanxi-like
relationships in Hungary throughout the Communist period – to deal with
bureaucratic rigidities, material scarcities and personal political
insecurities – but also in the post-Communist period – to deal with rapidly
changing markets, transmuting institutions, and personal economic insecurities.
(See also Kipnis.)
2)
Documenting the
characteristics of guanxi relationships.
It provides
evidence about the extent to which guanxi
relationships are:
3) Proposing the
interplay between the behavioral practice of guanxi and internalized norms and values that may be associated with
it. Many authors in this book argue that it is important to distinguish between
guanxi normative feelings (renqing/ganqing) – the sentiment of acting with respect for human feelings
– and guanxi practices – the
supportive behaviors in which people actually engage.[6] There is always a marked
disjunction between how people feel and what they actually do (Deutscher 1973;
Cancian 1975). Situational ethics, opportunities and constraints make
norm/behavior differences inevitable and often unacknowledged – whether among
cadres in China or evangelicals in America. Thus Hwang (1987) argues that renqing
depends on the perceived position of relationships in power structures.
Potter notes that complex social networks makes personal trust more
problematic, as individuals must negotiate contingent, sometimes transitory
relationships rather than rely on the coherent norm enforcement of an all-
encompassing densely-knit group.
Although I note these important issues here, I do not address them in this
article.
4) Showing how privately interpersonal guanxi
operates in conjunction with behavior in public spaces (Farrer), formal
bureaucracies (Bian, Guthrie, Hanser, Kiester, Li, Smart and Smart, Wank, and
Wong and Sun), and the legal system (Potter). The authors amply show that guanxi is best seen as a component of
overall Chinese societies – for example, providing leverage on bureaucracies –
rather than as an isolated system of interpersonal relationships (see also Lin
forthcoming). Potter does this for the legal system, and Smart and Smart
demonstrate how guanxi fits into the
relationships of Hong Kong petty capitalists with businesses in China. Guthrie
strongly argues that people’s positions in Chinese societies affect how they
engage in guanxi. Ties spills
over national borders as overseas Chinese use guanxi to engage in
mainland enterprises (Segal 1999). Guanxi is probably eternal, but I
wonder how did it operate differently in the previous system of bureaucratic
rigidity than in the current system of fluidly, changing norms and
relationships.[7]
5) Demonstrating that guanxi has remained important in
multiple aspects of recent and current Chinese societies (an issue on which all
authors except Guthrie agree; see also Guthrie 1998). As Hanser argues, guanxi can best be seen as part of a
person’s toolkit. Is guanxi is an
asset, to be “banked or deployed as needed to serve the interests of the holder
in the context of a larger institutional system”? (Hanser). Taken jointly, the
chapters in this book show what guanxi does
for individuals, interpersonal ties, social networks, organizations,
institutions, and regional, sectoral, and overall aspects of Chinese societies.
But is it central or peripheral to different arenas of Chinese societies?
The Social
Network Analytic Approach
From Method
and Metaphor to Paradigm and Substance
Social network analysis has moved from a suggestive metaphor to
an analytic paradigm. It conceives of social structure as the patterned
organization of network members and their relationships. Analysis starts with a
set of network members (sometimes
called nodes) and a set of ties that
connect some or all of these nodes. Ties consist of one or more specific relationships, such as kinship, frequent
contact, information flows, conflict or emotional support. The interconnections
of these ties channel resources to specific structural locations in social
systems. The pattern of these relationships --- the social network structure
--- organize systems of exchange, control, dependency, cooperation, and
conflict.
Thinking in network terms leads away from individual-level
research perspectives whose inherently social psychological explanatory bases
see internalized norms driving interpersonal relations. Network analysts reason
from the whole to the part, from structure to tie to individual, from behavior
to attitude. They study how social networks work for individuals, for
relationships, and for social systems. Social network analysts study both
inter-personal ties between people (Wellman 1999a) and inter-organizational
ties between firms, government departments, etc. (e.g., Mizruchi and
Galaskiewicz 1994) and inter-national ties in the world-system (e.g., Breiger
1981). Such larger-scale analyses either collect data at the unit of the
organization or nation, or else use a “network of networks approach” to treat
ties between members of different organizations as ties between the
organizations themselves (Craven and Wellman 1973; Wellman 1988).
A Network Is
Not Always -- Perhaps Not Often – A Group
As Guthrie notes, scholars tend to find what they are looking
for because their approach affects how they frame their questions and research
design. The network approach provides ways to think about social relationships
that are neither groups nor isolated duets. There is no assumption that groups are
the normal building blocks of social systems, nor that the absence of groups is
a deviant aberration. Groups are not privileged by definition; they are
discovered. A group is only a special type of social network, one that is densely-knit (most people are directly
connected) and tightly- bounded (most
relations stay within the same set of people).
