The authors explore the role of hubs (people with an exceptionally large number of social ties) in diffusion and adoption. Using data on a large network with multiple adoptions, they identify two types of hubs-innovative and follower hubs. Contrary to recent arguments, hubs tend to adopt earlier in the diffusion process, even though they are not necessarily innovative. Although innovative hubs have a greater impact on the speed of the adoption process, follower hubs have a greater impact on market size (total number of adoptions). Importantly, a small sample of hubs offers accurate success versus failure predictions early in the diffusion process.

No abstract

No abstract

No abstract

The authors develop an approach to reveal segmentation in response to marketing variables at a brand-level perspective. In the proposed procedure, response segmentation is analyzed separately for each brand instead of jointly across all brands. This yields a segmentation picture oriented toward the potential targeting objectives of the brand manager. Using the multinomial logit and probabilistic mixture models, the procedure first calibrates consumer response in the brand choice decision. Individual-level measures of response for a given marketing variable (e.g., price) are then computed, and brand-level segments are obtained by clustering brand-specific response. Using scanner panel data, the approach is applied to price response segmentation for brands that compete in the ground coffee category. The results illustrate a series of implications for brand strategy, particularly the potential for targeting marketing activity to different response segments.