Blog Assignment: Social Networks and Car Pooling

It was Wednesday evening, around 6pm. The traffic was heavy as always during rush hours. I was coming back home after have run along Charles River on the Boston side. When I was crossing the bridge that connects Boston to Cambridge I don’t know why, I started looking to all those people alone inside their cars, waiting 5 minutes to move just a few meters. Hours and more hours every day wasted in the crazy traffic. It reminded me a year ago, before coming to Hult, when I used to spend 40 minutes to drive only 8 kilometers from home to work and on the way back. I started counting the number of cars with only one person. Out of 72 cars only 12 had more than one person. I asked myself, why all those people were not using the T, a bus (mass transportation options) or even sharing their cars with other people. It would help a lot to reduce traffic and improve their quality of life.

Someone would argue that is impossible to implement a system that allows people to share their vehicles with other people, that individuals like privacy and don’t want to share their sacred time inside their cars with someone else, that they don’t want to depends on other people schedules to move around the city, in other words, there will be ten thousand of arguments against the idea.

Nowadays car-pooling exists as a brave attempt of some to improve people lives. You can find websites and apps that try to help others to share their rides. In some cities car-pooling is implemented by the government but using a fear tactic of punishment (by issuing fines).

What I believe is missing in this whole idea is the use of a powerful tool to create a real map of possibilities that allows people to share their cars. This tool is Social Network Analysis. I also believe that in order to be successful, a study should be made using a small network. We could have at first a small sample and afterwards expand the results to a large number of people. It is important not rely on governments since the bureaucracy and different interests would create barriers against the initiative.

To make things easier I am going to get EF as an example of where we could start testing the tool to solve the issue. It is a company that cares about social responsibility and is open to any new idea that helps the community which is part of the company. The first step would be to collect as many data as possible. The data would be gender, age, address, friends at work, friends at “home” (community), time to commute, type of transportation, and distance from home to work. I think that would be easy to collect these data since we are talking about only simple information. The HR might have most of them and if not, it is possible to make a survey with all employees to gather all the complementary information.

After having all information compiled we advance to the second step that would be to create the network map. We could use for example UCINET and NETDRAW as tools to create the map. The third step would be to analyze the data using network measures. In this case the most important measures are density and distance of the entire group and degree (number of connections), betweenness (connector between most important nodes) and closeness (lowest distance between nodes) of all individuals. What we are looking for here when analyzing the data is for people that live closer, are related to each other (as friends) and use car as the way of commuting to work.

Lastly we would have to make the connections available and present them to all people involved in the organization in order to create awareness of how these people can start sharing their rides when they come to work and on the way back.

SNA would be used all the way in this analysis. First in identifying who are the possible people that can share their cars with other people. Second in making the connections with these people and showing them all possibilities that they have when they are looking for someone to commute together. And finally by integrating possible candidates to an existing network, by using the map provided during the analysis.

By using SNA, EF in this case, would be able to increase the number of interactions with its employees outside work (when they are sharing their rides), reduce its carbon footprint because its employees are going to use less cars to move around, and help all community by being an example on how to implement a simple idea that could be expanded to the entire city.

Jose Grecco