Instead of treating officially-defined group or neighborhood
boundaries as truly social boundaries, network analyses trace the social
relationships of persons or institutions,
whomever these relationships are with and wherever they go. In this way,
formal boundaries can be tested to see if they are relevant rather than treated
as a priori analytic constraints. For
example, people who spend much time together -- at work, in the household, in
villages, at markets, in neighborhoods -- can be studied as either a group or a
social network. Those who study them as groups assume that they know the
membership and boundaries of the groups. They might ask how important each
group is to its members, how the groups are governed and make decisions, how
the groups control members, and the circumstances under which members enter and
leave. By contrast, those who treat such entities as social networks can
address membership and boundaries as open questions. Frequent participation in
a friendship circle might be treated as the basis for membership but so might
be the indirect connections (and resource flows) that friends provide to others
outside the circle. The pattern of relationships becomes a research question
rather than a given.
This empirical approach to dealing with groups should be useful
for studying guanxi. China, like much
of the world, is experiencing a paradigm shift, not only in the way people
perceive society, but even more in the way in which people and institutions are
connected. It is the shift from living in “little boxes”[8] to living in networked
societies. Members of group-oriented little-box
societies deal only with fellow members of the few groups to which they
belong: at home, in the neighborhood, at work, or in voluntary organizations.
They belong to a discrete work group in a single organization; they live in a
household in a neighborhood; they belong to a kinship group (one each for
themselves and their spouse) and to discrete organizations: professional
associations, neighborhood groups, and the like. All of these appear to be
bodies with precise boundaries for inclusion (and therefore exclusion). Each
has an internal organization that is often hierarchically structured:
supervisors and employees, parents and children, party leader, cadre and local
resident; union leader and proletariat. In such a society, each interaction is
in its place: one group at a time. To oversimplify on purpose, this was the standard
description of China before the Dengist turn to a market society.
A key meta-story of this book is the shift in China from a
group-based to a network-based society (see also Gold 1998; Lin forthcoming).
This Chinese experience is far from unique. Throughout the Western developed
world and in much of the less developed world, a network society has come into
being. In such societies, boundaries are more permeable, interactions are with
diverse others, linkages switch between multiple networks, and hierarchies
(when they exist) are flatter and more recursive. The change from groups to
networks can be seen at many levels. Trading and political blocs have lost
their monolithic character in the world system. Organizations form complex
networks of alliance and exchange rather than cartels, and workers (especially
professionals, technical workers, and managers) report to multiple peers and
superiors. Management by network is replacing management by (two-way) matrix as
well as management by hierarchal trees (Berkowitz 1982; Wellman 1988, Castells
1996). The Western developed world – and perhaps Chinese societies – have seen
the rise of “networked individualism”:
Individuals, – and not groups, kinship units, or households – are the key
interpersonal units. Yet individuals are rarely isolated in “lonely crowds” (as
Reisman mistakenly thought, 1950). They are more likely to have partial,
changing ties to multiple social networks (Wellman 2001).
To be sure, Chinese societies – as others – have densely-knit,
tightly-bounded, publicly- functioning work groups and community groups. Yet
the chapters by Bian, Farrer, Hsing, Smart and Smart, and Wilson show
sparsely-knit, loosely-bounded work and community networks, with only a
minority of members directly connected with one other. Even when Farrer shows
the persistence of public neighborhood networks in Shanghai, he makes it clear
that this is one among multiple, partial networks. Hsing shows cadres near
Shanghai manipulating their local and long-distance ties, and Wank notes how
Fujianese entrepreneurs deliberately created long-distance business ties. Other
research has described how the technocratic graduates of Qinghua University
help each other move upwards in their business and political careers (Cheng
1994). Such relationships often ramify out in many directions like an expanding
spider's web rather than curling back on themselves into a densely-knit tangle.
It is a “glocalized” situation,
showing the interplay of local involvements and long-distance connectivity (Wellman
and Hampton 1999).
The social network approach can be applied to a wide range of
social structures. For example, the approach is able to discover densely-knit
communities in which almost all community members have a wide range of
relationships with each other (e.g., Hinton 1966) as well as the rational
bureaucratic organizations that Guthrie describes. But the social network
approach especially affords the discovery of other forms of guanxi networks — perhaps sparsely-knit
and spatially-dispersed — and other forms of organization — perhaps
loosely-coupled or virtual (Koku, Nazer and Wellman 2001). Hence it can help to
describe and analyze the operation of guanxi
as it complements and supplements bureaucratic and formally legal
interactions. Instead of an either/or distinction between group membership and
social isolation, analysts can study a more diversified set of phenomena, such
as:
· The density and clustering of a guanxi network
· How tightly bounded a network is
· Which kinds of people occupy similar roles
· Whether a guanxi network is variegated or constricted in its size and heterogeneity
· How narrowly specialized or broadly multiplex are its relationships
· How indirect connections and structural positions affect behavior
·
How
patterns of connectivity and cleavage channel supportive resources
·
The
ways in which people and organizations are indirectly connected
The self-conscious, relatively coherent development of social
network analysis began in the 1960s (Wellman 1988, 2000). In the past decade,
doing social network research has become easier. Information for analysis may
be gathered through ethnographic field work, survey research, or archival
analysis (finding for example, investment patterns between enterprises; e.g.,
Mintz and Schwartz 1985). Although network analysts often think about networks
as graphs (in which the points represent persons and the lines ties between
them), they usually manipulate matrices to analyze the networks (Figure 1).
