globalization and heterogenization: cultural and civilizational clustering in telecommunicative...

Telematics and Informatics 23 (2006) 316–331

www.elsevier.com/locate/tele

Globalization and heterogenization: Culturaland civilizational clustering in

telecommunicative space (1989–1999)

Sorin Adam Matei *,1

Department of Communication, 2132 Beering Hall of Liberal Arts (BRNG), Purdue University,

100 N. University Street, West Lafayette, IN 47907, United States

Received 11 October 2004; received in revised form 27 June 2005; accepted 9 September 2005

Abstract

The globalization of telecommunicative ties between nations is studied from a heterogenizationperspective. A theoretical model inspired by Appadurai�s ‘‘disjuncture hypothesis,’’ which stipulatesthat global flows of communication are multidimensional and reinforce regional/local identities, istested empirically on an international voice traffic dataset. Spatial-statistical measures (global andlocal versions of Moran�s I) indicate that countries that share the same linguistic (English, Spanish,or French) or civilizational (Catholic, Protestant, and Buddhist–Hindu) background are more likelyto be each other�s ‘‘telecommunicative neighbors’’ and that this tendency has increased over time(1989–1999).� 2005 Elsevier Ltd. All rights reserved.

Keywords: Globalization; Heterogenization; Disjuncture; Autocorrelation; Telephone traffic

0736-5853/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.

doi:10.1016/j.tele.2005.09.002

* Tel.: +1 7654947780; fax: +1 3602341545.E-mail addresses: [email protected], [email protected]

1 Has a variety of research and instructional interests, including socio-spatial shaping of communicationtechnology, on-line social interaction and communities, and spatial analysis (Geographic Information Systems)applied to local and international communication processes and flows.

mailto:[email protected]

mailto:[email protected]

S.A. Matei / Telematics and Informatics 23 (2006) 316–331 317

1. Globalization processes between homogenization and heterogenization

For more than 20 years scholars from a variety of fields have been engaged in a vigor-ous debate about a new social phenomenon: globalization (Belk, 1996; Castells, 1996;Featherstone, 1990, 1995; Ger and Belk, 1996; Giddens, 2000; Held et al., 1999; Heldand McGrew, 2002; Hirst and Thompson, 1996; Liebes and Katz, 1993; Robertson,1992; Sklair, 2002; Waters, 1995). The discussion is two pronged. On one hand, it aimsat defining the meaning of the concept itself. On the other, is concerned with the effect thisphenomenon has on local social and cultural entities.

Although no single definition is generally accepted, a number of seminal works havesucceeded in narrowing the meaning of the globalization concept to an increase in density

of connections between a variety of actors (individual, organizational and statal) across na-tional and cultural borders (Held et al., 1999). To this, mainly quantitative, description ofglobalization, some researchers add a qualitative one. The process can be seen, accordingto them, as a profound change in the patterns of connections between world actors(Appadurai, 1996). The nuance added to the concept is quite important; through it glob-alization ceases to be a purely descriptive term, which simply asserts that a web of flowsbetween nations exists. It suggests that the web of flows has increased to the point whereit becomes a qualitatively new international order. In a globalizing world density andintensity of connections are of a new order of magnitude, entailing structural changes inthe basic arrangements of relationships between nations (Held et al., 1999).

The nature of these structural changes is, however, far less clearly defined, which is thereason why theorists are also less likely to agree on the second point of the globalizationdebate, that about its effects. The contention point can be summarized as follows: doesan increased, quantitatively and qualitatively, number of global flows improve or deteri-orate people�s everyday lives? A popular view is that globalization tends to follow a hier-archical pattern of diffusion, the flows that ever closer enmesh the world into their nethaving a unique point of origination: the Western-American cultural areal (Schiller,1976; Sklair, 2002; Tomlinson, 1991). This bias renders globalization into a form of impe-rialism, which leads to cultural impoverishment. Globalization is equated with spreadingand imposition of Western values, products and images onto the world. As the worldbecomes more interconnected, it also becomes more homogeneous, following a WesternEuro-American model of social organization, image consumption, and lifestyle (Liebes,2003). The net effect is a negative one, since local identities are destroyed and what takestheir place often does not match the social and economic reality on the ground (Amin,1997).

There are scholars, however, who although do not deny the obvious, i.e. globalizationhas a number of Western and European anchoring or origination points, which are rootedin inequality, contest the idea that globalization should be understood strictly as world‘‘homogenization’’ and ‘‘convergence’’ (Appadurai, 1996; Featherstone, 1995; Friedman,1999; Micklethwait and Wooldridge, 2000). They assert that the homogenization modelis too simplistic, lacking an in-depth understanding of how the global flows of ideas, prod-ucts, and people work. These flows do not simply erase national cultures, they changesome of their features, while reinforcing others. National cultures, which have always beenfluid constructs (Wiley, 2004), more recently have become part of a heterogeneous trans-national field of culture, whose vectors are partly global (sometimes, although not always,Western in origin), partly surprisingly local (Appadurai, 1996).

