INTERNET DIFFUSION AMONG ITALIAN FIRMS: THE

DIGITAL DIVIDE EXISTS

Maurizio Martinelli, Irma Serrecchia, Michela Serrecchia

Institute for Informatics Institute for Informatics and Telematics (IIT-CNR)

Keywords: Internet diffusion, digital divide, domain names.

Abstract: The digital divide can occur either as a “local” (within a given country) or “global” (between developing

and industrialized countries) phenomenon. Our study intends to offer an important contribution by

analyzing the digital divide in Italy and the factors contributing to this situation at the territorial level (i.e.,

macroareas: North, Center, South and at the regional level). To do this, we used the registration of Internet

domains under the “.it” ccTLD as proxy. In particular, we analyzed domain names registered by firms. The

analysis produced interesting results: the distribution of domains registered by firms in Italian regions is

more concentrated than the distribution according to income and population, suggesting a diffusive effect.

Furthermore, when analyzing the factors that contribute to the presence of a digital divide at the regional

level, regression analysis was performed using social, economic and infrastructure indicators. Results show

that Italian provinces that have good productive efficiency, a high cultural level, and greater spending for

investment in telephony and telematics are the best candidates for utilization of the Internet.

1 INTRODUCTION

The analysis of the Internet presence in various

social activities and economic and political areas

indicatess a serious problem: the existence of a

“digital divide” between those who possess the

material and cultural conditions to exploit the new

technologies, and those who do not, or who lack the

crucial ability to adapt to the rapid continual change

that characterizes the Internet today (Warschauer,

2001; OECD, 2001).

The term “digital divide” first appeared in the

1990s during the privatization phase of the Internet,

to indicate a condition of relative disadvantage

experienced by certain user categories in terms of

accesssibility and cost - for example, by residents of

inland areas compared to those on the East and West

coasts (NTIA, 1995, 1998, 1999, 2000, 2001). Many

studies have been conducted at the national and

international levels concerning Internet diffusion,

and reveal the presence of a digital divide between

developing and industrialized countries (“global

digital divide”) as well as within a given country

(“local digital divide”).

Furthermore, the presence of the digital divide

has stimulated researchers and governments

worldwide to identify contributing factors and

propose methods for reducing this gap.

There are two schools of thought regarding this

subject. Some authors, for example Dasgupta et al.

(2001), maintain that the digital divide is a problem

which exists and will continue to persist because

“development researchers” do not see the potential

benefits of Internet use in poor countries. Duncombe

(2000) insists that Internet access is not justified

among the African poor because lack of information

will prevent them from using technology. Others

believe that in the future, the benefits of the web will

also spread among those who are disadvantaged in

terms of accessibility and cost; it is only a question

of time, whereas those who are currently more apt to

use the new technology will reach a saturation level

(Norris, 2001; Roger, 1995). Other studies (Lal,

1996; Anand, 2000; IDC, 2000), in agreement with

this theory, confirm that where Internet services are

available, poor families do not appear to hesitate or

be incapable of using the new technology. Bayes

(1999) noted the rapid adoption of e-mail by

families in Bangladesh as a cost-effective alternative

to telephone calls. In a recent study involving more

than 100 companies in developing countries,

Rajkumar (2000) discovered that Internet use was

accompanied by increased exports and sales, and

encouraged greater customer loyalty. Kenny et al.

(2005) showed that since the mid-1990s the increase

in Internet users in the developing world has been

431

Martinelli M., Serrecchia I. and Serrecchia M. (2005).

INTERNET DIFFUSION AMONG ITALIAN FIRMS: THE DIGITAL DIVIDE EXISTS.

In Proceedings of the First International Conference on Web Information Systems and Technologies, pages 431-435

DOI: 10.5220/0001232504310435

 SciTePress

more rapid than the growth rate in wealthy countries.

South Asia, the Middle East, and Africa are far

behind in terms of hosting web sites. “The situation

of computers in education is similarly mixed ”

According to the economics literature, factors

determining the presence of the digital divide in the

world do not derive exclusively from the impact of

income level (Chinn and Fairlie, 2004; Norris,

2001).

Some studies show that low-income countries

that have undergone considerable reform towards

competition saw a growth of 80% in fixed and

mobile teledensity compared with non-reformed

countries (Kenny at al., 2003). In a study based on

the experiences of 86 countries from 1985 to 1999

Fink et al. (2001) show that sector reforms have a

higher percentage of “mainline provisions” and a

higher percentage of labor productivity compared

with non-reformed countries. Studies show that

competitive provision reduces the cost of

infrastructures for Internet access (Rassotto et al.