They use a variety of statistical and mathematical techniques to tease out
selected underlying structural properties of the social system. Network
analysts currently have three journals, a professional society, and an annual
meeting. They are active in all social science disciplines, mathematics and
statistics.[9]
Whole Networks
Patterns of
Connectivity and Cleavage
Whole network analyses describe the comprehensive structure of
role relationships in an entire social system, be it a village, a region, an
enterprise, a set of enterprises (e.g., the steel industry), or linkages
between institutions (e.g., enterprises and bureaucracies). Such analyses
provide simultaneous views of the social system as a whole and of the parts
that make up the system. They often map social systems, asking, for example, if
the systems are socially integrated or if there is an empirically-identifiable
ruling bloc.
> Figure 1: Graphical and
Matrix Representation of a Network
One straightforward approach to studying whole networks is to find who
in a population is directly connected with whom. Researchers are able to trace
lateral and vertical flows of information, identify senders and receivers of
resources, and detect structural constraints (such as decouplings and the
shapes of networks) operating on flows of resources. Analysts often want to
discover densely- connected clusters
of network members in which most network members are directly connected, and
the extreme case of cliques, in which
all network members directly connected. Finding clusters and cliques can
empirically discover groups whose members cooperate extensively with each other
and develop collective identities. Because of the dense interconnectivity
within a cluster, resources are often conserved and social control tends to be
active. Yet extensive within-cluster involvement can also mean few ties to
outside the cluster. As a result, those in densely-knit clusters may have
difficulties acquiring new information, goods and other resources from
outsiders. They may also lack the external ties necessarily for forming coalitions
with others to deal with difficulties or opportunities.
Consider, for example, the situation of overseas Chinese in
Toronto. As in other ethnic enclaves, strong ties among members of the Chinese
community often are important for successful business start-ups (Portes 1993).
These ties tend to develop into densely-knit clusters. However, those business
people who also have networks outside of the Chinese community tend to have
higher income levels (Ooka 2001; see also Ooka and Wellman 2001).
Structurally
Equivalent Role Relationships
The hiring practices of many Chinese family businesses show
"structural equivalence" (Wasserman and Faust 1992) Key positions at
higher levels are often occupied by close relatives or friends (Kao 1990; Tsui
and Farh 1997). Different kin are seen as equivalent in their relationship to
the owners.
But structurally equivalent people do not actually have to be
related to each other if they occupy similar positions. In the 1980s,
Toronto-Chinese sociologist Li Fan asked the residents of an Inner Mongolian
town to report who provided resources to each other: gifts, information and the
like. He was then able to use the network analytic technique of blockmodeling (White, Boorman and
Breiger 1976; Arabie, Boorman and Leavitt 1978) to identify the town’s elite.
Instead of looking for clusters of densely- connected people -- the usual
approach to elite studies in China and elsewhere -- Li looked for patterns of
role relationships. He manipulated data matrices to identify which townspeople
had similar patterns of exchanging resources. The UCINet computer program
placed people with such similar patterns in the same “block”. It demonstrated
substantial differences in structural position according to both ethnicity and
organizational position. For example, one elite block consisted of people who
received gifts from members of other (analytically-constructed blocks) but only
exchanged gifts among each other. To be sure, this substantial effort in data
collection and analysis revealed party cadres and different ethnic groups to be
in distinct positions -- not startling findings for the time. But this finding
was made inductively -- by studying exchanges of resources -- and not by
deductively assuming that cadres were the elites. Moreover the analysis sorted
the other residents into several blocks, reflecting their position in the
town’s social structure.[10]
Although Li’s actual blockmodel is not available now, Nazer’s
(2000) blockmodel of a scholarly network provides a good illustration of the
approach. Although the core elite members of Block I are not necessarily in
direct contact with each other, they seek advice from other Block I members
and, to a lesser extent, from the members of the other elite group in Block II.[11] Symmetrically, Block II
members principally seek advice only from each other, and to a lesser extent
from the members of Block I and one member of Block III. The blockmodel shows
that Blocks I and II are two distinct social circles that have some
advice-seeking connections with each other. By contrast, Blocks III and IV are
more isolated because their disciplines are peripheral to the interests of the
core. Only one of the members of Block III (Smith) seeks advice from anyone,
and the two members of Block IV mainly seek advice from each other.
> Table 1: Blockmodel
<
Indirect Ties
Between Persons and Organizations
Not only do ties link people
and ties link organizations, ties also link people to organizations. People’s
membership in organizations can be treated as affiliation networks and analyzed just like interpersonal networks
(Wasserman and Faust 1994) . For example, identifying which persons belong to
the same or similar organizations can help to discover the gathering places for
elites (or dissidents). Indeed, the U.S. Federal Bureau of Investigation (FBI)
uses a similar technique for conspiracy cases (Davis 1981).
There is a duality of persons and organizations (Breiger 1974).
