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The decision support framework for developing Ecodesign at conceptual phase based upon ISO/TR 14062

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  • Kengpol, Athakorn
  • Boonkanit, Prin

Abstract

The objective of this research is to propose a decision support framework for developing Ecodesign at the conceptual design phase based upon ISO/TR 14062 (2002). The contribution of this research lies in the decision support model for integrating analytic network process (ANP) and the distance-to-target (DT) method in order to calculate a single score Ecodesign concept indicator that makes the new product more eco-effective than the baseline product. The highlight of this framework is that the model can reduce bias and ease the decision-making process as well as enhance presentation of the new idea to stakeholders. A case study, recommendations, limitation, and further research are also presented.

Suggested Citation

  • Kengpol, Athakorn & Boonkanit, Prin, 2011. "The decision support framework for developing Ecodesign at conceptual phase based upon ISO/TR 14062," International Journal of Production Economics, Elsevier, vol. 131(1), pages 4-14, May.
  • Handle: RePEc:eee:proeco:v:131:y:2011:i:1:p:4-14
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Miguel Afonso Sellitto & Juliane Luchese & Jéssica Mariella Bauer & Gislaine Gabrielle Saueressig & Cláudia Viviane Viegas, 2017. "Ecodesign Practices in a Furniture Industrial Cluster of Southern Brazil: From Incipient Practices to Improvement," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-25, March.
    2. Thies, Christian & Kieckhäfer, Karsten & Spengler, Thomas S. & Sodhi, Manbir S., 2019. "Operations research for sustainability assessment of products: A review," European Journal of Operational Research, Elsevier, vol. 274(1), pages 1-21.
    3. Cicconi, Paolo & Landi, Daniele & Germani, Michele & Russo, Anna Costanza, 2017. "A support approach for the conceptual design of energy-efficient cooker hoods," Applied Energy, Elsevier, vol. 206(C), pages 222-239.
    4. Brandenburg, Marcus & Govindan, Kannan & Sarkis, Joseph & Seuring, Stefan, 2014. "Quantitative models for sustainable supply chain management: Developments and directions," European Journal of Operational Research, Elsevier, vol. 233(2), pages 299-312.
    5. Subramanian, Nachiappan & Gunasekaran, Angappa, 2015. "Cleaner supply-chain management practices for twenty-first-century organizational competitiveness: Practice-performance framework and research propositions," International Journal of Production Economics, Elsevier, vol. 164(C), pages 216-233.
    6. Kheybari, Siamak & Rezaie, Fariba Mahdi & Farazmand, Hadis, 2020. "Analytic network process: An overview of applications," Applied Mathematics and Computation, Elsevier, vol. 367(C).
    7. Marcus Brandenburg & Tobias Rebs, 2015. "Sustainable supply chain management: a modeling perspective," Annals of Operations Research, Springer, vol. 229(1), pages 213-252, June.
    8. Chia-Nan Wang & Ming-Hsun Lin & Chung-Jen Huang & Ching-Chiu Huang & Ruei-Yuan Liao, 2017. "Using TRIZ to Improve the Procurement Process of Spare Parts in the Taiwan Navy," Sustainability, MDPI, Open Access Journal, vol. 9(10), pages 1-12, October.
    9. Schrettle, Stefan & Hinz, Andreas & Scherrer -Rathje, Maike & Friedli, Thomas, 2014. "Turning sustainability into action: Explaining firms' sustainability efforts and their impact on firm performance," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 73-84.

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