Date of Award
8-25-2015
Degree Type
Thesis
Degree Name
Master of Philosophy (MPHIL)
Department
Computing and Decision Sciences
First Advisor
Prof. LIU, Liming
Abstract
Intuitively, quoting dynamic lead time and price to customers based on real-time system state provides more efficient capacity utilization and increases revenue compared with quoting static lead time and price. However, dynamic quotation may require higher operational costs for the firm and it is often inconvenient to customers. This study aims to compare dynamic and static lead time and price quotations under fixed capacity and different potential demand rates. We hypothesize that there exists a potential demand rate under which the additional costs of dynamic quotation and the additional profit from dynamic quotation are equal. Thus static quotation may yield better performance under certain potential demand rates. We use an M/M/1 queuing model to model the supply system of a firm and formulate profit maximization models in an average reward criterion under both static and dynamic lead time and price quotations. Numerical analyses are presented to illustrate performances of both static and dynamic lead time and price quotation and thus find the threshold potential demand rate. Besides, we study performance of two different kinds of dynamic lead time quotation and find that when firm can decide their price, performance of dynamic lead time quotation is good enough and when firm cannot decide their price, the dynamic lead time quotation is good only when lead time sensitive factor is small and potential demand rate is big.
Copyright
The copyright of this thesis is owned by its author. Any reproduction, adaptation, distribution or dissemination of this thesis without express authorization is strictly prohibited.
Recommended Citation
Zhang, G. (2015). Joint lead time and price quotation: Dynamic or static? (Master's thesis, Lingnan University, Hong Kong). Retrieved from http://commons.ln.edu.hk/cds_etd/10/
Included in
Business Administration, Management, and Operations Commons, Management Information Systems Commons