Just as people belong to organizations, organizations belong to people. If two
persons belong to the same organization, they are indirectly linked to each
other through their joint membership. Similarly, if a person belongs to two
organizations, the two organizations are indirectly linked to each other
(Figure 2). Matrix multiplication (using UCINet or other software) makes it
easy to discover this -- and other -- indirect ties. For example, North
American studies have shown how elites are connected through organizations in a
"network of networks", and how organizations are connected when board
members are involved in multiple organizations (e.g., Mintz and Schwartz 1985;
Carrington 1981; Richardson 1987).
> Figure 2: A Network of
Networks: From an Interpersonal to an Interorganizational Network
Such analyses are obviously possible for Chinese societies when
membership lists are available. They give additional ways to study the business
and political relationships investigated by Keister and by Wank (see also
Guthrie 1998; Wank 1999). Both within-network centrality and inter-network
connectivity affect the market positions of Chinese businesses (Keister
2000).Yet analyses of indirect connectivity do not have to be limited to
elites. For example, Mark Chapman (forthcoming) is currently studying how
various evangelical Canadian church groups are connected, and David Tindall
(1993) has analyzed links among ecologically-friendly (“tree-hugger”) social
movements in British Columbia, Canada. Factory workers (e.g., Walder 1986) and
small businesspeople (e.g., Hsing; Smart and Smart) are apt subjects for such
analyses.
Indirect ties are also vital for the study of the spread of
information and other phenomena (Rogers 1983; Valente 1995): How fast does a
rumor about political events in Beijing or a Tibetan town spread? How quickly
and to whom does a computer or biological virus disseminate? Are there biases
in the spread of such information so that people in certain social network
positions are more apt to acquire the information (or virus) more quickly? Does
the information eventually spread throughout the entire society, as when
Milgram (1967) suggested that the entire world is connected by six or fewer
ties? Or does socially-structured “decoupling” limits universal connectivity
and concomitant spread of information. For example, not everyone in a school
population is chosen as a “friend” or hears all rumors (Rapoport 1979).
Personal
Networks
Suppose we are interested in which kinds of people get
information about jobs, get emotional support, get help with building a home,
or get useful business information from friends. In such cases, we are
interested in the ties of each person in a population (or a sample of that
population). Hence social network analysts often study personal networks rather than whole networks -- that is the network
of Wang, Hsung or Li -- rather than
their village or workgroup (e.g., Hwang 1987). Although the personal network
approach does not provide information about the structure of the overall social
system, it does show how different types of relationships --- kin or friend,
strong or weak, local or distant --- affect the flow of guanxi resources to the focal
person at the center of each network.[12] Figure 3, for example,
shows the significant interpersonal ties of a typical North American (drawn
from Wellman and Wortley 1990). She is directly linked with each network member
(by definition), and many network members are also significantly tied with each
other. She has a densely-knit cluster of kin — three of whom are her
socially-close intimates — and more
sparsely-knit relations among a half- dozen friends and neighbors. One workmate
stands apart, his isolation reflecting a separation of work and social life in
this focal person’s life.
> Figure 3: A Typical
North American Personal Network <
There are analytic and epistemological reasons for studying
personal networks (see also Hsung 1998). The personal network approach avoids
the problem of a predetermined population boundary. For example, how do you
deal with guanxi as a long-distance
phenomenon (Hsing’s and Wilson’s concerns in this book) if you limit your
analysis only to neighborhood or within-city relationships? Moreover, whole
network analyses are not always methodologically feasible or analytically
appropriate because such analyses must define the boundaries of a population,
compile a list of all the members of this population, and collect a list of all
the direct ties (of the sort the analyst is interested in) between the members
of this population (Laumann, Marsden and Prensky 1983). Indeed, as Hsing’s and
Lin’s accounts of the local and long-distance relationships of entrepreneurs
and villagers show, attempts to impose improper boundaries may lead to analytic
confusion. Yet it was common for
earlier generations of community sociologists in many countries to ignore non-
neighborhood friendships and so declare --- wrongly --- that urbanites are
lonely and isolated (e.g., Stein 1960; see the reviews in Wellman and Leighton
1979; Wellman 1999a).
Personal network studies have documented the pervasiveness and
importance of connectivity in Western developed and less developed societies,
thereby rebutting mass society contentions (Kornhauser 1959) that
development-driven social transformations have produced isolation and
alienation. Community, network analysts argue, has rarely disappeared from
societies. It has been transformed into new forms, with guanxi-like relationships continuing in abundance and vitality even
as they have been affected by capitalism, socialism, urbanization,
industrialization, bureaucratization, and new transportation and communication
technology. Numerous scholars have described how networks link individuals
through strong and weak ties, situate them in large social systems, and affect
flows of resources to and from them (reviewed in Wellman 1999a). Similarly, the chapters in this book show an abundance
of long-distance ties as workers seek jobs (Bian, Hanser, Kiester, Wilson),
farmers seek markets (Hsing, Smart and Smart), and husbands seek wives
(Kipnis). Rather than finding self-contained “little boxes,” the authors in
this book reveal complex webs of relationships, often stretching over
substantial differences and ramifying out to connect multiple social circles.
