An order allocation methodology based on customer repurchase motivation drivers using blockchain technology

Abstract

In the e-commerce market, the cost of customer acquisition continues to rise. One of the main profits for e-commerce companies comes from repurchase; therefore, increasing customer’s repurchase motivation can effectively increase profits. One of purposes of customer relationship management (CRM) is to protect and increase consumer loyalty through proper order allocation for e-commerce platforms. This paper presents a new repurchase motivation-driven, bi-level scheme of order allocation methodology with the aid of blockchain technology. Blockchain technology is used to integrate multiple platforms into a single platform to make allocation decisions for different consumer groups. Order allocation rules with low, medium, and high repurchase motivation drivers are constructed for different consumer groups classified by blockchain to improve consumer loyalty. This study found that the consumer group of low repurchase motivation drivers (LRMD) can be reformulated as an order allocation problem with linear time complexity. In the case of high repurchase motivation drivers (HRMD) and medium repurchase motivation drivers (MRMD), an improved simulated annealing (SA) algorithm with linear time complexity is used to solve NP-hard allocation problems. Thus, cost minimization schemes of order allocation are formed by using flexible allocation rules for e-commerce platforms with blockchain technology. Robustness checking is also designed by strengthening the constraints on repurchase motivation drivers (RMD) to prove the validity of theoretical findings.