Proposed SNA: Collaborative Consumption and Social Networks

Stefanie Chang 

(I will be taking D217.)

The age-old human practices of renting, lending, swapping, bartering, and gifting[1] are being transformed through technology into a new phenomenon: collaborative consumption. From ad hoc asks and offers coming through the Social List, to Craigslist, Zipcar, and Airbnb, today’s increasingly urbanized and connected populations are sharing everything from goods to skills to places and experiences while redefining the value of possession.

For my social network analysis, I’d like to look at the characteristics of the real-world and virtual network of acquaintances/friends/users of a collaborative consumption service. Possible subjects could be Tufts Bikes or Zipcar, or possibly even the connections between all of these sharing services themselves. My hypothesis is that participation in social networks and participation in collaborative consumption will be mutually reinforcing. Attributes such as age and participation in multiple social networking services will also correlate to a higher chance of collaborative consumption participation. Attribute analysis would yield some insight into what kind of user profile would be a good indicator of sufficient trust, (essentially the currency of collaborative consumption,) and thus participation.

In my survey, I could ask questions along the lines of:

-          Mark all of the social networking sites you participate in. (Enumerated list, with an option for “other” as well.)

-          Mark all of the collaborative consumption sites you participate in. (Enumerated list with an option for “other” as well.)

-          Age

-          Gender

-          Did you participate in swapping or sharing before signing up with an “official” service?

-          Where did you grow up?

-          Where do you currently live?

-          Rural/suburban/urban?

-          Household annual income?

I would look at the social network of a service’s members (and how they are connected to each other), and analyze both within the network and across peoples’ individual networks. Data may be available directly (if using a subject like Tufts Bikes), or possibly through Facebook for sites that are integrated with that. I could also survey a random sampling of people, and survey each of their networks.

This idea needs further development, but I’m looking forward to tweaking it and doing some analysis.

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[1] http://www.collaborativeconsumption.com
Another great site for shared consumption models and discussion: http://www.shareable.net