318 S.A. Matei / Telematics and Informatics 23 (2006) 316–331

This view, which emphasizes the transformation and continuous reinvention of localcultures under the influence of global forces, can be identified as the ‘‘heterogenization’’perspective (Appadurai, 1996). While the scholars and analysts promoting it do not denythe tendency of cultural blocs to converge along certain dimensions, they also believe thatthe exchanges between them are not always one way or always preordained by powerstructures. What emerges from these exchanges is a quilt-like global culture, where regio-nal and local ethnic identities are embraced even when global connections across regionaland national borders become stronger. In essence, heterogenization is an ambivalent pro-cess, through which discrete national, cultural or civilizational blocks emerge at the same

time and probably spurred on by intensification of global flows (Barnett, 2004). As Barberhas shown in his seminal work (1995), embracing a fundamentalist world view in someparts of the world (which he identifies as the world of Jihad) is inextricably connectedto the way in which our globalized (Mac)world makes these ideas available to a universalaudience (Barber, 1995).

Several studies have looked, directly or indirectly, at the issue of heterogenization. Forexample, Belk�s empirical research on international consumer behavior and cultures doc-uments how ‘‘global’’ cultural artifacts—such as advertising of global consumer brands—are resignified to express unique local or national concerns (Belk, 1996; Ger and Belk,1996). Resignification of cultural meanings is also documented by Liebes and Katz(1993), in their groundbreaking study on the soap opera ‘‘Dallas’’, which shows howthe greed-ego-love triangles of the Dallas oil elite were differently incorporated into themythos of each local culture.

Appadurai�s work on global heterogenization is probably the most ambitious, both interms of scope and theoretical grounding (Appadurai, 1996). He makes a two-part argu-ment, similar to a certain extent to the logic behind Barber�s two-faced concept of global-ization (Barber, 1995). He starts by accepting what he considers as being obvious: thetechnological explosion, largely in the domain of transportation and information, rendersobsolete the locally ‘‘constructed ethnicities’’ (Anderson, 1983) of the print-dominatedworld. Yet, the new condition of neighborliness we have entered, which can bring thosewho live far apart together, also reminds us of Joshua Meyrowitz�s assertion that thenew media have created communities ‘‘with no sense of place’’ (Meyrowitz, 1985). Theneighborliness they create is of those who were separated by the mobility created by glob-alization itself (Appadurai, 1996).

Thus, globalization is profoundly dialectical; it is a process that by its very nature gen-erates outcomes that seem to be at odds with each other. It dissipates local groups andcultures in the four corners of the world, to immediately reconnect and reinforce them,modified as they are, through the same channels that made their diaspora possible. Usingas one example the Indian (Hindu) diasporic experience, Appadurai notes that while glob-alization has spread the Indian middle class and the cultural elite throughout the world,the same globalization, through email, listservs, cheap international calling cards, satellitebroadcasts and web pages, has enabled expatriate Indians to resist assimilation in theircountries of emigration (Appadurai, 1996). Moreover, the emigrants� new sense of beinga Hindu reinforces the wave of Hindu nationalism back home. He points to the fact thatthe new nationalist movement in India, which is quite powerful and has won a number ofnational elections, would�ve been far less successful without the support it has receivedfrom the Indians living abroad (Appadurai, 1996).


The dialectic nature of globalization is also synthesized by Appadurai�s contention thatthis is a process of differentiation and disjuncture, as much as is one of interconnection(Appadurai, 1990). By this he means that a globalizing world should not be described asa monolithic network, slowly but ineluctably spreading around the world. Rather, he seesit as a collection of partially overlapping socio-techno-cultural landscapes, sometimes trulyglobal and sometimes regional, each characterized by a specific speed of growth and direc-tion of movement. He divides these landscapes, or rather layers of globalization, accordingto their nature into: technoscapes (i.e. the various global telecommunication networks),mediascapes (the flow of content and symbols—movies, books, songs, etc.), financecapes(monetary exchanges), ethnoscapes (people flows—tourists, refugees, immigrants or colo-nizers), and ideoscapes (flows of action-oriented ideologies—environmentalist, feminist,socialist, communist, neo-liberal, religious fundamentalism, etc.) (Appadurai, 1990).

2. Globalization as social space: from theoretical insight to empirical questions

The main strength of the heterogenization/‘‘globalscapes’’ idea is that it proposes a flex-ible research framework, which preserves, on the one hand, the notion that there is anintensification and densification of connection between nations, and on the other thatthese processes unfold with various speeds and in different shapes at several ontologicallydiscrete levels (technologic, economic, cultural, etc.), reinforcing a renewed sense of ‘‘glo-cal’’ identity (Hampton, 2001). This perspective is valuable not only for its theoretical effi-cacy, but also for the dialogue it opens with empirically oriented research. Utilizing alanguage that refers to flows, the framework allows designing empirically oriented studies,addressing, in a data-driven, but theoretically informed manner, the twin issues of culturalhomogenization/heterogenization via network and geospatial analysis.

