Emerging Trends in The Social and Behavioral Sciences

Visualizing Globalization

Item

Title

Visualizing Globalization

Author

Mahutga, Matthew C.

Nash‐Parkera, Robert

Research Area

Social Processes

Topic

Globalization

Abstract

This essay reviews current approaches to visualizing globalization. We give special attention to relational data‐analytic approaches that implement social network analysis and geographic information systems, and emphasize the social structure of globalization as revealed in cross‐national and city‐to‐city relations. Cross‐national relations include international trade, comemberships in international governmental organization (IGO) and international nongovernmental organization (INGO), and other kinds of cross‐national relations. City‐to‐city relations include air‐passenger flows, transnational corporation (TNC) headquarter–subsidiary relations, among others. We conclude by discussing future directions in visualizing globalization. The analytical frontier in visualizing globalization lies squarely in statistical/model‐based approaches to spatial and social network analysis. While these analytical approaches hold much promise for visualizing globalization, the dearth of geocoded subnational relational data and the complexity inherent to modeling them create significant obstacles.

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Identifier

etrds0379

extracted text

Visualizing Globalization
MATTHEW C. MAHUTGA and ROBERT NASH-PARKER

Abstract
This essay reviews current approaches to visualizing globalization. We give
special attention to relational data-analytic approaches that implement social
network analysis and geographic information systems, and emphasize the social
structure of globalization as revealed in cross-national and city-to-city relations.
Cross-national relations include international trade, comemberships in international
governmental organization (IGO) and international nongovernmental organization
(INGO), and other kinds of cross-national relations. City-to-city relations include
air-passenger flows, transnational corporation (TNC) headquarter–subsidiary
relations, among others. We conclude by discussing future directions in visualizing
globalization. The analytical frontier in visualizing globalization lies squarely in
statistical/model-based approaches to spatial and social network analysis. While
these analytical approaches hold much promise for visualizing globalization, the
dearth of geocoded subnational relational data and the complexity inherent to
modeling them create significant obstacles.

FOUNDATIONAL RESEARCH
The concept of globalization has been analytically controversial from the
outset. Popularized in the 1990s, globalization quickly became a topic of
controversy. Most scholars acknowledged the strengthening of centripetal
processes of globalization, but they disagreed over its definition, historical
novelty, and its saliency for political-economic outcomes (Chase-Dunn,
Kawano, & Brewer, 2000; Strange, 1996; Robinson, 2004). While some of this
debate remains ongoing, there is an emergent consensus that globalization
is best conceptualized as a set of “processes involving flows that encompass
ever-greater numbers of world’s spaces and that lead to increasing integration and interconnectivity among those spaces” (Ritzer, 2007, p. 1). That is,
most conceptualize globalization as a set of inherently relational processes
linking place-bound actors and fostering interdependence among the global
populace, or in other words creating a “network society.”
This relational conceptualization of globalization coalesces with a branch
of social science called social network analysis (SNA), which focuses on
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

“relationships among social entities, and on the patterns and implications of
these relationships” (Wasserman & Faust, 1994, p. 3). More specifically, the
foundational principles of SNA include an understanding of social actors as
“interdependent, rather than independent, autonomous units”; of relational
ties as “channels for transfer or ‘flow’ of resources”; and of social structure as
“lasting patterns of relations among actors” that provide “opportunities for
or constraints on individual action” (Wasserman & Faust, 1994, p. 4). Much
empirical work on visualizing globalization thus makes copious use of
social network analytic tools by defining node sets that vary from countries
to cities to firms, and using network tools to visualize, quantify, and analyze
the pattern of relationships between these nodes.
VISUALIZING HIERARCHICAL NETWORKS AMONG NATION-STATES
The earliest network analysis of global relations predated the concept of globalization and instead found theoretical inspiration in world-systems analysis.
Snyder and Kick (1979) analyzed four cross-national relations—international
trade, diplomatic exchanges, military interventions, and joint treaty
memberships—and found that the interaction pattern among these relations
resembled a “core–periphery” network. As the hypothetical sociomatrix
in Figure 1 illustrates, a core–periphery network is a network with one
large and dense (many interconnections) component to which individual
network members are more or less attached.1 “Core-like” actors reside
at the center of the network (upper left quadrant of Figure 1) and tend
to forge relations with actors in both the core and periphery. Conversely,
“peripheral-like” actors reside at the margins of the network (bottom right
quadrant of Figure 1) and tend to forge relations primarily with core actors.
Countries in the “core” of Snyder and Kick’s analysis included most of
the advanced industrial democracies, while extremely poor developing
countries populated the periphery. The authors interpreted these findings
as evidence in support of arguments from world-systems theory that
nation-states occupied hierarchically ordered positions in an interdependent
world-system structure.
Subsequent to the seminal work of Snyder and Kick (1979), other scholars analyzed a growing array of cross-national relations. One line of research
analyzes multirelational commodity trade data by disaggregating trade into
different levels of “industrial sophistication” varying from raw materials and
animal products through light weight/low wage and into high tech/heavy
1. A sociomatrix (A) is a N × N matrix that typically consists of the same actors on the rows and
columns, so that the cell Aij records the presence/absence or value of the tie between i and j. N is the
number of actors, and ij represents the tie (or cell) connecting actor i and actor j.

