Elsevier

Telecommunications Policy

Volume 28, Issues 5–6, June–July 2004, Pages 439-457
Telecommunications Policy

Wireless diffusion and mobile computing: implications for the digital divide

https://doi.org/10.1016/j.telpol.2003.11.005Get rights and content

Abstract

Despite significant improvements in nominal levels, severe gaps of digital inclusion still exist in the American economy. This paper argues that, for certain groups, migration towards mobile computing and digital inclusion may transpire from 2G voice centric mobile telecommunications to data centric mobile computing devices. Accordingly, this analysis employs a large data set to investigate what socio-economic factors are determinant for the diffusion of mobile telecommunications; how these findings can be extended to help close the digital divide; and how these findings can inform policy making concerning the digital divide.

Introduction

Gaps in Internet adoption continue to command considerable attention from telecommunications policy makers due to the threat of even greater polarization between those who do, and do not, have Internet access and the compound consequences of digital inequality. US government representatives have set a clear public priority to make Internet connections as common as telephone connections (Hoffman & Novak, 1998 (2000), CNN.com (2001)). In investigating reasons for digital divide, empirical research has focused upon a variety of defining social characteristics including race, gender, education and age (Hoffman & Novak (1998), Hoffman & Novak (2000); McConnaughey & Lader, 2000), but the exact causes remain uncertain.

In the past 5 years, significant improvements have been made in increasing Internet access in those socio-economic groups thus far lacking it. According to the latest report from the US Commerce Department's National Telecommunications and Information Administration (Cooper & Victory, 2002), not only has the percentage of households with Internet connections increased substantially, from 26.2% in December 1998 to 50.5% in September 2001, but the traditional groups of technology “have-nots”, including females, rural areas, and minority groups, have made dramatic gains in Internet access. In particular, the disparity between male and female Internet users has effectively disappeared, and the gap between rural and urban areas has decreased to about one percentage point.

However, even with this overall positive trend, policy questions surrounding the digital divide are equally, if not more, concerned with relative differences in Internet inclusion between socio-economic groups, and how these variances evolve within the aggregate development. The digital divide is still present, and for some groups in the United States it has even increased. The gap between Afro-Americans (39.8%) and the national average (53.9%) has remained significant, whereas the gap between Hispanics (31.6%) and the national average widened further by 6.3% from 1998. Moreover, additional digital divides can be found for individuals aged 50 years or older and for single-parent households, compared with the rest of the population.

Where the evidence confers relative certainty regarding the existence and evolutionary pattern of the digital divide, less understanding exists as to its causes. According to the National Telecommunications and Information Administration, differences in income and education do not fully account for the digital divide (Cooper & Victory, 2002). It has been suggested by several studies (Katz & Aspden, 1997; Hoffman & Novak, 2000) that the presence of a computer in the home is particularly vital to Internet adoption. It should follow that policies intended to increase Internet inclusion should encourage home computer ownership or possession of similar devices that enable Internet access. Paradoxically, Hoffman and Novak (2000) have pointed out that PC ownership for the Afro-American population, where the digital divide has been high, is stagnant, while adoption of cable and satellite dish technology is increasing dramatically. This suggests that the potential for increasing Internet inclusion rates in certain socio-economic groups may best be realized via alternative technologies.

Accordingly, attention is focused towards wireless telecommunications, which are converging into a product segment with mobile computing devices to offer Internet connectivity at a lower price than traditional home PC/modem constructions. Despite delay in the negotiation and deployment of new standards, it is expected that wireless telecommunications will migrate from 2G-based mobile systems, which are mainly designed to support voice communications, to 2.5G-based systems, which are more data centric, and further to 3G-based systems which embrace multimedia transmission (Lindsay, 2000; Meta Group, 2001; Dhawan, 2001). Since this convergence offers great potential for increasing Internet inclusion rates for population groups currently below the national average, it is argued that valuable insights from the diffusion of 2G mobile telecommunications can be garnered to inform and guide managerial and public policy regarding the growth and dispersion of advanced mobile communication devices.

With this aim, we have conducted an analysis of the diffusion patterns of mobile telecommunications based upon two cross-sectional survey samples of households, using data gathered by PNR Associates in 1994 and 1998. The main research questions posed in the present study are: (1) what socio-economic factors are determinant for the diffusion of 2G mobile telecommunications; (2) how can these findings be extended to inform prospects of Internet diffusion; and (3) how can these findings inform policy concerning the digital divide? In order to address these issues, the paper is organized as follows: The next section reviews literature on technology diffusion models and surveys predominant practice in the econometric methods applied to estimate diffusion patterns. After the estimation model is introduced, a statistical analysis is conducted in Section 3 by focusing on socio-economic heterogeneity. The socio-economic factors that explain statistical variation in adoption rates for cellular phones are determined, and then further employed to identify two distinct groups with different diffusion rates and long-term market shares. Given the statistical results of 2G diffusion, Section 4.1 analyzes the prospects for Internet diffusion with the assumption that some users of 2G telephone devices will migrate towards mobile computing and Internet connectivity through advanced 3G devices. Remaining aware of the differences between 2G and 3G diffusion, Section 4.2 draws policy implications for the digital divide in pragmatic terms.

Section snippets

Models of technology diffusion

The diffusion of technology and products has been approached from a number of different perspectives, including geography (Brown, 1981; Clark, 1984), marketing and consumer behavior (Mahajan, Muller, & Bass, 1990), economics (Gurbaxani, 1990) and sociology (Rogers, 1995). Early empirical studies depicted the diffusion of an innovation as a generally slow process, wherein the intensity at which adoption of a new technology spread across an economy changed over time with an S-shaped logistic

Survey data

The data used in this study consists of two cross-section survey samples of households conducted by PNR Associates (now TNS Telecoms). The first sample was obtained in 1994 and contains information from 8700 households, while the second sample was gathered in 1998 and contains over 16,000 households. Each household filled out a questionnaire and submitted copies of its telephone bills. The questionnaire asked whether a household member owned a mobile telephone as well as questions related to

Policy implications for bridging the gaps of Internet inclusion

Given the results that are measurable in current 2G mobile diffusion data, the question arises as to how these findings can be extended to inform prospects of Internet diffusion as well as policies concerning the digital divide. Accordingly, this section is dedicated to analyzing the implications of the digital divide by assuming that 3G mobile innovation will follow a diffusion path similar to 2G mobile telecommunications, and by highlighting policy concerns for 3G diffusion by taking account

Conclusion

This study has examined the diffusion of mobile telecommunications based on cross-pooled samples of data from 1994 to 1998. As expected, it was found that mobile telephone adoption is positively correlated with income and metropolitan area size, as well as strongly correlated with occupation, specifically sales and executive professionals. It was also determined that one ethnic group, African Americans, adopted mobile phones significantly faster than the general population, whereas families

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