W ith the rise of internet and ease in travelling, distance doesn’t deter us anymore from sharing information across the globe. An email can be sent across the world in the matter of seconds, and people in different continents can hold a face-to-face conversation online, without having to travel one step outside of their rooms. Also, numerous globalized social network systems allows us to easily share out thoughts and ideas with anyone else on the Web. But despite the easiness in sharing ideas worldwide, we still find plenty of ideas that don’t penetrate through many international borders; one example: bicycle ownership.
Last year at MODL, we began exploring bicycle ownership around the world. By collecting and analyzing the sporadically available data, we were able to characterize 150 different countries into four levels of bicycle ownership. And in visualizing this characterization on a world map, we saw that there were many bordering countries with similar levels of ownership. So this year, we went a step further to analyze how these levels of ownership was related to the locations of the countries. To do this, we built a model network, designating each country as a point (or node) on the network, and drawing a connecting line (edge) between two points to represent neighboring countries. And in analysis of this model, we found that countries close to each other are very likely to have similar level of ownership.
Despite the likeliness of neighboring countries to save similar levels of ownership, there are some countries whose ownership level much differs from that of its neighboring countries. Burkina Faso is an example of a country that has much higher level of ownership than its neighbors, probably because of its extensive work in promoting bike tourism. On the other hand, the UK has much lower level of ownership, which may have been influenced by poor attitudes and infrastructure for biking.
This study provides a little more insight into understanding the spatial relation of bicycle ownership. But to have a better understanding of how bicycle ownership is influenced between countries, we would need to observe how ownership is affect by other factors, such as climate, topography, cultural history, and much more. Furthermore, we hope to build a more dynamic model that will help us understand how bicycle ownership has changed over time.