Online pricing with bundling and coupon discounts

Abstract

We propose an online pricing strategy by utilising product bundling and coupon discounts. Given customer’s purchase behaviour and preference for bundling and coupon, we propose a nonlinear mixed-integer programming model to determine the most appropriate bundle discount and instant coupon so as to maximise e-tailer’s profit. A fast heuristic algorithm is designed to implement the proposed model online in real time. We investigate the robustness of the proposed method by examining how uncertainties in system parameters affect performance. Through collaborative optimisation, we offer important insights and managerial implications, and show how marketers can attract more purchase and maximise profit by properly integrating marketing tools such as bundling and coupon.

Keywords:

• online pricing
• product bundling
• coupon discount
• nonlinear mixed-integer programming
• sensitivity analysis

Acknowledgements

The authors thank the anonymous reviewers for insightful comments. This work was supported by National Science Foundation of China [grant number 71490725], [grant number 71302064], [grant number 71371062], [grant number 71571058], [grant number 71501057]; National Key Basic Research Program of China [grant number 2013CB329600]; the Humanity and Social Science foundation of Ministry of Education [project number 12YJC630073]; Research Fund for the Doctoral Program of Higher Education of China [project number 20120111120029] and CCF-Tencent Open Fund [CCF-TencentRAGR20140109].

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Amazon.cn is a Chinese subsidiary of Amazon.com and use the same recommendation technology as its parent company.

2. One-product transaction consists of book The Help, two-book transaction {The Help, A Thousand Splendid Suns} , three-book transaction {The Help, A Thousand Splendid Suns, The Memory Keeper's Daughter}  and four-book transaction {The Help, A Thousand Splendid Suns, The Memory Keeper's Daughter, What the Dog Saw}.

Additional information

Funding

This work was supported by National Science Foundation of China [grant number 71490725], [grant number 71302064], [grant number 71371062], [grant number 71571058], [grant number 71501057]; National Key Basic Research Program of China [grant number 2013CB329600]; the Humanity and Social Science foundation of Ministry of Education [project number 12YJC630073]; Research Fund for the Doctoral Program of Higher Education of China [project number 20120111120029] and CCF-Tencent Open Fund [CCF-TencentRAGR20140109].