2004; Qiang and Pitt, 2003; Reynolds et. al. 2004;

Wallsten, 1999). Other factors having some impact

on Internet use are schooling and illiteracy,

urbanization and electricity consumption (Kenny at

al. 2005; Dasgupta, Lall and Wheeler, 2001).

Regarding the extent of e-commerce, studies once

again suggest the critical role of the underlying

infrastructure but also point out the importance of

strong institutional structures in the form of the “rule

of law” and the availability of reliable methods of

payment such us credit cards (Kenny at al., 2005;

Oxley and Yeung, 2001).

2 METHODS

Several metrics are available for measuring Internet

diffusion. The most convenient are the so-called

endogenous metrics which can be “obtained in an

automatic or semiautomatic way from the Internet

itself” (Diaz-Picazo, 1999). These metrics have the

undeniable advantage of accuracy; according to the

literature the most frequently used are Internet hosts

based on hostcount procedures (see studies

published by Internet Software Consortium or da

RIPE-NCC) and second-level domain names (Naldi,

1997; Zook, 1999; Bauer, Berneand and Maitland,

2002).

To measure the analysis of Internet diffusion in

Italy, we used the endogenous measure of second-

level domain names registered under the “.it”

ccTLD, managed by the Institute of Informatics and

Telematics of CNR, Pisa.

Despite the advantages offered by endogenous

measures, there are also a few disadvantages, since

in some cases they tend to underestimate and in

others to overestimate the phenomenon being

studied (Zook, 1999, 2000, 2001). Overestimation

can occur when the number of hosts is used, often

associated with IP addresses, while if we consider

the number of domains registered, more than one

domain may be associated with the same registrant.

Underestimation can occur because not all internet

users register a domain name under their own

ccTLD, and in many countries the regulations allow

foreign citizens to register under their own ccTLD .

In the case of hosts, underestimation may be due to

the growing presence of firewalls and private

networks (Intranet) and the use of dynamic IP

addresses, increasingly accompanied by new tools

for access to the Net (for example, mobile phones).

In spite of these disadvantages, the numbers of hosts

and Internet domains are the principal means utilized

for analyzing Internet diffusion.

The Institute for Informatics and Telematics (IIT-

CNR), which manages the “.it” ccTLD Registry, is

conducting a study analyzing the diffusion of

Internet use in Italy. Data were extracted from the

databases of registrations managed by the IIT-CNR,

using automatic and semi-automatic procedures

[This means that we have created a new database

useful for analyzing Internet diffusion by initially

consulting the WHOIS

database using an automatic

procedure, for example in order to determine the

category of the applicant, the automatic procedure

verified whether a ORG field existed and if there

was, classified it as a firms. If the field was

erroneous, the LAR

database (semi-automatic

procedure) was consulted]. Approximately 550,000

domain names have been analyzed and grouped into

several categories (individuals, firms, universities,

associations, public groups, foundations,

The WHOIS database contains information regarding the

domain names registered under the “.it” ccTLD, applicants who

have signed a contract with IIT-CNR and technical and

administrative contacts.

The LAR is a letter requesting the registration of a domain

name, with which the applicant assumes full civil and penal

responsibility for the use of the domain name requested. To be

able to register a domain name under the “it.” ccTLD, firms must

send the IIT-CNR (Pisa) a LAR , containing the applicant’s

identifying data, declaration of the knowledge of basic principles

for use of resources and the Internet, and examination of the laws

established by the Rules Commission, concerning the technical

registration procedures.

WEBIST 2005 - SOCIETY AND E-BUSINESS

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committees, and other organizations) in order to

identify the determinants of adoption and then of

diffusion, for each category. A careful data cleaning

procedure was followed. As of September 7, 2001,

the database WHOIS contained 265,437 domains

registered by companies, of which 3,503 were

domains registered by companies with their legal

headquarters in the various EU countries. The

remaining 3,331 domains were not classified, since

it was impossible to ascertain the area where these

companies operate. A total of 258,603 domains

registered by businesses were analyzed.

thermore, in this paper we will only consider one

domain name for each business: in other words, if a

company registered multiple domain names, we

considered only the first one registered.