Studying
Personal Networks
Conceptualizing a
person’s network as the central node linking together complex interpersonal
relationships leads to quite different analytic concerns than focusing on
membership in a single, discrete solidarity. It liberates analysts from
searching only for vestigial traditional solidarities hanging on in changing
societies. Rather than looking to see if what they find measures up to the
traditional ideal of densely-knit, tightly-bounded, broadly-based solidarities,
analysts can evaluate the ways in which different kinds of social structural
patterns affect flows of guanxi
resources to network members.
Personal network studies mesh well with survey techniques.
Researchers interview a sample of respondents, asking them to enumerate the
personal and relational characteristics of each member of their network. As the
average size of a network in the Western developed world contains more than
1,000 people, generally only the 5-30 strongest ties are studied (see Kochen
1989; Wellman 1999a). To measure network density, they typically ask the focal
persons in their samples to report about relationships among the members of
their networks.
Analysts tend to study the
personal networks’:
·
Composition: the attributes of network
members (e.g., is the network homogeneous or heterogeneous; primarily composed
of women or men?)
·
Ties: the attributes of ties
connecting network members to the “focal person” (or Ego) of each personal
network (e.g., which ties are strong, in frequent contact, between kin?)
·
Contents: (e.g., who provides job
information or emotional support?)
·
Structure (e.g., is the personal
network densely or sparsely-knit; is it better suited for conserving and
controlling resources, or for exchanging resources with other social circles?)
Yet, looking at guanxi only in personal networks does
have its costs:
·
It
concentrates on strong ties — and sometimes only on strong, supportive ties — neglecting the weaker
ties that can transmit new information between groups and integrate social
systems (Granovetter 1973, 1982, 1995).
· It ignores the ecological juxtapositions with which all people must deal in their residential and social spaces. Even if they are not in a person’s network, rapacious politicians may affect the society in which one is embedded, and vigilant residents may make one’s neighborhood safe.
· Analyzing the network structure of each personal network is procedurally difficult. This is because software for social network analysis such as UCINet is designed to analyze only one network at a time. Although each personal network can be treated as a whole network, the lack of provision for batch processing means that the data-crunching of hundreds of personal networks must be undertaken one at a time.
· In a sample survey of any size, interviewing the members of a person’s network is impractical because such an approach would increase the sample size enormously. (For example, a sample of 300 persons – each linked with an average of 20 network members – would require 6,000 interviews.) Hence personal network studies usually rely on surveyed respondents’ reports about their network members. This hinders reliability (Bernard, et al. 1984) although no more so than the respondents’ reports about other aspects of their behavior. The least reliable and valid survey data are the respondents’ reports about the nature of the relationships among the members of their personal networks. Many people just do not know how Cousin Wong feels about Great Aunt Lee.
Differentiated
Ties
Three basic issues that arise in unbundling guanxi and analyzing specific types of
supportive relationships are:
1. Which kinds of guanxi are often conveyed in the same ties?
Wong and Sun show that social networks provide the basis for interpersonal
social capital, what my group has called “network
capital” (Sik and Wellman 1999;
Wellman and Frank 2001; see also Bian’s and Lin’s chapters).[13] The term is an apt one for this book, with its concentration on
relations of work and entrepreneurship. Yet the authors also make it clear that
guanxi comprehends a variety of
supportive relationships: providing emotional support, helping neighbors,
relatives and friends; gossiping about neighbors; and providing a sense of
belonging. Farrer, Smart and Smart, and Wilson make such relationships their
focus. As Li notes, analysts cannot assume that all ties provide all types of guanxi. In the Western developed world,
different types of ties provide different kinds of resources (Wellman 1999a),
and guanxi analysts should leave open
this possibility in Chinese societies (Lin forthcoming).
Are the people who help someone find a job the same people who
provide emotional support or help with care for the elderly, children, and the
infirm? Is guanxi support broadly
available in a tie, or do different types of ties provide different kinds of
support? This is a matter for both ethnographic observation and quantitative
analysis using factor and cluster analyses (Hall and Wellman 1985; Wellman and
Hiscott 1985; Wellman and Wortley 1989). Both Hsung and Ruan and their
associates show important commonalities and differences between Chinese and
Western societies in this regard (Hsung and Lin 1995; Hsung 1998; Ruan et al.,
1997; Ruan and Zhang 2000; Ruan forthcoming). In Toronto, our group has found
that active network members usually supply only one or two out of the five
types of social support, for example, small services and emotional aid but not
large services, companionship or financial aid. By contrast, Toronto spouses
supply each other with all types of social support (Wellman and Wellman 1992).
Those network members who provide small services or emotional aid rarely
provide large services, companionship or financial aid (Wellman, Carrington and
Hall 1988; Wellman and Wortley 1989; Wellman and Wortley 1990).
2. Which types of dyadic (interpersonal) relationships tend to provide
what kinds of guanxi? If guanxi
support is specialized, then it is likely that such specialization is
associated with different types of ties. Because personal networks rarely
operate as solidarities, people cannot count on all the people in their network
to leap in and provide needed help. Hence the provision of network capital
partially depends on the social characteristics of network members and the
kinds of relationships they have with the person whose network they "belong"
to.