The present paper focuses on the over-time evolution of heterogenization in the techno-

scape, more specifically, at the level of the telecommunicative (international telephonic)flows between nations. It starts from Appadurai�s insight that globalization can be de-scribed as a dynamic process and as a multilayered flow of connections (Appadurai,1990). The ‘‘globalscape’’ paradigm proposed by Appadurai is clearly a network/spatialproblem, since it postulates that macro-social global phenomena take a ‘‘field’’ structure,being organized in networks of connections. As recent advances in social network analysisindicates, social networks are rarely homogeneous; they manifest a natural tendency to-ward centralization around specific nodes, patterns of local agglomeration being shapedby node attributes (Barabasi, 2002). This local agglomeration can be tested for significancethrough spatial analysis techniques commonly employed in geostatistics (Anselin, 1995;Cliff and Ord, 1973; O�Loughlin and Anselin, 1996; O�Loughlin et al., 1994; Upton andFingleton, 1985).

The goal of this paper is to determine the amount of heterogeneity found in the globalphone traffic and its over-time development. A state of ‘‘heterogeneity’’ can be describedas a network structure in which nodes have a tendency to connect to each other along spe-cific cultural attributes. Over time we expect an increase in the tendency of the nodes tosurround themselves telecommunicatively with cultural and civilizational peers.

We focus our attention on only one type of global network, that created by interna-tional telephonic calls, for several reasons. First, this is an essential component of theworld communication system. Second, we are building on a growing literature dedicated


to this type of technoscape (Barnett, 2001; Barnett and Choi, 1995; Barnett et al., 1999;Guldmann, 2004; Kellerman, 1990; Sun and Barnett, 1994). For example, Barnett, his stu-dents and associates have shown in a number of pioneering studies that linguistic affilia-tion and culture explain to a significant extent the traffic between nations, which is anindirect sign that culture matters (Barnett and Choi, 1995). Employing a complex conver-gence theory, Barnett has shown that while telecommunications reduce the importance ofnational identities, some local variations will subsist (Barnett, 2004). He has also demon-strated that, over time, the world telecommunicative network has become slightly morecentralized, although there are signs of regionalization, especially within and betweennon-Western cultural areals (Barnett, 2001). Other studies have also investigated the ten-dency of the world telecommunicative network toward ‘‘balance’’ and away from ‘‘depen-dency,’’ concluding that there are clear signs that the world goes toward a more balanced(although not necessarily egalitarian) pattern of flows in telecommunications (Monge andMatei, 2004).

The present study takes this line of inquiry to a new level, addressing the cultural het-erogeneity issue more directly. Starting from Appadurai�s theoretical insights we expectthat over time nations that are culturally or civilizationally similar have become moretightly enmeshed with each other. Thus the central research question is:

RQ1: Have the world telecommunicative flows, measured as number and duration ofphone calls between countries, become increasingly clustered along cultural and linguisticdimensions, during the globalization decade (1989–1999)?

If the answer were yes, then we have good reason to believe that what we are capturingis a process of cultural heterogenization, which unfolds within the process of globalization.

3. Method

3.1. Research strategy

The empirical goal of this paper is to investigate the changes that have occurred duringthe 1990s in the telecommunicative technoscape, i.e. that defined by the pattern of interna-tional phone calls between nations. Specifically, did these changes indicate a tend towardheterogenization due to strengthening of connections between nations that share commoncultural characteristics?

The analysis starts with identifying the anatomy of the technoscape of reference (inter-national phone call flows) at two points in time, 1989 and 1999, dates which mark twoessential points in the ‘‘globalization decade’’ (Micklethwait and Wooldridge, 2000). Nine-teen eighty-nine corresponds to the fall of the Berlin Wall, which gave a tremendous impe-tus to international communication. Nineteen ninety-nine is also the last year of the‘‘telecom bubble,’’ which marked the end of a period of rapid growth in transborder com-munication. Operationally, the 1989 and 1999 telecom technoscapes are represented bytwo square (who-to-whom) matrices of connections between 110 target nations, selectedfrom all continents and socio-economic strata, and representing 90% of the world popu-lation. Selection criteria included population size (no nation has a population smaller than300,000 people) and telecommunicative data availability for both years (1989 and 1999).

