The influence of social communications networks on intentions to purchase on the web

Despite the increased offering of online communication channels to support web-based retail systems, there is limited marketing research that investigates how these channels act singly, or in combination with offline channels, to influence an individual's intention to purchase online. If the marketer's strategy is to encourage online transactions, this requires a focus on consumer acceptance of the web-based transaction technology, rather than the purchase of the products per se. The exploratory study reported in this paper examines normative influences from referent groups in an individual's on and offline social communication networks that might affect their intention to use online transaction facilities. The findings suggest that for non-adopters, there is no normative influence from referents in either network. For adopters, one online and one offline referent norm positively influenced this group's intentions to use online transaction facilities. The implications of these findings are discussed together with future research directions.

Stability criteria for unsupervised temporal association networks

A biologically realizable, unsupervised learning rule is described for the online extraction of object features, suitable for solving a range of object recognition tasks. Alterations to the basic learning rule are proposed which allow the rule to better suit the parameters of a given input space. One negative consequence of such modifications is the potential for learning instability. The criteria for such instability are modeled using digital filtering techniques and predicted regions of stability and instability tested. The result is a family of learning rules which can be tailored to the specific environment, improving both convergence times and accuracy over the standard learning rule, while simultaneously insuring learning stability.