Dynamic Online Bundling Pricing Model and Heuristics Analysis
Pages 102 - 105
Abstract
We propose a modeling method for the real-time and multi-stage online purchase decisions, construct an online dynamic bundle pricing model. An emergency replenishment model and a lost sale model were built for replenishment shortage. And then, heuristic algorithm is proposed to solve dynamic pricing and binding decisions. The validity and robustness of the bundling and pricing decision in ER and LS models are compared with. The results show that the two stage heuristic is the best choice when the number of products is low. The DRO heuristic in attrition rate algorithm is more effective when customers are less sensitive to product bundled price. The analysis helps to select packaging complements and choose the appropriate heuristic to calculate the bundled structure and the price of product package.
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Index Terms
- Dynamic Online Bundling Pricing Model and Heuristics Analysis
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Published In
July 2018
202 pages
ISBN:9781450364812
DOI:10.1145/3241748
Copyright © 2018 ACM.
© 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.
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- Beijing University of Technology
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 05 July 2018
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- Refereed limited
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ICEBT 2018
ICEBT 2018: 2018 The 2nd International Conference on E-Education, E-Business and E-Technology
July 5 - 7, 2018
Beijing, China
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