Visualizing Globalization

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Figure 1 Hypothetical sociomatrix illustrating a core–periphery network. Notes:
Dark areas indicate dense interaction; light areas indicate low or nonexistent
interaction.

manufacturing. These studies replicate Snyder and Kick’s (1979) initial finding of a core–periphery network. In addition to quantifying the structure
formed by these trade relations, this body of research also analyzes the way
in which interaction patterns vary by the type of trade relation and finds
that commodities with low levels of “industrial sophisticated” tend to flow
“up” the hierarchy (from the periphery to the core) while commodities with
high levels of “industrial sophistication” tend to flow “down” the hierarchy (i.e., from the core to the periphery). These analysts suggest that these
flow patterns illustrate a key mechanism of “unequal exchange” between
the core and periphery (Smith & White, 1992). Moreover, studies in this lineage incorporate a longitudinal component, and therefore analyze not only
the structure formed by international trade in a single point in time but also
dynamic change in that structure as well as the mobility of individual countries within it (e.g., Mahutga, 2006; Mahutga & Smith, 2011; Smith & White,
1992). Empirical work at the intersection of cross-national relations and SNA
is ongoing. This work includes continued efforts to quantify the network
structure of trade (Clark & Beckfield, 2008), assess patterns of mobility in the
international trade network (Clark, 2010), and move beyond trade to analyze the structure of international governmental organization IGO and international nongovernmental organization (INGO) networks (Beckfield, 2010),
bilateral investment treaties (Bandelj & Mahutga, 2013), and voting alliances
in the United Nations (Lloyd, 2005), among others. An important finding that
emerges from the panoply of this research, however, is that most networks of

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

international relations resemble a core–periphery structure (Lloyd, Mahutga,
& de Leeuw, 2009).
VISUALIZING HIERARCHICAL NETWORKS AMONG URBAN SPACES
Another prominent research tradition that allows for the visualization of
globalization is world-city research. In contrast to the work reviewed previously, research on world-cities draws theoretical inspiration from urban
geographers and sociologists including Friedman (1986); Sassen (1991), and
Taylor (2004). The early writing of John Freedman was the first systematic
attempt to “link urbanization processes to global economic forces,” and
subsequent work has proceeded in kind (1986, p. 69). In particular, research
on global cities takes as given the argument that (i) cities vary in how they
are linked into global capital circuits, (ii) this variation has significant implications for the kinds of economic activities that are contained within cities
and for the developmental consequences of those economic activities, and
(iii) political contestation in urban spaces should follow from the relation of
(ii) to (i). In particular, prototypical “global” cities are the “command and
control” centers of an expanding global economy, from which transnational
corporation (TNC) headquarters orchestrate a spatially diffuse production
system. Thus, research on global cities attempts to quantify the structure of
the world-city system by analyzing city-to-city relations.
One of the foundational tasks adopted by world-city analysts has been
the identification of prominence in world-city status. Early observers
hypothesized that New York, Paris, London, and Tokyo were the global
cities, and research utilizing relational data including city-to-city airline
passenger flows (Smith & Timberlake, 2001), TNC headquarter–subsidiary
relations (Alderson & Beckfield, 2004), and interlocking producer service
firms (Taylor, 2004) tends to support this proposition, with caveats. That is,
New York, Paris, London, and Tokyo stand out as exceptionally prominent
world-cities because resident headquarters tend to send subsidiaries to
many other cities, these cities send and receive large flows of airline passengers to/from many other cities, and contain a disproportionate share of
important offices in the producer-service firm network. The image emerging
from the litany of network analyses of the global city system is thus one of
hierarchy, in which a handful of “global” cities operate as command and
control centers. These cities are followed by cities with descending levels
of status and prominence in the various networks analyzed. Thus, while no
network analyses of world-cities have directly assessed the extent to which
world-cities confirm to a core–periphery network, the structural insights that
do emerge from research on global cities are exceedingly comparable. And,
there is some evidence suggesting a close mapping of a city’s centrality in

