A two-stage fuzzy-AHP model for risk assessment of implementing green initiatives in the fashion supply chain

Xiaojun Wang, Hing Kai Chan, Wai Yee Yee, Ivan Diaz-Rainey

Research output: Journal article publicationJournal articleAcademic researchpeer-review

255 Citations (Scopus)


Green or environmental concerns are drawing more and more attention both in academia and industry. Careful deployment of green initiatives or policies could not only fulfil the requirements of environmental legislation but also lead to a competitive advantage for firms. Nevertheless, making optimal decisions in this regard is not easy. This is principally due to two reasons: (1) the qualitative nature of, and (2) the uncertainty associated with, the parameters involved in the decision-making process. Analytic hierarchy process could be a useful tool to tackle the first challenge because of its ability to handle both qualitative and quantitative variables (decision criteria). Unfortunately, this approach is inadequate at addressing the uncertainties common in real-life applications. This challenge is particularly noticeable in the fashion industry since demand is very volatile, and there are many uncertain variables associated with the whole supply chain. As a result, this paper blends fuzzy logic, which is a popular method of incorporating uncertain parameters into the decision-making process, with analytic hierarchy process to form a selection (decision-making) model for different green initiatives in the fashion industry. The rationale behind the model is to analyse the associated risk of different alternatives, subject to different factors, be they deterministic or not. A numerical example is included in this paper to demonstrate how the proposed model works.
Original languageEnglish
Pages (from-to)595-606
Number of pages12
JournalInternational Journal of Production Economics
Issue number2
Publication statusPublished - 1 Feb 2012


  • AHP
  • Fashion
  • Fuzzy
  • Green initiative
  • Risk analysis

ASJC Scopus subject areas

  • General Business,Management and Accounting
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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