The matrices map out the relationships of vicinity in telecommunicative space betweennations. They indicate, for each nation in part, what countries can be considered its inter-national telecommunication ‘‘neighbors.’’ The criterion for determining vicinity for coun-


try i is that its ‘‘neighbors’’ (such as countries j, k, l, or m) should receive at least 5% of i�soutgoing international voice traffic. The 5% cut-off point was determined by analyzing thedistribution of raw outgoing traffic, which was found to be logarithmic. Each nation sendsmost of its traffic to about 4 out of the 110 nations. Each of these four nations typicallyabsorb between 10% and 35% of the outgoing traffic, and together consume about 80% ofthe total outgoing traffic. We found that the lower bound of the range of values for the top4 countries found under this steep portion of the logarithmic distribution (which is j, notbell curve shaped) is about 5%, which was set up as the cut off point. The raw data wasacquired from the International Telecommunications Union (ITU, 1999) and from Telege-ography (Telegeography, 2001), a consulting company that specializes in world telecom-munications network traffic measurement and analysis.

The telecommunicative vicinity matrices are analyzed for signs of cultural heterogeneityusing spatial statistical tools. These techniques can determine if there are significant culturalor civilizational clusters of nations in technospace. They presume that each matrix of con-nections is similar to classical neighborhoods matrices, widely used in geographic analysis,which summarize physical vicinity relationships between geographic units (Bailey and Gat-rell, 1995; O�Loughlin and Anselin, 1996). Our matrices are a direct variation of the classi-cal neighborhood matrix, in that they assume vicinity based not on geographic, but ontelecommunicative distance. Space is now treated not as a land, but as a technoscape.

3.2. Spatial statistical procedures

Two specific statistical tools, Moran�s I and Anselin�s LISA (local indicator of spatialassociation) version of Moran�s I, are used for identifying presence and significance of spa-tial correlation—an indication of heterogeneity—in the two telecommunicative spaces(Anselin, 1995; Cliff and Ord, 1973). The main goal is to identify possible cultural and civ-ilizational autocorrelative trends in telecommunicative space and their direction of move-ment in time. In simpler terms, did countries become during the 1990s more involved,telecommunicatively, with their cultural and civilizational peers?

The Moran�s I procedure detects heterogenization trends at the level of the entire tech-noscape, a separate measure being produced for each year. Anselin�s LISA values are cal-culated for each individual country in part and they facilitate identification of the clustersin which countries of a specific cultural and civilization background are the tightest con-nected with their cultural and civilizational peers.

For those new to spatial correlation, Moran�s I, as a ‘‘global’’ statistical method indi-cates if observations (in our case, nations) that have similar values on a specified variableare more likely to cluster together, when looking at the entire dataset, at the same time(Bailey and Gatrell, 1995). Moran�s local (LISA) version analyzes each specific observa-tion (nation) and its neighbors and it indicates if that specific observation is more or lesslikely to be surrounded by observations similar in value to it. The global Moran�s I is acomposite product of the local (country specific) Morans (Anselin, 1995).

The global Moran�s I is part of a larger family of statistical measures, i.e. those dealingwith autocorrelation (Cliff and Ord, 1973). Better known from time series analysis, wherewe talk about correlation between points proximate in time, autocorrelative processes alsoapply to spatial proximity. The basic assumption is that spatial, just like temporalmeasurements, will tend to be similar for units that are closer together. Mathematically,Moran�s I is expressed as


I ¼ ðN=S0ÞX

i

Xj

wijxixj

,Xi

x2i ð1Þ

where wij is a component of a spatial weight matrix, indicating the relation of contiguitybetween i and j; xi and xj are measurements at locations i and j (standardized as deviationsfrom the mean); N is the number of cases; and S is a normalizing factor, equal to the sumof all weights (Anselin, 1995; Upton and Fingleton, 1985). Moran�s I takes values between�1 and 1, similar to classical Pearson�s r correlation indicator, where high positive valuesdenote that countries high on the target variable are very likely to be each other� neigh-bors, while negative values indicate that, systematically, countries with high values on aspecified variable are surrounded by countries with low values (or vice versa).

Anselin�s LISA is a local spatial association measure and a version of Moran�s I. It mea-sures, for each observation in part, how tightly this is associated with its neighbors. Thesum of LISAs for all observations is proportional to the global indicator of spatial asso-ciation (Anselin, 1995). More formally, LISA for a variable yi, measured at location i, isthe statistic Li, expressed as

Li ¼ f ðyi; yJiÞ ð2Þ

where f is a function, and the yJi are the values observed in the neighborhood Ji of i. Morespecifically, the local version of the Moran�s I statistic takes the expression:

I i ¼ zi

Xwijzj ð3Þ

where zi is the standardized value of observation i, zj, for observation j and wij representsthe same weight element as in (1). Values for local Moran�s I are not limited between �1and 1, although, if positive, they also indicate correlation of similar cases and, if negative,of dissimilar ones.

As spatially oriented measures, global and local versions of Moran�s I present specialproblems in terms of determining significance. Due to the specific structure of each neigh-borhood matrix used for determining the value of the autocorrelation statistics, the distri-bution of these statistics is hard to determine and only approximate or asymptotic resultsare available. An alternative system for determining significance is however available,which employs a conditional randomization or permutation approach. According toAnselin:

The randomization is conditional in the sense that the value is yi at a location i isheld fixed (that is, not used in permutation) and the remaining values are randomlypermuted over the locations in the data set. For each of these resampled data sets,the value of Li can be computed. The resulting empirical distribution function pro-vides the basis for a statement about the extremeness (or lack of extremeness) of theobserved statstic, relative to (and conditional on) the values computed under the nullhypothesis (the randomly permuted values) (Anselin, 1995, p. 96).

