The dynamic nature of innovation

We have seen how a combination of strong international agreements, national climate-related laws and changing societal expectations are accelerating the global transition towards net zero. As businesses and policymakers are introducing new policies and innovative products, technologies or business models, these in turn give rise to further innovations.

This reinforcing feedback mechanism is an important feature of the dynamic nature of innovation. Feedback loops encourage further innovation and help to shift the expectations, decisions and behaviours of individuals, businesses and policymakers towards decarbonisation (Rubin, 2011).

Growing knowledge base and adoption cycles

Innovation builds on previous innovations. As innovation occurs, the knowledge base on which to drive further innovation expands. This incentivises new or improved products and services to emerge as well as enabling technologies and processes. This, in turn, begins to shift social norms and increase the adoption of these innovations.

Innovators also build on previous knowledge and experience to take advantage of opportunities and resolve existing problems and constraints. The resulting knowledge capital becomes a key asset that, like financial capital, generates future benefits. Unlike other capital, knowledge capital is not subject to decreasing returns and does not deplete with use. In fact, the reverse is true: ideas feed off each other and tend to be self-generating.

For example, smartphones were a technological innovation that initially built on prior electrical and mobile telephone innovations. People with access to these phones then developed software that made them more desirable and useful, encouraging more people to buy them, and so a positive feedback loop was established.

The adoption of new technologies is commonly depicted as a bell curve that divides consumers or adopters into five main categories, as shown in Figure 2.

This figure shows a bell-shaped curve illustrating the typical technology adoption cycle, which begins with innovators and early adopters (who make up the initial 2.5% and 13.5%, respectively). These two groups are the visionaries and enthusiasts who welcome change and accept that the benefits of using new technologies will require support in overcoming barriers and switching costs.

If a new technology is to break into the market, the gap between early adopters and the early and late majority needs to be bridged. If this is successful, 34% will comprise of the early majority and 34% will comprise of the late majority, making up 68% of mainstream adopters. 

Even if a new technology successfully breaks into the market, there will likely always be a percentage of laggards (approximately 15%) who are classified as resisters and refuse to adopt an innovative idea.

Figure 2: A typical technology adoption cycle.
(Adapted from: Yudelson, 2018)

In this model, the five groups are distinguished by how likely they are to accept and adopt a new innovation (eg product, service or technology). Consumers typically rely on advice from people within their own group. This creates a gap between each of the five groups and represents a challenge for those trying to bring an innovation to market. Bridging the widest gap, which lies between the early adopters and the early majority, is often seen as critical for an innovation to successfully break into the market and become profitable (Business-to-you, 2020).

Existing technologies tend to go through a life cycle from R&D, to growth and maturity, to a plateau where the potential gains from a growing knowledge base declines. As enough actors in the market then shift their investment towards new technologies, the cost of deployment comes down, making further investment in new technologies increasingly attractive.

Structural transitions

At the start of this millennium, the UK still generated most of its electricity from coal. By 2020, the country had virtually eliminated coal from its electricity system (Department for Business, Energy & Industrial Strategy, 2020). By that time, investment in renewables had also by far surpassed investment in fossil fuels worldwide (IEA, 2020). By 2030, the UK and several other countries will ban the sale of combustion engine cars, in favour of electric vehicles (EVs) (Calma, 2020).

These shifts signal a structural transition away from carbon-intensive energy sources towards cleaner and cheaper low carbon alternatives. Theses transitions also reflect four key reinforcing feedback mechanisms relevant to innovation:

  1. Learning effects: Cost tend to fall with increased experience and expanding deployment. As innovations are applied and tested in the market, lessons are learned on how to manufacture, distribute, install, run and maintain equipment more efficiently.
  2. Economies of scale in production and distribution: After the initial, large fixed costs of deploying innovations have been recuperated, larger production and distribution networks generate lower unit costs, encouraging increased output and further driving unit costs down.
  3. Network and coordination effects: Implementing innovations in collaboration with – or at the same time as – others can multiply the benefits for individual businesses. The more businesses or societal actors who are taking similar action, the higher the potential gains. Sometimes, these network effects may involve spill overs across sectors.
  4. Social and institutional feedbacks: New social norms increase the demand for clean technologies, thereby spurring innovation and learning. New business lobbies and trade union demands induce supportive policies to support new innovations (Boyd, Green & Stern, 2015).

Encompassing all the above is the role of changing expectations. When new technologies are seen as superior, resulting behavioural changes facilitate their successful adoption. Investment in supporting infrastructure and networks increases. Social norms change and new institutions, such as ministries, agencies and business lobbies, are created. In addition, governments often enact supportive policies, such as carbon taxes, deployment support and standards and regulations (Krugman 1991, Matsuyama 1991).

These important amplifying feedbacks generate a structural transition, or tipping point, that can lead to rapid shifts in key technologies and behaviours (Farmer et al., 2019). As a rule, structural shifts tend to progress frustratingly slowly, even when the necessity for change is clear and the opportunities apparent. Often, after decades of inaction, a series of rapid and inexorable shifts to new solutions or systems ensues (Otto et al., 2020).