Environmental performance evaluation of suppliers: A hybrid fuzzy multi-criteria decision approach

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TUZKAYA G., ÖZGEN A., ÖZGEN D., TUZKAYA U. R.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, cilt.6, sa.3, ss.477-490, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 6 Sayı: 3
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1007/bf03326087
  • Dergi Adı: INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.477-490
  • Anahtar Kelimeler: Decision-making, Environmental criteria, Fuzzy sets, Green supply chain, ANALYTIC NETWORK PROCESS, EXTENT ANALYSIS METHOD, PROMETHEE METHOD, SELECTION, AHP, MODEL, CRITERIA, RANKING, DESIGN, MANAGEMENT
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Increasing environmental problems enforce companies to be more environmental responsible. A company's environmental performance is not only related to the company's inner environmental efforts, but also it is affected by the suppliers' environmental performance and image. As a stakeholder of the company, a supplier with bad environmental image affects badly the company's environmental image. Also, raw materials and semi-finished products supplied from out of the company recourses-suppliers-affects the products environmental features such as life cycle, re-usability, re-manufacturability, hazardous substances, etc. Considering these direct and indirect effects, managers should also consider environmental performances of their suppliers in their supplier evaluation process. In this paper, a methodology for the evaluation of suppliers' environmental performances is proposed. In this methodology, a hybrid Fuzzy-Analytic Network Process and Fuzzy-Preference Ranking Organization METHod for Enrichment Evaluations approach is utilized. Additionally, a numerical example is given to foster the better understanding of the methodology and the obtained results are analyzed with sensitivity analyses.