This procedure delivers an approximate standard error value, which is used to deter-mine the significance of the individual Moran�s I indicators and of the differences betweenthe 1989 and 1999 Moran�s I values. The significance test we use for the global Moran�s I

indicators is a traditional one: the paired-sample t-test procedure. The local, LISA mea-sures, are similarly compared using paired-sample t-tests, with the caveat that for each


cluster we only employ the sub-sample of nations that presented a significant level of localautocorrelation in 1999 (i.e. we compare the nations clustered in 1999 with their values in1989).

In terms of specific procedures, we start by calculating Moran�s I values for each cul-tural and civilizational areal both for 1989 and for 1999. Then we calculate nation-specificLISA values for all cultural and civilizational areals, retaining for further analysis onlythose nations that are significant at .05. The results are interpreted to indicate a tendencyfor heterogenization if the global statistics are positive in value and have increased be-tween 1989 and 1999. In addition, the trend toward heterogenization is consider to havefurther strengthened over time if the clusters revealed through the local autocorrelationprocedure increase in size and the average LISA values in these clusters increase over time,as well. These increases can be interpreted as a sign of heterogenization with even greatercertainty if they are detected in cultural and civilizational areals other than the dominantones (English-speaking and Protestant).

3.3. Variables

To operationalize cultural background, two complementary criteria were used: linguis-tic and civilizational affiliation. First, we determined which of four ‘‘universal’’ linguisticareals (English, French, Spanish and Arabic) a nation should be attached to and whatweight this attachment should be assigned. Since language is sometimes a product of con-quest and desire (or need) to access valuable educational and scientific resources, ratherthan effective attachment to a cultural paradigm, we also use, as an alternative measure,civilizational affiliation employing as a proxy measure for civilizational affiliation percent-age of population associated with one of the three major religions: Christianity, Islam andBuddhism–Hinduism. Cognizant of the difficulties involved in defining civilization in reli-gious terms, illustrated by the controversy surrounding Huntington�s work (Huntington,1996; Huntington and Harrison, 2000; Inglehart and Norris, 2003; Said, 2001), the presentpaper uses the concept only as a complementary operationalization strategy. In addition,it allows, following the Weberian tradition, to separate the Protestant tradition, which wasearly and successfully involved in the promotion of globalization, from the other Chris-tian, especially the Catholic, areals.

These cultural and civilizational distinctions were used for building a total of eight vari-ables, organized into two groups: four for linguistic and four for civilizational affiliation.The linguistic variables measure degree of closeness of each nation to the English, French,Spanish and Arabic linguistic environments. ‘‘Closeness’’ is measured on a 0–1 scale, using.25 or .05 increments, where 1 is maximum closeness and 0 is no attachment. For each var-iable, 1 was assigned to nations where the target language is the official one and is spokenby the vast majority of the nation as a mother tongue (e.g., UK got a score of 1 forEnglish). Nations where the language is official, but where there is either another officiallanguage or a considerable minority speaks another language than the official one wasassigned a .75 value (e.g., Canada for the English variable, since in this nation Frenchis both official and spoken by a large minority of the population as a mother tongue).If a language is official in a country, but is spoken by a minority, or if the language is spo-ken by the majority as a second language, even if it is not an official language, the countrygets a .5 score (e.g., Canada for French or The Netherlands for English). If a language isspoken by a majority of the educated class, but is not official, or if although official, is not


widely used by the public, the country gets a .25 for that language (e.g., Belgium, Rwandaor Sri Lanka for English). Finally, if the upper crust (the top political, cultural or businesselite) uses a specific language for education and/or everyday life, or if there is a small buttraditionally important minority speaking that language, the country gets a .05 score (e.g.,Syria or Argentina for French or Cyprus or Qatar for English).

Although an ordinal scale, the fractional metric was preferred to a straight ordinal (1–5)one, to reflect the probable distribution of the speakers of each language in a country andto allow finer distinctions at the lower level of the scale, where equal differences betweengroups could not be assumed. Classification of each country was done using the informa-tion provided by the Ethnologue database (http://www.ethnologue.org/), Infoplease.com(http://www.infoplease.com/), The Economist (http://www.economist.com) and the CIAfactbook (http://www.cia.gov/cia/publications/factbook/).

Civilizational affiliation was measured as a set of four different variables, in a mannersimilar in logic to the procedure above, but different in operational terms. The key mea-sures, extracted from the CIA factbook, are the percentages of total population estimatedto be affiliated to one of the following religious groups: Catholic, Protestant, Islamic, Bud-dhist and Hindu. Due to low number of cases (countries) affiliated with Hinduism and tothe fact that Buddhism is in fact a variation of Hinduism, we have combined these last twocategories into one variable.

