ASSESSING DISRUPTIVE POTENTIAL / How Technology Adoption Affects Global Economies

ASSESSING DISRUPTIVE POTENTIAL

History reveals numerous technologies that never achieved their anticipated disruptive impact. Some failed because of barriers to adoption (e.g., pricing, use case, competition, or consumer acceptance); others failed because they turned out to be technologically or scientifically infeasible. There are a number of conditions that facilitate innovation—in particular, technology disruption. These are described in the following sections.

 

Technology Push and Market Pull

The adoption of disruptive technologies can be viewed from two broad perspectives—technology push and solution (or market) pull (Flügge et al., 2006).

Technology Push

Technology push refers to disruption stemming from unanticipated technological breakthroughs in areas previously considered to have a relatively low probability of success. Such breakthroughs are most likely to occur when the basic science is not yet well understood (e.g., nanoscience) or where technological advancement is impeded by physical limitations (e.g., heat dissipation in semiconductor devices).

Technologies that are disruptive owing to technology push can come from very disparate areas of research, including biotechnology, cognitive technology, and materials technology. Particularly when they are combined with advances in nanotechnology and software, such sectors have the potential to create the building blocks for an extremely diverse range of applications.

Market Pull

The second perspective, solution (market) pull, refers to disruption attributable to market forces that result in the very rapid adoption of a technology (such as the exponential growth of Internet users after release of the World Wide Web) or stimulate innovative advances to address a significant need (such as currently emerging solutions for renewable energy).

When venture capitalists look for potentially disruptive technologies to invest in, they may search for markets that have threats, needs, or demands that could be addressed by novel technologies. They may also look for markets in desperate need of innovation and renewal, which could be threatened and disrupted through the introduction of a new technology. Market need is a critical factor for determining a technology’s potential value and market size. Some market pull conditions and their potential technological solutions follow:

• Reduce oil dependency: vehicles powered by alternative sources of energy.
• Reduce carbon emissions and slow global warming: green technologies.
• Protect vulnerable yet critical information networks: innovative cybersecurity technologies.
• Power portable devices: alternative portable power sources and battery technologies.
• Increase mobility: high-speed transportation networks.

When the Central Intelligence Agency (CIA) participated in the formation of In-Q-Tel, a 501c3 organization tasked with identifying and investing in new technologies and applications relevant to intelligence, its analysts drew up a set of critical needs they believed could be met through the use of innovative commercial technologies.

In 2002, Secretary of Defense Donald Rumsfeld specified a capabilities-based requirements process for the Ballistic Missile Defense System (BMDS). BMDS was one of the first large-scale DoD programs that used a capabilities-based approach to acquisition instead of a requirements-based approach. Instead of specifying the method and performance requirements of a solution, the DoD described the capabilities necessary to overcome a generally defined projected problem or threat. Capabilities-based approaches call for the development of an initial capability and then spiral development to enhance the system as the problems and threats become more defined. Capabilities-based acquisition is fundamentally changing the way the DoD buys and engineers systems (Philipp and Philipp, 2004). This approach demonstrates that projecting future needs can be more important than specifying an exact technical solution.

The committee believes that same concept holds true for forecasting disruptive technologies. Forecasting future needs, problem areas, pain points, threats, and opportunities is just as important as forecasting the specific technologies that might cause disruptions. By associating market pull and capabilities with potential technologies, a forecast should be able to describe the disruption.

A good disruptive technology forecast should forecast not only potential technologies but also potential market (or military) opportunities, competitive threats, or problem areas that might drive technical innovation. Formulating a problem set and a capability list may let a decision maker know how to prioritize R&D initiatives and prepare for future disruptions. It may also help the decision maker take advantage of opportunities even if a pathway to the potential technical solution is not yet clear.

Investment Factors

When examining technology sectors from an investment perspective, it is important to distinguish between the fundamental research investments focused on technology push and investments in the development of new applications to address market pull. These two categories are not entirely decoupled, as most research is in fields that hold potential for application to known problems—for example, quantum science, nanoscience, and cognitive science—but the source of the funding and the kinds of applications being developed tend to be different.

