The transportation system is on the verge of a rapid transformation and consumers are at the core of this change. In the last century, consumer demand for cars as a key household product paved the way for the age of fossil fuels. Now, as the emerging market’s middle class grows by the hundreds of millions, they are demanding the same consumer goods the developed world enjoys, ie. cars.

Cars and trucks are responsible for about a fifth of global carbon emissions. If the transportation needs of the emerging middle classes in developing regions are to be served by fuel-based technologies, the climate mitigation goals of COP21 will be impossible to reach.

In order to make a change, billions of people around the globe need to change the way they get around by continuing to adopt new technologies like electric cars or smart-phone enabled solutions. Businesses need to anticipate the consumer demand for these new solutions. Governments will need to implement new policy decisions to accelerate the adoption of sustainable solutions.

To understand today’s transport and mobility revolution, Dalia conducted a study with over 43,000 respondents from 52 countries all over the world. The survey questions for this study were created in collaboration with more than a dozen leading researchers in the field, to understand how new technology solutions will shape the future of mobility and transportation. The MIT Energy Initiative is using this dataset for a large study called “Mobility of the Future”. The survey underlying the dataset will take place multiple times per year and is open to participation from researchers and businesses. You can explore the results of the survey using this interactive dashboard here.

Stay tuned for more in-depth articles about what modes of transportation people use worldwide, the future car market (EVs & driverless cars), public support for sustainable transportation policy solutions, and the use of on-demand transport (apps, and ride sharing).

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About the survey:

The survey took place between December 5, 2016 and February 2, 2017. The total sample size of 43,034 was distributed across 52 countries based on overall population and feasibility estimates. The sampling process took into account current population distributions with regard to gender and age (14–65).

In order to obtain census representative results for the overall estimates within each country, the data were weighted by age and gender based upon the most recent statistics available through the International Data Base of the U.S. Census Bureau. Taking into account an estimation of the design effect based on the weights distribution, the average Margin of Error for overall population estimates within each country is 4%.