4. Analysis

Each variable was tested using both the global and the local version of Moran�s I

using Anselin�s GeoDa software package (http://sal.agecon.uiuc.edu/csiss/geoda.html).Through the global procedure we determined how likely, are countries with specific lin-guistic or civilizational affiliation to be surrounded telecommunicatively by countries sim-ilar to them in linguistic or civilizational terms. The second (local) procedure helps us findout what specific countries, through their high, positive and significant LISA scores aremost tightly clustered together along linguistic and cultural lines, and if the average valueof each cluster�s LISA scores has increased over time.

A synthetic overview of the results provided by the first (global) Moran�s I procedure ispresented in Fig. 1. They indicate, in terms of global Moran�s I scores, a general clusteringtrend along cultural and civilizational lines during the 1990s. Fig. 1 shows, for example,that Moran�s I values for 1999 are, except for the Arabic speaking and Islamic areals, con-sistently higher than those for 1989. A paired-sample t-test procedure found all valuechanges, except for that for the Islamic areal, to be significant. The Cohen d values asso-ciated with these differences, ranging from 1.1 to over 2 (see Tables 1 and 2), indicate largeand very large effect sizes (‘‘large’’ effects should be greater than .8, see Cohen, 1988).

The greatest I value increase is registered in the Spanish and French speaking areals,followed by the Catholic, Islamic, Buddhist areals, while the smallest increase is detectedin the English speaking areal. The systematic tendency of nations that are similar cultur-ally to become more tightly enmeshed in telecommunicative space with each other, and thetendency of the English areal to lag behind the other ones, is the central evidence uponwhich our claim that the 1990s have seen a trend toward heterogenization rests. The spe-cial situation of the Arabic speaking and Islamic nations will be discussed below.

Table 3 and Appendix A add further details to this picture by summarizing the averageLISA cluster value increases, across years and cultural/civilizational areals, and by listing

http://www.ethnologue.org/

http://www.infoplease.com/

http://www.economist.com

http://www.cia.gov/cia/publications/factbook/

http://sal.agecon.uiuc.edu/csiss/geoda.html

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

Englis

h

Frenc

h

Spanis

h

Arabic

Prote

stant

Catho

licIsl

am

Budd-

Hindu

Cultural and civilizational areals

Mo

ran

's I

valu

e1989

1999

Fig. 1. 1989 and 1999 Global Moran�s I values for target cultural and civilizational areals.

Table 1Global Moran�s I values for target cultural areals

English French Spanish Arabic

I SD I SD I SD I SD

Telecom vicinity 89 0.53 0.05 0.54 0.06 0.34 0.06 0.45 0.06Telecom vicinity 99 0.60 0.06 0.70 0.05 0.48 0.06 0.39 0.06I change t-value 5.06 3.20 3.88 �3.49Cohen�s d 1.27 2.91 2.45 �1.18

All I values significant at p < .001.

Table 2Global Moran�s I values for target civilizational areals

Protestant Catholic Islam Buddhist–Hindu

I SD I SD I SD I SD

Telecom vicinity 89 0.38 0.05 0.31 0.06 0.30 0.06 0.30 0.06Telecom vicinity 99 0.44 0.05 0.43 0.06 0.38 0.05 0.37 0.05I change t-value 2.6 2.83 1.67 4.66Cohen�s d 1.10 2.04 �1.39 1.32

All I values significant at p < .001.


the countries in each cluster. Table 3 shows that values are generally greater in 1999, com-pared to 1989, with one exception, the Protestant areal. Increases are not, however, signif-icant except for the Spanish speaking nations, at p < .05, (t(9) = 2.785, Cohen�s d = 1.35)and at p < .1 in two other, the Buddhist (t(5) = 2.39, Cohen�s d = .45) and Catholic(t(13) = 1.93, Cohen�s d = .64) clusters.

Table 3Cluster size and LISA values for cultural and civilizational areals

Cluster size (# countries) LISA values

1989 1999 1989–1999 change 1989a 1999 1989–1999 change t p

English areal 24 23 �1 3.45 3.40 0.05 �0.43 0.67French areal 11 11 0 3.70 5.53 1.83 1.29 0.22Spanish areal 6 10 4 2.25 3.80 1.55 2.78 0.02Arabic areal 8 6 �2 4.96 5.05 0.09 0.17 0.87Protestant areal 15 16 1 2.79 3.07 0.28 0.69 0.50Catholic areal 11 14 3 1.20 1.72 0.52 1.93 0.07Islamic areal 8 7 �1 1.81 1.86 0.05 0.30 0.77Buddhist–Hindu areal 5 6 1 3.18 4.21 1.03 2.39 0.06

a Values calculated only for countries identified as cluster members in 1999.


