Optimal apparel supplier selection with forecast updates under carbon emission taxation scheme |
| |
Authors: | Tsan-Ming Choi |
| |
Affiliation: | Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hung Hom, Hong Kong |
| |
Abstract: | ![]() Carbon emission tax is an important measure for sustainable supply chain management. This paper studies an optimal supplier selection problem in the fashion apparel supply chain in the presence of carbon emission tax. We consider the scenario in which there are multiple suppliers in the market. In the basic model, each supplier offers a supply lead time and a wholesale pricing contract to the fashion retail buyer. For the fashion retail buyer, the supplier which offers a shorter lead time allows it to postpone the ordering decision with updated and better forecast, and also a smaller carbon tax. However, the wholesale price is usually larger. We propose a two-phase optimal supplier selection scheme in which phase one filters the inferior suppliers and phase two helps to select the best supplier among the set of non-inferior suppliers by multi-stage stochastic dynamic programming. The impacts brought by different formats of carbon emission tax are explored. Finally, we examine an extended model in which there is a local supplier who offers a buyback contract and accepts product returns. Insights from the analysis are discussed. |
| |
Keywords: | Optimal supplier selection Carbon emission tax Dynamic programming |
本文献已被 ScienceDirect 等数据库收录! |
|