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the world-city network to the “coreness” of the country in which it is located
(Alderson & Beckfield, 2004; Mahutga, Ma, Smith, & Timberlake, 2010).
CUTTING-EDGE RESEARCH
MAPPING GLOBALIZATION WITH GEOGRAPHIC INFORMATION SYSTEMS
If the foundational research on visualizing globalization has to date focused
primarily on using network analytical techniques to visualize and describe
the structure of globalization that emerges in these networks, there is a good
degree of unrealized potential in using geographic information systems
(GISs) to map globalization processes. For example, trading patterns in the
modern global community are complex and multifaceted. Tables presenting
bilateral trading patterns in different commodities are often complicated
and difficult to read. However, GIS can clearly visualize some of the more
interesting two-way trade flows. The map displayed in Figure 2 focuses on
four different bilateral trade flows in clothing, an industry that touches just
about every resident of each country in the world-system. These examples
highlight the spatiality of important organizational characteristics in the
global clothing industry. For example, the bilateral trade flow of clothing
between the United States and the United Kingdom is just about even, with
the clothing imported into the United States from the United Kingdom just
under $200 million and the imports from the United States to the United
Kingdom at just over 200 million. The situation for China and Canada is
quite different. Canada receives more than $800 million in clothing imports
from China, but sends less than $400,000 to China. We could have picked
almost any developed country to pair with China in garment trade and
observed a large trade imbalance in clothing trade, because China and other
developing countries have now become key countries in globally organized
clothing value chains, where firms in developed countries engage in design,
marketing, and retail, and those in developing countries engage in simple
manufacturing (Mahutga, 2012).
The map in Figure 2 also illustrates the enduring influence of colonial
legacies on the structure of globalization. For example, Cameroon exports
very little clothing to France, but France has the second highest export tie
to Cameroon, who imported just over $1 million in clothing from France in
2000. Finally, we present the trade flow in clothing between Italy and Brazil
for the year 2000, which shows another imbalance in such goods. Italy,
known as a producer of fine fabrics and designer suits and dresses for both men and
women, serves a growing economic elite in Brazil with substantial imports
of clothing, worth more than $17 million, while Brazil exports very little in
the way of clothing to Italy, creating a substantial imbalance in this category

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

Legend
Cameroon

China

1029 from France

387 from Canada

United Kingdom

France
152 from Cameroon

Canada

288,374 from USA

United States

879,446 from China

Italy
4470 from Brazil

Brazil
17,623 from Italy
World

175,192 from UK

Figure 2 GIS map of clothing trade among key countries. Notes: Dollar amounts
are expressed in thousands of US$ 2000.

of trade good. As the map in Figure 2 illustrates, relationships are readily
discerned in a GIS format, and there are many additional tools that could
enhance a map such as this including three dimensional mapping, where
the height of each country could be a function of, say, trade dollar values to
illustrate the relative importance of countries in a globalizing economy.
KEY ISSUES FOR FUTURE RESEARCH
THE ANALYTICAL FRONTIER FOR VISUALIZING GLOBALIZATION
The analytical frontier for research on visualizing globalization lies squarely
in the identification of statistical network and spatial models to explain them.
Recent examples include a study published in Science that not only visualized globalization via network analyses of commodity trade but also quantified the link between a country’s position in these networks and economic
development by highlighting the opportunities and constraints to economic
development imposed by networks structure (Hidalgo, Klinger, Barabasi, &
Hausmann, 2007). Similarly, a recent study of the world-city system analyzes
the extent to which a city’s integration into the global city system causes it
to reduce its connections with cities in its own country (Ma & Timberlake,
2012). And, in a departure from the focus on either countries or cities, a recent
study of the network formed by ownership relations among transnational

