Managing Service Systems in the Presence of Social Networks

We study the optimal service-level differentiation for service organizations whose customers engage in communication through social networks. In our setting, customers learn about service quality from both their experience and the experiences of others as reported through their social networks. We characterize a firm's optimal service differentiation policy in such settings. We then study the value of knowing the structure of the social network. We demonstrate that the value of knowing the social network structure critically depends on the correlation between customers' economic value and their social influence. The social network value is higher if the correlation is lower. We then use a novel dataset with more than 6,000 service providers across 11 cities to empirically show that many service providers face negative correlations and can benefit significantly from obtaining information on how their customers engage in social networks. Furthermore, we empirically demonstrate that a service provider's price range is an important indicator of how their customers' economic value and social influence correlate, with service providers who target high-end markets having more negative correlations