Dynamic modeling of sustainable operation in green manufacturing environment

Abstract

Purpose

Globally, supply chains compete in a complex and rapidly changing environment. Hence, sustainable supplier selection has become a decisive variable in the firm’s financial success. This requires reliable tools and techniques to enhance understanding on how supplier behavior evolves with time and to select the best sustainable supplier. System dynamics (SD) is an approach to investigate the dynamic behavior in which the system alterations correspond to the system variable changes. Fuzzy logic usually solves the challenges of imprecise data and ambiguous human judgment. The paper aims to discuss these issues.

Design/methodology/approach

This work presents a novel modeling approach for integrating information on supplier behavior in fuzzy environment with SD simulation modeling technique. This results in a more reliable and responsible decision-support system. Supplier behavior with respect to relevant sustainability criteria were sourced through expert interviews and simulated in Vensim to select the best possible sustainable supplier. The simulation runs were carried out in four scenarios, namely, past, current, future and average time horizon for four different suppliers. A multi-criteria decision-making model was presented to compare results from the systems dynamics model.

Findings

An increase in the rate of investment in sustainability by the different suppliers causes an exponential increase in total sustainability performance of the suppliers. The growth rate of the total performance of suppliers outruns their rate of investment in sustainability after about 12 months.

Originality/value

While a significant work exists regarding supplier selection, little work has been found that investigates how to insure sustainable suppliers maintain their status for a long period of time.

Citation

Orji, I.J. and Wei, S. (2015), "Dynamic modeling of sustainable operation in green manufacturing environment", Journal of Manufacturing Technology Management, Vol. 26 No. 8, pp. 1201-1217. https://doi.org/10.1108/JMTM-11-2014-0120