A mixed integer programming optimization of bundling and pricing strategies for multiple product components with inventory allocation considerations
College
Gokongwei College of Engineering
Department/Unit
Industrial Engineering
Document Type
Conference Proceeding
Source Title
IEEE International Conference on Industrial Engineering and Engineering Management
Volume
2017-December
First Page
16
Last Page
20
Publication Date
2-9-2018
Abstract
© 2017 IEEE. Bundling has been practiced in different industries because of the numerous opportunities that it can provide both to the company and to the customers. However, the implementation of bundling entails the need for retailers to face several challenges in coming up with decisions that will successfully actualize the benefits. This is why literature has witnessed a spurt in the articles dedicated to the study of bundling. This study proposes a mixed integer programming model that maximizes profit by simultaneously optimizing the bundling and the pricing strategies, along with the inventory allocation decisions, of a firm having multiple product components. Results showed that the bundling decisions are dependent on the customer's preference and the profit margin of the bundles which are influenced by different factors including cost, inventory, and valuation. Increasing valuation can increase profit but can also threaten the profit margin of other bundles unlike cost reduction which will always lead to higher profits. Finally, inventory reduction limits the profit of the firm while making mixed bundling selling strategy or pure components selling strategy more profitable to adopt.
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Digitial Object Identifier (DOI)
10.1109/IEEM.2017.8289842
Recommended Citation
Barrios, P., & Cruz, D. (2018). A mixed integer programming optimization of bundling and pricing strategies for multiple product components with inventory allocation considerations. IEEE International Conference on Industrial Engineering and Engineering Management, 2017-December, 16-20. https://doi.org/10.1109/IEEM.2017.8289842
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