Probabilistic fuzzy decision network analyses in the development of a sustainable manufacturing strategy

• Main Author: Ocampo, Lanndon A.
• Format: text
• Language: English
• Published: Animo Repository 2014
• Online Access: https://animorepository.dlsu.edu.ph/etd_doctoral/387
• Institution: De La Salle University

Manufacturing strategy is widely recognized in literature as an important link in creating competitiveness of manufacturing firms. With current global concerns on sustainability, manufacturing industry becomes a focal point of discussion that is brought about by the impact of its manufactured products and manufacturing processes on the triple bottom line. There is thus a need for the manufacturing industry to shift from merely market-based perspective of competitiveness into more holistic and challenging issues of sustainability. Current literature has exclusive discussions on these two approaches and lacks cohesive framework that assimilates competitiveness and sustainability particularly in content strategy development. This work integrates the classical model of manufacturing strategy and sustainability into a comprehensive framework that attempts to develop a sustainable manufacturing strategy. Since this decision-making process involves several objective and subjective decision components that are linked in complex relationships in uncertain conditions, a probabilistic fuzzy analytic network process (PROFUZANP) is proposed. This method addresses the conditions of a quasi-collaborative group decision-making that best describes the expert group carried out in this work. In the proposed method, analytic network process (ANP) addresses the complex interrelationships of various decision components fuzzy set theory (FST) captures the vagueness of individual decision-making and probability theory with simulation is used to describe the randomness and uncertainty in group decision-making. The proposed framework is able to address other pertinent issues such as firm sizes, stakeholders interests that drive competitive priorities and the inherent strategic responses of manufacturing firms toward sustainability. The novel contribution of this work lies in (1) developing a framework that integrates manufacturing strategy and sustainability in identifying the content of a sustainable manufacturing strategy, and (2) proposing a methodological framework that holistically addresses uncertainty in group decision-making especially in modelling quasi-collaborative group decisions.