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firms finds that it, too, resembles a core–periphery interaction pattern, and
quantifies the concentration of ownership among a handful of firms, where
737 firms control 80% of the value of the full 43,060 firms analyzed (Vitali,
Glattfelder, & Battiston, 2011).
While statistical network and spatial models do reside at the analytical frontier, there are two issues that limit the expansion of this frontier in the short
term. First, statistical approaches to relational data in both their network analytical and spatial form are explicitly designed to deal with the violation of
the assumption of independent observations. The extra analytical leverage
provided by these models does not come without a cost. While the scope
of this entry limits our ability to discuss technical details, the mathematical and computational procedures necessary for modeling relational data are
well beyond the average social scientist’s methodological toolbox. Moreover,
there are comparatively few examples of statistical software for relational
data. Those that do exist either do not include ready-made packages for statistical models (e.g., Borgatti, Everett, & Freeman, 2002) or have a steep learning curve (Statnet). Second, a key argument made by globalization scholars is
that globalization transcends national borders, but most data is still collected
at the national level (with the exception of the city-level data discussed previously). Thus, our ability to visualize globalization with tools such as SNA
and GIS would be much improved by the compilation of subnational and
geocoded relational data.
CONCLUDING COMMENTS
As processes of economic globalization progress, so, too, do social scientific
efforts to visualize them. We have learned much about the structure of relations among countries and cities as this literature has matured, which in turn
has helped us to understand the structure of globalization itself. In this essay,
we reviewed the large and growing literature that employs social network
analytic tools to visualize and analyze processes of economic globalization
and highlighted some unrealized potential in the utilization of GISs for the
same purposes. The primary limits to scientific efforts to visualize globalization lie in the complexity of efforts to collect and compile transnational
relational data and simplify these data with visual and statistical techniques.
While this limitation appears daunting, it also points to the limitless possibilities that exist for social scientists to advance the analytical frontier.
REFERENCES
Alderson, A. S., & Beckfield, J. (2004). Power and position in the world city system.
American Journal of Sociology, 109, 811–851.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

Bandelj, N., & Mahutga, M. C. (2013). Structure of globalization: Evidence from
the world-wide network of bilateral investment treaties (1959–2009). International
Journal of Comparative Sociology, 54(2), 95–123.
Beckfield, J. (2010). The social structure of the world polity. American Journal of Sociology, 115, 1018–1068.
Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). Ucinet for Windows: Software for
social network analysis. Harvard, MA: Analytic Technologies.
Chase-Dunn, C., Kawano, Y., & Brewer, B. D. (2000). Trade globalization since 1795:
Waves of integration in the world-system. American Sociological Review, 65(1),
77–95.
Clark, R., & Beckfield, J. (2008). A new trichotomous measure of world-system position using the international trade network. International Journal of Comparative Sociology, 50(1), 5–38.
Clark, R. (2010). World-system mobility and economic growth, 1980–2000. Social
Forces, 88(3), 1123–1151.
Friedman, J. (1986). The world-city hypothesis. Development and Change, 17(1), 69–83.
Hidalgo, C. A., Klinger, B., Barabasi, A. L., & Hausmann, R. (2007). The product space
conditions the development of nations. Science, 317(July), 482–487.
Lloyd, P. (2005). An empirical test of theories of world divisions and globalization
processes: An international and comparative regional perspective. PhD Dissertation, Department of Sociology, University of California at Los Angeles.
Lloyd, P., Mahutga, M. C., & de Leeuw, J. (2009). Looking back and dorging
ahead: Thirty years of social network research on the world-system. Journal of
World-Systems Research, 15(1), 48–85.
Ma, X., & Timberlake, M. (2012). World city typologies and national city system Deterritorialisation: USA, China and Japan. Urban Studies, 50(2), 255–275.
doi:10.1177/0042098012453859
Mahutga, M. C. (2006). The persistence of structural inequality: A network analysis
of international trade, 1965–2000. Social Forces, 84, 1863–1889.
Mahutga, M. C. (2012). When do value chains go global? A theory of the spatialization of global value chains. Global Networks, 12(1), 1–21.
Mahutga, M. C., Ma, X., Smith, D. A., & Timberlake, M. (2010). Economic globalization and the structure of the world-city system: The case of airline passenger data.
Urban Studies, 47(9), 1925–1947.
Mahutga, M. C., & Smith, D. A. (2011). Globalization, the structure of the world economy and economic development. Social Science Research, 40(1), 257–272.
Ritzer, G. (Ed.) (2007). The Blackwell companion to globalization. London, England:
Blackwell Publishing.
Robinson, W. I. (2004). A theory of global capitalism: Production, class, and state in a
transnational world. Baltimore, MD: Johns Hopkins University Press.
Sassen, S. (1991). The global city: New York, London and Tokyo. Princeton, NJ: Princeton
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Smith, D. A., & Timberlake, M. F. (2001). World City Networks and Hierarchies,
1977–1997: An Empirical Analysis of Global Air Travel Links. American Behavioural
Scientist, 44, 1656–1678.

