Technology Diffusion & Adoption

OWID presents work from many different people and organizations. When citing this entry, please also cite the original data source. This entry can be cited as:

Hannah Ritchie and Max Roser (2017) – ‘Technology Diffusion & Adoption’. Published online at OurWorldInData.org. Retrieved from: https://ourworldindata.org/technology-adoption/ [Online Resource]

This entry presents data on the adoption and diffusion of particular technologies across the world.

# Empirical View

# Technology adoption in US households

The visualisation below details the rates of diffusion and adoption of a range of technologies in the United States, measured as the percentage of US households with access or adoption over time. Specific definitions of what constitutes ‘adoption’ or ‘diffusion’ of each technology can be found in the ‘Sources’ tab of the chart below.

We were pointed to the relevant sources by Horace Dediu, who documents, blogs and analyses technological change over time. We have tracked down all of his original sources and assembled our dataset based on these original sources.

# Fixed (landline) telephone adoption

# Mobile phone adoption

# Internet access & technology

# Share of population with internet access

# Number of secure internet servers

# Road vehicles

# Road vehicle ownership per 1000 people

# Correlates, Determinants & Consequences

# Technology leapfrogging

# Fixed telephone subscriptions vs. income

The visualisation below measures the number of fixed (landline) telephone subscriptions, measured as the number per 100 people versus gross domestic product (GDP) per capita, measured in 2011 international-$. Overall, we see that richer countries typically have a higher number of landline telephone subscriptions.

Interestingly, there appears to be a typical income threshold beyond which the use of landline telephone technologies became common. We see that generally the adoption of fixed telephones was rare below a GDP per capita threshold of approximately $7000-8000. Below this level of income, there were only a few subscriptions for every 100 people. Although the use of landline telephones has declined in recent years, subscription rates for high-income countries typically reached greater than 50 per 100 people.

# Mobile phone subscriptions vs. income

The visualisation below measures the number of fixed (landline) telephone subscriptions, measured as the number per 100 people versus gross domestic product (GDP) per capita, measured in 2011 international-$. Unlike landline subscriptions, there appears to be no clear income threshold for the adoption of mobile phone technologies. Even at the lowest income levels (below $1000 per capita), subscription rates reach greater than 25 per 100 people.

# Mobile phones: leapfrogging landline telephones

The difference in income relationships between fixed (landline) and mobile phone adoption shown above leads to what is often termed the ‘technology leapfrogging’ effect. This is visualised in the chart below which shows landline and mobile phone subscriptions (per 100 people) by country, over time. You can change the country in view using the ‘Change country’ option on the chart.

Typically we see that trends for higher-income countries show a distinct pattern, as shown for the United Kingdom in the example below. Landline subscriptions grow from 1960 onwards, generally peaking in the late 1990s , before steadily declining post-Millennium. This decline strongly coincides with the rapid uptake of mobile phone subscriptions from the 1990s onwards.

If we compare this to trends for lower-income countries (for example, Gambia), we see that there has been negligible adoption of landline telephones (reaching only a few per 100 people), however growth in mobile phone adoption has shown rapid uptake since 2000 (often exceeding 100 mobile subscriptions per 100 people). This is often referred to as the ‘leapfrogging effect’: lower-income countries have effectively leapfrogged/surpassed the earlier landline phone technology and have embraced the modern mobile technology instead.

# Road vehicle ownership vs. income