Fundamental research, particularly in the United States, is primarily funded by the government and performed by academia. The results of this research are, in general, published openly (NRC, 2007). In fact, the U.S. export control regime contains an explicit exemption pertaining to the results of fundamental research. Investment in fundamental research in other nations can be less transparent than in the United States. There is a growing trend to funding international collaborations among academic researchers, particularly in the basic research for nanotechnology, biotechnology, information technology, and cognitive science. Because of concerns about intellectual property protection and global competitiveness, the many research programs sponsored by large, multinational corporations are kept confidential and their results are proprietary.

Venture capital is a significant and growing source of investment for technological innovation intended to address market demand and promote regional S&T objectives. Of the $11 billion invested in fuel cell development in the United States between 1997 and 2009, $1 billion came from venture capitalists (Wu, 2009). This type of funding is particularly important for small corporations and start-ups, although some large corporations have implemented an internal version of venture capital investment to focus on the need to link investment and market demand. It is possible to monitor investment trends by sector (cleantech,⁷ biotechnology, Web, enterprise, and consumer electronics) as well as region or country. Information on venture capital can be found in the publications of venture capital associations as well as from analytical groups that track and report on venture investing. Nevertheless, it remains difficult to identify funding activities by specific application, given the proprietary nature of many start-ups.

A slightly different perspective on investment can be obtained by analyzing corporate acquisitions. Large corporations in particular often buy a smaller corporation to gain access to new technology that they then exploit in existing or new product lines.

It is worth noting that the size and type of the investment required to foster technological advancement vary significantly by sector. For example, software development requires virtually no investment in infrastructure beyond basic computing capabilities, whereas nanotechnology development requires significant laboratory capabilities (NRC, 2008). Similarly, the emerging field of computational biology relies on computing power, whereas biotechnology more generally requires significant investment in laboratory equipment.

Social Factors

Social and cultural attitudes have always played a role in the viability and impact of technology and its applications. In many cases, social and cultural attitudes are as important for technology disruption as are performance and functionality factors.

Many technologies and applications are adopted not only for what they do (functionality) but also for what they mean (social identity).⁸ One driver of technology adoption is identity reinforcement. The following examples of social identity affect the adoption of technologies and their applications:

• Being green (e.g., buying an electric or hybrid car);
• Displaying affluence (e.g., driving a very expensive sports car);
• Demonstrating computer savvy (through choice of computer operating system);
• Having a high-tech lifestyle (e.g., using smart phones and digital media players);
• Being connected (such as by posting on social networking sites); and
• Being a superpower (e.g., by possessing or aiming to possess nuclear weapons).

Technologies and applications may also be resisted for cultural, religious, or ethical reasons that make certain technologies unacceptable. Examples include the banning in various cultures of cloning, human genetic modification, embryonic stem cell technologies, contraceptives, and government surveillance of a person’s activities through electronic data using data-mining technologies. Regional preferences also affect the social acceptability of a technology or resistance to it. Examples include the resistance to nuclear power in the United States, to bioengineered foods in Europe, and to nuclear weapons in Japan.

Demographic Factors

Generally, younger adults are much more prone than older adults to take risks. These risks can include sensation seeking (for example, thrill seeking and a predilection for adventurous, risky, and exciting activities), experience seeking (such as a desire to adopt a nonconforming lifestyle), disinhibition (a need for social stimulation), and susceptibility to boredom (avoidance of monotonous situations) (Zuckerman, 1979; Trimpop et al., 1984). Indeed, recent research has shown that the age-associated differences in acceptability of risk have a neuropsychological basis. For example, Lee and colleagues found that younger and older adults relied on different brain mechanisms when they were making decisions about risk (2008). This research suggests that neuropsychological mechanisms may underlie decisions on risk and cause impulsive behavior across an individual’s life span. In keeping with this effect, younger researchers, scientists, and entrepreneurs may be more willing to risk their careers and financial well-being to pursue the research, development, and application of risky but potentially disruptive, highly profitable innovations.

Geopolitical and Cultural Influences

This area of analysis includes not only the geopolitical and cultural influences that may extend beyond the boundaries of a given nation, but also the social influences stemming from a demographic that is globally impacted by technology-savvy youth. Each of these dimensions may serve to impede, or accelerate, the development and diffusion of a given technology.

Historically, there has been concern for disruption stemming from geopolitical influences in areas where transparency is minimal due to an intentional disregard for international conventions or norms. For example, although many nations have accepted limitations on the use of biological and chemical weapons for warfare, there is no guarantee that the United States will not encounter such weapons on future battlefields. Other asymmetric techniques made possible by emerging technologies may fall into this category as well.