The dyadic tie between two persons is at least as important as
the network and milieu in which it is embedded (Wellman 2001; Wellman and Frank
2001). This is a major change from preindustrial society where a wide range of
support tended to be available from all sorts of kinfolk and neighbors
(Poggioli 1975). In contemporary France, kin and neighbors engage in mutual
aid, but friends and neighbors are the confidants (Ferrand, Mounier and Degenne
1999). By contrast, in Toronto, parents and adult children provide the widest
range of support although they rarely supply sociable companionship. Accessible
ties — people living or working near-by, or otherwise in frequent in- person or
telecommunications contact — provide important goods and services (Wellman and Wortley
1990: Wellman and Frank 2001). The strength of ties is important, with
socially-close voluntary and multiple-role ties providing high levels of
support. Yet Granovetter (1973, 1982) has cogently argued the importance of
weak ties for linking sparsely-knit communities and providing people with a
wider range of information.
Many of the chapters in this book look at how specific kinds of
relationships provide specific kinds of support, but there could be more
analysis of which types of relationships occur under what kinds of situations.
Do similar types relationships provide similar kinds of support in Chinese and
Western developed societies (Ruan and Zhang 2000)? Another comparison would be
with other East Asian societies. For example, interpersonal relations in Japan
appear to be similar to those in Western societies (Otani 1999; Nozawa 1999).
3. Which sorts of network structures tend to provide what kinds of
guanxi? Chinese scholars know even better than Hillary Clinton (1996)
that it “takes a village to raise a child”. More accurately, it takes a
network. As Gold, Hanser and Li emphasize, guanxi
comes from networks as well as from two-person ties. There is more to
interpersonal life than just individuals and their one-to-one ties. People are
often immersed in milieus filled with companionship, emotional support or
caring for others whose dynamics go beyond the level of the individual alter or
tie. There may be group pressures to provide or withhold certain kinds of
support. There may be differential access to resources, with some networks
better structured than others to hear about problems, mobilize internal
resources or access external resources. Yet as Li notes, “Despite wide
recognition of guanxi as [the] nexus
of multilateral social networks, dyadic interaction remains the focus of
analytic attention.”
There is an interplay between the dyadic relationship and the
multiperson network. The specialized provision of support – in the Western
developed world and perhaps in Chinese societies – means that people must
maintain differentiated portfolios of ties to obtain a variety of resources.
They can no longer assume that any or all of their relationships will help
them, no matter what is the problem. In market terms, people must shop at
specialized stores for needed resources instead of casually dropping in at a
general store. This means that people who only have a few network members
supplying one kind of guanxi have
insecure sources of supply. If the relationship ends — if the boutique closes
— the supply of that particular type of
guanxi may disappear.
At the network level of analysis, social network researchers
look at the composition of the
networks (e.g., network size, network heterogeneity, mean frequency of contact,
the percent who are friends) and the structure
of these networks (e.g., density of links among alters). Such analyses seek to
understand how the properties of networks affect what happens in them (and to
them). Which attributes of networks tend to occur together? For example, are
densely-knit networks more supportive, more controlling, or both? The size and
heterogeneity of a network (its “range”) affect its members’ access to
resources (Haines and Hurlbert 1992; Burt 1983, 1992). Heterogeneous networks –
having a variety of network member with different characteristics – and
networks with more socioeconomic resources can better mobilize supportive
network capital (Lin 2000).
Nor is it only a question of whether the characteristics of the
network, the tie, or the alter independently affect the availability of network
capital. Kin may be called on for support when they are enmeshed in
densely-knit networks, and adult sons are more likely to aid their elderly
parents when there are not any adult daughters available (Stone, Rosenthal and
Connidis 1998). People navigate nimbly through partial involvements in multiple
networks, as members of these networks they are subject to the networks’
constraints and opportunities. For example, the helpfulness of ties for job
searches is enhanced by membership in resource-rich networks (Bian 1994, 1997;
Hsung and Lin 1996; Lai, Lin and Leung 1998; Lin and Bian 1991).
Instead of total involvement in a single solidary community,
the personal mobility and connectivity that are the hallmarks of the industrial
and information ages have replaced solidarity with cosmopolitanism. People move
through partial specialized involvements with multiple sets of network members.
Interactions with network members are between two single people or two couples,
or small, informal get-togethers of friends and relatives. These are not
simple, homogenous strictures but complex compositions and sparsely-knit
structures. Most interactions are not in public places, but tucked away in
private homes or telecommunications. Relationships are not permanent: Even
socially-close ties are often replaced within a decade (Wellman, et al. 1997).
Rather than each network member providing a broad spectrum of support, people
get specialized support from a variety of ties (Wellman 1999a, 2001).
