Publications [#329111] of David B. Dunson

Papers Published

1. Durante, D; Paganin, S; Scarpa, B; Dunson, DB, Bayesian modelling of networks in complex business intelligence problems, Journal of the Royal Statistical Society. Series C: Applied Statistics, vol. 66 no. 3 (April, 2017), pp. 555-580, WILEY [doi]
   (last updated on 2024/04/19)

   Abstract:
   Complex network data problems are increasingly common in many fields of application. Our motivation is drawn from strategic marketing studies monitoring customer choices of specific products, along with co-subscription networks encoding multiple-purchasing behaviour. Data are available for several agencies within the same insurance company, and our goal is to exploit co-subscription networks efficiently to inform targeted advertising of cross-sell strategies to currently monoproduct customers. We address this goal by developing a Bayesian hierarchical model, which clusters agencies according to common monoproduct customer choices and co-subscription networks. Within each cluster, we efficiently model customer behaviour via a cluster-dependent mixture of latent eigenmodels. This formulation provides key information on monoproduct customer choices and multiple-purchasing behaviour within each cluster, informing targeted cross-sell strategies. We develop simple algorithms for tractable inference and assess performance in simulations and an application to business intelligence.