Differing cultural beliefs, on the other hand, may be quite transparent and nonetheless lead to some degree of disruption simply by virtue of the creation of capabilities that would not be anticipated in certain cultural environments. Human cloning or more general human enhancements would fall into this category.

Overall, the strengths of each country or region in specific scientific research areas vary. Technology priorities may also vary by country or region depending on societal needs and governmental policies. So, uniformity cannot be expected.

How Technology Adoption Affects Global Economies

In a series of research papers, Comin and colleagues investigated the relationship between a country's historical rate of technology adoption and its per capita income. It stands to reason that adopting a new technology would increase a nation's wealth.

According to his findings, the rate at which countries adopted new tools hundreds of years ago strongly affects whether they are rich or poor today. Comin also has begun to uncover why there's still such a disparity in the wealth of nations, in spite of the fact that technology adoption lags have shortened dramatically in the past few decades.

In their paper An Exploration of Technology Diffusion, Comin and fellow researcher Bart Hobijn described a scientific model to track the effects of technology adoption, testing the model on 15 technologies in 166 countries from 1820 to 2003. They covered major technologies related to transportation (from steamships to airplanes), telecommunication (from the telegraph to the cell phone), IT (the PC and the Internet), health care (MRI scanners), steel (namely tonnage produced using blast oxygen furnaces), and electricity. For each technology, they compared when it was invented with when it was adopted by each country: for instance, the automobile was invented in 1885, but didn't reach many nations until the latter half of the twentieth century. 

 

According to the data, countries have adopted new technologies an average of 47 years after they are invented, with the United States and the United Kingdom leading the way in adoption rates over most of the past two centuries. More importantly, adoption lags account for at least 25 percent of cross-country per capita income differences: in short, the longer the lag in technology adoption for any given nation, the lower the per capita income.

Extensive Vs. Intensive Margins

While those findings were significant, Comin was puzzled by one apparent paradox related to the fact that technology adoption lags have diminished dramatically in recent decades, across the globe. For example, the United States launched the Adams Power Station at Niagara Falls in 1895, only a few years after the invention of a three-phase power system. India, meanwhile, didn't adopt electricity until the 1900s. But when it comes to modern technology, the lags tend to be almost identical: both the United States and India adopted cell phone technology in the 1980s. However, the difference in per capita income between those nations remains huge: in 2011, the United States had a per capita GDP of around $48,000, while India's was the equivalent of US$3,600. 

So why doesn't the shrinking gap in technology adoption lags naturally lead to a smaller disparity between per capita incomes? Comin says the answer lies in the difference between "extensive" and "intensive" margins. In his aforementioned research, technology adoption was measured according to extensive margins; that is, how long it takes a country to adopt a technology at all. But that research did not account for intensive margins; that is, the extent to which a technology is adopted by the nation as a whole. 

For instance, the extensive margin of cell phones would measure the gap between the invention of the cell phone and the date when cell phone technology first entered a country. But the intensive margin would measure the number of cell phones in a country relative to that country's population. When applicable, the intensive margin also takes into account the amount of output associated with a new technology, such as the tons of steel produced in blast oxygen furnaces in any given country. 

Comin focused on intensive margins in his working paper "The Intensive Margin of Technology Adoption," coauthored with Martí Mestieri. Studying the same 15 technologies and 166 countries from Comin's earlier research, they found that while adoption lags have diminished extensively across the globe, they have not diminished intensively. In other words, while a new technology may reach a third-world country faster than ever before, it's not necessarily reaching the majority of people in that country. 

Significantly, they found that differences in the intensive margin of technology adoption account for some 45 percent of cross-country differences in per capita income. "This intensive margin has not converged at the same rate of extensive margins," Comin says. "In fact, it has diverged."

Taken together, the results of Comin's research with Mestieri and the results of his research with Hobijn, Easterly, and Gong suggest that up to 70 percent of differences in cross-country per capita income can be explained by differences in technology adoption. 

Comin reports that future research will elaborate on how intensive adoption margins affect growth"We're getting closer at understanding the drivers of technology and its effects on the wealth of nations," he says.

http://hbswk.hbs.edu/item/how-technology-adoption-affects-global-economies