Does this depiction apply in whole or in part to Chinese
societies as well as to Western societies? The matter is well worth examining,
rather than assuming that Chinese exceptionalism. Certainly, Farrer shows the
persistence of public, supportive and controlling sociability in a Shanghai
neighborhood, and Hanser, Hsing, Smart and Smart, and Wilson show Chinese
networks that extend well beyond neighbourhoods provide guanxi in sparsely-knit, loosely-bounded, frequently-changing
networks. Indeed, migration and trade globalizes guanxi, as emigrants move from Hong Kong and China to Canada and Australia (Wong and
Salaff 1998; Salaff, Fong and Wong 1999; Dong and Salaff 2000), and overseas
Chinese use the resulting complex networks (Li 2000).
A Multi-Level
Approach
Until very recently, the theoretical understanding of the
network basis of support/guanxi went
far beyond the methodological grasp of social network analysts, constrained by
their methodological inability to integrate analytic levels into a comprehensive
analysis. Technical incompatibilities largely led individual, tie, network, and
interactive analyses to develop separately.[14] Quantitative analysts
examined separately the effects of either individual characteristics, ties, or
the personal networks in which they are embedded. Because many statistical
techniques assume independence between units of analysis, they cannot focus
simultaneously on different units of analysis. Yet the availability of guanxi may well be affected by
individual “agency” (self-organized actions on one’s own behalf), ties dancing
interpersonal duets, and the constraints and opportunities provided by networks
with different sorts of structure and composition. Not only do people need –
and want – to know which kinds of people (an individual-level analysis) and
relationships (a tie-level analysis) are apt to provide different kinds of guanxi, they also need and want to know
the extent to which their social networks as a whole can provide guanxi (a network-level analysis).
To analyze such matters, multi-level
analysis integrates “nested data” into a single statistical model, such as
occurs with residents in neighborhoods, children in schools, nation-states in
world- systems, or, as here, individuals and ties in personal networks (e.g.,
Sampson in press; Thomése and van Tilburg 1998; van Duijn, van Busschbach and
Snijders 1999; Wellman and Frank 2001). “Multi- level or hierarchical linear
models explicitly take into account the nested data and the related dependency
structure by incorporating unexplained variables between ties . . . and also
between egos” (van Duijn, van
Busschbach and Snijders 1999: 188).
As multi-level analysis goes beyond a single focus on the
effects of either individual, tie, or network properties on behavior, it
engages with the basic social scientific question of emergent properties. Is guanxi
related only to the characteristics of individuals or ties, or is it also
related to the characteristics of the personal networks in which these ties are
embedded? Does one also have to take into account the characteristics of all
network members – will women be more supportive in networks filled with women?
– and the social structures in which their ties are embedded – will people be more supportive in densely-knit networks?
Are “structural holes” (Burt 1992) – regions of thin connections – as important
as densely-knit connectivity for successfully acquiring and controlling
resources? Bian shows that having trusted informants and controlling access to
information is important for getting desired jobs (see also Bian 1999), and
Hsing demonstrates that cadres need maneuvering room to operate their local and
long-distance ties.
Our group’s Canadian research suggests that all levels are
contingently important for the provision of support. For example, while ties
with immediate kin (parents - adult children) are especially supportive, these
ties are even more supportive when they are located in networks containing
several other immediate kin (Wellman and Frank 2001). The dynamics of the whole
are more than the sum of the parts. an accurate way for representing the
contemporary network world in which phenomena are inherently multi-level.
A Network
Society
Our group's findings fit the nature of loosely-coupled
communities and organizations that are not enveloping, binding solidarities.
The authors of this book have convinced me that this is as true in China as it
is in Canada. Their chapters all portray a significant shift from bureaucratic
power to market power (see also Nee 1996; Keister 2000). Both bureaucracies and
markets entail social networks to operate. Social network analysis provides
analytic tools to move the debate about state power and entrepreneurial markets
beyond an either/or discussion. Bureaucracies need interpersonal work-arounds
to avoid rigidities (Sik and Wellman 1999) and to make sure that high-status
people get “properly” treated. Markets need the social stability and
trust-enhancing qualities of interpersonal ties (Cohen 1969; Fong and Dong
1999; White 1981). This suggests that, contra Guthrie, guanxi will flourish in China’s evolving market society.
Interpersonally, in China as well as the Western world, people
are members of multiple networks, and they enact specific ties and networks on
an hourly, daily, monthly and yearly basis. They invest in close ties with
immediate kin and good friends, rather than in weaker ties with neighbors and
workmates. They can – and do – change ties and networks in response to
opportunities, difficulties and changes in their personal and household
situations. Rather than being externally imposed by social control, ties are
valued for what they can do instrumentally as well as enjoyed as sociable ends
in themselves. (Gold 1985; Wellman, et al. 1997, Wellman 1999a, 2001).
Under these circumstances, network phenomena can only be
facilitating and partially constraining – and rarely dominating or controlling.
Even though people no longer inhabit solidary groups, they do not function
alone. Even though personal networks are fragmentary and loosely- coupled,
support is given to clusters within a network as well as to an ego. Ties do not
operate in isolation. Ties contribute to networks; networks encourage and
potentiate ties. The guanxi
relationship is social in another sense. Support is often given for the general
benefit of a household or a network rather than for the specific benefit of the
individual. Just as investment is not just zero- sum but builds a fund of
capital, guanxi can also contribute
to the network of which both are members. The network’s provision of guanxi adds to the fund of network
capital circulating in a community as well as benefiting the individual. Guanxi is rarely a zero-sum game.
