Back to Search Start Over

Crowdrebate: An Effective Platform to Get more Rebate for Customers

Authors :
Ni, Wangze
Chen, Nian
Cheng, Peng
Chen, Lei
Lin, Xuemin
Ni, Wangze
Chen, Nian
Cheng, Peng
Chen, Lei
Lin, Xuemin
Publication Year :
2021

Abstract

To encourage users to buy more products, many online stores offer coupons. When a customer finds that the price of the products she/he wants to order is below the threshold of a coupon, she/he might want to place the order together with others to meet this threshold and enjoy more instant rebates. However, to conduct these orders and deliver products to receivers, users may need to pay extra delivery costs. When an order comprises several receivers' requests, the products in the order should first be delivered from stores to an assigned warehouse, packed into different packages, and delivered to the different receivers. It may be costly than directly delivering products from stores to receivers. For the benefits of buyers, we propose a platform, the Crowdrebate platform, which collects requests from users, groups requests into a set of orders to get more rebates, and relays products to different receivers in an order. The platform will make a profit by getting a proportion from the benefit of the receiver (defined as the rebate minus the extra cost) of orders as its revenue. In this paper, we define the Crowdrebate problem, which aims to maximize the benefit of receivers. We prove the NP-hardness of the Crowdrebate problem. Therefore, we propose a heuristic solution to address the problem. Moreover, we evaluate the effectiveness and efficiency of our algorithm via comprehensive experiments. © 2021 IEEE.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1363067207
Document Type :
Electronic Resource