Visualizing Globalization

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Smith, D. A., & White, D. (1992). Structure and dynamics of the global economy:
Network analysis of international trade, 1965–1980. Social Forces, 70, 857–893.
Snyder, D., & Kick, E. (1979). Structural position in the world system and economic growth 1955–1970: A multiple network analysis of transnational interactions. American Journal of Sociology, 84, 1096–1126.
Strange, S. (1996). The retreat of the state: The diffusion of power in the world economy.
Cambridge, MA: Cambridge University Press.
Taylor, P. J. (2004). World city network: A global urban analysis. London, England:
Routledge.
Vitali, S., Glattfelder, J. B., & Battiston, S. (2011). The network of global corporate
control. PloS One, 6(10), e25995. doi:10.1371/journal.pone.0025995
Wasserman, S., & Faust, K. (1994). Social network analysis: methods and applications.
Cambridge, MA: Cambridge University Press.

FURTHER READING
Carrington, P. J., Scott, J., & Wasserman, S. (Eds.) (2005). Models and methods in social
network analysis. Cambridge, MA: Cambridge University Press.
Choi, J. H., Barnett, G. A., & Chon, B. (2006). Comparing world city networks: A
network analysis of internet backbone and air transport intercity linkages. Global
Networks, 6(1), 81–99.
Mapping Globalization at Princeton. http://www.princeton.edu/globalization/.
Princeton University
Globalization and World Cities Research Network. http://www.lboro.ac.uk/gawc/.
Loughborough University
Parker, R. N., & Asencio, E. K. (2009). GIS and spatial analysis for the social sciences:
Coding, mapping, and modeling. New York, NY: Routledge Press.

MATTHEW C. MAHUTGA SHORT BIOGRAPHY
Matthew C. Mahutga (http://matthewcm.ucr.edu/) is an Associate Professor of Sociology at the University of California, Riverside. His research
examines the global determinants of economic organization and the socioeconomic consequences of these global processes, as well as quantitative
macrocomparative research methodology. His work appears in Social Forces,
Social Problems, Global Networks, Social Science Research, Review of International
Political Economy, and elsewhere.
ROBERT NASH-PARKER SHORT BIOGRAPHY
Robert Nash Parker is a Professor of Sociology and Co-Director of the Presley
Center for Crime and Justice Studies, University of California, Riverside; previously, he held professorial appointments at The University of Akron, Rutgers University, and the University of Iowa. Between 1991 and 1996, Parker

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

was a Senior Research Scientist at the Prevention Research Center in Berkeley,
CA. His main research interests include Alcohol and violence, youth violence
and gangs, geographic information systems and spatial modeling, and the
study of the causes of homicide. He recently coedited special issues of New
Directions in Evaluation (vol. 110) on failed evaluations and Contemporary
Drug Problems on Alcohol Policy and Harm Reduction (2007); Parker is also
the author of Alcohol and Homicide: A Deadly Combination of Two American Traditions (SUNY Press, 1995) and GIS and Spatial Modeling for the Social Sciences
(Routledge, 2009). His most recent articles deal with alcohol availability and
youth violence, and the impact of single-serve alcohol containers in retail settings on neighborhood violence; these were published in September, 2011 in
the Drug and Alcohol Review. His newest book is called Alcohol and Violence:
The Nature of the Relationship and the Promise of Prevention and is published in
2013 by Lexington Books.
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Visualizing Globalization

11

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