Strategic responses decision model in developing a sustainable manufacturing strategy
College
Ramon V. Del Rosario College of Business
Department/Unit
Management and Organization Department
Document Type
Conference Proceeding
Source Title
2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2014 - 7th HNICEM 2014 Joint with 6th International Symposium on Computational Intelligence and Intelligent Informatics, co-located with 10th ERDT Conference
Publication Date
1-1-2014
Abstract
This work presents a decision model that highlights the integration of manufacturing strategy and sustainability with strategic responses as a significant component. Due to the complexity and uncertainty of the decision components and elements derived from literature, a proposed hybrid MCDM approach in the form of an integrated probabilistic fuzzy analytic network process (PROFUZANP) is presented. In the proposed method, analytic network process (ANP) handles complexity of the decision model. Fuzzy set theory is used to describe vagueness in decision-making which is carried out by eliciting judgment in pairwise comparisons using linguistic variables with corresponding triangular fuzzy numbers (TFNs). Probability theory is used to handle randomness when aggregating experts' judgments. Results are reported in this paper. Insights were also discussed. © 2014 IEEE.
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Digitial Object Identifier (DOI)
10.1109/HNICEM.2014.7016191
Recommended Citation
Ocampo, L. A., Clark, E., & Tanudtanud, K. (2014). Strategic responses decision model in developing a sustainable manufacturing strategy. 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2014 - 7th HNICEM 2014 Joint with 6th International Symposium on Computational Intelligence and Intelligent Informatics, co-located with 10th ERDT Conference https://doi.org/10.1109/HNICEM.2014.7016191
Disciplines
Business Administration, Management, and Operations
Keywords
Sustainability; Industrial ecology; Multiple criteria decision making
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