Production
https://prod.org.br/article/doi/10.1590/0103-6513.20230035
Production
Research Article

Prioritisation of criteria for sustainable and agile global manufacturing outsourcing partner selection using simulation based stochastic fuzzy PIPRECIA method

Mohammad Akhtar

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Abstract

Paper aims: To develop an effective and novel decision making method to assess the strategic priority of the criteria for sustainable and agile global manufacturing outsourcing partner (GOP) selection

Originality: The PIPRECIA Simplified method using random number based stochastic and triangular fuzzy number is applied for setting priority of the GOP selection criteria

Research method: Sustainable and agile criteria were adopted for global manufacturing outsourcing partner selection from the literature review and discussion with industry experts. Criteria weight and strategic priority was determined using a novel stochastic fuzzy PIPRECIA Simplified method using triangular fuzzy number and random number based uniform distribution of each criterion minimum-maximum ratings. This method will overcome the impreciseness, uncertainty and randomness in subjective group rating.

Main findings: Customer driven innovation, worker's training and career development, multi-skilled and flexible workforce, delivery flexibility, collaboration with partners, green manufacturing process, and worker's occupational health and safety are found to be the most important criteria in GOP selection in footwear industry. Main criteria in decreasing order of strategic priority are agile, social, environmental and economic.

Implications for theory and practice: The proposed novel method was applied with a case study of footwear industry to determine the criteria weight and priority, which will enhance supply chain agility and sustainability. The managers in the footwear industry can use the agile and sustainable criteria and proposed method easily.

Keywords

Global manufacturing outsourcing partner selection, Sustainable and agile outsourcing criteria, Fuzzy PIPRECIA, Simulation based stochastic model, Footwear industry

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Submitted date:
05/17/2023

Accepted date:
10/20/2023

656e045ca95395291b391b77 production Articles
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