Optimal apparel supplier selection with forecast updates under carbon emission taxation scheme

Tsan Ming Choi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

115 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)2646-2655
Number of pages10
JournalComputers and Operations Research
Issue number11
Publication statusPublished - 21 Jun 2013


  • Carbon emission tax
  • Dynamic programming
  • Optimal supplier selection

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation
  • Management Science and Operations Research


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