More important than the increases in the LISA indicator values are changes in clustersize and composition (Table 3 and Appendix A). In terms of size, more than twice asmany (9 to 4) nations have joined the clusters, compared to those that have left them,and more clusters have increased in size. Four out of the 8 clusters have increased in size(Spanish, Catholic, Protestant and Buddhist–Hindu), one has remained stationary(French) and three have declined in size (English, Arabic and Islamic). The largest increaseis found in the Spanish areal, which contained four more nations in 1999, compared to1989.

It is also significant to note that the cluster of English-speaking nations decreasesnumerically, from 24 to 23 members, and its average clustering value is constant. In addi-tion, the United States joins the English-speaking cluster in 1999 and its grip on the worldtelecommunication networks seems to have faded. In 1989, 73 nations of the 110 studiedsent at least 5% of their outgoing traffic to the United States. In 1999, only 63 nations werefound in the same situation. At the same time, in 1999 the US had only 4 significant tele-communicative partners: Mexico, Canada, United Kingdom and Germany, the same as in1989, but minus one important partner: Japan. Losing Japan, the US has become moretightly integrated with English speaking nations, since in all nations that remained US tele-communicative partners in 1989 English is more widely spoken than in Japan. This evi-dence can, indirectly, support the idea of heterogenization, as we will argue in Section 5.

In terms of qualitative changes we note an ideological realignment in the world of tele-communications (see Appendix A). For example, Cuba, Poland or Nicaragua join theSpanish or Catholic areals in 1999. Similarly, the Buddhist areal incorporates in 1999two central nations, Japan and South Korea, neither of whom were surrounded telecom-municatively by Buddhist or Hindu countries in 1989. Exception makes, again, the Arabicareal. Here, the cluster loses in 1999 two rich and important nations: Saudi Arabia andUnited Arab Emirates.

As an overall analysis conclusion: the fact that with one exception, that of the Arabicnations, the global Moran�s I values have increased over time; the fact that the Englishareal is the least likely to tighten its connections; and the fact that the clusters are generallybigger and the local association values greater in key non-Western areals (Spanish andBuddhist), the answer to the question: have the world telecommunicative flows become

increasingly clustered along cultural and linguistic dimensions during the globalization decade

(1989–1999)? should be a qualified ‘‘yes’’.


5. Discussion

The main goal of the present paper is to investigate the process of globalization alongits telecommunicative dimension and to reveal a tendency of cultural heterogenization intechnoscape. Heterogenization was described, using Appaduari�s framework, as the pro-cess by which intensification of flows across borders can also lead to a more inwardly look-ing world. Operationally, we have posited that the global network of international callflows will manifest an over-time tendency of clustering nodes (nations) along culturaland civilizational ties.

The statistical procedures employed here show that for some significant cultural andcivilizational areals this is true. As shown by changes in most global and local indicatorsof spatial association, countries that share similar languages or religions are more likely tocluster with each other telecommunicatively in 1999, compared to 1989. More impor-tantly, we found that this trend is the strongest at the global level not in the English,but in the Spanish and French areals, which conceptually we interpret as an a fortiori argu-ment for the heterogenization theory. The reasons are as follows. English speakingnations, especially the US, are considered to be the central hub around which the worldis supposed to have grown to depend during the globalization decade. Seen from a‘‘homogenization’’ perspective, which argues that the world is increasingly organizedaround a core culture and cluster of countries, this means that telecommunicative cluster-ing along the cultural dimension should�ve increased significantly between 1989 and 1999only in the English areal, while the other areals should�ve seen a significant decline in clus-tering. However, our findings show that clustering in the English areal lags behind all oth-ers. This indicates a clear tendency for fragmentation in the global technoscape, which weinterpret as evidence of heterogenization.

The heterogenization argument is also strengthened by the finding that the UnitedStates, the nation that is supposed to dominate the new globalized world, regardless of cul-ture and locality, seems to become not less, but more involved with its own cultural areal,the English one. At the same time, the United States was not as central in the global tele-communications landscape in 1999, compared to 10 years earlier. This is suggested by thefact that fewer nations sent their traffic primarily to US in 1999, compared to 1989, andthat USs telecommunication neighbors decreased from 5 to 4 during the same period.The relative decline of the US as a world telecommunicative hub suggests a more frag-mented and less centralized technoscape.

Finally, the fact that globalization seems to be spurred on by cultural factors, whichlead to increased heterogenization, is supported by closer alignment along linguisticand civilizational lines of nations erstwhile in opposite ideological or power camps.Cuba, for example, one of the last traditional Communist bastions, appears as one ofthe significant members of the Spanish areal in 1999. Poland has similarly become inte-grated in the Catholic cluster, while two sworn enemies, Japan and South Korea, neitherof which were strongly present in the Buddhist cluster in 1989, have become its anchors in1999.

