Mitigating Bullwhip in Integrated Remanufacturing and Refurbishment Supply Chains: A Forecast-Control Framework

This study develops a stochastic analytical framework to examine how concurrent remanufacturing and refurbishment processes influence variability propagation and the bullwhip effect (BWE) in multi-echelon closed-loop supply chains (CLSCs). The model integrates ARIMA-based forecasting with a control-theoretic replenishment structure and incorporates a third-party refurbishment provider who functions as a distributor, allowing explicit analysis of how their decisions interact with retailer and manufacturer policies. Our results show that, unlike in traditional forward supply chains, demand amplification in CLSCs is governed primarily by replenishment parameters and the remanufacturing–refurbishment mix rather than by demand variance. Remanufacturing in general dampens inventory variations at third-party and generates lower amplification than refurbishment when retail replenishment parameters are relatively low. In contrast, at higher replenishment policy values, refurbishment-dominated CLSCs show slightly reduced amplification but higher inventory fluctuations. Forecasting plays a decisive stabilising role by narrowing the bullwhip-prone region, smoothing out the inventory variations and providing structural synchronisation between refurbishment and remanufacturing conditions. The study offers theoretical insights into how recovery loops reshape bullwhip dynamics and provides practical guidance for designing coordinated replenishment and forecasting policies that enhance stability in CLSCs, particularly those involving third-party recovery partners.