Mass customization of travel packages: data mining approach

Abstract

This article employs a mass customization strategy to design travel packages that minimize the operation and processing costs for the service provider on one hand, while aligning the components of the packages to maximize customer satisfaction on the other. Data mining is used to identify rules of association to develop this model. Hidden relations in the massive travel agencies’ databases are revealed by using the association rules technique to customize travel packages according to customers’ requirements. This approach leads to fewer, but more manageable and popular travel package promotions. The overall package selection problem is modeled as an integer program that minimizes costs of operation and processing. Two different solution approaches were used: a mathematical modeling language approach and a heuristic algorithm approach. An illustrative numerical example based on a synthetic data set is also presented.