In the west, the network society is changing. In the twentieth
century, household-based networks supplanted village solidarities. At present,
there is a shift towards networked
individualism, with the consequent weakening of within-household (and
within-single workgroup) ties. This shift is associated with changing marriage
patterns, increased geographical mobility, and individually- oriented
communication technologies such as the mobile phone and personal computer
(Wellman 2001). It is probable that Hong Kong, Singapore, and Taiwan are
undergoing similar shifts
The authors of this book have shown that the situation in
mainland China is, as always, more complex – with intertwined social and
geographical regions of stability and mobility. Even as the government attempts
to control the Internet, millions of Chinese are using it to maintain existing
ties, establish new ones, chat in groups, link with the disapora, search for
information about jobs, politics, and other matters, and even organize protests
and social movements (Economist 2001; see also Sheff's [2001] account of
Internet growth). It will be interesting to see whether and how the Internet
helps to transform the social networks of China that are now often locked in
small groups, especially work organizations (danwei) and neighborhoods (juweihui).
Will its potential for less-controlled, less-bounded information and
communication promote physical and social mobility? Will it develop voluntary
associations that transcend "little boxes" and foster new forms of
civic society.
I believe that social network analysis – in combination with
multi-level analysis – can contribute to theory, as well as to method and
substance in understanding social support in general and guanxi in particular. It is an intriguing prospect. As a child of
American cultural stereotypes, I grew up believing China to be a land of
isolated, broadly-supportive, “little-box”, village solidarities, as described
before World War II by Pearl Buck’s The
Good Earth (1930), updated for the revolutionary Communist era by Hinton's Fanshen (1966). The story is continued
in this book by Wilson and, in transition, by Kipnis. My young adult life in
the sixties and seventies was filled with pictures of massed ranks waving
little red books – the isolated individual engulfed by the state. This book
provides abundant convincing detail that Chinese society is not composed of
either little boxes or isolated individuals. It gives us another picture, one
that is closer to current Western experience: It shows people spinning,
manipulating, using, and by networks of guanxi.
The authors have ensnared me in their exciting web.
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Table 1: Blockmodel of
Seeking Advice
|
|
|
|
I |
II |
III |
IV |
||||||||||||
|
|
|
|
|
|
1 |
1 |
|
1 |
|
|
1 |
1 |
|
1 |
1 |
|
|
|
|
|
|
|
1 |
2 |
5 |
0 |
9 |
2 |
3 |
8 |
3 |
6 |
7 |
4 |
1 |
4 |
5 |
6 |
|
|
|
|
M |
A |
B |
C |
H |
S |
G |
S |
D |
G |
S |
O |
H |
M |
J |
W |
|
|
1 |
Mann |
|
1 |
|
1 |
1 |
|
|
1 |
|
|
|
|
|
|
|
|
|
|
2 |
Applebaum |
|
|
|
|
1 |
|
|
|
|
|
|
1 |
|
|
|
|
|
I |
15 |
Brown |
1 |
|
|
1 |
1 |
|
|
|
|
1 |
|
|
|
|
|
|
|
|
10 |
Cook |
1 |
|
1 |
|
1 |
|
|
|
|
|
1 |
|
|
|
|
|
|
|
9 |
Hart |
1 |
1 |
1 |
1 |
|
|
|
1 |
|
1 |
1 |
|
|
|
|
|
|
|
12 |
Scott |
|
|
1 |
|
|
|
1 |
1 |
1 |
1 |
|
|
|
|
|
|
|
|
3 |
Green |
|
|
1 |
|
|
1 |
|
1 |
|
1 |
|
|
|
|
|
|
|
II |
8 |
Stone |
|
|
|
|
1 |
1 |
1 |
|
1 |
1 |
1 |
|
|
|
|
|
|
|
13 |
Demore |
|
|
|
|
|
|
|
1 |
|
|
|
|
|
|
|
|
|
|
16 |
Grey |
|
|
1 |
|
|
|
1 |
1 |
|
|
1 |
|
|
|
|
|
|
|
7 |
Smith |
|
1 |
|
|
|
|
1 |
1 |
|
1 |
|
1 |
1 |
1 |
1 |
|
|
|
14 |
Oldfield |
|
1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
|
III |
11 |
Hopkins |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
4 |
Martins |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
IV |
5 |
Jones |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
|
6 |
Wood |
|
|
|
|
|
|
|
|
|
|
1 |
1 |
|
|
1 |
|
|
R2
= 0 Overall Network Density = 0.24 Standard Deviation within Blocks = 0.43
Source:
Nazer (2000) Table 4.4. All names are pseudonyms.
Figure 1: Graphical and Matrix
Representation of a Network
Copyright © Barry
Wellman 1988
Figure 2: A Network of Networks:
From
Interpersonal to Interorganizational Network
Copyright © Barry
Wellman 1988
Figure 3: Typical North American
Network