3 RESULTS

As the literature suggests, analysis shows that a

technological divide exists among companies

operating in specific geographic areas in Italy. As

shown in the following Figure, the North is more

likely than other areas to use the new technology.

Since Italy is divided into 20 administrative units

called regions, in this article we have found it

advisable to analyze internet diffusion by region.

Lombardy, Alto Adige and Lazio (in that order) are

the regions showing the highest penetration rates

(penetration rate is calculated by dividing the

number of domains registered by companies by the

number of companies in Italy, and multiplying the

ratio by 100. At the macro-area level, the relative

penetration rate recorded in North and Central Italy

are higher compared to the South (7.23 and 7.07

respectively for every 100 companies, compared to

4.04 in the South.). The calculation of the Gini index

and the construction of the Lorenz curve show that

the concentration of domains is higher compared to

the number of firms and total income. The Gini

index, calculated according to the number of

domains registered, was 0.557 compared to 0.468

computed according to the number of companies and

0.466 calculated according to total income.

3.1 Determinants of adoption

According the OECD (1999), the digital divide is the

distinction between “Who has and who does not

have access to information (OECD)”. Several

aspects of this phenomenon exist. It is possible to

observe a digital divide among countries

(international digital divide), among individuals or

organizations and within a country at the local level

(domestic digital divide). In order to analyze

whether there is a domestic digital divide in Italy,

we ran exploratory stepwise regressions using

economic and social indicators at the regional level.

This allowed us to examine the determinants of

Internet diffusion, by singling out the factors leading

to registration of domains by company. The

dependent variable of our regression models is the

penetration rate calculated as

Penetration Rate = (Number of domains registered

by companies/number of companies)*100;

We constructed three model. The first two (M1, M2)

analyzed the influence on Internet diffusion of two

key economic factors: per-capita income and added

value per employee and model 3 using social,

economic and infrastructure indicators.

As expected, these two variables positively

correlated with penetration rates per capita income

and value added per employee (0.701 and 0.827

respectively).

Table 1: Stepwise regressions with per capita income as

independent variable

Table 2: Stepwise regressions with per added value

employee as independent variable

The economic literature, in fact, underlines that

differences in income distribution play a crucial role

in explaining differences in ITC access and

Lorenz curve for domains, income, number of firms

0,2

0,4

0,6

0,8

Equidistribution Number of domains registred by firms Number of firms Total income

INTERNET DIFFUSION AMONG ITALIAN FIRMS: THE DIGITAL DIVIDE EXISTS

433

utilization (Norris, 2000; Pohjola, 2002, Hansons,

2000 Warschauer, 2001). We included these crucial

indicators in distinct models in order to address

multicollinearity problems. Per capita income and

added value per employee are very likely to be

correlated with other social and economic indicators

at a local level, generating distortions in the

estimated coefficients. Although it includes only a

independent variable, the model is quite powerful,

and explains about 49% per cent of the variability in

registrations among Italian regions. The coefficient

of per capita income is highly significant and has the

expected sign, showing a positive influence of per

capita income on Internet diffusion at a local level.

Quite similar results are obtained in M2 including

the added value per employees as independent

variable. The R2 is even higher, stating that the

efficiency of the productivity structure account for

68.5 % of the variability in the Internet diffusion. As

previously stated, and in agreement with the

economics literature, the variation in Internet

diffusion between regions may derive from other

factors as well. In the model 3 (Table 3) we analyzed

the stepwise regression, taking into consideration as

dependent variable an economic factor (employees

in the service sector); one related to education

(number of college graduates); a socio-cultural

variable (spending for theatrical and musical

performances); one related to infrastructure (founds

for telephony and telematics) and one relative to

public spending (hydraulic works and electrical

systems).

Table 3: Stepwise regressions taking as dependent variable

the penetration rate of the companies

The Table shows that regions that spend

considerable funds on musical and cultural activity

are more likely to use the new technology (spending

for theater has the second-highest Beta value

compared to the other variables). As might be

expected, the index of spending for telephony and

telematics also plays an important role (the Beta is

equivalent to 0.708). In fact as the literature

proposes (Warschauer, 2001) one of the determining

factors in Internet diffusion is the presence of

adequate network infrastructures.

In brief, it is possible to conclude that regions with

an efficient and service-oriented structure, a lively

cultural scene, and a good educational level ( greater

number of college graduates) are more inclined to

use the new technology and are the best candidates

for a more active and interactive use of the Internet.

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