Optimizing customer's selection for configurable product in B2C e-commerce application

Many companies provide configurable products on Internet to satisfy customers' diversified requirements. Most of business-to-consumer (B2C) e-commerce software systems use tree- or wizard-like approaches to guide customers in configuring a customized product on Internet web pages. However, customers may feel confused while they are selecting components of a product from option lists, since they are usually not familiar with the technical details of these components. A few e-commerce sites use recommendation systems to provide suggested products for customers, but they have to maintain user profiles and have limitations such as new user problem and complexity. Therefore, they may not be suitable for small and medium-sized enterprises. This research proposes a new approach to help customers configure their expected products. By using this approach, once a customer inputs the levels of importance of requirements, total budget of the expected product, the software system can figure out a customized product which maximally meets the customer's expectations, and can also provide the suboptimal solutions for further selections. A mathematical model to formulate this optimization problem is established. A case study is used to demonstrate the feasibility and effectiveness of this approach.