"For example, the model could allow us to quantitatively determine why people may recycle or not, insulate their homes or not and buy energy-efficient light bulbs or not," Gallo told environmentalresearchweb.

Gallo and colleagues say their work could provide policymakers with a unique tool for designing cost-effective policies capable of inducing dramatic behaviour change in a population. That would take place by tapping into powerful "imitation forces" that are inextricably linked to sudden structural changes. "Governments could thus encourage significant behaviour change without having to impose unpopular 'nanny state' polices on the population," said Gallo.

Such initiatives include raising specific environmentally-related taxes, subsidising an environmentally-friendly product or concentrating effort and resources on a certain socio-economic group. "More importantly, the tool could identify potential tipping points and offer options to actually trigger a sudden transition to a new 'equilibrium'," he explained.

More generally, such an approach could also encourage experts from the physical and social sciences, and policy-making, to work together and develop innovative and evidence-based policy options. "This multidisciplinary approach has been notably absent in the UK and Europe," said Gallo.

The model identifies the key drivers and preferences behind people's decisions. "What determines whether an individual buys a new energy-efficient light bulb instead of an old incandescent one?" asked Gallo. "What impact has the cost, as opposed to energy efficiency or the colour of the light? This knowledge would allow us to influence consumer behaviour."

He stresses that the model is not trying to turn public opinion per se but offers the potential to understand how and why people adopt certain behaviours and make certain decisions.

The model is made up of two distinct components. The first is a mathematical representation of the decision-making process, which links decisions taken by individuals to decisions taken by the entire population. The second is a method for measuring the factors involved in these decision-making processes in specific circumstances, such as which mode of transport to choose when travelling to work.

The first part of the model contains an imitation element because we are social creatures influenced by other people's choices and opinions. We are subject to peer pressure and tend to conform to the values held by other people around us, explained Gallo. If most people in our neighbourhood recycle, for instance, we will do so too.

The second part of the model contains a set of empirical factors that quantify the "weight" of underlying variables, such as the cost or energy consumption of light bulbs, and the extent to which we are influenced by other people's choices. According to Gallo, this approach has been designed so that it can be applied to the vast body of data found in existing polls and surveys.

The mathematics of the model comes from the second law of thermodynamics in physics coupled with economic theories of discrete choice developed by Nobel Laureate and economist Daniel McFadden.

The researchers now plan to implement their model by analysing widely available and abundant "micro-level" data, such as that in existing surveys and polls. "Once the reliability of the model has been consolidated, our next step will be to apply it to a number of real case studies - with the issue of climate change taking priority," said Gallo.

The work is being published in the book Mathematics and Society (Springer). A related paper on the topic Phase transitions in social sciences: two-populations mean field theory will appear shortly in the International Journal of Modern Physics B.