A Mashup Application to Support Complex Decision Making for Retail Consumers

Abstract

Purchase processes often require complex decision making and consumers frequently use Web information sources to support these decisions. However, increasing amounts of information can make finding appropriate information problematic. This information overload, coupled with decision complexity, can increase time required to make a decision and reduce decision quality. This creates a need for tools that support these decision-making processes. Online tools that bring together data and partial solutions are one option to improve decision making in complex, multi-criteria environments. An experiment using a prototype mashup application indicates that these types of applications may significantly decrease time spent and improve overall quality of complex retail decisions.