Price bundling for personalized recommendation

Authors:
Li-Hua Li;Rong-Wang Hsu;Shao-Shin Hung;Pei-Jung Tsai
Affiliations:
Institute of Informatics, Chaoyang University of Technology, Taiwan, R.O.C;Institute of Informatics, Chaoyang University of Technology, Taiwan, R.O.C;Department of Computer Science and Information Engineering, WuFeng Institute of Technology, Chiayi, Taiwan, R.O.C;Institute of Informatics, Chaoyang University of Technology, Taiwan, R.O.C
Venue:
ISTASC'10 Proceedings of the 10th WSEAS international conference on Systems theory and scientific computation
Year:
2010

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Abstract

Bundled pricing, the selling of two or more products or services for a single price, is becoming increasingly common in the service industry. From the consumer's perspective, the bundling of services can offer monetary savings. The pricing bundling literature has focused on many of the aspects of bundling that are associated with providing monetary savings to the consumer. There are, however, many issues with price bundling that have not been addressed. If personalized recommendation is implemented concurrently through bundling or tie-in sales strategies, businesses are likely to increase sales opportunities for their products. In other words, the businesses design the product composition and they rarely take into account customer requirement and preferences. Therefore, we proposes the periodical product bundling -recommendation system (PPB-RS), thereby analyze customer's periodical needs, preferences, and product purchasing periodicity, while taking the product periodicity and preference as reference for product composition of bundling or tie-in sales strategy. The empirical experiment from the study proves the superior performance of PPB-RS.