The trend toward heterogenization seems to be questioned by only one areal, that of theArabic-speaking nations. At the global level, these countries were significantly less likely totelecommunicate with each other in 1999 compared to 1989. Also, the local cluster ofArabic nations lost two wealthy nations—Saudi Arabia and United Arab Emirates(UAE)—during the same period. The process is further strengthened by a decline in size


of the Islamic cluster (for the entire areal the global Moran�s I value, although small, ispositive and significant). In essence, what we see is that telecommunicative ties betweenthese nations have weakened. This might be a consequence of the increasing politicaland economic stagnation in a number of Middle Eastern countries and a reorientationof the richer nations, such as Saudi Arabia and UAE, toward the central hubs of the worldtelecommunication system (USA). This rupture can be another facet of the increasinglygreater tensions created by the centrifugal and centripetal forces of globalization affectingthe Middle East today. The recent political and military events in the Middle East suggestthat they are deep and their consequences long ranging, having the potential to change theprocess of globalization itself. It would be interesting to repeat the present study with morerecent data, to observe if the increasing tensions between the West and the Arab world haslead to a reversal in telecommunicative ties between Saudi Arabia or UAE and other Arabnations.

The present results offer a tantalizing insight into the role international telecommunica-tion processes play in a globalizing world. Yet, we should acknowledge that the presentpaper studies only one of the possible facets of the process of globalization, the technolog-ical one. Globalization unfolds not only in technoscape, but also in finance, econo, cultureor ideoscapes. Identifying the relevant flows for each of these social spaces (e.g., foreigndirect investment, trade, media content, etc.) and analyzing their patterns, with an eyetoward revealing tendencies toward heterogenization, are also crucial research agendaitems. Also productive would be building predictive models for node attributes, other thanthe ones mentioned here (culture), using insertion of nations in a specific technoscape asone of the independent variables. In addition, we need to spend more time on revealingthe concrete mechanisms that facilitate or hinder heterogenization, such as those relatedto cultural fashion, regulation, pricing and/or technological innovation.

In sum, studying the processes of heterogenization at the global level needs furtherrefining of variables and methodologies both at regional and local level. Studying andanswering these questions will help in elucidating the nature and extension of what wecould only partially reveal in this paper: the process of heterogenization.

Appendix A. Nations most tightly connected with their cultural and civilizational peers

(LISA clusters)

English areal

1989: Ireland, New Zealand, Jamaica, Canada, Trinidad, Guyana, Australia, UnitedKingdom, Zimbabwe, Ghana, South Africa, Zambia, India, Bangladesh, Swaziland,Netherlands, Singapore, Sri Lanka, Pakistan, Norway, Denmark, Sweden, Kuwait,Malaysia.

1999: Ireland, New Zealand, Jamaica, Canada, Trinidad, Guyana, Australia, UnitedKingdom, United States, Zimbabwe, Ghana, South Africa, Zambia, India, Bangladesh,Netherlands, Philippines, Singapore, Sri Lanka, Pakistan, Norway, Denmark, Sweden.

French areal

1989: Algeria, Morocco, Niger, Burkina Faso, Senegal, Ivory Coast, Togo, Benin,CAR, Chad, Rwanda.

1999: New Caledonia, Madagascar, CAR, Niger, Togo, Burkina Faso, Senegal, Benin,Algeria, Ivory Coast, Rwanda.


Arabic

1989: Sudan, Syria, Jordan, Saudi Arabia, Kuwait, United Arab Emirates, Qatar,Egypt.

1999: Syria, Sudan, Jordan, Kuwait, Qatar, Egypt.

Spanish areal

1989: Paraguay, Bolivia, Guatemala, Argentina, Uruguay, Venezuela.1999: Peru, Chile, El Salvador, Argentina, Nicaragua, Bolivia, Costa Rica, Guatemala,

Cuba, Paraguay.

Protestant areal

1989: Sweden, Norway, Finland, Denmark, Jamaica, New Zealand, Australia, Canada,Ghana, South Africa, Zambia, Guyana, Netherlands, Madagascar, Trinidad.

1999: Denmark, Norway, Sweden, Finland, Estonia, Jamaica, New Zealand,South Africa, Canada, Ghana, Australia, Zambia, Netherlands, Zimbabwe, Angola,Trinidad.

Catholic areal

1989: Argentina, Venezuela, Paraguay, Chile, Guatemala, France, Brazil, Uruguay,Slovenia, Angola, Switzerland.

1999: Peru, Chile, Venezuela, Paraguay, Cuba, Guatemala, El Salvador, Nicaragua,Portugal, Argentina, Poland, France, Uruguay, Germany.

Islamic areal

1989: Syria, Sudan, Qatar, Saudi Arabia, UAE, Jordan, Kuwait, Iran.1999: Qatar, Syria, Saudi Arabia, UAE, Jordan, Kuwait, Sudan.

Buddhist/Hindu areal1989: Myanmar, Sri Lanka, Thailand, Malaysia, Bangladesh.1999: Myanmar, Sri Lanka, Korea, Republic of, Japan, Thailand, Malaysia.

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