By: Christopher R. McGovern, Manager, Research Development, Connected Nation
On Monday, November 8, 2010, the Economics and Statistics Administration and the National Telecommunications and Information Administration (NTIA) of the U.S. Department of Commerce released a new study titled Exploring the Digital Nation: Home Broadband Internet Adoption in the United States. This study is interesting on a number of levels.
First, the magnitude of this study is huge. Data for this study came from the U.S. Census Bureau’s Current Population Survey (CPS) in October 2009, with a sample size of over 54,000 Americans, representing over 119 million households. The size of this sample allows for in-depth analysis of broadband adoption, as well as barriers to adoption; with a sample of 12,467 non-Internet users, the Department of Commerce is able to explore the issues that affect non-adopters across a wide variety of socio-economic factors.
The results of this survey are similar to what Connected Nation has found in the states/territories it serves. For example, the Commerce Department’s study found that 64% of American households subscribe to home broadband service, compared to the average adoption rate of 65% in the states/territories for which Connected Nation works. In addition, the top barrier to adoption among non-Internet users is the perceived lack of need, a finding that echoes Connected Nation’s long-held belief that consumer education and demand stimulation are necessary for any successful broadband expansion effort.
The Commerce Department reports lower adoption rates among several of the same socio-economic groups as reported by Connected Nation studies, including minorities, adults with disabilities, older adults, and adults with less education. For example, this national study found a 19-point gap in broadband adoption between non-Hispanic white respondents and non-Hispanic black respondents (68% compared to 49.4%, respectively). By comparison, Connect South Carolina’s 2010 Residential Technology Assessment recently showed a similar adoption gap, with 42% of African Americans and 70% of Caucasians subscribing to home broadband service. In the years since Connected Nation and its subsidiaries began conducting their residential technology assessments, these gaps have unfortunately persisted.
What is particularly interesting about this Commerce Department study, though, is that it takes the survey data one step further and uses a linear probability regression model to look at the marginal effect of a variety of socio-economic factors, including income, age, education, and a variety of other factors. The results of this model suggest that multiple factors affect broadband adoption for each household; for example, while there is a 19 point gap between non-Hispanic whites and non-Hispanic black respondents, that gap shrinks almost in half to 10 points after controlling for household characteristics like age and income. While the difference is still significant, this type of analysis provides an opportunity to determine just how much each demographic factor affects the decision to adopt broadband.
A case in point is disability status; according to the survey results, adults with disabilities (who tend to be older and have lower household incomes) have lower broadband adoption rates (this study shows a 30 point adoption gap, comparable to the 31 point gap found in South Carolina). Once other socio-economic factors are filtered out, though, the marginal gap between respondents with disabilities and those without disabilities shrinks to 5 points in the national study.
This study is a great addition to the discussion about the socio-economic factors that affect adoption (and barriers to adoption), and how organizations should go about closing the adoption gaps. It also opens the door to discussions about whether a linear probability model is the best predictor, and which factors should be incorporated into such an adoption model; one obvious factor that comes to mind is broadband availability. There is a lot of potential to be found in this report for states as they look toward year two of the State Broadband Data and Development program.
Share this Post