Abstract

Shipping-fee charges by online retailers have been known to impact customers' order incidence and cart size. While the importance of managing shipping fees is well documented, few studies have provided normative guidelines for e-tailers to determine optimal shipping-fee schedules. This paper provides two nonlinear mixed-integer programming models to optimize e-tailers' shipping-fee charges for single and multiple product transactions. Given e-tailers' cost information and heterogeneity across consumers' reservation prices and delivery time requirements, our models aim to concurrently determine the optimal shipping-fee schedules and product selling prices. To solve the sophisticated models in real-time, we develop search techniques based on the concept of genetic algorithms. Numerical studies indicate that the proposed methods offer attractive product prices and low shipping charges. The proposed models not only meet the online requirement of instant response time, but also draw more customers and enhance e-tailer profitability.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.