This examine applies Bayesian community technique to analyse the relationships among customer online shopping behaviours and buyer requirements. This research first proposes an preliminary behaviour-requirement relationship model as area data. Through conducting a survey buyer data is collected as evidences for inference of the relationships among the many factors described in the mannequin. After making a graphical structure, this study calculates conditional probability distribution among these components, and then conducts inference through the use of the Junction-tree algorithm. A set of helpful findings has been obtained for customer online buying behaviours and their requirements with motivations. These findings have potential to help businesses adopting more appropriate online system growth.

Interestingly, the youngest internet buyers (16-24 yr olds) are the keenest to maintain their social networking activity separate from their buying activity. More than half (57{d8f2b0aca19448ff880590c084a6732ed34c3e97f3c01f69fc4b0e6e98494cf7}) don’t love sites equivalent to Twitter and Facebook to be linked with their buying history …