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I would like to combine two approaches, survival analysis and social network
analysis, and I'm a bit struggling in doing so.
I have a dataset including information from 13,000 customers of a company.
This company is operating in a contractual business, meaning that customers
sign a contract with the company when they start using the product/ service
and cancel this contract when they do no longer want to use the product/
service. Imagine a cable TV provider or a telecommunication service
provider. For each of these customers I know when the customer signed his/
her contract, i.e. the acquisition date. Additionally I know whether the
customer is still with the company or not and, in case s/he is not, how long
s/he has been with the company before resigning. In addition to that I also
have information about the social relationships between customers.
The question I would like to ask is: Is a customer more likely to leave
(i.e. resign) when one of his 'friends' left previously? Essentially this
means that I would like to incorporate social network effects into survival
analysis (e.g. Cox regression). My idea is somewhat to make the hazard rate
of one customer dependent on the hazard rates of this customer's friends,
but I'm not really sure how to do that.
Any input from your side would be very much appreciated!
Thanks in advance,
Assistant Professor of Marketing
ESCP-EAP European School of Management
79, Avenue de la République | 75011 Paris | France
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